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Climate Monitoring and 

DiagnoJStics Laboratory 

Summary Report No. 26 

2000-2001 

-- Annual Fossil Fuel Emissions 

-- Atmospheric C02 Growth Rate 

Linear Ave age C012 G owth Rate 

0 -1--~~--~~~---+~~~-+-~~~-1-~~~ 

1955 1965 1975 1985 1995 2005 

U.S. Department of Commerce 

National Oceanic and Atmospheric Administration 

Oceanic and Atmospheric Research 
Climate Monitoring 

and Diagnostics Laboratory 

Summary Report No. 26 

2000-2001 

Daniel B. King , Editor 

Russell C. Schnell, Editor 

Rita M. Rosson , Assistant Editor 

Christine Sweet, Assistant Editor 

Boulder, Colorado 

March 2002 

U.S. DEPARTMENT OF COMMERCE 

Donald L. Evans, Secretary 

National Oceanic and Atmospheric Administration 

Vice Admiral Conrad C. Lautenbach er, Jr., 

Under Secretary of Commerce for Oceans and Atmosphere 
NOTICE 

\lention ofa commercial compan) or product doc, not con:.t1tutc an endorsement b) "\O.\ \ Otlice of Oceanic and 

.\tmo:,phcric Research. Use for publicll) or ad' enising purpos~s of infom1atio11 from this publication concerning 

proprietar) products or the tests of '>UCh proclucb i> not authori1ctl. 

For sale b} the :"Jlwnal Technical lnforma11on Sen ice. 5185 Pon RO}JI Road 

Spring lie Id. \ \ 111 b I 

II 
Preface 

The Climate Monitoring and Diagnostics Laboratory (CMDL) is located in Boulder, Colorado, 

with Baseline Observatories in Barro\\', Alaska; Mauna Loa, Hawaii: Cape Matatula, American Samoa: 

and South Pole, Antarctica. It is one of t\\'elve research components within the Office of Oceanic and 

Atmospheric Research (OAR) of the National Oceanic and Atmospheric Administration (NOAA). 

CM DL conducts research related to atmospheric constituents that are capable of forcing change in the 

climate of the Earth through modification of the atmospheric radiative environment. for example. 

greenhouse gases and aerosols. and those that can cause depletion of the global ozone layer, for 

example. chlorine- and bromine-containing compounds. 

This report is a summary of CM DL activities for calendar years 2000 and 200 1. It is the 26th 

consecutive report issued by this organization and its Geophysical Monitoring for Climatic Change 

predecessor since formation in 1972. From 1972 through 1993 (numbers I through 22), reports were 

issued annually: thereafter, the reports were issued on a biennial basis. At CM DL's Internet home page 

(\\'ww.cmdl.noaa.gov) you will find information about our major groups and Observatories, latest 

events and press releases, publications, data availability, and personnel. Numerous data graphs and ftp 

data files are ava ilable. Information (program descriptions, accomplishments, publications, plans, data 

access, etc.) on CM DL parent organizations can best be obtained via the Internet (OAR: 

W\\'\\'.Oar.noaa.gov; NOAA: ww\\'.noaa.gov). 

This report is organized into the following major sections: 

l. Observatory, Meteorology, and Data Management Operations 

2. Carbon Cycle 

3. Aerosols and Radiation 

.f. Ozone and Water Vapor 

5. Halocarbons and other Atmospheric Trace Species 

6. Cooperative Programs 

These are follo\\'ed by a list ofCMDL staff publications for 2000-2001. 

Inquiries and/or comments should be addressed to: 

Director. R/CMDL 

NOAA Climate Monitoring and Diagnostics Laboratory 

325 Broad,say 

Boulder. CO 80305-3328 

(303) 497-6074 

or 

Russell.C.Schnell(t:1 noaa.gov 

Ill 
Judy Pereira John Chin 

Years of Service: 1 966-1 999 Years of Service: 1960-1962; 1964-1966; 1 968-2000 

Together, Judy Pereira and John Chin were a unique team that helped to make the Mauna Loa Observat01y the 

world-class institution it is today. One cannot think of Mauna Loa Observatory without being reminded of their 

dedication, service, and outstanding personalities. 

Judy Pereira 

In 1966, Judy, the reigning "Miss Aloha Hawaii" and a student 

at the University of Hawaii, Hilo, joined Mauna Loa as a parttime worker. She soon became the permanent secretary and 

served as the heart and soul of Mauna Loa until her retirement in 

December 1999 after a 33-year association with the observatory. 

Over those years she worked for eight different directors, or rather 

eight directors worked with her, as she often knew much more 

about MLO history and daily operations than they did. She ran 

the observatory office in an efficient and professional manner 

with dashes of Hawaiian Island navor and local culture mixed in. 

Because she was related to a large percentage of the people in the 

Hilo area, Judy could usually get repairs and services completed 

any time of the week, often free as a favor to a "family member. " 

And, any member of the Mauna Loa staff was considered part of 

this extended family, with the requisite invitations to weddings, 

first-year birthday parties, Christmas celebrations, and family 

luaus. 

Judy's ready smile, enthusiasm, empathy, friendliness, and 

knowledge made her memorable to all she met. She continued 

her role as the official greeter for Mauna Loa and Hilo throughout 

all her years of service. Visitors and scientists who came to 

Mauna Loa from around the world remained her friends for life. 

Often these people would come back to the Big Island decades 

later just to renew her acquaintance and to introduce their spouses 

and children to her, a living embodiment of the "Aloha" spirit. 

IV 

John Chin 

John joined the Mauna Loa Observatory, U.S. Weather Bureau 

Research Station, in 1960 to work on the Scripps Institution of 

Oceanography (SIO) C01 program. He left in 1962 to broaden 

his skills at NASA and Lockheed before returning to Mauna Loa 

in 1964 to again conduct the S IO atmospheric C02 monitoring 

program along with other observatory duties. In I 966, John left 

for a brief time to work at Cloud Physics, University of Hawaii, 

studying warm rain projects. In 1968, he rejoined Mauna Loa and 

Federal service. In 1974 he helped in the expansion of the NOAA 

carbon cycle programs at MLO. As a physicist he continued to 

operate both SIO and NOAA C02 programs, in addition to many 

other observatory duties, through to his retirement in December 

2000, completing 3 7 years of service at Mauna Loa. 

It has been calculated that during his tenure, John made at least 

6000 round trips on the Mauna Loa Road, which is equivalent to 

driving around the Earth 25 times at the equator. 

John is known for his reliability and predictability. He always 

arrived for work within 2 minutes of a set time, and his weekly 

lunch menu never varied. For 37 years, his lunch always consisted 

ofa sandwich, tuna or chicken, a banana, carrot or celery sticks, and 

a small box of raisins that he ate exactly at 12 noon. 

When John first entered service at Mauna Loa Observatory in 

1960, the annual mean atmospheric C02 concentration was 3 16 

ppm. The annual mean was 370 ppm in the year he retired. The 

MLO C02 curve is recogni zed around the world as one of the 

longest and most important geophysical records in existence; John 

can be proud that he was instrumental in helping make it so. 
Contents 

Preface ...................... ....................................................................................................................................... ....... 111 

CMDL OrganiLation. 2001 ..................................................................................................................................... \ 111 

CMDLStaff 2001 ................................................................................. ................................................................. 1x 

CMDL Station Information...... .. ........................................................................... .................................. ... ............. x 

I. Obsen ator) .. Metcorolog). and Data Management Operations .................................................. .................. .. . 

1.1. Mauna Loa ObserYator) ......................................................................................................................... . 

I . I. I. Operations ................................................................................................................................. . 

1.1.2. Programs ......................................................... .. ............................................................... .... ....... 2 

1.2. Barro\\ Obserrntory ..................................................................................................................... .... ....... 6 

1.2.1. Operations ................ ....................................................................................................... ........... 6 

1.2.2. Programs ................................................................................... ....................................... .... ....... 7 

1.3. Samoa Obserrntor) ......... ............................................................................................ .......... ..... .. .... ...... . I 0 

1.3.1. Operations .............................. ................. .......... ................... ...................... ..................... .... ....... I 0 

1.3.2. Programs ..................................................................................................................................... 11 

1.4. South Pole Obsenator") ............................................................................................................ .. ............. 11 

1.-l. I. Operations .. ............................ ............................. ........................................................ ............... I I 

1.4.2. Programs .............. ................ ... .................................................. ......................... .............. ........... 13 

1.5. Meteorological Measurements ............................................................................................................... . 16 

1.5.1. 'vleteorology Operations.............................................................................................................. 16 

1.5.2. Station Climatologies.................................................................................................................. 16 

1.6. References ............................................................................................................................................... 27 

2. Carbon Cycle ............................................................................................................................ .............. ......... 28 

2.1. Q,·en ie\\ .. .......... ..................... .. ....................................................... ..... .............................. ........ .... ........ 28 

1 1 Carbon Dioxide .. . .. . . .. . . .. ... . .... .. .... ... ..... ... ..... .. .. ... .. . .. . .. .. ... . .. .. ..... .. . . . .. ..... .. .... .. .. ... .. ... .. ... ........ .. .. . .. ... . ........ 29 

2.2. 1. In Situ Carbon Diox ide i\1easurements ...................................................................................... 29 

2.2.2. Flask Sample Carbon Dioxide i\ leasurements ............................................................................ 29 

2.2.3. Carbon Dioxide Standards and Reference Gas Ca librations.................. ..................................... 31 

2.2.4. Measurements or Stable Isotopes or Atmospheric C0 2...... ................... ..... ....... . . ...... .... ... ...... . .... 32 

2.3. i\1ethanc .............. .............................................................................. .................. ..................................... 36 

2.3.1. In Situ Methane Measurements............................. ...................................................................... 36 

2.3.2. i\1easurements of Methane in Discrete Samples................................................................... ...... 37 

2.3.3. Atmospheric 811CH4 Since 1998 ................................... ........................................... ................... 39 

2.4. Carbon Monoxide.. ........................... ......................................... ................................ ......................... ..... 40 

2.4. 1. Measurements of Carbon Monoxide ...................................................................................... ... .. -lO 

2.-l. 2. CO Reference Gases................................................. .. ..................................................... ............ -l2 

2.5. Nitrous Oxide and Sulfur I lcxanuoride........................... ........................................... .................... ......... -l3 

2.6. i\leasurements on Tall Towers ................................ ................................................ .. ...................... ........ -B 

2.7. Data Integratio n (GLOBAL VIEW)....... ....... ............................................................. .............................. ..+5 

2.8. ln\'erse Modeling.. .. .. .. .... .. .......................................................................................... ... ................. ......... ..+7 

2.9. References......................................................... ...................................................................................... ..+8 

\ ' 
3. Aerosols and Radiation..................................................................................................................................... 51 

3. 1. Aerosol Monitoring................................................................................................................................. 51 

3. I. I . Scienti fie Background ...... ...... ........ ... .. . ... ....... .. ..... .. . .. .. ....... ...... .. .. . ................. .. .... ... .. .. .. . ..... .... . .. 51 

3.1.2. Experimental Methods................................................................................................................. 52 

3.1.3. Annual Cycles............................................................................................................................. 54 

3.1.4. Long-Term Trends...................................................................................................................... 54 

3.1.5. Special Studies............................................................................................................................ 57 

3.2. Solar and Thermal Atmospheric Radiation............................................................................................. 67 

3.2.1. Radiation Measurements............................................................................................................. 67 

3.2.2. Basel ine Surface Radiation Network......................................... .................................................. 70 

3.2.3. Solar Radiation Calibration Faci lity ............................................................................................ 71 

3.2.4. Monitoring Aerosol Optical Depth.............................................................................................. 71 

3.2.5. MLO and Boulder UV Spectroradiometers................................................................................. 74 

3.2.6. Broadband UV............................................................................................................................. 77 

3.2.7. Radiative Effects of an Earlier Spring SnO\\melt in No1ihern Alaska........................................ 77 

3.2.8. UV Variability in the Alaskan Arctic.......................................................................................... 78 

3.2.9. Data Processing........................................................................................................................... 82 

3.3. References............................................................................................................................................... 83 

4. Ot:one and \Vater Vapor ................................................................................................................................... 86 

4.1 . Continuing Programs .............................................................................................................................. 86 

4.1.1. Total Ozone Obser\'ations .......................................................................................................... 86 

4.1.2. Umkchr Observations.................................................................................................................. 87 

4. 1.3. Cal ibration of Dobson Spectrophotometers................................................................................. 87 

4. 1.4. Surface Ozone ................................ ............... .............................................................................. 88 

4. 1.5. Ozonesondcs................................................................................................................................ 91 . 

4. 1.6. Atmospheric Water Vapor........................................................................................................... 92 

4.1.7. Atmo<;pheric Transport................................................................................................................ 93 

4.1.8. Stratospheric Aerosols................................................................................................................. 94 

4.2. Special Projects....................................................................................................................................... 95 

4.2.1. JOSI E-2000 .................................... ........................................... .................................................. 95 

4.2.2. Dobson and Ozonesonde Measurements at Fairbanks During TO!\IS3F..................................... 95 

4.2.3. Long-Term Total Ozone Trends.................................................................................................. 98 

4.2.4. Longitudinal and Temporal Distribution of Dehydration in the Tropical Tropopause Region... I 0 I 

4.2.5. Tropical Tropospheric Ozone...................................................................................................... I 03 

4.3. References............................................................................................................................................... I 04 

5. Halocarbons and other Atmospheric Trace Species.......................................................................................... I 06 

5. I . Overview .. .. .. . . . .. .. ... ... .. .. . .......... .. . .. ... . . . ... . . . .......... ... ....... ... .. ... .. . .. ... . ... . . . .. .. . .. . .. .. . .. .... ... ... .... ... .. . .. . . . .. . ... . ... I 06 

5.2. Continuing Programs.... ........................................................................................................................... I 06 

5.2.1. Flask Samples.............................................................................................................................. I 06 

5.2.2. In Situ Gas Chromatograph Measurements................................................................................. 11 3 

5.2.3. Gra\ imctric Standards................................................................................................................. 11 8 

5.3. Airborne Projects..................................................................................................................................... 120 

5.4. Ocean Projects......................................................................................................................................... 125 

5.4.1. Data Analysis.............................................................................................................................. 125 

5.4.2. 200 I Ocean Cruise...................................................................................................................... 126 

5.5. Special Projects....................................................................................................................................... 127 

5.5. 1. l\leth) I Halide Emissions from Tomato Plants............................................................................ 127 

5.5.2. Trans-Siberian Obser\'ations into the Chemistry of the Atmosphere (TROICA)........................ 128 

5.5.3. Firn Air Sampling. 200 1.............................................................................................................. 132 

5.6. References............................................................................................................................................... 133 

\ i 
6. Cooperative Programs ............................. ........... .......... ............................................................................ ........ 136 

UV Spectroradiometer Monitoring Program: Calculation of Total Column Ozone 

from Spectra of Global lrradiance Measured at South Pole and Barrow and 

Comparison with CMDL/Dobson and NASA/TOMS Ozone Data 

G. Bernhard, C.R. Booth, and J.C. £hra111jian ............................................................ ........... ..... 136 

Size-Resol\'ed Trace Elemental and Organic Aerosols at Mauna Loa Observatory, Spring 2000 

T A. Cahill, S.S. Cl!fJ: M. Jimene::-Cm::, SC. Riddle, P.B. Kel~v. and K.D. Peny ..................... 139 

Migration Rates and Flight Behavior of Migrating Eiders Near Towers at Barro\\', Alaska 

R. H. Day, J. R. Rose, B.A. Cooper, and R.J. Blaha........ .......................................... ......... ........... 141 

Occurrence Probability of Pc 1 Micro Pulsations Observed at Barrow During the Solar Quiet Period 

K. Hayashi.......................................................................................................................... ......... 143 

NIWA's NDSC UVNisible Measurements at the Mauna Loa Observatory 

P. V. Joh11s1011........................................................................................................... ......... ........... 144 

Quasi-Biennial Oscillation Signatures in Ozone and Temperature Profiles Measured 

by the J PL Lidar at Mauna Loa 

T LeB/a11c and 1. S. Mc Denn id.................................................................................................... 145 

Investigation of Chemical Transfer Processes between Atmosphere and Snow at South Pole 

JR. McConnell and R.C. Bales........................................................................................ ........... 148 

Microwave Measurements of Middle Atmospheric Water Vapor from Mauna Loa. 1996-200 I 

G.E. Nedoluha, R.M. Bevilacqua, R.M. Gome::, B. C. Hicks, and J.M. Russell Ill...................... I SO 

Aerosol Chemical Species and Volatile Organic Compounds at Barrow 

S. Ohta, N. Murao, and T. Fukasmra ..................................................... ................. ... ................. I 52 

Advanced Global Atmospheric Gases Experiment (AGAGE) 

R.G. Prinn, R.F. IVeiss, D.i'vl. Cunnold, P.J. Fraser, and P.G. Simmonds................................ .. I 56 

USDA UVB Mon itori ng and Research Network Langley Calibrations at Mauna Loa Observatory 

J. Slusser...................................................................................................................................... 1 59 

Long-Term Trends of Trace Gases over Mauna Loa 

R. Van Allen, F.J. 1vlurcray. TM. Stephen, and R.D. Blatherll'ick ......................................... .. .. . 161 

Geomagnetic Field Monitoring at Barrow, Alaska 

£.IV 1Vorthingto11 and J.J. L ove... ... ............... ..... ............. ...... .... ..... ........... .... ............................. 166 

UA F-Frontier Snowfall/Blowing Snow Observations at CM DL, Barrow: Preliminary Result for 200 1 

D. Yang, K. Sugiura, and T Olwta................................................................. ............................. 171 

The ANSTO-CMDL Radon Program at MLO 

IV. Zahorowski, S. Chambers, a11d P. Fuk111nura-Sall'ada ... ...... .......... ............................. ... .. ...... 174 

7. Publications by CMDL Staff. 2000-200 1 ................................. ........................................................................ 176 

8. Specialized Abbreviatio ns and Acronyms ........................................................................................................ 180 

Vil 
CMDL Organization, 2001 

The CMDL organization structure features five research areas organized according to scientific discipline as 

follows: (I) Carbon Cycle; (2) Halocarbons and other Atmospheric Trace Species; (3) Ozone and Water Vapor: (4) 

Aerosols and Radiation; and (5) Observatory Operations. At the end of 200 I. the laboratory staff consisted of 50 

Ci\'il Service personnel (excluding part-time student assistants), 26 CIRES/University of Colorado personnel. and 2 

NOAA Corps officers, as well as several visitors and people on special appointments. 

Director, CMDL 

David Hofmann 

(303) 497-6966 

Program Management Specialist Physical Science Administrator Budget Analyst 

Ann Thorne Russell C. Schnell Brenda Seader 

(303) 497-6074 (303) 497-6733 (303) 497-6070 

I I 

Carbon Cycle Halocarbons and other 

Atmos. Trace Species 

Pieter Tans James W. Elkins 

(303) 497-6678 (303) 497-6224 

Ozone and Water Vapor Observatory Operations Aerosols and Rad iation 

and Data Management John Ogren 

Samuel Oltmans Russell C. Schnell 

(303)497-62 10 

(303) 497-6676 (303) 497-6733 Ellsworth Dutton 

(303) 497-6660 

I I I 

Barrow Observa tory f\1auna Loa Observatory Samoa Observatory South Pole Observatory 

Daniel J. Endres John Barnes Joel Michalsk i Pauline Roberts 

(907) 852-6500 (808) 933-6965 (684) 622-7455 (303) 497-6655 

\ 'Ill 
Director's Office 

David J. I lofmann, Director 

Russell C. Schnell, Phys. Sci. Admin. 

Ann Thorne, Pgm. Management Specialist 

Brenda Seader. Budget Analyst 

Linda Sachetti, Admin. Assistant 

Rita Rosson, Editorial Assistant 

Special Projects 

Lori Brull\\ iler, Physical Scientist 

Eric Hackathorn, Computer Specialist 

Aerosols and Radiation 

l:llswonh Dutton, Meteorologist 

John Ogren. Physical Scientist 

Connie Craig. Secretary 

EliLabeth Andrews, CIRES 

Gail Anderson, USAF 

Greg Bland, Student 

Barry Bodhaine, Meteorologist 

David Jackson, Electronic Technician 

Anne Jefferson, CIRES 

David Longenecker. Cl RES 

Donald Nelson, Meteorologist 

Katie O'Gara. CIRES Student 

Patrick Sheridan, Physical Scientist 

Roben Stone. CIRES 

Renee Tatusko. Physical Scientist 

James Treadwell. Electronic Technican 

James Wendell. Electronic Technician 

Norman Wood. CIRES 

Ozone and Water Vapor 

Samuel Oltmans, Physicist 

Beverly O'Donnell, Secretary 

Gloria Carbaugh, Physical Scientist 

Dan Chao, Phys. Science Aid 

Mark Clark. CIRES 

Roben Evans, Research Scientist 

Joyce Harris, Research Physical Scientist 

Bryan Johnson, Research Chemist 

Michael O'Neill. CIRES 

Doroth) Quine), CIRES 

Eric Rice. CIRES Studem 

David Sherman. CIRES 

Brian Vase!, CIRES 

llolger Vomel. CI RES 

Brooke Walsh, Student 

CMDL Staff, 2001 

Carbon Cycle 

Pieter Tans. Senior Scientist 

Connie Craig. Secretary 

Peter Bakwin. Physicist 

Thomas Conway, Research Chemist 

Ed Dlugokencky, Research Chemist 

Sara Fletcher, Cl RES Grad. Res. Asst. 

Douglas Guenther, CIRES 

Michael I lahn. CIRES 

Duane Kitzis, CIRES 

Patricia Lang. Physical Scientist 

Kenneth Masarie. Research Physicist 

John Miller, CI RES Grad. Res. Asst. 

Anthon) epomuceno, Phys. Science Aid 

Paul Nm elli. Research Chemist 

Karen Panak, CIRES 

Natalie Pa)nter, CIRES 

Britt Stephens, CIRES 

Kirk Thoning, Physicist 

Michael Trudeau, CIRES 

Conglong Zhao, CI RES 

Halocarbons and other Atmospheri c 

Trace Species 

James Elkins, Supen isory Physicist 

Debra Hansen, Secretary 

James Butler. Research Chemist 

Geoffre) Dutton, CIR ES 

Brad I lall. Physical Scientist 

Dale Hurst, CIRES 

Daniel King, CIRES 

Eric Kline, CIRES 

Debbie Mondeel, CIRES 

Ste\e Montzka, Research Chemist 

Fred Moore, CIRES 

David Nance. CIRES 

Karen Pietruszka, Student 

Pavel Romashkin, CI RES 

Thayne Thompson, Physicist 

ix 

Observatory Operations 

Russell C. Schnell, Phy. Sci. Admin. 

Debra Hansen, Secretary 

Andre'' Clarke, Chemist 

Thomas ~lefford. CIRES 

Donald Nell ~ Physicist 

Daniel Endres. Physicist, 

Station Chief. Barrow 

Glen McCom ille. Electronic Technician 

John Barnes, Physicist. 

Director. i\launa Loa 

Leslie Pajo. Office Automation Clerk 

Paul Fukumura-Sawada, Electronic Engineer 

Darryl Kuniyuki, Electronic Engineer 

Ste, en Ryan, Physical Scientist 

Robert Uchida. Electronic Technician 

Alan Yoshinaga, Chemist 

Joel 1'v1ichalski, NOAA Corps, 

Station Chief, Samoa 

Malcom Gaylord. Electronic Engineer 

Pauline Roberts. NO/\/\ Corps. 

Station Chief. South Pole 

Eric Sandberg, Electronic Engineer 

Scott Wingerter. 10AA Corps 

Loreen Lock, Chemist 
Name: 

Lati tude: 

Longitude: 

Elc\ation: 

Time Zone: 

Office Hours: 

Telephone 

Offi ce hours: 

Fax: 

Postal Address: 

Freight Address: 

Name: 

Latitude: 

Longitude: 

Elevation: 

Time Zone: 

Office Hours: 

Telephone: 

Office hours: 

After hours: 

Fax: 

Postal Address: 

Freight Address: 

CMDL Station Information 

Barrow (BRW) 

7 J .323°N 

156.609°\V 

8 Ill 

GMT -9 

8:00 am-5:00 pm 

(907) 852-6500 

(907) 852-4622 

Offi cer in Charge 

NOAA ERL CMDL 

Pouch 888 

Barrow, AK 99723 

Officer in Charge 

OANERLCl\IDL 

6 17 Cunn ingham 

Barrow. AK 99723 

Samoa (SMO) 

14.232°S 

I 70.563°W 

77 Ill 

GMT- II 

8:00 am-5:00 pm 

0 I I (684) 622-7455 

0 11(684)258-2847 

0 11 (684) 622-7455 

Officer in Charge 

U.S. Dept. of Commerce 

NOAA - CMDL Samoa Obsen a tory 

Pago Pago, American Samoa 96799 

Same as above 

x 

!\fauna Loa (l\ILO) 

19.539°1 

155.578°\V 

3397 111 

GMT - JO 

8:00 am-5:00 pm 

(808) 933-6965 

(808) 933-6967 

U.S. Dept. of Commerce 

OAA - Mauna Loa Observatory, Rm. 202 

P.O. Box 275 

llilo, 111 9672 1 

U.S. Dept. of Commerce 

OAA - Mauna Loa Obserrntory 

154 Waianuenuc A\c. 

Hilo. HI 96720-2-t52 

South Pole (SPO) 

89.997°S 

I 02.0°£ 

2837 111 

GMT + 12 

8:00 am-5:00 pm 

Relayed through CM DL Boulder 

Officer in Charge 

NOAA/CM DL Clean Air Facility S-257 

South Pole. Antarctica 

PSC 468 Box 402 

FPO AP 96598-5402 

Same as above 
1. Observatory, Meteorology, and Data Management Operations 

I.I. :\L\l '\",\LOA OH~ER .ATOR\ 

J. BAR'\I s. J. C111::-.. P. Fl Kl.\ILR.\-S \\L\DA. D. Kl '\IYLKI. 

L. p ·\JO. s. RY\'\. B. l:CHID \. \'\I> A. YOSlll'\.\GA 

1.1.1. 0PER.\TIO.'\S 

The most noticeable changc to thc \1auna Loa 

Obsen ator) (\I LO). I lawaii. "as 1110\ ing the Jct Propubion 

Laborator) (JP L) o.i:one lidar from the trailers into the 

Nel\\ork for the Detection of Stratospheric Change (NDSC) 

building in \ larch 2001. This llll)\e \\as long a\\aited and 

"ent smooth I). The trailers ''ere moYed to the upper 

parking lot for equipment remo,al and ''ill be returned to 

J PL in the future. A ft er thc trailers "ere mO\ ed. 

construction 11as started in August 200 I on a ne\\ lidar 

building to house a Doppler lidar built b) Michigan 

,\erospace to measure ''ind from the ground through the 

troposphere. The project is being funded b) NOAA and 

managed b) the Uni,crsity of l\e\\ Hampshire. The old 

radiation platform abo\e the Keeling building 11as modified 

for ne" mercury detection equipment installed b) the 

Em ironmental Protection Agency ( l:.P A) in August 2000. 

The top section of the platform ''as remo,ed and the lo\\ er 

part re inforced. 

U.S. Army contractors installed a ne'' pole for the 

Army· s radio repeater antenna. The pole is do\\ nslope f1u111 

1 LO and shou ld soh e a pre,·ious electrical noise problem 

with the Nationa l Institute of Water and Atmospheric 

Research ultra\ iolet (N IWA UV) spectrometer. The 

contractors also began modifying the 'isitor building to 

house the radio equipment. A scientific drilling group for 

the lla,1·aii Volcano Obscn·atOr) (ll VO). U.S. Geologica l 

Sun ·ey (USGS). drilled a 140-m (-IOO-ft) ll'Cll for the 

placement of a seismometer and strain gauge for monitoring 

\ I auna Loa \ olcano. The instruments and telemetr) arc 

solar poi' creel and located on the edge of the helicopte r pad. 

Observatory use by 'isiting groups for short-term calibrations of their instruments (of a fe1\ ''eeks duration) 

continued to increase. There 1\ere many repeat' isits as 1\cll as 

SC\ era I ne1\ groups. For the most part. the instrumems are for 

1 arious solar radiation measurements of 1 arying comple:-.ity. 

One Japanese group left an instrument ru nning unattended for 

se\'cral \1eeks, returning 10 pack and ship the instrument back 

to Japan. Computer network connections \\ere added to the 

1 isitor building to accommodate them. 

John Chin, who retired after more than 30 years of 

scn·ice at i\ILO. \\US replaced b~ an electrical engineer'' ith 

experience at Pearl I !arbor '' ith the Department of Defense 

and'' ith telescopes on \llauna Kea. 

Outreacli 

Requests to 1 isit the obser\'ator~ continued. man~ through 

the lmernet. SC\cral classes from the Uni,ersit) of ll awaii at 

llilo toured i\ILO. and se1eral lcc111res ''ere gi,cn b) the 

station chief on campus. A National Aeronautics and Space 

. .\dministration Earth Obser\'ing System (~ASA EOS) Aqua 

Satellite educational '' ebcast ''as transmi11ed through \IL()' s 

l111erne1 connection in i\la) '.WOO. \ILO personnel \1ere 

filmed and inten iewed. and participated in the on line 

discussions 11 ith the elementar) schools that were logged OIL 

The i\ILO station chief lectured on climate change and 

pollution to a group of 60 senior citi/cns in Kona and 10 

about 20 at an Aloha E:-.change Club mee ting. I le also 

judged the lla1\aii Count) Science Fair and presented 

:mards for en\ ironmentall) related projects. T1\0 high 

school summer students ''ere mentored each >ummer on 

short data analysis projects for part or the Uni,crsity of 

1-la\Htii at I lilo·s Up11ard Bound project. Two uni1ersit) 

students also '' orked summers on the lidar program. one 

from the Uni\ersity of Pennsyhania and the other from the 

Uni1crsit) of Ha,, a ii at Hilo. 

A i\ILO scientist receiYcd the Department or Commerce 

bron.i:c medal for his work 1\ith the lla1\a ii schools Volcano 

Gas obsen·ator) Network (VOGNET). The VOGNET 

program began its sixth year in 2001. A protOt)pc PCoperatcd co111inuous condensation nuclei (CN) counter was 

de1eloped and tested in the summer of 2000 at i\ILO. This 

CN counter can be built by students for S-l50 11i1h readily 

a\ailable parts. 1-lall'aii Preparator) Academ) (HPA) 

receh eel a grant from the local electric com pan) 10 fund a 

ncll,ork of these instruments at schools around the Big 

Island. In spring 200 1 students and teachers at six schools 

began assembling their CN counters. '' hich wc1·e then tested 

and calibrated at \I LO Hilo in August-September 2001. At 

the end of 200 I. the instruments. connected to the central 

!I PA data archi1al computer by modem, \\'ere col lect ing 

continuous data at the schools. A \1eb page dc,clopcd and 

run b) I-IPA students 11 ill pro\ idc the public with near-realtime information on the le1els of \Olcan1c pollution around 

the island. 

C 0111p 11ters/Net11•ork 

The networks at the llilo office and at portions of the 

mountain site IHI\ e been changed from the older coax type 

to the 10 base-T t)pe. The ll ilo office 1\aS upgraded further 

by instal lating fast Ethernet de\ ices runn ing at I 00 

megabits on its Local Arca '\Jet work (LAN). The router in 

the I lilo office. three computers. and t110 ncl\\Ork printers 

11ere obtained from excessed census equipment. i\lorc 

nct11ork hubs 11crc added at ,·arious locations at the 

obscn ator) to accommodate increased l'isiting projects 

requiring Internet acce>.s. Most or the computers and 

net11ork de\ ices are no'' on some t) pe of unintcrruptiblc 

power supply (UPS). At the end of 2001 f\ILO had 51 

computers at its site. Three additional racks \\'ere installed 

to pro1 idea more efficient use of space. 

i\ILO's domain name ''as changed at the Hilo site from 

··11110.ha11aii.go' ·· 10 ··m10.noaa.go1 ·· and is ofliciall) 

registered in the NOAA database. This allo11s the staff 

access to NOAA sites 10 obtain data and programs '' i1hou1 a 

fee . It affects onl) the i\ILO Hilo addresses. The U.S. Fish 

and \\'ildlife Sen·ice still retains the ··m10.ha11aii.go' ·· 

address. and the mountain site remains at ··mtn.noaa.go' ·-, 

i\I LO's new ''cb address is "wwll'.mlo.noaa.gm ''. In June 

the lligh Altitude ObsenatOr) (HAO! in talled it;, 01111 56-K 

line al the obsenatory. I IAO is no1' independent from the 
TABLE I. I. Summar) or :'\ lcasurcmcnt Programs at i\ILO in 2000-2001---co111inued 

Progra111 ~leasurement 

\h-1t•oro/og1 

\1r 1e111perature 

\1r temperature (30-70 km) 

Temperature gradient 

De" point temperature 

Reial I\ e humidit) 

Prcssun.: 

\\ ind (speed and direction) 

Prcc1pi1a1ion 

Total precipitable water 

Pn.'cipittllit111 Cl1<•111i11r1· 

pll 

Conducti\ II) 

Co111><'1'<1f/1·,. Progrcim' 

CO (SIO) 

co_. c." o (SIO> 

co. CO. CIL. 'c 'c (CSIRO) 

0 anal)ses (SIO) 

Total -.uspentkd particulates (DOE) 

Ultra' 1ole1 radiation (CSL: and LSD,\) 

Rad1onucilde deposnion (DOE) 

\erosol che1111stry (L'ni'. of Ca lif.. Da\ isl 

Ilg. Ilg . Ilg" !EPA NE RL) 

Particulate 2.5-10 μm (EPA \'ERL) 

Sulfate. nitrate. aerosols ( Cni'. of Hawaii) 

Radon ( .\~STOJ 

\I RO'.ET ;,unphotometer;, ('.AS\ Goddard) 

Global Pnsi11on111g Syste111 (GPS) Test Bed 

(f\,\ and Stanford Lni\ersity) 

I arthquakc;, ( 11 \'0-LSGS enlo Par1') 

Larthquakcs (i\orth\\e>tcrn Lni\ersity) 

CO i;.otopcs (SL'. Y) 

Clhmic dust (CAL TECll) 

\ 'okanic acti,it) (11\10) 

rhpiratcd thermistor. 2-. 9-. r-111 heights. 

\ la'l..-111111. 1hcr1110111e1cr;.. 2.5-m height 

Lidar 

Aspirated 1her111istors. 2-. 9-. 37-111 height;,* 

De" point hygro111etcr. 2-m height* 

TSL. 2-m height* 

Capacitance tram,ducer• 

8.5-. I 0-. and 38-111 heights* 

Rain gauge. 20-cm diameter 

Rain gauge. 20-cm diameter; 

Rain gauge. tipping bucket* 

l"oske11 IR h) gromctcr• 

pll meter 

Conducti\ ll) bridge 

,\pp lied Physics IR anal) /Cr* 

5-L C\ acuated gla-.s llasks~ 

Pre'>'>ur11ed glass llask sample 

5-l gla-s llasJ,.-. through tO\I a line and pump unit~ 

lhglHolumc sampler 

\ lulti-\la\ elength radiometer (direct. diffuse. shado" band) 

lon-c\change column 

Programmed filter sampler 

Tekran 2537,\. 1130andI135p (began 7 01) 

Dichotomous Panisol-Plus \lode! 2025 (began 8 01) 

lihcrs)'>le111 

Aerosol "'" cnging of Rn daughters: 

t\\O-filtcr system• 

,\u1oma1ed -.olar-po'' erect sunphotometer> 

GPS-dcri,ed column \later \apor prolilcs 

Sci-.mometcr 

Sc1-.momc1a (ended 6 0 I) 

I 000 psi C) tinder 

\ lagnel 1c collector 

Seismic and e'l.pansion 111strument in 370-ft-decp \\Cit 

\e11n1rk.fi1r the Detectio11 o(Stmtospheril 

Lltra\ 1olc1 radiation 

Clu111g<! I\ DSCJ 

(t\OAA and NIWA) 

Stratospheric 0 1 profile;,. 20-66 km 

(Lni'. of ass .. Amherst) 

Stratospheric water 'apor pro ti Jes. 40-80 1'm. 

10-15 k111 m,olution (NRL) 

Strato-.phcric 0 1 profiles ( 15-55 km). 

temperature (20-75 km). 

aerosol pro tiles ( 15-40 km) (J PLJ 

'.O ('-I\\ \and '.OAA) 

BrO ('. I\\ ,\ and :-:OAAl 

Column 0 .. L\'B (AES. Canada) 

';olar -.pcctra (Lni'. of Dc1ncr) 

All 111s1rumcnts arc at \ILO unle>s indicated. 

UV spcctroradiomctcr (285-450 nm). 0.8-nm resolu11 on 

l\lillitcch Corp .. 110.8-Gll; microwa\e 01one 

spectroscopy 

\till11ne1erwa\ e -.pectrometer 

L\' lidar· 

Slant column '.O_ -.pectrometer 

Column BrO spectrometer 

f\\O Bre\\Cr spectrophotometers 

fTIR spectrometer. automated* 

Data from this instrument recorded and proces-.cd by microcomputer>. 

·i·Kumukahi onl). 

+Kulani \lauka. 

~\ILO and Kumukahi. 

Sampling f'requency 

Continuous 

I da) 1

. \I cckdays 

I profile'' k- 1 

Continuous 

Continuous 

Continuous 

Continuous 

Continuous 

5 \\ k" 1 

I '' k- 1 

Continuous 

Continuous 

Contmuous 

I pair ,,~-I 

3 pair mo-1 

3 (2 mo) I 

( ont 111uous (I fi her '' J,.-1) 

Con1111uous 

Quarterly sample 

Integrated 3-da) sample. 

I continuous and 

I do\\ nslope sample 

(4 days) 1 

Continuous 

I dO\\ nslope sample '' k·

1 

Daily. 2000-0600 LST 

Co111111uous: integrated 

30-min samples 

Continuous 

Con1111uous 

C. ontinuous 

Continuous 

I '' k" 1 

I \\ k"1 (ended I 0 I): 

I (2 ''~r (began I 01) 

Con1111uous 

Continuous 

3 profi ks h 1 

( OnllntlOU S 

3-4 profiles '' J,. · 1 

( ontinuous. daytime 

Con1111uous. daytime 

Daily 

5 days ,,i,_-
remained on line. The Chromatograph for Atmospheric 

Trace Species (CATS) GC had a ne'' co mputer install ed in 

Januar) 200 I. In April 200 I all halon lire e:-..tinguishcrs 

\\en: remO\ e<l from all buildings at MLO at the request of 

Bo ulder. This alle\ iated a nois) background trace that had 

existed for a \\hilc. In August 2001 the RITS and CATS 

units \\Cre shut down because the calibration tanks and 

\ah e replacement parts did not arri\ e. Normal o peration 

resumed the next month when tanks and parts were 

recei,ed. The last remaining channel (B) o n RITS \\as shut 

dO\\ n in December 2000 as the last few intercomparisons 

''ere completed. 

Aerosols 

The Atmospheric Sampling System. installed in April 

2000. is a nC\\ automated system for measuring aerosol 

lig ht scattering as a function of ,,.a,elength. aerosol lig ht 

absorption. a nd condensation nuclei. T'' o partic le 

impactors are used to measure these properties for aerosol 

sizes less than I and 10 μm. The main components arc a 

Thermo Syste ms Incorporated (TS IJ three-\1a,elcngth 

nephelometer (model 3563). a Radiance Re search particle 

soot absorption photometer (PSAP). and a TS I condensation 

nucleus counter (CNC: model 3760). The system measures 

the folio\\ ing parameters: total and back\1 ard scattering 

coefficient time series at ~50- , 550-. and 700-nm 

,,a,elc ngths in l\\'O size ranges: absorption coefficient time 

series at 565 nm in two size ranges: and CN concentratio n 

time series. From the measurements the follO\\ ing 

parameters can be calculated: sing le scatt ering albedo at 

about 550 nm in t\10 siLe ranges: Angstrom coefficient: and 

hemispheri c back\\ ard scattering fra ctio n in l\\"O siLe 

ranges. 

Condensation nuclei. The old TS I unit was shipped to 

Boulder 111 May 200 I after a year o f comparison \I ith the 

ne \1 TS I unit. The Pollak CNC is no longer in use and was 

mo,ed to the Hilo office to calibrate the VOG ET 

continuo us CNCs. 

Aerosol light scattering. The three-\\ 3\ elength 

ncphelo mctcr measuring at 450. 550. and 700 nm was 

shipped to Boulder in May 200 I aft e r a year o f comparison 

'' i th the replacement nephclometer. 

Aerosol light absorption. The aethalometer was found to 

be non-Y2K co mpliant. Whe n a leng thy pO\\ er failure 

occurs. the instrument" s year resets to 1994. MLO staff 

mu st manuall) rese t the date to the current year. In August 

2000 the roller mechanism had to be repaired. which caused 

the unit to be do,,n for 5 days. In July 200 1 the instrument 

was sent to Magee Scientific to be upgraded. In October a 

nC\\ SC\ e n-\\ a vclength spec trum aetha lo metcr was insta ll ed 

at the obserrntory. 

Stratospheric am/ upper tropospheric aerosols. Weekly 

ob sen at ions continued with the N d: Y AG lidar thro ug hout 

2000 and 200 I. The background period continued. and no 

stratospheric aerosol ''as conclu si,·el) measured from a 

'olcanic eruption. Raman '' ater \'apor measurements ''ere 

initiated in 2000 and impro\'ed '' ith the purchase o f ne\1 

photomultiplier tubes optimi zed for the red part o f the 

spectrum. The telescope optical suppo rt structure ''as 

C.\ tended to accommodate one of the 74-cm-diameter (lo ngfocal-length) mirrors that had ne\'er been used. At that time 

the rub ) telescope ''as remounted for test ing. A proposal to 

5 

NASA \\<JS funded to \ a lidate water \ apor measurements 

from the Atmospheric Infrared Sounder (A IRS) instrument 

on the Aqua satellite. A computer power suppl y for the 

e.\pansion chassis failed and ''as replaced in August 200 I. 

Other maintenance consisted of nashlamp and cooling water 

changes for the laser. 

Solar Radiation 

The Physikalisch-Metcorologischcs Obsenatorium Da\'os 

(PMOD) thrce-\\a,·eleng th (380, 500, and 778 nm) sunphotometer was re mo\ cd from sen ice in Apri I 200 I 

becau se of degraded tilters. The normal incidence 

pyrhcliometer (the data go bac k to 19 58) is calibrated 

periodically against an acti\e-ca\ ity radiometer. SeYen of 

these comparisons were done in 2000 and three in 200 I. 

The acti\'e-ca\ ity radiometer ''as sent to Boulder for 

intcrcomparisons in l\ la) 2001. l\launa Loa Obsenatory is 

also used to calibrate handheld sunphotometers by the 

Langley technique: two instruments \\ere ca librated in 2000 

a nd 14 were calibrated in 200 I. The observatory is used to 

ca librate CMDL"s Yankee UV B instruments: three were 

cal ibrated in 2000 and none \\ere calibrated in 2001. S PO lA and SP02 instruments (four-channel tracking 

sunphotometers) were installed temporarily in the tracking 

dome for calibrations and comparisons '' ith the precision 

tilte r radiometer. T\\'o S POl -A instruments ''ere installed 

in 2000. and two SP02 instruments were in stalled in 200 I. 

A data line and a pressure sensor \\ ere connected to the HP 

data acquisition system, and a temperature controller ,,·a s 

installed in the dome to support the SP02 installati ons. 

M eteoro/ogy 

A computer-based "Ne\\ l\let System" measures station 

pressure. temperatures at the 2-. 9-, and 37-m le\'els. 

dewpoint temperature at the 2-m le\ cl. and \\ind speeds and 

directions at the 8.5-. 10-. and 38-m leYe ls o f the l\ ILO 

Obsen ation Tower. Precipitation is measured \\'ith a 

tipping bu cke1 rain gauge. This ne\1 system continues to 

operate unaltered and with high reliabilit) . 

Precipitation Chemistry 

The l\ILO modified program of precipitation chemistry 

collecti on and anal yses continued throughout 2000-2001 

'' ithin the basic M LO operational routine. This program 

consists of collections of a \\eekly integrated precipitation 

sample from the llil o N\VS station and the collection of 

precipitation event samples at MLO. These samples are 

analyzed in the Ii i lo laboratory for pll and conducti\ ity. 

Cooperatil•e Programs 

l\ILO cooperati\e programs arc listed in Tabl e I.I . Ne\1 

programs and changes not disc ussed in the NDSC section 

(next) are presented here. 

In Jul y 2001 mo scientists from the U.S . EPA ational 

E:-..posure Research Labo rator) (NERL) arri\'ed at l\ILO to 

install a mercury anal) zer and di chotomo us pa rt isol sampler 

and train l\I LO staff on its operation and maintenance. On 

Jul y 3 1, 2001. the mercur) anal)Ler was placed on line. 

The system continuous!) measures elemental mercury 

(ll g0 ). reacti\c gaseous mercury Il g~). and particulate 

mercury (llgP). On August 23 . 200 I. the particle sampler 

\\as acti,·atcd. The State of ll awaii Heahh Departme nt \\'i ll 
\\'eigh the filters from the partisol sampler. Filters arc 

collected only during downslope conditions. and one filter 

sample is collected each week. 

The Australian Nuclear Science and Technology 

Organi;ation (ANSTO) has measured radon continuously at 

i\I LO since 1989. A new data logger and compute r were 

installed in i\ larch :moo. and a ne" tlO\\ meter \\'as install ed 

in May 2001. 

For the Uni\'ersit) of California, Da' is. particulate 

special-e' ent projects, the Asian Paci fie Regional Aerosol 

Characterization Experiment (ACE-Asia)-MLO Co llaboration. multistage drum units and hi-vol filters were 

installed exposed in March 2000, March 200 I. and August 

200 I for approximately 6 weeks each and then shipped back 

to the Uni' ersity of Ca lifornia. Da' is. The State Uni,ersity 

of Ne\\' York (S UNY) CO isotope sample compressor failed 

in June 2001. The California Institute of Technology 

(CAL TEC H) cosmic dust collector continued to operate, 

although the weekl y sampling was changed 10 bi\\'eekly in 

January 200 I. 

Network for the Detectio11 of Stratospheric Change (NDSC) 

All NDSC instruments from pre\ ious years cont inued 

obsenations. Th e NOAA lidar. ozonesonde. and Dobson 

operations, ''hich are also part of the l\ILO NDSC faci lit), 

arc described in other sections of this report. 

Ultr(ll•iolet/Visib/e (UV/VIS) absorption spectroradiometer. 

The UV instrument began operat ion in the M LO NDSC 

building in November 1997. The UV spectroradiometer 

uses a double monochromator grati ng spectrometer to 

measure the UV spectrum bct\\'een 285 and -150 nm "ith a 

resolution of 0.8 nm. i\leasuremcnts are taken at 5° so lar 

zenith angle inten·als throughout the day. The instrument is 

calibrated \\Cckly with a mercury lamp and a 45-\V quartz 

lamp. An absolute-standard 1000-W FEL lamp calibration 

is performed twice each year. In August 2001 l\VA 

installed a new cal ibration lamp unit and a precision po\\'er 

supply unit. The power supply unit is programmable and 

maintains and controls the output current automatically 

during week ly cal ibrations. 

licroll'ave ozon e a11d ll'ater vapor spectroscopy systems. 

The Uni\ersity o f Massachusetts mi cro\\'a\'e instrument 

measures the \ertical profile of ot:one from 20 to 66 km 

\\ ith a ,·ertical resolution of I 0 km or less up to -10 km. 

degrading to 17 km at 60 km. The ozone altitude 

distribution is retrieYed from the details of the pressurebroadcned line shape. The Naval Research Laboratory 

(N RL) operates a simil ar \\ater vapor system that measures 

'ertical profiles t) pically from 40 to 80 km. Both systems 

recci\ ed the usual maintenance and continued operations in 

2000 and 200 I. 

l'V lidar. In March 2001 the JPL o7one lidar \\aS mo,ed 

out of the trai lers and into the NDSC building. The 1110\ e 

took about 6 weeks. A ne\\' Nd:YAG laser replaced one or 

the e:-.c imer lase rs for better reliabilit) for all-night 

operation during campaigns. JPL also used the opportunity 

offered b) the mo' e to extend the range of its measurements 

to lower altitudes by redesigning some or the optics and 

adding channels. The additional space has made the lidar 

easier to operate and maintain. 

6 

1\'0 1, BrO spectrometers. Since July 9. 1996. stratospheric 

NO~ has been measured at l\1 LO by the t\\ ilight-zenith 

technique \\'ith a NIWA UV VIS spectrometer. T\\o 

additional spectrometers \\'ere added in December 1999 for 

column measurements of N01 and BrO. The BrO 

spectrometer is used to measure stratospheric bromine 

monoxide, an important species in current attempts to model 

future nonpolar ozone trends. The instruments can be 

operated O\'cr the Internet by l\VA in Lauder. Ne\\ Zealand. 

Brell'er spectrophotometer. The measurements of 0 3 and 

UVB radiation \\'ith a single monochromator Brewer 

instrument are supplemented by all-sky images recorded 

e'ery 10 minutes to assist in the analysis of the UVB data. 

o, en ie" s of the automa tic operation of the instrument and 

data retrievals arc carried out remotely from Atmospheric 

Environment Sen ice (AES), now called Meteorological 

Service, in Toronto over the Internet. The data are archived 

at the World 07one and Ultraviolet Data Centre (WOUDC) 

in Toronto. Up-lo-date preliminary data arc available over 

the Internet from AES. Publication of ne\\' resu lts is 

planned after thorough analysis of a longer data record. 

This program continued throughout 2000-200 I. Annual 

mai ntenance and calibration checks and other 

in strumentation calibrations were carried out in March 

2000. 

Solar Fourier tramform infrared (FTJR) spectrometer. 

The University of Dem er FTIR spectrometer routinely 

monitors HCI. ll N03 • 0 3 , NiO, llCFC-22, HF. Cll 4, NO. 

HCN. CO. 1-l ~, and Cil 16. Because of the automatic 

nalllre of the instrument. the program is ab le 10 look at 

diurnal 'ariations in the species. Data are not collected on 

Sundays or Monda) mornings unl ess specia l operators are 

on site to add liquid nitrogen into the instrument. 

1.2. BARROW 0BSEIWATORY 

D. E;-;oRES A'D G. McCo-..:\'JLLE 

1.2.1. 0PERATIO;>;S 

Begun in January 1973. operations at Barrow Obser\'atory 

(BR \V). Barro". Alaska, ha\'e gro" n from a small program to 

one that no"· touches upon. or supports components of. 

almost c,·cry major cl imate change stud) in the U.S. Arctic. 

In addition to a full suite of CMDL measurements. programs 

include research acti' itics from se' era! U.S. go' crnment 

agencies and a broad selection of uni\'ersities in the United 

States and other cou ntri es. As the Arctic becomes recogni7ed 

as the location \\ here global climate \\'arming "ill probably 

be obsen eel first and "here the effects of the warming \\ill be 

rclati\CI) easy to detect. BR\V measurements and facilities 

are becoming e'er more in demand . 

In 200 1 a ne\\ garage with greater square footage than the 

main laborator) was constructed to house obsenatory 

'chicles and up to I 00 large compressed gas cylinders. There 

is also room for a small \\'orkshop and storage. The abil ity 

to park ,·chicles in a warm garage \\ill sa,·e on ' chicle 

maintenance and "ill allo\\ for a safe and dry ell\ ironmcnt to 

unload, pack. and unpack shipments. Compressed gas 

C) lindcrs were pre\iousl) stored at the Air Force Long 
Range Radar Site. formerly the Distant Early Warning 

{DEW) Line site, in an unheated storage bui lding one-half 

mile from the Barro\\ station or at the station on the tundra 

in summer mud or under sno\\' in the" inter. All the small. 

old buildings on si te were remo\ ed as part of the garagebuilding program; this has resulted in a much-impro\ed 

O\ erall appearance. 

Construction on the BR \V access road ''as essentially 

compl eted at the end of summer 2000. and it was graded in 

200 I. By summer 2002 the road \\'ill be settled to the point 

that the final graHI coating can be applied. The road \\as 

passab le to wheeled vehicles most of winter 2000-200 I for 

the first time ever, with on ly minor interruptions from 

drifting snow. 

From 1994 to 2000 there were no personnel changes at 

BR\V. In 2000 the station chief completed 16 )Cars at BR\V 

and the electronics technician 6 years. In July 2000 the 

technician transferred to the CM DL American Samoa 

Obsen·ator) {SMO) and was replaced '' ith a technician ''ho 

had pre\ iousl) '' orked at BR\\'. This technician left in 

December 2000 and ''ill be replaced b) a technician ''ho 

former!) "intered at the Ci\IDL South Pole Obsen a tor) 

(SPO). 

The station staff continues to be ill\oh ed '' ith the 

Barro'' Arel ic Science Consortium ( BASC). and the stat ion 

chi ef is a member of the Barro\1 En' ironmental 

Obsen·atory i\lanagement Committee. The station chie f 

''ill tra\el to Nome. Alaska. in January 2002 to help train 

fi ve nati\c stud ents and two teachers from 1 illagcs along 

the Beri ng Sea coast of Russia in techniques for the 

collection of SllO\\ samples for later analysis of the merctir) 

content. The chie f'' ill similarly train a number of nati\ e 

students and teachers from the North Slope of Alaska. The 

project is a 5-) r effort funded by the U.S. State Department 

and the U.S. Ell\ ironmental Protection Agcnc) (EPA) 

through BASC to determine the extent and SC\ crit) of 

mcrcur) pollution in Bering Sea coasta l areas of Alaska and 

Russia. i\lercur) found in the milk of nati\ e subsistence 

hunter mothers is belie,ed to ha\t: its origins in pO\\er plant 

plumes Oo\\ ing into the Arctic from lower latitudes. 

In the middle of 200 1 Internet sen ice to BRW. supplied 

b) the U.S. Department of Encrg) (DOE) Atmospheric 

Radi ation i\1easurement (A RM) program, \\3S reduced from 

1-1 to 256 K scr\'icc when the cost of a T- 1 connection 

increased 560°·0. As a consequence. access to man) I\ eb 

pages needed for efficient station operation is no longer 

possible. A return to T-1 connecti\ ity is being pursued . 

In 2000-200 I. 232 \ isi tors to BR\\' signed the guest 

book. including the acting admin istrator of NOAA and 

documenta1") tele\ ision crt:\1 s from England and Japan. The 

communit) of Barro\1 hosted the Alaska Press11ome11 

con1 ention in 200 I. wh ich brought reporters from around 

the C1111ed States to Barro11. A group of journalists from 

the mee1111g 11sited BR\\ to gather in formation for their 

local nc11 spapcrs and magaLines. For one of man) resulting 

articles. BR\\ ll'as featured on the co\ er of Bio/ogr Dige.11. 

The Y2 K prob km turned Olli to be a 11011-1:\ ent for BR\\ . 

All data computers passed th rough the change of the year 

''1th no problems. One old office computer e\perienced 

some d1rtieulties. signaling that 1t 11as in need of 

replacement. 

7 

1. 2.2. PROGRA:\I S 

Table 1.2 lists programs for 2000-200 I at BR \\I as ''ell 

as cooperati\'e programs that operated in 2000-200 I and 

that are appro1·ed for 2002. l li ghlights of the programs are 

as follo11 s: 

Gases 

Carbon dioxide. The CO~ system continues to ha\'e 

problems associated \\'ith aging components. The Siemens 

Ultramat 5-E analyzer is showing signs of a temperaturedependent signal. The solution has been to leave the door 

to the rack open for better airflow around the in strument. 

Flask samples. Flask samples 11 ere collected as a\'a ilable 

and as schedul ed '' ith no major problems. Isotopic 

composition measurements of co~ continue, and data from 

this program can be fou nd else\\ here in this report. 

Methane. The llP-6890 gas chromatograph (GC) 

continues to run \\'ith 1 er) fc1\ problems. Data show a 

clear!) defined annual frequency. '' ith higher rnlucs 

occurring in the " inter months and lower \ a lues in the 

summer. 

Total column o:one. Dobson spectrophotometer no. 91 

ra n well the entire period with no major problems. Regul ar 

cal ibrations \\'ere performed to maintain data qualit) at a 

high standard. A nois) bearing 11 ill be repaired 11 hen the 

BR \V instrument is sent to Boulder in 11 inter 2002 for 

reca li bration. Dobson measurements are not possible 

during the \\'inter months because of the lack o f sunlight. so 

no measurements 11 ill be missed during the recalibration of 

the instrument. Column ozone \alues as hi gh as -WO 

Dobson units (DU) and \alucs as lo" as 290 DU 11ere 

recorded O\er the past 2 years. 

Carbon monoxide. A Trace Anal) tical GC has been the 

station instrument since 1991 and continues to run 11 ith 

minimal maintenance. The major 11 ork to the system this 

past year 11as replacement of the Ilg scrubber and the UV 

lamp. 

Halocarbons and other atmospheric trace species. The 

Chromatograph for Atmospheric Trace Species (CA TS J ran 

11 ell '' ith onl) minor problems. Fourteen compounds arc 

measured in situ \\ ith the CATS system. Th e most notable 

problem 01er the past 2 years \1as an inopcrati1e water trap 

that produced poor data on one of the four channels for a 

short period of time. J\ ft er the trap ''as rep laced. the 

instrument has run proper!). A flash heater for the cryocooler was replaced '' hen the old one burned out. 

I lalocarbon flask sampl es ''ere collected on a routine 

schedule and prO\ ide a comparison for 1n situ instrument 

performance. The) a lso enable analysis of chemical 

species that arc not measured in the field. 

Aerosols 

Arctic haze. air pollution from l:.urasia. continues to 

dominate the springtime aerosol measurements at BR\\'. 

The haze concentrations build up O\er ''inter follo11cd b~ 

declines in late spring earl) summer 11 hen persistent 

cloudiness rewrns to the North Slope. The a.:rosol 

equipment ran 11 el I for the entire 2000-200 I period 11 ith 

onl) minor problems. Personnel from Boulder performed 

annual maintenance and system calibrations. All data from 
TABLE 1.2. Summar) of t\lcasurcment Programs at BR\\' in 2000-2001 

GaH'' 

Program i\ leasureme111 

co_ 

co .. Cl I,. CO. and 1C 'c and 

'O 1' 0 of CO, 

Cll, 

Surface o, Total O, 

co 

1',0. CFC-I I. CFC-12. CFC-113. c11,cc1 .. 

CCI,. SF0 • llCIT-22. HCFC-21. 

llCFC-12-1. HCFC-1-llb. llCFC-l-12b. 

HCFC- I 52a. Cl I.Br. Cll11. CH1CI. Cl!,CI,. 

Cl ICI,. Cll, Br,. CllBr1. C,CI,. H-1 301. 

11-1211. llFC-1 3-la. C. H •. COS 

CFC-I I. CFC-12. CFC-113. N,O. CH1CCI.. 

CCI,. Cl l,Br. Cl l1CI. 11-1211. SF,. I ICFC-22. 

llCFC-l-12b. CHCk COS 

.·leroso/1 

Condensation nuclei 

Optical properties 

13 lack carbon 

Solar Rac/i(//io11 

Global irradiance 

Direct irradiance 

Albedo 

Ultra' iolet B irradiance 

Ultra\ iolet spectral irradiance 

Aerosol optical depth 

TerreHrial (/RJ Radia11011 

l;p\\elling and do\\ nwelling 

.\/eteorology 

Air temperature 

De\\ point temperature 

Pressure 

\Vind (Speed and direction) 

Precipitation 

Cooperu111·e Program.\ 2000-1001 

Total surface particulates (DOE) 

Precipitation gauge (USDA) 

:-lagnetic fields (USGS) 

COc. 11C. N,O (SIO) 

Cll, (Uni\. of Calif .. In me) 

O, in air (Princeton) 

CO_ flu, (San Diego State L'ni\.) 

Instrument 

Siemens Lltramat 5-E analyLer 

3-L glass llasl..s 

0.5-L glass llasl..s. through analyzer 

0.5-L glass llasl..s. P3 pump unit 

Carle automated GC 

Dasibi O/Onc meter 

Dobson spectrophotometer no. 91 

Trace Anal)tical GC 

850-ml. 2.5-L. or 3-L stainless-steel llasl..s 

,\utomated C \TS GC 

Pollak C'C 

TSI C1\C 

Three-\\ a' ekngth ncphclomcter 

Radiance Research PSAP 

Acthalometcr 

Eppley p) ranometers "ith Q and RG8 fi ltcrs 

Tracking p)rheliomcter 

Epple) p) rheliometer with Q. OG I. 

RG2. and RG8 filters 

Epp IC) p) ranometer 

NILU radiometer 

Yanl..cc U\ 'B radiometer 

Biosphcrical fiH~·"a' elcngth pho1omc1er 

Cartcr-Scoll four-\\ a\cleng1h sunpho10111e1cr 

Eppley p) rgeome1ers 

Thermistor. t\\ o le\ els 

i\ta,.-min. thermometers 

De\\ point hygrometer 

Capacitance transducer 

i\lcrcurial barometer 

R.i\I. Young aerO\ane 

Rain gauge. tipping bucket 

II igh-\ ol umc sampler ( I Ii ltcr "k· t l 

Niphcr shield. Alter shield. 1wo buckets 

Three-component flu:-.gate magnetometer and total field 

proton magnetometer 

Dechna1ion inclination magnetometer sample 

5-L e' acua1ed g lass flasks (3 flasks se1· t) 

Stainless-steel flash 

3-L glass llasl..s 

CO· and 11 ·0 infrared gas anal)7er and '>Onie 

anemome1er 

8 

Sampling Frequenc) 

Continuous 

I pair" k-1 

I pair" k· l 

I pair \\k·l 

I sample ( 12 min)·I 

Continuous 

3 day·l 

I sample (6 min)' I 

I pa1r\\k· 1 

I sample Ii" 

I day· I 

Continuous 

Continuous 

Continuous 

Continuous 

Continuous 

Continuous 

Discrete 

Continuous 

Continuous 

Co111inuous 

Co111inuous 

Continuous 

Cont111uous 

Continuous 

I day·t 

Continuous 

Conunuous 

Discrete 

Continuous 

Continuous 

Continuous 

I rno·I 

Con1111uous 

6 SCIS mo·I 

I SCI\\ k·I 

I set (3 mo)' I 

lpair\\k· 1 

Conunuou-.. checl.. 

'>itc I \\ k ·I 
TABLE 1.2. Summary of!\lcasurement Programs at BR\\ in 2000-2001--<:ontinued 

CooJ1ert11in! Progrt1111\ :!11110-:!IJO /-um111111ed 

:'l lagnetic fields (N,\ \'S\\ CJ 

\lagneiic micropu lsa1io11' (Lni'. of Tokyo) 

LV (NSf) 

Thaw depth 111 permafrost (SG~Y) 

Total \ 'OC and hea\) mctab 

(Hokkaido Uni' .) 

Atmospheric mercllr) (I- PA) 

A1111m,pheric mercur) <'0,\ \ ,\RL) 

Arctic coastal ice charac1e ri.,1ics 

(l,rti'. of Washington. Seallk) 

(began :!00 I) 

POES satellite transmission dm\Jtlink 

(NESDISJ (began :!001 l 

hder duck migration pallerns 

(Uni'. of ,\la>ka. lairbanks) 

(began 200 I ) 

Soil organic matter (Urm. of Alaska. 

Fairbanks) (began 200 I) 

Organochlorine con1a111111an1s 

(Oregon State Un i\.) (began 2001) 

Sno\\ radiation (Ji\IA i\IRI. Japan) 

(began 200 I) 

\lercury in sno\\ (Uni\. of /\lichigan) 

(began 200 I ) 

Cooperatit"e Program\ AJ1pro1·edfor !Oii! 

Persistent organic pollutants 

(Bauclle-Nonh" est Labs.) 

SuomiNel GPS mcleorolog) station 

(Uni\. of Ala ska. Fairbanb) 

NOAA Climate Reference 'ernork Station 

Dimelh) I sulfide (l.Jni'. of Alaska. 

Fairba nks) 

Removal n11.:chanisms of Arctic hate 

(\\'a)ne Sta te Cni' .) 

Optical proper!ies of Arctic ecosystems 

(California State Uni' .) 

lns1rumcn1 

1

1 lc sensors 

:'l lagnc10111e1er and casselle recorder 

U\ spectrometer 

Temperature probe 

Fi Iler samples 

:'1 lcrcur) 'apor monitors 

:'llcrcur) 'apor monitors 

Optical sensors 

J-m dish and rccei' er 

Radar and optica l obscnations 

Vegetation samples 

Air samples 

Albedo and relleciions from sno" 

Sno" samples 

ll igh-\olumc pump 

GPS water 'apor mcasunng station 

Global climate reference station 

Gas chroma tograph 

Aerosol samples 

i\luhispectral optica l sensors 

Sampling Frequenc) 

Con1111uous 

I (3 "k)" 1 

I scan (0.5 h ) 

Continuous 

I h-l 

Continuous. >pring 

Con1111uous 

( OnllnUOUS 

Continuous 

Seasonal 

Discrete 

Discrete" eek I) 

Con11nuous 

\\ 1n1er season 

Continuous 

Continuous 

Co1111nuous 

Continuous 

Continuous. "eckl) 

filler change 

Continuous 

Ji\IA i\IRI. Japan \leteorological Agencyii\le1corol ogical Research lns1i1u1e. 

the aerosol system are monitored directl y from Boulder in 

real time via the Inte rne t except the aetha lo me ter black 

carbon measurements that are lirst coll ected on lloppy dis ks 

before being tra nsferred to the aerosol program computer. 

Solar Radiation 

SC\ era I ne" solar radiati o n instruments were installed 

O\Cr the 2000-200 1 period to spec ifica ll y measure 

ultra,·iolet B (UV B ) radiation. One s uch in strument from 

Norwa). the Nor\\egian Institut e for Air Research ( ILU) 

UV B irradiance rad iomete r. \\as fou nd to be less than 

satisfactory fo r conditions in BR\V. A Yankee UV B 

rad iometer installed about the same time is operating up to 

design specifications. A third UV B spectral irradiance 

photometer. from Biospherical Inc .. a lso appears to operate 

9 

well. A new sunphotometer. the SP0-1 manufactured b) CarterScott. was insta lled in summer 2000 for testing. It \\as sent 10 

Boulder for calibration during the "inter and \\'as subsequent I) 

replac<:d "ith the SP0-2 in spring 200 I. The SP0-2 had a fc" 

problems \\'ith water leaking into the data control cable 

connector, but other\\'ise it worked well. 

In October 200 I a new albedo rack was insta lled in the 

clean-air secto r. 1110\ ing the sensors from I .2 m ( 4 fl) abm e 

g ro und le\ c l to 3. 7 m ( 12 rt). This affords a broader field of 

' ic" for the sensors. 

The majority o f data qualit) issues in the solar radiation 

program during 2000-200 I came from instrument grounding 

p roblems that produced nois) data. Complete replacement 

of groundi ng li nes on a number of instruments thed the 

p roblems. 
iH eteorology 

The meteorology system had some problems '' ith the 

tvletrabyte modules during 2000-200 1. One modu le lost its 

program and had to be reinitialiLcd. There were some 

problems '' ith the de\\ point sensor due to corrosion. and the 

sensor head \\'as repl aced. All other sensor probes were 

calibrated rind adjusted as needed. 

Cooperath•e Programs 

The largest ne'' program '' ris a sllld) funded by the 

NOAA Arctic Reserirch Office and unde rt aken by the 

NOAA Air Resources Laboratory (A RL) and CMDL 10 

continuousl) measure mercur) concentrations in air and the 

flux of mercury into and out of sno\\'. This program 

entailed installat ion and maintenance of instrumentation 

along \\'ith mounting of sensors on the roof of the main 

building. The program \\'il l continue to operate through 

2002 and possibly much longer. For 2 months each in 

spring 2000 and 200 I. the U.S. EPA operated complementary mercury in air and mercLll") flux stud ies at BR \V. 

The newest cooperati\'e program at BR \V comes from the 

NOAA Na tional Erl\ iron mental Satellite. Data. and 

Information Sen ice ( ESD IS) and consists of a satel lite 

downlink antenna (J-m diameter) lo col lect data from the 

Polar Operational En\ ironmcntal Satellite (POES) series of 

polar-orbiting satelli tes. This is not a cooperati\ e science 

program in the traditional sense. but the BR\V stat ion no'' 

has near-real-time access to polar \ ic\\'S of cloud. ice. and 

coastal conditions that will aid in the interpretation of data 

and the plann ing of measurement timetables. If this program 

prO\cs 10 be of high \alue 10 OAA 'ESDIS. a fcasibilit) 

study will be cond ucted 10 determine if a 13-m dish could 

be installed at BR \V to control the POES satellites. The 

imtallation of the 1 ESDIS facilities \\ ill C\Cntuall) 

necessitate T- 1 or T-J data transmission lines to the BR\V 

site. Th is ''ill benefit Cl\IDL in tha t the added Internet 

transmission capabi lities ''ill be made a\·a ilablc for BR \\I 

obsen ator) use. 

A number of relati\'el) short cooperati,·c programs 

operated at Barro'', such as a Uni,crsity of Alaska stud) of 

eider duck migration \\ ith a radar de\ ice mounted at the 

BR\V facility: a soil organic and '' inter CO~ n u, study. also 

from the Uni\ersit; of Alaska: Arctic \egetation studies b} 

the Uni\ersity or Colorado: and mercur; in sno\\ sampling 

b; a scientist from the Uni' crsit) of Michigan. 

An unprccede111cd number of coopcrati\e programs ''ill 

be coming to BR\V in 2002 and man; of them ha\C required 

the cons~ruction of nC\\ infrastructure in 200 I. For 

instance. a NOAA ARO-funded project to measure 

persistent organic pol lutan ts (POPs) in the atmosphere. 10 

be conducted by Ba11clle-North1,est Laboratories. Richland. 

\\"ashin!!ton. necessitated construction or an e\lension 10 

the filt~r platform and a small. enclosed filter-changing 

room. The platform C\lension required the insertion of four 

pilings 5.5 m ( 18 ft) into the permafrost. Another piling ''a~ 

installed 10 support a Global Positioning System (G PS) 

antenna for an Uni\ersit; or Alaska water \apor monitoring 

program. also 10 begin in spring 2002. Three more pilings 

were inserted 10 support ins1rumc111ation for a Climate 

Reference Net,,·ork (CRN) site to be installed b) the NOA/\ 

National Climatic Data Center (:-:CDC). also in spring 2002. 

10 

The long-term stability of BRW made the site an ideal place 

for CR instruments. Instrumentation from the University of 

Alaska to measure dimethyl su lfide in a continuous mode will 

be installed in late spring 2002. and a program from \Va; nc 

State Uni\ crsit; to measure radiochemicals in /\retie haze 

will also begin in late spring 2002. 

1.3. SA.\ IOA OBSER\'ATORY 

J. 1'.llCllALSKI. M. GAYLORD. A~D E. SA)'.Dl3ERG 

l.3.1. 0PERATI O:'\S 

American Samoa is located in the mi ddle of the South 

Pacific Ocean. about midway between Hawaii and e'' 

Zealand. The island is characteriLed by yerir-round warmth 

and humidi ty. lush green mountains. and the strong Samoan 

culture. 1'.1any changes occurred at the American Samoa 

Obscnatory (St-.10) during 2000-2001 . 

During the first hair of 2000 the ent ire station was 

cleaned and ornaniLed. Truckloads of trash. including 

broken instrume~lls. out-of-date spare parts and manuals. 

7000 pou nds or leaking lead acid batte ries. and a cabinet 

full of mostly unidentified. corroding hanrdous materials. 

''ere hauled 10 the appropriate disposal areas. Both the 

batteries and haLardous materials were disposed of b; the 

local ErHironmcntal Protection Agency (EPA) office. 

Data collection ''as made more reliable with the 

institution of ''eckly File Transfer Protoco l (FTP) data 

transfers and \\eet..ly data backups. Ne\\ daily check sheets. 

modeled after those at Barrow and South Pole. were created 

for al l instruments. 

Basic station maintenance was completed. including 

painting the llC\\ Dobson dome. and painting and 

weatherproofing the roof. \\'hich fixed the leaks. A nc\\' 

wood cro\1 n on the parapet was installed and painted. ew 

'' indo\\ glass replaced the old. yellowing Plexiglas in the 

main laboratory. The old meteorologicri l scaffolding tower 

''as dismantled and rcmo' ed. 

lmpro\emcnts in air sampling \\ere made with the 

mo\'emcnt of all instruments previously on the old 

scaffoldin!! 10,,er to the new Blue Sk; mobi le phone tower. 

The ne\\ ~owcr prO\·ides higher sample positions for the 

CMDL lla locarbon and other Atmospheric Trace Species 

( ll A TS) group and Adm need Global Atmospheric Gases 

bpcriment (AGi\GE) gas chromatograph (GC) intakes, and 

better positions for the meteorological wind and 

temperature sensors. The i\I iami Sea-Air Exchange 

l:xperimelll South Pacific Aerosol Nct\\Ork (SEASPA ) 

liltcr apparatus also was relocated to the top of the new 

t01\er. All data rind pO\\er cables were protected inside 

conduit connecting the I ludson building to the top of the 

lO\\ er. 

To further complete the sciemific impro,cments. all 

computers \\ere networked \\ith modern 10 basc-T cabli ng. 

and a data link between the lludson building and the main 

laboratory was installed. All computers can nO\\ share and 

copy Ii les. making it much easier 10 back up data 

throughout the laborator). 

Du;in!! 200 I facilities were significantly impro\ ed '' ith 

the completion of some major projects. The old. rolling 
carport was demolished and replaced with a ne\\. three-stall 

port. The ne\\ ca rport has the dual purpose or shad ing 

parked cars and supportin g the rehabilitated sola r 

photO\Oltaic (PV) array. The P V array. which \1as dormant 

for the last decade. was rehabilitated \\ ith a grant from the 

U.S. Department of Energy (DOE) th rough the American 

Samoa Go\ernment" s Territorial Energ) Office (TEO). a 

local agency supporting island-wide energy consen at ion 

and alternati\ e energy sources. With the he lp of people at 

TEO and the local Commun ity College, all the solar pane ls 

were refurbished and a grid-tied inverter 1\ as installed, 

\\'hich puts the solar power directl y into the station's main 

breaker panel. The solar-electric power suppleme nts the 

e lectricity demand whenever the Sun is shining and can 

pro\ idc up to 30°0 of daytime electricity demand. Along 

with the new carport and solar project, the old and 

disintegrating cedar shake on the station a1\ning \\as 

replaced \\ ith corrugated roofing material, matched to the 

color of the new carport. 

The last link for state-of-the-an scientific data collection 

at SMO is a real-time connection to the Internet. During 

200 I sign ifi cant progress was made in developing an agreement \\ ith the Pan-Pacific Education and Communication 

Expe rime nts by Satellite ( PEACESAT) program to con nect 

to its island-wide Internet education nell\ork. The 

agreement has been finalized and only needs to be signed 

and enacted. It is realistic to plan on real-time Internet 

service to the laboratory by the end of the second qua rt er of 

2002. 

Finally, the c hiefs and technician's ho uses 1\ere 

complete !) gulled and remodeled. The chief's house \\US 

remod eled by island contractors. supen ised b) the A rmy 

Corps of Engineers. The technician's house 1\as remodeled by the technician. and a ne\\ kitchen. bath. 

laundry. utility. bedroom. computer room. and li vi ng room 

were added. T\\'O new trucks, Ford Rangers \\ ith extended 

cabs. \\'ere acquired for obsenator) operations. The o ld 

Toyota and l\ litsubishi trucks were sold in a go\ernment 

a uction. The ne\\' hou ses and station \chicles \\ill make 

for a much more enjoyable lifestyle for employees 

working at SMO. 

For the near future. areas that need immediate allention 

inc lude replacement of the stairs down to the point and 

rehabilitation of the underside of the obscrrntory roof 1\ here 

the concrete is se\erely flaking off. 

1.3.2. PROGRAi\IS 

Table 1.3 summarizes the programs at Sl\10 for 2000-

2001. Operational highlights fo lio\\: 

Gases 

Carho11 dioxide. In situ monitoring and AIRK IT 

sampling continued \\·ithout interruption during this 

report ing period. 

Surface 0:011e. In si tu monitoring \\ ith the Thermo 

Ell\ ironme111al Instruments (TEI) ultra\ iolet (UV) photometric 01one analyzer continued uninterrupted throughout 

the reporting period. 

Total 0:011e. The Dobson spectrophotometer continued 

to operate rel iabl) during 2000-200 I. In October 200 I it 

II 

\\as sen t to Christchurch. 1C\\ Zea land. for an 

intercomparison and calibration. 

O:o11eso11de bal/0011s. \\'eekl) 07onesonde flights 

continued during this reporting period 11 ith the 1 ational 

Weather Sen ice (N\\IS) balloon inflation facilit) at the 

Tafuna airport. 

Ha/ocarho11s all(/ other atmospheric trace species. The 

Chromatograph for Atmospheric Trace Species (CA TS) 

operated throughout this reporting period. and the 

Radiati\'e ly Important Trace Species (RITS) system was 

retired on September 29, 2000. 

Aerosols 

The only aerosol-measuring instrument at Samoa is a 

Pollak condensation nucleus counter (CNC). Daily Pollak 

obser1'3lions \\'Crc conducted in 2000-200 I. although a 

significant \·ah e leak prevented observations in late 200 I. 

pending arrival of replacement pans. 

Solar Radiation and Metenrology 

The solar radiation and meteorological instrume111s 

continued to operate throughout the reporting period. In 

early 2000 the meteorological instruments 11 ere 

repositioned o n the ne\\ mobile phone tower after the old 

meteorolog; sea ff old ing to\1 er was re mo\ ed. 

Cooperatii•e Program.\· 

A complete list of SMO cooperative projects is gi\'en in 

Table 1.3. A ll operated \\'ithout significant problems during 

2000-200 I. One ne\\ project I\ as added in May 200 I. the 

U.S. Geological Survey (USGS) Evapotranspiration Study. 

\\'hich is designed to measure the combined loss of water 

from the Earth via e\aporation and transpiration. Fo r this 

program a small monitoring station \\aS set up on the 

grounds of the obsenatory and 11 ill remain there un til ~lay 

2002. 

1.4. SOUTll POLE 0BSER\'ATO IH ' 

D. Nt:H. P. ROBERTS. A. Ct \RKt, J. MICHALSKI. 

E. s "DBERC1. "[) B. llAL Tl R 

l.4.l. 0PERATIO~S 

The CMD L South Pole Obsenatory (SPO) is located at 

the geographic somh pole on the Antarctic plateau at an 

elevation of 2838 m abo\e sea le\cl. The majority of 

CMDL SPO projects arc housed \\'ithin the Atmospheric 

Research Obsenatory (ARO). a National Science 

Foundation (NSF) facility that is used in support of 

scientific research related to atmospheric phenomena and is 

pan of the o\·erall Amundsen-Scott South Pole Station. The 

C l\1 DL SPO projects \\ere pre\ iously located at the 1101\· 

demolished Clean Air Facilit) (CAF). and the C~IDL 

obsenatory at ARO is still often referred to as the CAF. 

Amundsen-Scott South Pole Station is an i111egral pan of 

the U.S. Antarctic Program ( USAP). I\ hi ch is funded and 

managed by :\SF. ~lost of the administrati\C. logistical. 

and operat ional support for USAP is pro\ ided b) pri\·ate 

business under contract to NSF. The current prime support 

contractor is Ra) th eon Polar Sen ices (RPS). Antarctic 
TAB LE 1.3. Summary of Mea surement Programs at SMO in 2000-200 I 

Ga>e.1 

co, CO, . CH, 

Program i\lca>urcmcnt 

co,. CH,. CO. and " C. " O of co, Surface O , 

Total 0 3 

O , profiles 

, ,0. CFC-I I. CFC- 12. CFC- 11 3. 

Cll,CC!i. CCIJ. SF6 • HCFC-22. 

llCFC-1.Jlb. HCFC-142b. HCFC-21. 

HCFC-124. HFC- 134a. ll FC-152a. CI U3r. 

Cl l;CI. C H31. CH,Cl c. CHCl3. C,CL. 

H-1301 . H-1 211. Cl lBri. Cll1Br, . 

c..11 •. cos 

CFC-I I. CFC-12. CFC-113. N, O. CCI,. 

11-1211. CIJ;CCl 3• SF0 • HCFC-22. 

CH1CI. CH3Br. COS. HCFC-142b. CHCl3 

:-: ,o 

Aero10/1 

Condensation nuclei 

Solar Radi{lfio11 

Global irradiancc 

Direct irradiance 

Diffuse irradiance 

Terre.11rial (/RJ Radia1io11 

DO\\nwcJling 

,\fe1eorolog1· 

Air temperawre 

De\\ point temperature 

Pressure 

Wind (speed and direction) 

Precipitation 

Coopera/il'e Progra111I 

CO, . JJC. N, O (SIO) 

CO, . O, . , , (S IO) 

C HJ. N,O. CHCI;. CFC- I I. CFC-12. 

CFC- 113. CCIJ. Cl l,CCl3 (NAS/\-AGAGE) 

Instrument 

Siemens Ultramat-5E anal)LCr 

0.5-L g lass tlasks. through ana lyzer 

2.5-L glass tlasks. AIRKIT 

TEI UV photometric ozone analyzer 

Dobson spectrophotometer no. 42 

Balloonborne ECC sonde 

2.5-L glass tlasks. AIRK IT 

850-mL. 2.5-L. or 3.0-L stainless-steel tlasks 

CATS four-channel automated GC 

Shimadzu automated GC (ended 9 00) 

Pollak CNC 

Epple) p) ranometcrs \\ ith Q and RG8 Ii ltcrs 

Eppley pyrheliometer \\'i th Q filter 

Eppley p) rheliometcr "ith Q. OG I. 

RG2. and RG8 filters 

Epple) pyranometers "ith shading disk and Q filter 

Eppley pyrgeometer 

Thermistors (3) 

Polished mirror 

Capacitance transducer 

i\lcrcuria l barometer 

R.i\I. Young Windbird 

Rain gauge. tipping bucket 

Rain gauge. pla stic bulk 

5-L t!\acuated g lass llasks 

5-L g lass tlasks 

II P5890 Seri es II 3 channel gas chromatograph 

Total suspended particulates ( DOE) lligh-rnlume filter sampler 

Total suspended particulates (SEAS PAN) High-\'Olume filter sampler 

Light hydrocarbons (Univ. of California. Irvine) 1-L evacuated stainless steel tlasks 

o, (Princeton Uni'.) 2.5-L glass tlasks 

11 ,0 budget (USGS. Samoa EPA) E'apotranspiration pan 

SIO. Scripps Institution of Oceanography. 

Sampling Frequcnc) 

Continuous 

I pair wk' 1 

I pair" k'

1 

Continuous 

4 day· 1 

I wk· 1 

2 pairs mo·' 

I pair wk' 1 

I sample h·' 

I sample h' 1 

I day·

1 

Continuous 

Continuous 

Discrete 

Continuous 

Continuous 

Continuous 

Continuous 

Continuous 

I \\'k·

1 

Continuous 

Continuous 

I day'1 

I trio" k· 1 

2 trios mo·' 

3 h'

1 

Continuous (I filter \\'k. 1

) 

Contin uous (I filter wk' 1

) 

3-4 tlasks qtr' 1 

I pair l\'k· 1 

Continuous 

Support Assoc iates (ASA) was the prime contractor from 

April 1990 through March 2000. 

The ARO faci lity is located approximately 500 m grid eastnorthcast of the new e levated station. physically separated 

and genera lly up\\'i nd of all other station facilities. (Grid 

north. g rid 0° 360°. is defined as parallel to and 111 

the d irection of the prime meridian from the South Pole; 

Greenwich is situated grid north of South Pole Station.) 

The A RO building is located at the \ertex of an obtuse 

angle, \\'ith sides aligned to grid 3-l0° and grid 110°. which 

define the Clean A ir Sector (CAS). The prevailing winds at 

Sou th Pol e are from the CAS more than 90% of the lime. 

12 
The CAS was established to preserYe the unique 

atmospheric and terrestrial conditions from South Pole 

Station influences. Except for special circumstances. access 

to the C AS is prohibited, allo\\ ing for nearly continuous 

measurement of trace constituents of the atmosphere in a 

locat ion remote from anthropogenic sources and sinks. 

CM DL · s stratospheric ozonesonde program is conducted 

from the Balloon Infla tion Facility (B IF). which is located 

grid south (generally dO\\nwind) of the ne\\ elernted 

station. This facility is shared "ith the RPS meteorology 

staff and occasionally" ith other research groups. 

There are. for practical purposes. two distinct "seasons" at 

South Pole Station. The austra l summer season (November 

through January) and the austral winter season (February 

through October). Current staffing at the station exceeds 200 

persons during the summer season and is reduced to 

approximately 50 "wintcrovcrs" during the\\ inter season. 

The only USAP transportation to and from South Pole 

Station is on one of more than 300 "routine" Lockheed 

Martin LC-130 Hercu les aircraft flights during the austral 

summer season. These flights. currently flown by the I 09'h 

Airlift Wing of the Ne" York A ir National Guard, typica lly 

take place from late October to mid-February (station 

opening to station closi ng) each year. Occasional USAPcontractcd de Havilland DI 1-6 T\\ in Otter aircraft flights arc 

made to the station. mostly using South Pole as a stopo\'er 

during special programs. 

South Pole Station. including Ci\IDL 's observatory. is 

physically isolated from the rest of the world during the 

austral \\inter season. During this period. temperatures are 

generally too low, the weather too unpredictable, and the 

risk to hydraulic systems too great for aircraft to operate 

safely. An unprecedented Twin Otter "medevac" flight was 

made to the station in April 2001. but this capability cannot 

be re lied on in general. 

Due to the 9-mo isolation. air samples taken during the 

austral \\inter cannot be returned for analysis until the station 

reopens the following November. Howe\ er. communications 

and data access via satellite (including Internet connecti\ ity) 

are a\Uilablc for several hou rs each day throughout the year. 

Data collected in situ are transmiucd regular!) ' ia the 

Internet to locations around the world. 

During the austra l summer season the CAF usually 

receives a large number of Distinguished Visitors (DVs). 

Typical DVs are members of Congress and their staff. U.S. 

and N.Z. Embassy officials. U.S. military delegations. U.S. 

Executi\'e Branch delegations, members of the Na tional 

Science Board, ex-astronauts. and members of numerous 

nc\\ s organizations. 

The summer season at South Pole Station is marked by a 

variety of activities. re lati\ ely "warm" temperatures (about 

- 30°C average and sometimes as warm as I 5°C). and 

constant sunlight. The average temperature during the 

winter season is about -60°C, but temperatures can drop 

belo" -75°C on occasion. The Sun sets to\\ard the lauer 

pan of mid -March, twilight is generally significant through 

the middle of April. and the "inter night begins in earnest 

to\\ ard the end of April. The first faint signs of light from 

the Sun are c lea rly \'isible again in early August. preceding 

sunrise in the latter part of mid-September. Station life 

generally runs at a slo\\ er pace during the "inter season. 

13 

A RO El ectrical 

South Pole Station power is generally reliable. but 

outages and other problems occasionally do occur. ARO 

and BIF are equipped \\ ith uninterruptable pO\\Cr supplies 

(UPS) for some of the more sensiti\e equipment. However. 

in recent seasons. the buildings· UPS systems ha\e not been 

reliable. and individual UPS systems have been installed for 

most of the CMDL experiments. 

The ARO first-floor UPS system failed in December 

:moo. A replacement was installed within 2 months. but it 

also failed prior to carrying an electrical load. Sc' era I 

smaller UPS systems \\Cre shipped from CMDL in the 

interim \\hile NSf and Raytheon \\Orked to provide 

generalized UPS systems for ARO. The ARO second-floor 

UPS system has been inoperable for several seasons and 

continues to be unusable. A 30-kV A transformer was 

installed in February 2001 within ARO to supply power to 

temporary buildings occupied throughout the year by other 

atmospheric scientists. 

S tation Netll'ork/Co11111111nicatio11s 

Voice and Internet access to from South Pole Station are 

a\ ailable for sc,eral hours each "day" dependent on satellite 

coverage. equipment. and weather. Detailed technical 

information is pro\ idcd on the RPS \\Cbsitc 

(www.rpsc.raythcon.com) and on the NSF website 

(\\"" .nsf.go' ). The ARO Local Arca Network (LAN) is 

connected to the station-wide system, "hi ch is managed by 

RPS for NSF. Selected ARO computers are connected to 

this system for remote login and data retrieval. CMDL data 

retrieval is conducted through satellite connections. when 

available. 

0 11treaclz 

Unofficial visitors at South Pole Stat ion are rare. but 

outreach is possible through Internet connections and to 

some extent through the mail. School groups frequently 

write, curious about the Ii festyle and the science at the 

station. 

The number of 'isitors (official USAP and "nongovernmental") on record at ARO for the three reported 

seasons are 20 for the 1999 season, 5 7 for the 2000 season, 

and 40 for the 200 I season. 

The actua l numbers are slightly higher, because visitors 

occasionally slip through without signing the CMDL guest 

book. 

1.4.2. PROGRA:\IS 

Table 1.4 summarizes the programs at SPO for 2000 and 

200 I austral seasons. Operational high lights fol low for the 

1999. 2000. and 2001 seasons. Items mentioned refer to all 

three seasons except where otherwise noted. For specific 

operational details, refer to the monthly SPO station reports 

and the individual equipment chccksheets and digital logs 

a\·ailable from the CMDL Observatory Operations office. 

Gases 

Carbon Cycle. The Siemens continuous carbon dioxide 

ana lyzer ran with very few signi Ii cant problems. The 

analyzer's chopper lamp was replaced with a "mini-maglite" 
TABLE I .4. Summary off\leasurement Programs at SPO in 2000 and 2001 Austral Seasons ---------

Go\es 

CO: 

Program J\lcasurcmen1 

CO:. Cit,. CO. II:. N:O. SF •. 13C' 1:C of Cit,. 

and 'c :c. 'O 1•0 of CO: 

Surface o, Toial column 0 1 

OLOne 'erlical profiles 

CFC- I I. CFC-12. CFC-113. llCFC-2 1. 

llCFC-22. llCFC- 124, llCFC- 141 b. 

HCFC-1 42b. llFC-134a. HFC- 152a. ll-12 1 I. 

H-1301. C lliCI. Cll:CI:. C HCl3• CCI,. 

C H,CCJ;. C:CI,. CH1Br, Cll:Br:. CHBri. 

CH11. N:O. SF •. COS, C6H6 

CFC- I I. CFC-12. CCI,. Cit ,CCl3 • 1 :0 

CFC- I I. CFC-12. CFC- 11 3. HCFC-22. 

llCFC- 142b. 11 -12 11 . Cl'3Cl, CHCl 3• 

CC I,. ClhCCli. CH1Br. N:O. SF6. COS 

Aerosols 

Condensa1ion nuclei 

Optical proper1ics 

Solar R11dia1io11 

Global (toial) irradiancc 

Direc1 irradiance 

Di ff use irradiancc 

,\lbcdo 

Op1ical dep1h 

Terres/rial (/RJ Rmlia1io11 

Up" e lling and dO\\lmelling 

.\/ereorology 

r\i r 1emperature (2- and 20-m heigh ls) 

Pressure 

\\'ind (speed and d ircc1ion al I 0-m hei ght) 

Frost-poin1 temperature 

Coopermi1·e Progra1111 

CO:. " C. N:O (S IO) 

0 : N,. CO: (SIO) 

Surface Air Sampling Program (DOF F;\IL) 

(natural and an1hropogcni c radionuchdes) 

lnterhemispheric 1 'c i:c (CS IRO) 

(CO:. CH,. CO. II:. N:O. and 

'C :c. "o"•o of' CO: ) 

11:0: (Uni'. of Ari1ona) 

TFA (Uni\. or Ari zona) 

Ox)gen ismopcs (UCS D) 

Sulfur compounds (ISC ·\ Tl 

ln s1rumcn1 

Siemens non-dispersi'c IR analyzer (ended 200 1) 

Ll-COR system (began 200 I) 

2.5-L glass flasl-s. 1hrough analyze r 

2.5-L glass fl asks. J\I AKS pump uni1 

Dasibi and TEI surface 01onc analyzers 

Dobson spec1rophotomctcr no. 80 

Balloonbornc ECC sonde 

0.85-L. 2.5-L. or 3.0-L siainless-steel flasks 

2.5-L glass flasks. pump uni1 

Two RITS Shimad1.u GCs (ended 12.00) 

Au1oma1cd CATS GC 

Pollak CNC 

TS I CNC 

Four-'"a' cleng1h nephelomcter 

Eppley pyranomclcr "ith Q liltcr 

Eppley pyranomc1cr "ith RG8 lilter 

Eppley pyrhcliomctcr " i1h Q and RG8 liltcrs 

(tracking N IP) 

Eppley pyrhe liometer "ith Q. OG I. RG2. and RG8 

lilters (manua l lilter-\\ heel NIP) 

Eppley p) ranometer "i1h shading disk and Q lilter 

Eppley pyrano111e1er "i1h Q lilter (dm' n" ard facmg) 

Eppley pyrano111e1er \\ith RG8 liltcr (do"n"ard facing) 

Eppley pyranomc1er "i1h Q lilter (on 1owcr do" nward 

fa cing) 

SPO I -A multi\\ m el cng1h aureole sunpho1omc1cr 

T" o Eppley p) rgeometers 

Logan pla1inum resistance probe 

Setra capacili\ e pressure transducer 

lvlercuria l baromelcr 

R.J\1. Young wi nd monitor 

TSL dc"poinl hygro1hcrmomc1cr 

5-L evacua1cd glass llasks 

Pump uni1. 5-L glass flasks 

lligh-\olume pump and filters 

Pump unit. 0.5-L and 5-L flasks 

Su rface sno" sample collcc1ion 

Surface sno" sarnpk collecti on (200 I onl>) 

High-,olume pump and tilters (2001 on ly) 

ll igh-,olume pump and liltcrs 

1-L flasks (200 1 only) 

14 

Sampling Fre4ucncy 

Continuous 

Continuous 

I pair" k"

1 (2 mo· in 200 I) 

I pair \\k·

1 

Continuous 

3 sets da) ·

1 

- 3 wk· ', spring early 

summe r: - 1 wk·' . 

remainder of year 

2 pair mo·' (- I" and 15'

1

) 

I pair mo·' (- 1 S'h) 

I sample 1i·

1 

I sample 11·

1 

2 sel day· 

Continuous 

Continuous 

Con1inuous. summer 

Continuous. summer 

Con1inuous. summer 

- 3 sets day·

1

• summe r 

Continuous. summer 

Continuou s. summer 

Con1inuous. summer 

Conlinuous. sum111cr 

Con1inuous, summer 

Continuous 

Continuous 

Continuous 

I "k·' 

Continuous 

Con1inuous 

2 trios 1110· (- 1 '' and I S'h) 

2 trios 1110· ( I" and I 5'h) 

Continuous (4 lilters 1110· 11 

2pairs1110 ( l " andl 5'

1

) 

2 \\ k" 1 

I 1110· 1 

Con1inuous (I "k. ) 

Con1inuous (I mo· ) 

Periodicall) 
lamp from early !\l arch to late October 2000 in lieu of a 

standard spare. The zero-gas flo\\ was reduced in early 

April 2000 to conser\'c the supply, and old working-gas 

cylinders were used in li eu of 1ero gas from early May 2000 

o nward. In November 2000 the mini-maglite lamp was 

replaced with a ne" chopper lamp. The Siemens analyzer 

began to develop intermitt ent noise problems and 'oltage 

fluctuations early in 200 I and was replaced '' ith a new LICOR system at that time. 

Sample flasks \\ere filled through the analy7er twice per 

month during the 1999 and 200 I seasons and once per week 

during the 2000 season. Flasks were a lso filled once per 

week wi1h the l\1artin and Kitzis Samp ler (MAKS) portable 

pump unit. An external 12-V battery was connected to the 

l\IAKS unit in May 1999 to replace the standard internal 

batt ery that had fai led. 

~o e and ivater 1•apor. The Dasibi surface ozone 

analyzer operated conti nuously wi th no signi ficanl problems 

during the reported seasons. A second analyzer, 

manufactured by Thermo Environmenta l Instruments (TEI), 

was instal led in December 1999 and operated well. 

Preliminary results indicate the two instruments showed 

close agreement through the 200 I season. 

Routine measurements of tota l column ozone were taken 

three times dai ly during the austra l summer months with a 

Dobson total ozone spectrophotometer. \\'hene,·er possible. 

total ozone values were obtained in the austral winter with 

the Dobson and the full moon as the light source. 

The balloonbornc stratospheric ozonesondc program 

continued to run wcl I. During the annual austral spring 

early summer stratospheric ozone deplet ion, ozone profi les 

up to about 30 km were obtained about three times per week 

and up to once per da) during the total ozone minimum. 

Profiles were obtained once per week during the reniainder 

of the year. Se' eral special o7onesonde intercomparison 

flights were completed in Janua ry 1999. These flights we re 

part of a larger ozondesonde intercomparison program. 

Halocarbons and other atmosph eric trnce species. The 

custom-built Chroma1ograph for Atmospheric Trace Species 

(CATS) gas chromatograph (GC) and the cx1st111g 

Radiati\ely Important Trace Species (RITS) GCs were 

operated side by side 1hroughout the 1999 and 2000 

seasons. All instrumentation operated continuously except 

for the occasional repair or replacement of failed 

components. Routine maintenance and gas cylinder 

replacements caused \cry fe,, interruptions of GC 

measurements. Ultra-high purity (U I IP) air was used in lieu 

of calibration (CAL I) gas from earl) No,ember 1999 until 

the ne \\ CAL I cylinder arri,ed in the middle of February 

2000. The RITS GCs were rcmo\ ed. and the CATS gas 

select rnl\'eS ''ere replaced in December 2000. 

Sample flasks \\Cre fil led twice per month with the 

Halocarbon s and other Atmospheric Trace Species ( llATS) 

group flask pump. In addition. during austra l ''inter 2000. 

g lass flasks ''ere tilled once per month to be compared with 

the typical sam ples collected in stainless-steel flasks. Some 

species can be analyzed from air samples stored in glass 

fla sks that cannot be measured reliabl) from air sto red in 

stainl ess-steel flasks. 

15 

Aerosols 

The four-\\'a\ elcngth nephelometer suffered through a 

spate of problematic fi lter wheel motors. and except for the 

replacement of an electronics board and consequent 

reference calibrations. the instrument operated '' ithoul 

major problems during the 1999 season. The nephelometer 

operated continuously with no significant problems during 

the entire 2000 season. During the 2001 season the 

nephelometer was again problematic. and data collection 

was intermittent for most of the season even after extensi\'e 

repairs. Routine condensation nuclei (CN) measurements 

were carried out both seasons with the Pollak instrument. 

The Thermo Systems Incorporated (TS I) CN counter 

(CNC) operated with no major problems during the 1999 

season although SC\ era I minor repairs were necessa ry. The 

TS I CNC operated continuously wi th no significant 

problems during the entire 2000 season. A replacement TS I 

output module board was insta lled in Ma) 200 I to address 

discrepancies found between the TS I CNC front-panel 

readout and the corresponding va lue recorded by the 

Campbell Scientific Inc. (CSI) acquisition module. 

Solar and Terrestrial Radiatio11 

The instrumentation ran with no significant probl ems 

during the reported seasons. though occasional noise in the 

signal lines remained an issue . The majority or 

instrumentation is disconnected during the ''inter months. 

i\l ay to September. but the terrestrial radiation in struments 

arc ty pically left operat ional year-round. The 

instrumentation ''a~ connected to a single-point electrical 

ground d uri ng the 200 I 5eason to add ress pro blems wi th 

noise pickup. 

The albedo rack was raised in December 1999. A ne\\ 

precision spectral pyranometer (PSP) was installed on a 

boom suspended from the OAA meteorolog) tO\\ er in 

January 1999. Se\eral schedu led instrument replacements 

''ere made during austral summers 1999-200 I. The SPO I-A 

au reole sunphotometer was operated at SPO from late 

December 1999 to late January 2000. from mid-'\/o\ ember 

2000 to late March 2001. and again from late September 

200 I throug h mid- 1o\'ember 200 I. 

M eteorology 

The meteorolog) instrumentation operated cont inuousl) 

'' ith no significant problems. Daily weather obsen at ions 

were recorded. and spec ial obsen·ations \\ere taken. '' hen 

possible. if conditions changed significantly. 

The temperature and ''ind sensors on the tower were raised 

in early February 2000 and aga in in February 200 I to 

maintain the \Vi\ 10-recommended height specifi cations abo' e 

the e\ er-rising snO\\ surface. The sensors were calibrated 

and inspected during the February 2000 maintenance. 

Coopernt fre Programs 

Scripps Institution of Oceanography (SIO). Sample 

fla sks were filled twice per mo nth for later ana lysis at SIO. 

l'.S. Department uf Energy/£111•iron111ental Jlea.rnrements Laborato1:1' (DOEIEML). The Surface Air Sampling 

Program (SASP) pump ran continuously '' ithout significant 
problems. Sample filters \\Cre changed once per \\'eek. and 

a sample blank \\'as co llec1cd mon1hly. 

Co111111011wealth Scientific and flldustrial R esearch 

Orga11b1tio11 (CSJRO). Sample nasks \\'ere filled t\\ ice per 

mon1h for la1er analysis by CS IR O. 

U11il'ersity of ri~n11a. Sno'' samples were obtained and 

snow heigh1s were measured from a "sampling g rid " inside 

1hc Clean Air Scc1or "eekly during the 1999 season. 

Groups of s urface snow samples \\'ere obtained 

appro:-.imaiely SC\ en limes each month during the 2000 and 

200 1 seasons. Sno" samples were also collected mon1hly 

during 1he 200 I season for 1ri nuoroace1a1e analysis. 

Unii•ersity of California, Sa11 Diego (UCSD). Weekly 

rooflop filter samples were collected during 1hc 200 I season 

beginning in February 200 1. 

l111•estig ation of S ulfur Ch e111ist1:1· in the A11tarctic 

Troposphere (/SCAT). Fort y-e ight ai r samples were 

collecled in 111e1al sampling cans periodically throughou1 the 

200 1 season. Rooflop filter samples were collected weekly 

until February 200 1. A significanl number of air samples 

were also collected during 1he 1999 and 2000 seasons. 

though no filler samples were collected then. 

1.5. METEOROLOGICAL MEASURE:\IE:\'TS 

T. ME~roRD 

1.5.1. METEOROLOGY 0PERATIO:\'S 

Introdu ction 

The climatology o f surface meteorological observations 

at the four CM DL obscna1ories is based on hourl y a\crage 

measurements of the pre\ ai ling wind direction and speed. 

barome1ric pressure, ambient and dewpo int temperatures, 

and precipitation amounts. The meteorological sensors in 

use we re selected for their high accuracy as well as 1heir 

ability to \\'i thstand the extreme conditions of both the 

tropics a nd polar regions. Data is recorded as I-min 

averages so that the variability \\'ith in the hourl y a\·erages 

can be determi ned . To the extent that is possible, World 

i\le1eorological Organization (\Vi\10) si1in g standards 

[ WMO. 1969] are follo\\'ed. Thermo meters are a lso 

posi1 io ned at the top of 1he sampl ing IO\\ers at the Barrow 

Observatory (BR\V), Mauna Loa Observatory (MLO), and 

South Pole Observatory (SPO) to measure the temperature 

gradient and 10 determine the s1ability of the surface 

boundary layer. 

Pe1erso11 a11d Rosso11 [ 1994] gh e a detailed description of 

the PC-based data acquisition system. Table 1.5 describes 

1he Ci\IDL instrument deployment as of December 3 1. 

200 I. 

Data i'11a11age111ent 

The meteorological data acqu1s11 1on system ga1hcrs data 

from sensors that operate cont inuo usly at each of the four 

Ci\ID L obscrva1orics. Data arc transferred from the 

obser\'alorics to Boulder daily 'ia 1he ln1crnet. except for 

the Samoa Obsen·atory (SMO). whose data arc transferred 

10 Boulder "eekly. Preliminary hourly a' erages of 

prevailing ''ind direction and speed. barometric pressure, 

ambient and de\\ point 1empcra1urcs. and precipitation 

16 

amounts are sent to 1he stations daily. exccp1 for Si\10. 

which are sent \\'Cek ly. 

A comparison of the number of data poin1s recorded 

against 1ha1 e\pec1cd for 1he year ''as used to monitor each 

system· s performance. Table 1.6 sho\\ s the performance 

for each slat ion in :WOO and 200 I. On a\'crage. the 

meteorological data acquisi1ion system combined for the 

four ob sen atories operated 92.65% and 91. 92% of the time 

for 2000 and 200 I. respccli\ely. Because of the remo1eness 

of 1hc obscrrntories. po'' er outages arc common and arc the 

main reason for data loss. Hard\\ are failure. system 

restarts. and sys1em maintenance arc the other reasons. At 

BR\V. during the ''inter. rime ice and sno\\ occasionally 

build up on the sensors and ha\·c to be removed manually. 

1.5.2. STA.TIO:\' C Lii\I ATOLOG IES 

The 25-yr s1a1ion climatologies are an im portant record 

for the interpreiation of measured 'alucs of aeroso ls. trace 

gases. aimosphcric 1Urbidi1y. and solar radiation, and the 

long-term c hanges in the records themselves. and they serve 

10 ou1line periods of local contamina1ion. 

Barrow 

In Figure 1.1. "ind roses of hourl y a\'erage prc\'ailing 

wind direction and ''ind speed (\VS) at BR \\I are presen1ed 

in 16 direction classes and 3 speed classes. Winds from the 

"clean air" sector. north-nor1heas1 to southeasl. occurred 

62.6% of the time in 2000 and 64.0% in 200 1 compared 

with 61.-l"'• for 1he 23-y r period from 1977 through 1999 

(Figure 1.2). Wind speeds in excess of 10 m s·

1 in 2000 

(11.4%) \\ere more frequent than for 1he 23-yr climato logy 

(I 0 .8%), whereas in 200 I (7. I%) they were less frequent 

than in the 23-yr climatology. The average \\ind speeds of 

5.8 111 s·1 in 2000 and 5.5 m s·1 in 200 1 (Table 1.7) \\Crc 

sligh1ly below the long-term a\eragc (6.0 m s· 1

). 

The average air temperatures of - I I .5°C in 2000 and 

- I I . 7°C in 200 I (Table I. 7) \\'ere bo1h \\'armer than 1he 

c limatological average of-12.2 °C. The barometri c pressure 

in 2000 was 0.5 hPa abo\e the 23-yr a\'eragc of 101-l. I hPa. 

and the average for 200 I was 0.4 hPa below the 

c li ma1ological average. i\lay and August 2000 recorded 

new record-high baromelric pressure read ings for 1he 

respcc1i' c 111on1hs. The summcr1irnc precipitation amoun1s 

for 2000 (63 mm) and 2001 (57 mm) \\Cre abo\'C 1hc longterm a\·erage o f 39 mm. 

,\,fauna Loa 

The c limatology of MLO is best understood when it is 

considered in l\\'O dis1incti\e "ind regimes. 1he night 

(downslope) period o f 1800-0559 1 la\\'aiian S tanda rd Time 

( HST) and the day {upslope) period of 0600-1 759 HST. 

The 23-yr ( 1977- 1999) night and da y \\'ind charts il lustrate 

the two distincl wind regimes (Figure 1.3 ). 

For the night regime at M LO. the 23-yr \\'ind rose (Figure 

1.3) shows tha1 89.9% o f all ''inds obsened had a southerly 

component. The percentage occurrence of sou1hcrly '' inds 

\\'as 89.4°0 in 2000 (Figure 1.-l) and 90.1°0 in 2001 (Figure 

1.5). Pressure-gradient-controlled ''inds (\VS~ 10 m s· 1i 

from predominan1ly wes1erly and sou1heas1crly direc1ions. 

occurred 5.0°'o of the time in 2000 and -l. 7°0 in 200 I. both 
TAB LE 1.5. CMDL Meteorological Sensor Deployment December 3 1, 200 I 

Sensor 

Primal) anemomctert 

Secondary ancmometert 

Pressure transducer! 

:>lercurial barometer 

Air temperature A~ 

Air temperature " 

Air !Crnperaturc C* * 

De\\ poi Ill temperature 

Rain gauge 

BR\\' 

Serial Ele,ation• 

No. (m) 

14584 10.5 

374 199 9.5 

641 9.5 

2.4 

15.7 

2.9 

GOOOI 2.9 

--1 

Sena I 

No. 

23186 

15946 

374198 

278 

G0004 

.\ILO 

Elc\ation• 

(Ill) 

10.2 

38.2 

3398.4 

3398.4 

rn 

37.4 

2.0 

rn 

0.8 

S\10 

Serial Elc,·a1ion• 

No. (m) 

15945 22.9 

374200 78.5 

961 78.5 

18.9 

18.9 

18.9 

G0008 18.9 

--1 

SPO 

Seria l Elc\ at ion• 

No. (m) 

14583 10.3 

358960 2841.0 

1215A 2841.0 

1.6 

22.0 

2.0 

G0007 2.0 

*l lcights arc in meters abm c surface. except for the pressure transducer and mercurial barometer. \\'hi ch are with respect 10 mean sea level (i\ ISL). 

t Propellcr ane1110111c1cr, model no. 05103. R. i\I. Young Company. Tra,ersc Cit). i\lichigan. 

! Pressure transducer. model no. '.:!70. Setra S) stems. Acton. i\ lassachuscus. 

§Platinum resistance probe. Logan 4150 Series, Logan Emerprises. Liberty. Ohio. 

' 1 hermometcr. positioned at the top of the local sampling lO\\er 10 faci litate an estimation of boundal) layer stability. except at SMO "here both 

sensors "ere at the same height. 

••1 trnro1hennome1er. model no. I 088-400. Technical Sen ices Laboratol). Fort Wahon Beach. Florida. 

TABLE 1.6. CMDL l\1eteorological Operations Summary 

Station 

BR\V 

MLO 

S\10 

SPO 

A\crage 

BR\\ 

i\1LO 

Si\10 

SPO 

E:-.pected Number Data 

of Data Points Capture(%) 

4.216.320 

6.851.520 

4.216.320 

4.216.320 

·L:!04.800 

6.832.800 

4.204.800 

4.:!04.800 

](}(}() 

98.36 

91.55 

83.95 

96.74 

92.65 

1001 

97.34 

86.82 

93.43 

90.10 

91.92 

;\umber of \lissing 

Data Poims 

68.959 

579.028 

676.523 

137.395 

111.693 

900.727 

276.424 

-ll6.135 

of "hi ch "ere be lo'' the 23-yr a\erage o f 6. 9%. The 

annual average wind speeds for 2000 and 200 I were both 

bclo" the long-term a' erage (Tables 1. 8 and 1.9). The 

upslo pe. or northerly co mponent, winds (north-northwest 

through cast-northeast) that occurred 4.8°10 of the time in 

2000 and 3.9°0 in 200 1 are the result of the daytime upslope 

no\\ extending into the early evening hours. 

For the day regime at M LO. the 2000 and 200 I wind 

roses (Figures I.~ and 1.5) indicate that "inds from the 

west-northwest through east-southeast occurred 72.60.. of 

the time in 2000 and 7 1.5% of the time 2001 , com pared 

"ith 60.2% for the 23-yr climatology (Figure 1. 3). 

Pressure-gradient-controlled winds (\VS <:: 10 m s· 1

) 

occurred 3.60.. of the time in 2000 and 200 I. both of which 

17 

were lower than the climatological average o f 6.9°,o. In 

2000 and 200 I the pressure gradient "inds. which are 

usually associated "ith storms, fo llowed the expected 

pallern of fewer occurrences during the day regime. The 

day wind chart is more uniforml y distributed in the lightwind classes than the night \\ind chart. This is due to the 

occurrence of' ariable "ind directions during the transition 

periods at dawn and dusk. most of which are included in the 

da y regime. 

The a\erage ambient temperature for 2000 (Tab le 1. 8). 

combining both day and night regimes, was 7.1 °C, whi ch 

equals the long-term a' eragc of 7. I °C. whereas the 6. 7°C in 

200 I (Table 1.9) was below the long-term a\'crage. The 

ayeragc barometric pressure for 2000 (680. 1 hPa) was 

be lo" the c limatological average of 680.5 hPa. whereas for 

2001 (680.4 hPa) it was near the climatologica l a\erage. 

June 2000 tied the record minimum pressure rnluc for the 

molllh, and January 200 1 set a new maximum barometric 

pressure record for the month. The tota l precipitation 

amount in 2000 (212 mm) was considerably be lO\\ the longterm a\'erage of 352 mm. whereas in 200 I (359 mm) it was 

slightl y above the long-term average. 

Samoa 

A comparison of SMO"s 2000 and 200 1 wi nd roses 

( Fi gure 1.6) to the wind rose of the 23-yr period (Figure 

1.7) shows a considerably higher percentage of "clean air" 

sector winds (north-northwest through southeast) in 2000 

(77.6%) a nd 2001 (73 .4%) than the long-term a\crage of 

58.5%. The occurrence of winds in the I 0 m s· 1 or greater 

class \\US 9.8°0 in 2000 and 14.0°10 in 2001. whereas the 

expected occurrence based on the climatologica l average is 

5.0%. The annua l average wind speeds for 2000 (5.9 m s· 1

) 

and 200 I (6.0 m s· 1

) (Table I. I 0) were both abo\'c the longterm a\ erage of 5.0 m s· 1

• No "ind data arc arni labl e for 

January-March 2000 because of instrument problems. 
BARROW 

2000 

N WIND ROSE 

\ 

'>~J0' \ 

BARROW 

2001 

N WIND ROSE 

/ 

CALM 

-. 0.5\ - + lw t f ..: CALM I t El \ ~ l/-[5\ I \ \ \ \ ....-~ II """ \ 

-l 

s 

WIND SPEED (M/S) 

0.5 <= ws < 5 

---- 5.0 <• WS < 10 . 0 

---->= 10.0 

,, 

.., 

WIND FREQUENCY 

(HOURLY PERCENT) 

\ 

s 

WIND SPEED (M/S) 

-- 0 . 5 <= ws < 

---- 5.0 <= ws < 10.0 

---- >= 10.0 

I 

/ 

WIND PREQUENCY 

(HOURLY PERCENT) 

Fig. 1.1. Wind roses of the surface winds at BR W for 2000 (le fl) and 200 I (right). TI1e distributions of prevailing wind direction and speed arc given in 

units of percent occurrence for 16 direction classes and 3 wind speed (WS) classes. Percent frequency of calm winds (WS < 0.5 m s·') is indicated on 

the graphs. 

BARROW 

1977-1999 

/ 

/ 

N WIND ROSE 

T 

... , 

,.,/ ~ \. CALM .. - 1.0\ - -- + 

.,~ I , \ '!> " 

\ \ + 

s 

WIND SPEED (M/S) 

---- 0.5 <• WS < 

---- 5.0 <= ws < 10.0 

---- >• 10 . 0 

I 

I 

WIND FREQUENCY 

(HOURLY PERCENT) 

Fig. 1.2. Wind rose of surface winds at BR \V for 1977-1999. The distributions of prevailing wind direction and speed are given in units of percent 

occurrence for the 23-yr period for 16 direction classes and 3 speed classes. Percent frequency of calm winds (\VS < 0.5 ms·') is indicated on the graph. 

18 

J 

J 
Pre,•ailing wind 

direction 

A' eragc "'ind 

Jan. 

\V 

5.1 

14.7 

270 

10 11.9 

TABLE 1.7. BR\V 2000 and 200 1 Monthly Climate Summary 

Feb. !\larch April l\lay June 

ENE ENE E ESE ESE 

S. I 7.4 S.2 4.0 4.2 

11.8 14.3 14.5 9.0 13.S 

54 82 SS 113 230 

1014.6 101 7.7 1022.2 1017.3 1011.0 

July 

2000 

ENE 

S.3 

IS.2 

238 

10 10. 1 

Aug. Sept. 

E ESE 

6.3 S.I 

2 1.9 13.2 

25 1 346 

10 13.6 1008.6 

Oct. ov. Dec. Year 

NE ENE ENE ENE 

6.1 7.4 7.9 S.8 

14.5 20.6 18.3 2 1.9 

77 74 89 251 

1008.9 1014.9 1024.3 1014.6 

speed (m s·

1

1 

l\ taximum \\'ind 

speed* (m s·1

1 

Direction of max. 

wind* (deg.) 

Average station 

pressu re (hPa) 

l\laximum pressure* 

(hPa) 

1036.4 1032.1 1037.4 1037.6 1041.1 1029.6 1027.9 1035.8 1025.2 1022.3 1034.4 103S.7 1041.1 

I\ lini111u111 pressure* 

(hPa) 

979.6 997.6 1001.6 1004.8 1003.7 99S.O 99S.6 

Average air -25.0 

temperature (°C) 

l\laximum air tc111perature* - 11 .9 

(oC) 

Minimum air temperature* -39.2 

(oC) 

A veragc dewpoint 

1emperature (°C) 

Maximum de\\'point 

temperature* (°C) 

Minimum dewpoint 

temperatu re* (°C) 

Precipitation (mm) 

Prevailing wind 

direction 

Average wind 

speed (m s· 1) 

Maximum" ind 

speed* (m s· 1

) 

Direction of max. 

"ind* (deg.) 

-28.1 

-13.4 

-43.3 

0 

ENE 

7.7 

11.3 

6 1 

-26.6 -24.5 

-9.3 -1 S.O 

-41.1 -3S.7 

-29.7 -27.8 

- 10.6 -18.4 

-4S.9 -40.0 

0 0 

ENE ENE 

6.4 6.3 

16.2 13.2 

278 48 

-17.9 -9.5 1.5 

-4.6 -0.4 16.2 

-29.5 -22.5 -5.1 

-20.5 - 11.4 -0.1 

-5.5 -1.7 10.0 

-33.0 -24.8 -7.6 

0 2 11 

ENE E ESE 

S.6 4.0 5.0 

12.6 10.I I 1.9 

67 142 235 

2.9 

19.3 

-2.2 

1.6 

12.6 

-2.6 

3 1 

2001 

ENE 

5.2 

10.7 

237 

996.3 994.4 992.3 996.6 1009.2 979.6 

3.2 0.3 -7.2 - 16.3 - 19.8 -1 1.S 

15.3 12.7 0.3 -6. I - 10.0 19.3 

-1.6 -7.1 -18.3 -28.5 -3 1.4 -41.1 

0.3 - 1.8 -9. I - 18.6 -22.4 -14.7 

6.9 7.9 -0.1 -7.6 -11.4 12.6 

-3.0 -9.8 -20.I -3 1.9 -35.3 -4S.9 

14 5 0 0 0 63 

E E NE ENE ENE ENE 

5.7 S.I 5.4 5.7 4.4 5.5 

12.4 11.7 11.8 13.S 12. 1 2 1.3 

256 87 42 83 252 61 

A vcrage station 

pressure (hPa) 

Maximum pressure* 

(hPa) 

1009.7 1014.7 1023.4 1016.0 1017.3 1016.7 10 11.5 1007.7 1006.7 1016.9 101 3. 1 10 11 .0 101 3.7 

1029.8 1043.9 1046.9 1036.9 1031.2 1029.7 1024.S 1024.1 1017.8 1033.4 1032.0 1039.9 1046.9 

Minimum pressure* 

(hPa) 

981.6 988.8 997.0 

Average air 

temperature (°C) 

-23.3 

Maxi111u111 air temperature• -I 0.2 

(cC) 

Minimum air temperature* -33.2 

(oC) 

Average dewpoi111 

temperature (°C) 

Max imum dewpoint 

temperature* (°C) 

Minimum dc\\1ioint 

temperature* (°C) 

Prec ipitation (mm) 

-25.4 

- 12.0 

-3S.7 

0 

- 18.9 -26.5 

-S. I -1 5.8 

-33.5 -35.8 

-20.9 -29.3 

-6.2 - 18.0 

-36.3 -39.3 

0 0 

997.6 1006.6 100 1.6 995.3 

-16.7 -10.9 0.8 2.3 

-6.8 1.2 I I.I 19.9 

-32.4 -24.3 -4 .I -2.4 

- 19.1 -1 2.8 -0.6 0.3 

-8.8 -0.S S.9 12.8 

-35.2 -27.3 -5.7 -3.9 

0 0 2 30 

992.0 991.7 994.0 990.2 990.6 981.6 

1.7 0.1 - 11.9 - 16.4 -2 1.9 -11.7 

11.7 13.0 -2.4 -5.8 -S.3 19.9 

-2.0 -7.8 -24.5 -26.9 -3 1.6 -35.8 

-0.5 - 1.2 - 13.9 -18.9 -24.8 -14.2 

7.0 6.0 -3.5 -7.0 -7.1 12.8 

-4.0 -1 0.8 -27.3 -30.5 -36.0 -39.3 

20 5 0 0 0 S7 

Instrument heigh1s: wind. 10.5 m: pressure. 9.S 111 (MSL); air te111pera1ure. 2.9 m: dewpoint temperature. 2.9 m. \Vind and 1empcrature ins1mments 

are on a tower 2S m nonheast of the main bu ild in!!. 

*l\laxi mum and minimum va lue s are hourly averages. 

19 
HAUNA LOA 

1977-1999 

/ 

I 

N 

~ 

II 

'_J_ ~ 

• CALM ' 

rw 

1~ \ 

' 

' 

s 

WIND SPEED (H/S) 

---- 0 . 5 <= ws < 5 

---- 5 . 0 <= WS < 10 . 0 

---- >= 10 . 0 

WIND ROSE 

+ El I 

,, I 

,, 

WIND FREQUENCY 

(HOURLY PERCENT) 

HAUNA LOA 

1977- 1999 

WIND SPEED (H/S ) 

---- 0 . 5 <= ws < 

N 

s 

---- s.o <= ws < 10.0 

---- >= 10 . 0 

/ ,, 

' 

WIND ROSE 

WIND FREQUENCY 

(HOURLY PERCENT) 

Fig. 1.3. Wind roses of the surface winds at MLO for 1997-1999 night (left) and day (right). The distributions of prevailing wind direction and speed 

are given in units of percent occurrence for the 23-yr period for 16 direction classes and 3 speed classes. Percent freq uency of calm winds (WS 

< 0.5 ms·') is indicated on the graphs. 

HAUNA LOA N 

2000 

+ 

I 

~ 

lw 

' . , > 

. CALM _,.. 

I 

?/ ' 

s 

WIND SPEED (H/S) 

---- 0 . 5 <= ws < 5 

---- s.o <= ws < 10 . 0 

---- >= 10.0 

WIND ROSE 

El I 

WIND FREQUENCY 

(HOURLY PERCENT) 

I 

I 

HAUN A 

2000 

w 

WIND 

LOA N WIND ROSE 

/ 

/ 

..._ CALM

~ / ~ El 

,: ;t" I 

I 

,, 

,, 

s WIND FREQUENCY 

(HOURLY PERCENT) 

SPEED (H/S) 

o. s <= ws < 5 

5.0 <= ws < 10 . 0 

>= 10.0 

Fig. 1.4. Wind roses of the surface winds at MLO for 2000 night (left) and day (right). The distributions of prevailing wind direction and speed are 

given in units of percent occurrence for 16 direction classes and 3 speed classes. Percent frequency of calm winds (\VS < 0.5 m s·') is indicated on the 

graphs. 

20 
... 

I 

MAUNA LOA 

2001 

w 

WIND SPEED (H/S) 

N 

+ 

+ 

CALM 

2 . 1\ 

s 

0.5 <• ws < 5 

---- 5 . 0 <= WS < 10.0 

---· >• 10.0 

WIND ROSE 

.. 

WIND FREQUENCY 

(HOURLY PERCENT) 

MAUNA LOA 

2001 

WIND SPEED ( H/S) 

0 .5 <• ws < 

N 

s 

---- 5.0 <= WS < 10 . 0 

---->= 10.0 

WIND ROSE 

+ + 

WIND FREQUENCY 

(HOURLY PERCENT) 

Fig. 1.5. Wind roses of the surface winds at MLO for 2001 night (left) and day (right). The distributions of prevailing wind direction and speed are 

given in units of percent occurrence for 16 direction classes and 3 speed classes. Percent frequency of calm winds (\VS < O.S m s·') is indicated on the 

graphs. 

AMERICAN SAMOA N 

2000 

I 

w ~ 

I 

s 

WIND SPEED ( H/S) 

0 . 5 <• WS < 5 

---- 5 .0 <= WS < 10. 0 ---• >• 10.0 

WIND ROSE 

- E 

WIND FREQUENCY 

(HOURLY PERCENT) 

I 

AMERICAN SAMOA N 

2001 

' I I 

w ·'' CALM ~ 

s 

WIND SPEED ( H/ S) 

---- o.s <• ws < 5 

---- s.o <• ws < 10.0 

---- >= 10 . 0 

WIND ROSE 

' 

+ E l 

WIND FREQUENCY 

(HOURLY PERCENT) 

Fig. 1.6. Wind roses of the surface winds at SMO for 2000 (left) and 2001 (right). The distributions of prerniling wind direction and speed are given in 

units ofpercem occurrence for 16 direction classes and 3 speed classes. Percent frequency of calm winds (\VS < O.S ms·') is indicated on the graphs. 

21 
TABLE 1.8. MLO 2000 Monthly Climate Summa ry 

Pre\'ailing wind 

direction 

A'erage " ind 

speed (m s·11 

Maximum wind 

speed• (m s·1) 

Direction of max. 

wind* (deg.) 

A \'erage stat ion 

pressure (hPa) 

i\laximum pressure* 

(hPa) 

i\tinimum pressure* 

(hPa) 

Average air 

temperature (°C) 

Jan. Feb. i\ larch 

SE SSE SE 

-1.-1 5.6 6.2 

13.8 16.8 15.2 

154 15-1 155 

678.3 680.9 679.7 

683.0 683.9 682.S 

673.7 678.5 676.2 

2. 1 4.3 3.3 

Maximum air temperature* 7.9 

(oC) 

10.2 9.9 

Minimum air 1cmpcrature* -2.6 

(oC) 

-0.5 -1.8 

Average de\\ point 

temperature (°C) 

Maximum dewpoint 

temperature* (°C) 

Minimum dewpoint 

temperature* (°C) 

Precipitation (mm) 

Prevailing wind 

direction 

A\'eragc wind 

speed (m s·1) 

Maximum wind 

speed* (m s·1) 

Direction of max. 

wi nd* (deg.) 

Average station 

pressure (hPa) 

Maximum pressure* 

(hPa) 

Mi nimum pressure* 

(hPa) 

Average air 

temperature (°C) 

-12.8 -15.3 -16.9 

3.1 3.8 1.9 

-30.8 -33.8 -30.5 

0 0 

NW SE SE 

-1.3 5.0 6.1 

13.3 13.0 1-1.8 

152 141 143 

678.2 680.9 679.7 

682.9 683.6 683 .2 

673.4 678.-1 676.3 

5.2 8.6 7.5 

Maximum air temperature* I 1.6 15.0 14.3 

(oC) 

Minimum air temperature* -2.3 

(oC) 

Average dewpoint 

temperature (°C) 

Maximum de\\ point 

temperature* (°C) 

Minimum dewpoint 

temperature* (°C) 

Precipitation (mm) 

-8.2 

8.0 

-31.2 

4 

0.2 -1.-1 

-12.3 -11.9 

5.3 5.6 

-29.7 -29.4 

7 0 

April i\tay June July Aug. Sept. Oct. 

Nigh1 

SSE SSE E SSE SE SE SE 

5.5 -1.5 -1.0 3.9 -1.2 3.0 4.2 

13.0 12. 1 13.6 12.5 9.2 9. 1 12.6 

158 170 157 155 1-10 152 152 

679.9 680.8 680.1 680.7 680.-1 680.3 680.1 

W.2 5 W.1 W.S W.3 W2 W~ 

675.3 677.6 676.7 678.0 677.5 677. 1 677.8 

4.9 6.9 6.9 6.4 6.7 6.7 5.3 

11.0 12.1 13.7 13.1 12.3 11.2 10.9 

-2.3 2.7 0.6 3.2 2.5 1.9 1.7 

-19.3 -13.5 -16.1 -7.0 -11.-1 -6.7 -8.6 

2.7 3.1 6.2 6.9 7.8 7.7 7.1 

-35.9 -29.3 -30.8 -19.4 -3 1.5 -27.0 -28.1 

0 0 0 0 0 

Om· 

SE NNE NNE NNW NNW NE NNW 

5.2 -1.9 4.1 -1. I 3.-1 2.6 3.5 

11.8 11.6 10.5 I 1.4 8.6 7.9 12.2 

148 186 36 148 131 156 141 

680.0 680.8 680.2 680.8 680.6 680.3 680.0 

682.6 68-1.0 682.6 683.4 682.7 682.9 682.4 

675.4 678.2 677.S 678.4 677.6 677.3 677.8 

9.3 I 1.5 10.9 10.7 10.2 10.7 9.0 

16.5 16.5 18.2 16.0 16.5 16.2 15.4 

-1.-1 -1.8 2.5 4.2 2.9 3.3 1.9 

-13.0 -8.0 -6.0 -1.0 -2.-1 -0.7 -3.7 

5.3 5.4 7.2 9.5 8.4 9.6 8. I 

-3-1.2 -27.8 -28.9 -1 9.J -31.-1 -27.2 -26.8 

0 0 2 0 28 30 -17 

Nov. Dec. Year 

SSE SSE SSE 

-1.4 -1.3 4.5 

I I. I 13.6 16.8 

239 153 15-1 

679.7 679.9 680.1 

681.8 683.0 684.5 

677.0 676.5 673.7 

3.3 -1.5 5.1 

7.7 9.3 13.7 

-1.0 -0. 1 -2.6 

-8.6 -16.9 -1 2.8 

5.5 6.5 7.8 

-25.8 -30.5 -35.9 

0 27 

SE NNW NNW 

3.8 3.3 -1.2 

11.7 10.0 1-1.8 

2-15 1-1 1 1-13 

679.6 679.8 680. 1 

681.9 683.3 68-1.0 

676.7 677.3 673.-1 

7.0 8.3 9. 1 

I 2.5 1-1 .0 18.2 

-1.2 -0.-1 -2.3 

-6.1 -9.8 -7.0 

7.-1 9.-1 9.6 

-25.5 -30.2 -3-1.2 

67 0 185 

lnstrnment heights: wind. 10.2 m: pressure. 3398.-1 m (i\ISL): air temperature. 2.0 m: dewpoint temperature. 2.0 111. Wind and temperature instruments 

are on a tower 15 m southwest of the main build in!!. 

*Maximum and minimum values arc houri) a'crages. 

22 
TABLE 1.9. M LO 2001 Monthly Climate Summary 

Jan. Feb. 1\ larch April June Jul) Aug. Sept. Oct. 

Prerniling wind 

direction 

Average wind 

speed (111 s·1) 

1\ la:-.i111u111 ''ind 

speed• (m s·1) 

Direction of max. 

"ind* (deg.) 

A' erage station 

pressure (hPa) 

1\laximum pressure* 

(hPa) 

1\linimum pressure• 

(hPa) 

SSE SE SE 

5.5 4.7 4.2 

11.9 11.4 10.3 

157 158 158 

680.7 678.2 679.3 

684.3 681.6 684.4 

676.7 671.8 675.1 

Awragc air 4.5 2.6 2.9 

temperature ( C) 

1\laximum air temperature* I 0. 7 

(oC) 

:-..tinimum air temperature* -0.5 

(oC) 

A'erage de\\ point 

temperature (°C) 

:-..taximum de\\ point 

temperature*(°C) 

1\linimum dCl\poi111 

temperature* (' C) 

Precipitation (mm) 

-1 8.2 

4.9 

-37.0 

0 

8.4 I I. I 

-0.9 -1.7 

-10.3 -19.7 

1.7 2.9 

-33.7 -35.7 

17 0 

Pre, ailing" ind 

direction 

SE NNW NE 

A\eragc \\ind 

speed (m s·1) 

\laximum \\ind 

speed* (m s·1) 

Direc1ion of max. 

wind• (deg.) 

A\erage station 

pressure (hPa) 

Maximum pressure• 

(hPa) 

Minimum pressure• 

(hPa) 

4.7 4.1 3.8 

I I.I 10.5 9.8 

120 181 141 

680.7 678.2 679.3 

685.6 681.9 684.3 

676.4 672. 1 675.0 

Average air 8.5 5.8 7.0 

temperature(' C) 

Maximum air temperature• 16. 7 

(oC) 

Minimum air temperature* -0.2 

(°C) 

A'wage dcwpoint 

temperature (°C) 

Ma,imum de\\ point 

temperature* ( C) 

Minimum dcwpoint 

temperature• (°C) 

Precipitation (mm) 

-11.9 

8.1 

-37.1 

0 

12.5 12.7 

-0.7 -0.8 

-6. I -11.5 

-26.4 -34. 7 

20 

Night 

SSE SSE S SE SSE SE SE 

3.1 3.0 2.9 3.2 4.4 3.6 4.1 

10.2 8.6 8.1 11.3 10.7 11.4 12.0 

159 155 164 165 I 17 156 154 

680.2 680.5 680.4 680.9 681.5 681.0 680.4 

682.8 683. I 683.2 682.8 684.7 683.6 683.9 

676.5 677.5 677.4 678.5 679.2 677.9 677.2 

3.8 4.6 5.2 6.6 6.6 6.1 5.4 

8.9 11.3 11.5 12.4 12.2 I I. I 9.8 

-0.8 -0.3 0.4 1.9 1.5 1.3 1.0 

-14.5 -11.6 -8.4 -10.9 -8.7 -9.5 -9.8 

4.7 4.4 6.1 5.9 8.0 7.2 7.0 

-30.2 -27.9 -29.4 -26.9 -24.5 -26.3 -27.5 

0 0 0 0 0 6 8 

Day 

N \\' NE \IN\V '\l'\l\V NE NN\V NW 

3.1 2.9 3.0 3.3 4.2 3.1 4.1 

9.9 6.4 12.4 10.6 14.7 II.I 11.7 

155 116 174 168 121 156 142 

680.3 680.6 680.6 681.2 681.8 68 1.0 680.5 

682.6 682.7 683.0 683.9 68.J.8 683.5 684.7 

677.1 677.5 677.7 678.8 679.4 678.4 677. 1 

7.7 8.9 8.9 10.5 10.6 9.8 9.1 

13.0 15.8 15.6 15.8 15.7 15.8 14.0 

0.0 1.6 2.4 3.3 3.0 2.5 2.5 

-5.7 -5.0 -2.9 -4.4 -2.1 -2.7 -J.3 

.J.4 6.8 7.2 7.6 9.5 8.8 7.4 

-29.5 -26.4 -27.7 -2.J.5 -23.2 -23.9 -25.3 

5 9 25 0 6 13 0 

l\m. Dec. Year 

SSE SSE SSE 

4.4 8.4 4.3 

15.7 16.7 16.7 

173 15 1 15 1 

681.3 679.5 680.3 

684. I 682.6 684.7 

6 75.2 6 75.3 6 71.8 

5.8 4.2 4.8 

I I. I 8.J 12.4 

0.9 -1.0 -1. 7 

-I 1.2 -15.0 -12.6 

5.5 4.9 8.0 

-30.I -J 1.6 -37.0 

69 67 167 

NN\\' SE 1 \V 

J.4 7.J 3.9 

12.6 14.8 14.8 

156 125 125 

681.3 679.5 680.4 

684 .8 682. 7 685 .6 

675.3 675.4 672. 1 

9.1 7.6 8.6 

16.6 14.0 16.7 

1.3 -0.8 -0.8 

-6.4 -1 3.0 -6.4 

9.1 6.9 9.5 

-27.8 -29.5 -37.1 

69 44 192 

Instrument heights: wind. 10.2 m: pressure. 3398.4 m (1\ISLJ: air temperature. 2.0 111: dewpoint temperature, 2.0 m. \Vind and temperature instruments 

are on a tower 15 111 southwest of the main buildinl!. 

*\la\imum and minimum 'alues are hourly mei=;ges. 

23 
TABLE 1.10. SMO 2000 and 2001 Mo111hly Climate Summar} 

Prevailing" ind 

direction 

A1craee wind 

:.peed (m s" 1) 

\la\imum "ind 

speed* (m s" 1

) 

Direction of ma\. 

Jan. Feb. I\ larch 

"ind* (deg.) 

A1wage station 

pressure (h Pa) 

Maximum pressure• 

(hPa) 

1000. I 1001.8 1001.2 

I 005.4 I 006.5 I 005.3 

\linimum pressure• 

(hPa) 

993.1 

Ai crage air 27.1 

temperature(' C) 

;\laximum air tcmperalllre• 28.4 

( C) 

i\linimum air temperature• 23.2 

( C) 

J\1erage de\\ point 

temperature ( C) 

i\la\imum de11point 

temperature• ( C) 

l\linimum dc11point 

temperature• ( C) 

Precipitation (mm) 

Prevailing wind 

direction 

A 1 erat!c 11 ind 

speed (m s· 1) 

1\ 1<1 \imum wind 

speed* (m s·1) 

Dm:ction of ma\. 

11 ind* (deg.) 

22.9 

24.3 

19.9 

364 

E 

4.6 

11.0 

319 

996.8 996. 1 

27. 1 26.9 

28.7 28.7 

23.1 22.8 

23.0 23.2 

24.6 24.4 

20.5 21.5 

189 166 

E NW 

4.4 5.1 

12.8 15.2 

322 

Ai crage station 

pressure (hPa) 

I 00 I. I 999 .0 IOOO. I 

;\ laximum pressure• 

Ch Pa) 

1004.4 1002.7 1004.2 

i\linimum pressure• 

(hPa) 

997.7 995.0 993.5 

1\\'crage air 

temperature ( C) 

27.5 27.2 27.3 

\la\imum air temperature• 28.9 

('C) 

l\ linimum air temperature• 23.4 

( C) 

\ 1crage de11point 

temperature (' C) 

\l aximum dc11 point 

temperature• (°C) 

\linimum de11point 

temperature• (' C) 

Precipitation (nun) 

23. I 

24.8 

21.3 

137 

28.7 28.8 

23.3 23.8 

23.1 23.9 

24.5 25.2 

21.4 21.7 

132 

April June 

ESE ESE SE 

4.5 5.2 7.9 

11.3 11.6 15.6 

11 8 121 128 

!(}()() 

SS!:. 

6.3 

I S. I 

139 

Aug. 

SE 

6.6 

13.3 

133 

Sept. Oct. Nm. Dec. Year 

SE !:.SI::. ES!:. WNW Sf: 

6.4 6.5 5.2 4.5 5.9 

13.5 13.9 11.6 11.5 15.6 

127 131 13 1 297 128 

1001.3 1002.2 1002.9 1002.8 1002.5 1003.8 1001.5 1000.6 998.7 1001.6 

1005.3 1006.0 1006.7 1007.5 1006.2 1007.3 1005.4 1004.9 1003.2 1007.5 

997.6 997.8 998.1 

27.3 26.8 26.6 

29.I 29.2 29.I 

23.0 22.4 23.J 

23.3 22.7 22.5 

24.5 24.7 24.5 

21.5 17.0 17.8 

200 172 156 

!:SE SE l:SE 

4.0 6.0 5.8 

11.6 14.0 I 1.9 

132 I 52 126 

998.4 

25.7 

27.7 

21.1 

23.7 

15.4 

93 

!001 

SSE 

5.3 

12.6 

148 

998.5 999.8 996.0 995.4 993.5 993.1 

25.6 26.2 26.I 26.8 27.3 26.6 

27.0 27.7 27.4 28.0 29.6 29.6 

22.8 22.8 22.8 23.3 24.5 22.4 

22.4 22.4 22.6 23.3 23.2 22.7 

24.4 23.8 24.1 24.6 25.5 25.5 

19.4 20.5 20.4 18.5 20.6 15.4 

33 93 256 168 220 2110 

SE SE SE SE SE SE 

8.2 8.7 7.6 7.7 4.9 6.0 

13.5 17.0 16.7 16.0 14.9 17.0 

14'.! 140 137 127 330 140 

1000.4 1001.3 1000.8 1002.2 1002.2 1002.9 1001.3 1000.8 996.9 1000.8 

1003.7 1005.7 1005.1 1005.8 1006.5 1007.3 1005.6 1005.0 1000.8 1007.3 

997. I 996.7 997.4 996.2 995.8 999.4 996.3 996.8 992.8 992.8 

27.3 27.0 26.7 26.3 25.9 25.8 26.0 26.6 26. 9 26. 7 

29.2 28.9 27.8 28.1 27.4 27.4 27.6 27.8 28.6 29.2 

23.9 24.7 24.0 22.8 23.7 23.4 22.5 23.9 23.3 22.5 

23.8 23.J 24.0 22.6 22.5 22.9 23.7 23.9 23.3 

25.2 25.8 25.5 25.6 25.0 25.1 25.2 25.3 25.7 25.8 

20.7 16.6 22.0 15.8 17.5 17.7 19.6 19.2 19.9 15.8 

104 220 226 134 48 141 233 210 451 2036 

lnstmment heights: 11 ind. 22.9 m: pressure. 78.5 111 (i\ISL): air temperature. 18.9 111: dewpoint temperature. 18.9 111. Wind and temperature 

instrume111s arc on Lauagac Ridge. 110 111 nonheast of the main building. 

•J\Jaximum and minimum 1alue; arc houri) a1eragcs. 

24 
( 

AMERICAN SAMOA N WIND ROSE 

1977-1999 

.. / 

+ 

~ 

I 1 . .. I ..... CALM El lw t 2.4\ - ~ I 

l 

I I 

t I I 

r I 

/ 

s WIND FREQUENCY 

(HOURLY PERCENT) 

WIND SPEED (H/S) 

0.5 <= ws < 

5 .0 <= WS < 10.0 

>= 10. 0 

Fig. 1.7. Wind rose of surface winds at SMO for 1977- 1999. The distributions of prevailing wind direction and speed are given in units of percent 

occurrence for the 23-yr period for 16 direction classes and 3 speed classes. Percent frequency of calm winds (WS < 0.5 ms·') is indicated on the graph. 

SOUTH POLE N WIND ROSE 

2000 

/ 

--~ 

I I / slky ,. 

I 

lw " CALM 

El + .. 0. 2\ -- ... I ~.- \. ...... "' 

1, 

/ 

-~-

,, I 

/ / 

s WIND FREQUENCY 

-1 (HOURLY PERCENT) 

WIND SPEED (H/S) 

0 . 5 <= ws < 5 

5 .0 <= WS < 10.0 

>= 10.0 

SOUTH POLE 

2001 

/ 

! I 

lw--

/ 

I 

' 

WIND SPEED (H/S) 

N WIND ROSE 

J~ \ : CALM - - + ~- l ' 0.2\ l . \. 

/ 

- --

s 

I 

I 

WIND FREQUENCY 

(HOURLY PERCENT) 

---- 0 . 5 <= WS < 

---- 5 . 0 <• WS < 10 . 0 

---•>-10.0 

I 

I 

I __ ] 

Fig. 1.8. Wind roses of surface winds at SPO for 2000 (left) and 2001 (right). The distributions of prevailing wind direction and speed are given in 

units of percent occurrence for 16 direction classes and 3 speed classes. Percent frequency of calm winds (WS < 0.5 m s·1

) is indicated on the graphs. 

25 
TAB LE I. I I. SPO 2000 and 200 I Monthly Climate Summary 

Jan. Feb. i\larch April June July Aug. Sept. Oct. 

Pre, ailing" ind 

direction 

l\\crage wind 

speed (m s·1) 

Maximum "ind 

speed* (m s"1) 

Direction of ma:-.. 

"incl* (deg.) 

A\'cragc siation 

pressure (hPa) 

Maximum pressure• 

(hPa) 

Minimum pressure• 

(hPa) 

AHrage air 

tcmpcra1ure (°C) 

NNE E E 

-t.4 4.1 -U 

10. 1 10.3 16.0 

353 354 3 18 

68 1. 1 680.6 681.3 

690.4 69-l.2 695.0 

672.4 670.7 668.7 

-30.2 --l2.7 -5-l.7 

i\laximum air temperature• -'.!3.-l 

(oC) 

-29.1 -35.-l 

Minimum a ir temperature• -38.7 

(cC) 

Average de\\ poin1 

1cmpcrature (°C) 

Maximum de\\ point 

temperature• (°C) 

Minimum dcwpoint 

temperature• (°C) 

Preci piiation (mm) 

-33.3 

-25.5 

-42.7 

0 

-57.1 -69.7 

-47.1 -58.8 

-32.6 -38.1 

-6 1.9 -7-U 

0 0 

Prevailing'' ind 

direction 

NE N NNE 

A ,·eragc \\Ind 

speed (m s·1) 

i\la,imum "ind 

speed* (m s"1) 

Direction of max. 

" ind* (deg.) 

A' crage station 

pressure (hPa) 

i\laximum pressure• 

(hPa) 

Minimum pressure• 

(hPa) 

-l.O -l.I 6.2 

7.5 8.5 13.2 

23 328 28 

687.7 688.-l 678.7 

695.3 696. 1 692.-l 

68 1.0 676.8 669.6 

A\ erage air -29.2 -38.5 -55.7 

temperature (°C) 

i\laximum air temperature• -23.3 

(oC) 

i\linimum air temperature• -36.1 

( C) 

A' crage de\\ point 

tempcra1urc (°C) 

i\laximum de" point 

temperature• I C) 

i\linimum de,, point 

temperature• (°C) 

Precipilation (mm) 

-32.7 

-26.0 

-40.3 

0 

-25.9 -38.6 

-53.-l -64.6 

--l2.S -58.6 

-29.0 --11.8 

-58.I -69.3 

0 0 

!000 

ENE E N 

5.5 5.4 5.8 6.2 

11.6 1-U 11.6 12.2 

107 15 27 3 

679.8 676.3 681.3 677.1 

692.-l 695.7 701.3 697.3 

666.5 663.2 665.6 66-l.9 

-6 1.4 -59.3 -59. I -60. I 

--l5.7 --10. I --l 1.0 

-71.0 -71.1 -74.7 

-65.6 -62.9 -63. 1 

-49.7 --13.3 -44.6 

-75.0 -74.9 -79.4 

0 0 0 

--1 1.5 

-74.1 

-6-l.5 

--15.3 

-78.8 

0 

2001 

NE NE N 

5.5 6.0 5.7 

11.0 11.-l 12.5 

347 114 358 

676.9 678.6 672.5 

69-l.-l 702.8 682. 1 

662.7 659.9 660.2 

-59.2 -60.-l -50.-l 

--12.8 --11.8 -3-l.2 

-73.-l -7-l.8 -63.6 

-63.3 -64.5 -5-l.2 

--16.2 -45.0 -37.5 

-78.2 -79.6 -68. 1 

0 0 0 

E NNE NNE ENE :-.'NE N ENE 

5.8 6.0 6.7 6.3 6.8 6.-l 6.2 

I 1.5 1-l.6 13.4 14. 7 12.2 13.3 12.-l 

11 2 27 16 5 8 23 

675.4 680.5 677.6 679.2 669.7 677.5 672.9 

662.0 667.6 666.5 662.3 654.0 660.8 652.2 

-59.6 -57.9 -57.3 -60.6 -63.-l -56.4 -53.2 

-4-1 . 7 --10.2 -41.4 -39.8 --10.6 -33.2 -30.4 

-70.9 -70.8 -69.8 -73.2 -76.0 -72.1 -69.6 

-63.8 -62.0 -6 1. 1 -6-l.6 -67.6 -60.0 -57.3 

--18. I --l3.2 --l-1.6 --l3.3 --l-1.1 -36.-l -33.7 

-75.7 -75.7 -75.3 -78.2 -80.7 -76.1 -73.6 

0 0 0 0 0 0 0 

l\O\. Dec. Year 

N'lE NE NNE 

6.7 4.1 5.4 

14.9 7.7 16.0 

289 11 318 

687.-l 691 .5 680.3 

697.8 699.9 702.8 

668.7 681.3 659.9 

-33.4 -27.4 -50.1 

-2-1.0 -2-1.0 -23.-l 

-5 1.8 -31.1 -7-l.8 

-36.9 -30.8 -53.7 

-27.4 -27. I -25.5 

-56.2 -34.8 -79.6 

0 0 0 

ENE NNE NNE 

5.8 5.3 5.8 

12.6 9.5 1-l.7 

3-19 11 16 

681.3 683.2 679.3 

690.4 697 .5 697 .8 

671.1 670.8 652.2 

-34.8 -26.3 -49.6 

-22.-l -21.6 -21.6 

-42.7 -34.4 -76.0 

-39.0 -29.8 -53.6 

-25.2 -2-U -2-1.7 

--17.2 -38.1 -80.7 

0 0 0 

lnstmment heights: "ind. 10.3 m: pressure. 28-l l m (i\ISL): air tcmpcraturc. 2.0 m: dc,,poin1 temperature.2.0 m. \Vind and temperature instmments 

arc on a tower 9 1.4 m grid nonh-nonhwcst of the Atmospheric Research Obscn atory. 

*Maximum and minimum values are hou rly averages. 

26 
~ 

r' 

r 

\ 

SOUTH POLE 

1977-1999 

N 

t 

WIND ROSE 

I 

I , 

I ,; 

I r ;/ \ \ \

'I / 

[- ' L I 

CALM 

0 . 5\ 

~~' ' 

\ \ \ 

"' / / I I , ,, I I 

I I -+- / 

~ 

... / 

~ WIND FREQUENCY 

(HOURLY PERCENT) 

WIND SPEED (M/S) 

0 . 5 <~ WS < 5 

---- 5.0 <• WS < 10 .0 ---•>= 10.0 

Fig. 1.9. Wind rose of surface winds at SPO for 1977-1999. The distributions of prevailing wind direction and speed are given in units of percent 

occurrence for the 23-yr period for 16 direction classes and 3 speed classes. Percent frequency of calm winds (WS < 0.5 m s·') is indicated on the graph. 

The average ambient temperatures for 2000 (26.6°C) and 

200 I (26. 7°C) (Table I. I 0) were both coo ler than the 23-yr 

average of 27 .0°C. The average barome tri c pressure for 

2000 ( I 001.6 hPa) was higher than the 23 -yr average of 

1000.9 hPa, whereas for 200 1 ( 1000.8 hPa) it was slightly 

below the climatological average. Low-pressure records 

were tied in both January and February 2000. The 

precipitation amounts in both 2000 (2 110 mm) and 200 I 

(2036 mm) were higher than the cliniatologica l average of 

1754 mm. 

South Pole 

The distributions of the surface wind directions in 2000 and 

200 I (Figure 1.8) show percentages o f "clean air" sector (grid 

north-northwest through east-southeast) winds of 93.8% in 

2000 and 94.3% in 200 I , similar to the 23-yr average of 93.8% 

(Figure 1.9). The percentage of winds in the I 0 m s-1 or greater 

class was 2. 7% in 2000 and 5.3% in 200 I, compared with 4.0% 

for the long-term average. The annual average wind speed for 

2000 (5.4 m s- 1

) equaled the climatological average wind speed 

27 

o f 5.4 m s- 1

, whereas the wind speed for 200 I (5.8 m s- 1) was 

higher lhan the climatological average. 

The average temperatures for 2000 (-50. I °C) and 200 I 

(- 49.6°C) (Table I.I I ) were both colder than the long-term 

average of -49.3°C. January and February 2000 both set 

new record minimum temperatures for the month. The 

min imum temperature in 2000 of -74.8°C occurred in 

September. The minimum temperature in 200 I of -76.0°C 

occurred in August. The annual average barometri c 

pressure for 2000 (680.3 hPa) was I . I hPa higher than the 

23-yr average of 679.2 hPa, whereas for 200 I (679.3 hPa) ii 

was slightly above average. 

1.6. REFERE CES 

Peterson, J.T., and R.M. Rosson (Eds.), Climate Monitoring and 

Diagnostics labora/ory No. 22 S11111111my Report 1993, 152 

pp., NOAA Environ. Res. Labs., Boulder, CO, 1994. 

WMO (World Meteorological Organizati on), Guide lo Afeteorological /11s1ru111en1a1io11 and Observing Practices. WMO No. 8. 

Tech. Paper 3, 347 pp., Geneva, 1969. 
2. CARBON CYCLE 

p . P. T..\,S (rDl 1 OR). P.S. B \K \\ "· L. BRL II\\ ILrR. T.J. Co'\\ \Y. E.J. DI LGOKf'( KY. D. \V. GLL:\ 1 llrR. 

D.R. KITZIS. P.i\I. L"G. K.A. i\l-\S.\RIL J.B. \Ill I rR. P.C. :\0\ II LI. K.\\'. Tll0'1W •. 

B.11. VAUGH'*· J. \\ .C. \Vllll r *. A'-1> C. Zll \0 

2.1. OVER\ 'I EW 

The goal of the Carbon Cycle Greenhouse Gases group 

(CCGG) is 10 impro\c the understanding of the factors that 

determine the atmospheric burdens of major trace gases 

influencing the Earth's climate, in particular C01• CI-14 , and 

CO. Si nce 1997 N~O and SF6 ha\e also been measured. 

The anthropogenic impact on each of these species is large, 

but natural cyc les are inrnhed as \\ell. except for SF6 . The 

continuing international climate change negot1at1ons 

highlight the fact 1ha1 the world has tentati\ cly start ed to 

take steps 10 control the steadily increasing climate forcing 

by anthropogenic greenhouse gases. Two of the 

requirements for cffccti\ C policies are a reliable method 10 

track the atmospheric changes of each of these gases and a 

quantitative understanding of what controls the atmospheric 

concentrations. 

The main 1001 for studying the global budgets of the trace 

gases is the measurement of atmospheric spatial concentration patterns and their changes over time. Two 

methods have been employed from the start of the 

Geophysical Monitoring for Climati c Change program, the 

forerunner of CMDL: continuous eas uremen ~ are made in 

remote clean-air locations. namely the four CM DL 

obserYatories; and week!) pairs of discrete tl ask samp les 

are obtained, also at remote clean-air locations, and 

analyzed in Boulder. Initiall y the samples ''ere analyzed 

only for C01, but graduall y more species haYc been added 

(Table 2.1 ). The isotopic ratio measurements are being 

carried out al the lnslillltc for Arctic and Alpine Research 

(INSTAAR) of the University of Colorado (CU). in close 

cooperation with CCGG. Anomalous 170 enrichments were 

measured in some of the fla sks by scientists at the 

University of Ca lifornia al San Diego. A California 

lns1itu1c of Technology scientist started to measure D II of 

11 1 in a small subset of flasks in fall 2001. The global air 

samples pro\ ide a un ique resource for narro\\ ing 

uncertainties of greenhouse gas budgets as well as other 

atmospheric problems. CCGG continues 10 ill\ estigate the 

feasibility of additional measurements. CCGG also 

collaborates '' ith a sc ientist from Kyrgyzstan in a project of 

the International Science and Technology Center, l\loscm\. 

comparing spectroscopic absorption measurements of the 

total column abundances of C01 and other species to the 

CCGG network data. 

In formation on sou rces and sinks of the trace gases is 

obtained from their rates of change and from their spatial 

distributions. The quantilati\e link is pro,·ided b) 

numerical models of atmospheric transport, operating in 

both two and three dimensions. The method used is to work 

"backward " from observed concentrations 10 the sources 

•1ns1i1u1c for 1\rc11c and J\lp111c Rc,earch. l nl\crsll) of Colorado 

28 

TABLE 2.1. Species Analyzed in Samples of the 

Global Cooperative Air Sampling Net\\ork -- ---- -- --

Precision 

S!J<.--cies Stan Date i\lethod* ( lcr) Collahora1or.; 

- --------- -- -- co~ 1976 NDIR 0.05 ppm (0.0:!°0) 

Cl!, 1983 GC FID <I ppb (0.07%) 

co 1988 GC llgO 0.5 ppb (0.5-1 %) 

11 - 1988 GC llgO :! ppb(0.4%) 

co~. 'c 1990 IR\IS 0.01%0 CU l'ISTAAR 

C01. ''0 1990 IRl'vlS 0.03%0 CUllNSTA1\R 

N:O 1996 GC ECO 0.2 ppb (0.07"'•) I IA TS group 

SF, 1996 GCECD 0.03 ppb (I%) llATSgroup 

co~. 1·0 1997 IRMS 0.03?oo UC San Diego 

Cl l,. 'c 1998 GC IRi\IS 0.06°0. Cu l'ISTAAR -- -- -- -- --

•NDIR, non-dispcrsi'e inliared analyzer: GC. gas chromatograph: FID. 

flame ioni1.ation dc1ector: IR\IS. isotope rauo ma's -.pec1rometer. ! CD. 

ekctron capture detector. 

causing them, and therefore it is in the class or so-called 

inverse problems. The greatest limitation is sparseness of 

data. especially in regions close 10 important sources and 

sinks. Therefore the spatial CO\ erage of the cooperati\ c air 

sampling network has been gradually expanded. Isotopic 

analyses ha\ e been added because di ffercnl sources/si nks 

may be characterized b) different isotopic "signatures." 

To overcome the limitation of having only measurements 

from the remote marine boundary layer, two new 

approaches were initiated. The first is 10 continuously 

measure a number or chemica l species and atmospheric 

physica l parameters at different heights on \cry tall towers. 

Mole fra ctions (a lso called mixing ratios) in the continental 

boundar) layer arc highly \ ariable. making them more 

difficult 10 interpret and requiring much more auxiliary data 

than the traditional marine a ir samples. The second ne\\ 

approach is to obtai n discrete air samples from low-cost 

airplanes in automated fashion from the boundary layer up 

lo about 8-km altitude. These samples arc then sent back lo 

the laboratory in Boulder for ana lysis. II 1s hoped 1ha1 the 

combination of continuous co~ and tlask sampling can be 

greatly expanded on aircraft, especiall) O\ er North 

America. 10 pro' idc signifi cant regiona l-sca le constraints 

on the budgets of the gases measured. 

Because the global co\eragc of CMDL's sampling 

network is unmatched, it pl ays an active role in bringing 

together the measurements from many di ffcrenl laboratories 

around the world . Toward this end, measurements of 

standard reference gases as \\ell as actual field samples are 

being compared. For CO~ and CO. CMDL pro' ides cali-
bratcd reference gas mixtures under the auspices of the 

World Meteorological Organization (\VMO). Cl\IDL 

assembles a common global database for co . called 

GLOBALV F\V-CO~. \\hich is current!) based on the 

mea surements from laboratories in 13 countries, and in 

\\h ich an anempl is made to avoid significant ca libration or 

methodological inconsistencies. Its intended use is for 

three-dimensio nal (inverse) modeling. Its first release took 

place in 1996, and it has been updated once a year since then , 

around August (hllp://www.cmd l.noaa.gov/ccgg/globalvicw/co2/indcx.h1ml). A similar database was assembl ed for 

methane, GLOBALV E\V-C H~. The first re lease occurred in 

1999, and a second release took place in December 200 I 

[GLOBALV!EW-Cf-14, 2001]. 

Full indi\ idua l data records and monthly means can be 

obtained for each spec ies for each site from the CMD L 

World Wide Web page (hll p://w\\" .cmdl.noaa.go' ); from 

the ftp file server's "pub" directory (flp.cmdl.noaa.go' ); 

from the \VMO World Data Center for Greenhouse Gases in 

Tokyo. Japan ; and from the Carbon Dioxide In forma tion 

Analysis Center in Oak Ridge, Tennessee. 

2.2. CARBO:\ DIOXIDE 

2.2.1. I:'\ SITL CA RBON DIOXIDE MEASURE:\IE:'\TS 

The mole fract ion o f atmospheric CO~ was measured "ith 

continuously operating non-dispersi\e infrared (NDIR) 

analyzers at the four CMDL obsenatories d uring 2000 and 

200 1, as in pn::vious years. Monthl y and ann ual mean CO~ 

concentrations are given in Table 2.2. These \alues arc 

pro1 isional. pending final calibrations of refcn:ncc gas 

standards. Preliminary selected hourly a\ erage CO~ mol e 

fractions for 2000 and 200 I arc ploned for the four 

obscnatorics in Figure 2. 1. 

Except at the South Pole Obsen atory (SPO). the CO~ in 

situ analy1ers performed without any major problems. Al 

SPO. the Siemens Uhramat 5F CO~ analy7er experienced 

some mechanical problems in March 2000. An incandescent light bul b that is used to detect the rotational speed 

of the chopper \\heel inside the ana lyzer burned out. A 

replacement bulb, 1101 of the original l) pc, was installed 10 

a llow the analyzer to continue working. 1 lowcvcr, this 

change resulted in a change in the characteristics o f the 

analy1cr. such as reduced sensitivity and reduced outpu t. 

Although the measurements resu lting from th e analy7cr 

appeared lo be normal, further inspection of the data 

showed some sma ll offsets on the o rde r of sc\cral tenths of 

a pan per million (ppm) compared with nask data taken at 

SPO. There was also el'idence of changes in the anal) 7er 

characteristics whcne,·er the output signal of the ana lyzer 

was modi lied. This can be seen in December 2000 \\hen a 

shift in the data of about 0.5 ppm occurred after the 

anal)Ler output was shifted up\\ard. The anal)7Cr was 

replaced on February 14. 2001. with a Ll-COR Model 6251 

co~ anal)7Cr. Until the old Siemens ana l)ZCr can be 

returned to the Cl\1 DL Boulder laborator) for testing. and 

until all reference gases used in :moo and 200 1 are returned, 

the data from SPO must be considered \'Cr) preliminary and 

subj ect 10 change. 

29 

TABLE 2.2. Pro1isional 2000 and 2001 Monthl) and Annual 

Mean CO~ Mole Fractions from Co111inuous Anal)Ler 

Data (μmol mol" 1

, Rclati' e 10 Dry Air), for 

the Four CMDL Obsen atories 

}.ton1h BRW \ILO S:\10 

:!()()() 

Jan. 374.76 369.05 368.39 

Feb. 376.48 369.34 368.20 

I\ larch 374.54 370.35 368.60 

April 3 75.42 371.77 368.02 

!\lay 375.88 3 71.32 367.64 

June 3 72.34 371.53 367.37 

Jul) 365.98 369.75 368.16 

Aug. 360.77 368.20 368.36 

Sept. 363.07 366.86 368.07 

Oct. 368.62 366.94 368.73 

No1. 370.97 368.28 369.06 

Dec. 373.03 369.62 368.99 

Year 370.99 369.42 368.30 

:!0111 

Jan. 375.64 370.46 369.42 

Feb. 376.36 371.44 369.80 

\larch 376.29 372.38 369.78 

April 377.41 373.33 369.30 

\la) 377.49 373.78 368.41 

June 375.27 373.09 369.73 

Jul) 367.71 3 71.51 370.30 

Aug. 361.05 369.48 369.93 

Scp1. 363.58 368.12 369.97 

Oct. 368.81 368.59 370.08 

NO\. 373.94 369.74 370.24 

Dec. 376.19 371.10 370.51 

Year 372.48 371.08 369.79 

μmol mo1·1 is abbrc' iatcd as ppm. 

2.2.2. FLASK SA:\IPLE CA RBO:\ DIOXIDE 

i\1 EASUl~DI E"TS 

SPO 

366.36 

366.21 

366.15 

366.22 

366.35 

366.69 

367.15 

367.63 

367.84 

367.84 

367.75 

367.99 

367.01 

367.83 

367.54 

367.48 

367.75 

368.01 

368.26 

368.69 

369.19 

369.47 

369.71 

369.77 

369.58 

368.61 

The CMDL G lobal Cooperali\e Air Sampling Network 

(Figure 2.2) is the most ex1ensi1 e and representatil'e 

network in existence for lht: measurement of cli mat ically 

important trace gases. Samples arc currclllly collected 

approximately weekly at 4 7 fi xed locations. The samples 

arc mea sured at Cl\IDL for C02, Cl 14, CO, 11 2, N20, and 

SF0 • a nd at INSTAA R for 11C and ~0 or C02. In 2000. 

7400 samples were analyzed. a nd in 200 I, 7000 were 

analyzed. Samples from se1·en sites arc measured for 13C of 

C 114 at INSTAA R; samples from th ree sites arc measured 

for 170 of CO~ at the Uni' ersil) of California at San Diego: 

and sa mples from one site arc measured for II (deuterium) 

in II ~ at the California Institute of Technolog). The mole 

frac tion and isotopic measur1:men1s arc used to quantify 

globa l and regional carbon budgets b) i111erse techniques or 

to constrain source sink estimates obtained from proccssbased mode ls. 

Se\'cral c hanges lo the network occurred during 2000-

2001. Sampling began at l\lood), Tc,as (\VKT). in 2001 as 

pan of the ne11 tall-tower proj1:c1 there. After resumption of 
E 380 

a. 

.3: 370 

C\J 

0 

() 360 

E 380 

a. 

.3: 3 7 0 

C\J 

0 

() 360 

E 380 

a. 

.3: 370 

C\J 

0 

() 360 

Mauna Loa 

Samoa 

South Pole 

2000 2001 

Year 

2002 

Fig. 2. 1. 1 lourly mean CO, mole fra ctions in dry air. expressed in μmol 

111 0 1·1 (ppm. pans per million) measured al 1he four Ci\t DL observatories 

during 2000 and 2001. Data were 11 01 selected for background 

conditions. Only hours\\ ith instnnncnt malfunctions were omi!led. 

reg ular sampling at Christmas Island (CHR) in 1998. 

log isti cal problems aga in inte rrupted samplin g in 200 1. 

Resumption o f sampling at C HR or another island 

( Palmyra) in the reg ion is planned. Sampling was 

discont inued at the Kaashidhoo C lima te Observatory (KCO) 

when the observatory c losed: Gozo, Malta, was 

discont inued d!le to lack of sampling : and the W IT N talltowe r site in Grifton. North Caroli na (ITN), was 

discontinued when the towe r project there ended. 

T he last CCGG s hipboard sampling program in the 

Paci fi e Ocean ended when the Argentina Star completed its 

rou te in 200 I. Althoug h modeling studies have shown the 

importance o f the d ata obtained from the Pac i fie Ocean and 

the previously interrupted South China Sea cruises. these 

prog rams could not be co n tinued. 

30 

One component of the o ngoi ng effort to assure the qua lity 

of the nask network data is the measurement each analysis 

day o f test n asks filled w ith air of known composit ion. The 

test- n ask C02 results for 1998-200 I are plotted in Fig ure 

2.3a. The symbols represent the difference b etween the 

measured value of each nask and the va lue assigned to the 

hig h-pressure cylinder from whi ch the fla sks are filled. T he 

la rger scatter observed prior to 1999 (asterisks) was reduced 

in early 1999 when a new pe rson started fi 11 i ng the test 

nasks. Since that change, careful ad herence to the filling 

procedure has produced a test-nask record (plus symbo ls) 

that can be used to investigate instrument performance and 

sources of uncertaint y in the C01 measurements. 

The red cur ve in Figure 2.3a is a s mooth fit to the data, 

s howing significant long-term va ri ations in the test-flask 

differences. One possible explanation of these long-term 

vari ations is that the C0 2 mol e fractions of the n ask 

analysis re ference gases are chang ing over time. The black 

I ines in Figure 2 .3a show the drifts in the nask ana lysis 

reference gases relative to their ini tial assigned val ues 

determined b y periodic recalibrations during their lifetimes. 

Test-flask di fferences based on data corrected for reference 

gas drifts arc plotted in Figure 2.3b. Much less lo ng-term 

signal is seen in the drift-corrected results. The standard 

deviation of the test-flask d ifferences is 0.08 ppm, which is 

a good approximation of the anal y tical precision of an 

individual nask measurement. This value is the sum of 

several sources of imprecision. The unc ertainty arising 

from the high-frequency (I-Hz) noise of th e ND IR 

instrument is - 0.02 ppm (I standard error of the 30-s 

a verage). Additional lower frequency no ise is observed in 

the variabili ty of the three re ference gases used to calibrat e 

the instrument several times d u ring each analysis day. The 

red squares in Fig ure 2.3b represent th e difference between 

the value assigned to the mid re ference gas and the value 

calculated (linearly) for mid using the high and low 

reference gases. The offset from zero is due to the 

instrument nonlinearit y (whi c h is accounted for in the 

determination of actual fla sk va lues), and the variabil ity is 

measureme nt no ise resulting from pressu re and temperatu re 

va riations, and possibl e regulator o r other gas-ha nd I ing 

effects, whi ch are not accounted for by the cali bration 

scheme . This source contributes 0.04 ppm to the overall 

imprecision. Based on this anal ysis, the remain ing 0.07 

ppm (uncertainti es are summed in quadrature) of the testflask imprecision likely o ccu rs during the fi lli ng of the test 

flasks or results from intera ction of the test gas with the 

nask between fi lling and anal ysis. 

During 1999 and 2000 there was no significant o ffse t in 

the test-flask measureme nts. In 200 I there is an as- ye tunex plained offset of - 0.0 5 ppm. Reliabl e test-nask data , 

as shown in Figure 2.3b, are useful in the interpreta tion of 

results from interlaboratory fla sk intercomparison 

experiments (discussed in section 2.7). The stabi li ty of the 

CMD L C0 2 anal ytical apparatus demonstrated b y the test 

n asks makes it hard to postulate a CMDL analytical 

problem as the cause for the significant differences 

observed when C M DL and the Meteorologica I Service o f 

Canada (MSC) measure air from the same flas ks. 

The 20 00 and 2 0 0 I annual mean C02 mole fracti o ns 

(mixing ratios) calc ulated from s mo oth curves fitted to the 
90°N 

60°N 

30°N 

o· 

30°5 

• CMR " S hlAS 15Vt, J 

.. \ r.{Rl(At~ SA.VOA 

, .t RARolO~GA 

). EASIER • ISlA'O 

ZE"'f""" .. •, 

CllOZl • 

90°N 

60°N 

30°N 

o· 

30"S 

50•5 e Net\\ Ork (active) 

® Net\\ r~ (inacti,e) 

• Observatory 

+Aircraft 

Tl[PR,,\ ()( • E. 

60"S 

90•

5 .A TO\,er 

100°E 140°E 1 so· 140"VY 1 OO"VY 

•TH Pc ( 

60"VY 20"VY 20°E 60°E 

90"S 

100°E 

Fig. 2.2. Locaiions of the CCGG measurement programs, including the baseline observatories (squares), Global Cooperative Air Sampling Network 

(circles), discontinued sites of same (open circles with cross), aircraft vertical profiles (stars), and the very tall tower sites (triangles). 

data for 47 sites in the CMD L/CCGG Globa l Cooperative 

Air Sampling Network are g iven in Table 2.3. The g lobally 

averaged C02 mole fraction and long-term trend (seasona l 

cycle filtered out) are shown as smooth curves in Figure 

2.4a. In 200 1 the globa lly averaged C02 mole fraction was 

370.2 compared with the pre-industria l value o f - 280 ppm 

in 1880. The C0 2 increase from 1999 to 200 I was 1.35 

ppm yr 1

, slightly lower than the 1979-200 I average growth 

rate o f 1.5 ppm yr 1 and about half o f the 1997-1998 

increase o f 2.7 ppm yr·

1

. The globally averaged C02 

growth rate as a func tion of time is shown in Figure 2.4b. 

2.2.3. CARBON D IOXIDE STANDARDS AND REFERENCE 

GAS CALIBRATIONS 

The 15 primary WMO standards, ranging in C02 mole 

fraction from approximately 250 to 520 μmo l mor 1

, were 

calibrated at regul ar intervals of slightly more than I yea r 

by CM DL's manome tric system [Zhao et al .. 1997). The 

function of the primary standards is to provide cont inuity to 

the WMO sca le, as well as a quality control check on the 

performance of the manometri c system. From September 

1996 th rough August 200 1, 237 individua l manometric 

determinations were made of the C02 mole fraction s in 

these cylinders. The results of the analyses are summa rized 

in Table 2.4 . For comparison, the C02 mol e fractions 

3 1 

measured by the Scripps Institution of Oceanography (S IO) 

by infrared absorption relative to the WMO X93 mo le 

fraction scale, maintained by S IO, are also shown in Table 

2.4. The mean precision o f an individual manometric 

measurement by CM DL, indicated in Table 2.4 as the 

standard deviation, has been about I pa rt in 3200. The mole 

fractions analyzed by CM DL a re lower than by S IO at the 

low end of the sca le and higher at the high end , whil e in the 

atmosphe ri c C0 2 concentration range of 340 to 400 μmol 

mol' 1 SIO is on average 0. 10 μmo l mol' 1 less than CM DL. 

To maintain and propagate the WMO scale, the assigned 

va lues of the WMO primary standards have been based on 

both the SIO and CMDL measured va lues. The assigned 

va lues as o f January 2000 are indi ca ted in Table 2.4 as " o ld 

scale." Contrary to pl ans described in the previous CM DL 

report [Tans et al., 2001 ), it was decided to wait a bit longer 

before basing the assignments of the WMO primary 

standards on the CMD L manometri c measurements a lone. 

CM DL recently received from S IO revisions of its earlier 

reported IR measurements of the WMO prima ry standards 

(not incorporated in Table 2.4), and an assessment and 

revision of the WMO scale, to be named X2002 , will be 

described in detail in a futu re publication. 

Because the goal is to maximize the useful life span of 

the primary standards, the primary calibrat ion scale is 

transfe rred via NDIR measurements, approx ima tely twice a 
0.50 

0.40 

0.30 

:::--

0 0.20 

E 

0 0.10 E 

3 

0 0.00 u 

-0.10 -

-0.20 

-0.30 

1998 

(a) 

0.50 

0.40 

0 

E 

0 

E 

3 

d' u 

- 0.20 

- 0.30 

1998 

(b) 

1999 

1999 

Reference Gases 

2000 2001 

YEAR 

2000 

YEAR 

200 1 

2002 

2002 

Fig. 2.3. (a) Comparison of the measurements of test flasks filled from 

cylinders having well-calibrated concentrations with the assigned 

concentration of those cylinders. Drifts of high, mid, and low (1-1, M, and 

L) reference gases are used in the measurements of the test flasks (and all 

other flasks). The red curves are smooth fits to the test-flask data. (b) 

Same as (a) after correction for drift of H, M, and L. Squares are the 

measured values of reference cylinder M based on linear interpolation of 

measurements of H and L, plotted as the difference from the assigned 

value ofM. 

yea r, to a set of secondary standards. The secondary 

standards, whi ch typically have a useful lifespan of 3 to 4 

years, are in turn used to calibrate all other cylinders, in 

which each cylinder is always compared with a set of four 

bracketing seconda ry standards. During 200 I about 600 

cylinders were assigned a va lue o n the WMO Mole Fraction 

Scale in this way. The reproducibility, in the range between 

250 and 520 ~tm ol mor 1

' has generally been bette r than 0.05 

~tm ol mo l" 1

• In the range of 325-425 μmol mor 1

, the 

reproducibi lity ( l cr) has been 0.0 14 μmo ! mol" 1 [Kitzis and 

Zhao, 1999]. 

On request, calibrations can be performed with the 

manometri c system well outside of the range of atmospheric 

32 

C02 values. Because there has been some demand for 

calibrations well above 520 ~tmo l mor 1

, new primary C02 

standards were created at the high end of the range, at 

approximately 600, 700, 1000 , 1500, 2000, 2500, and 3000 

μmo! mor1

• The standards wi ll a llow C0 2 calibrations to be 

performed by the comparative infrared absorption technique 

rather than the time-consuming manometri c determinations. 

Cylinders prepared by CMDL with a specified C02 

concentration undergo the following procedures at its c leana ir pumping station at high elevat ion on Niwot Ridge, 30 

km west of Boulder: 

New or recently hydrotested cylinde r: ( I) The cylinder is 

vented and then pressuri zed twice with dry natural a ir to 

about 20 atm (300 psi) and vented again. (2) The cylinder 

is fil led to about 34 atm (5 10 psi) with dry natural a ir and 

stored for several weeks. (3) Before the fina l fi ll , the 

cylinde r is first vented and then spiked with eithe r 10% or 

zero COr in-air, depending on the desired final mixing 

ratio. (4) The final fill is made with ambient and dried 

natural air to 135 atm (2000 psi), during which the ambient 

C02 mixing ratio is monitored. (5) The water vapor content 

of the filled cylinder is measured; it must be less than 5 

ppm and is usua lly less than I ppm. Drying is 

accomplished with magnesium perchlorate, Mg(Cl04 )i. The 

pump is a RIX oil-less diving compressor. 

Previously used cylinder: Steps I and 2 are replaced by 

one vent and one fill with dry natural air to a pressure of 20 

atm. Other trace gases, such as CH4 and CO, can be targeted 

to specified values in the same cylinders. 

2.2.4. MEASUREMENTS OF STABLE I SOTOPES OF 

ATMOSPH ERIC C02 

The Stable Isotope Laboratory (S IL) at the Institute of 

Arctic and Alpine Research at the University of Colorado 

has, for the past decade, worked c lose ly w ith CCGG to 

measure stable isotope ratios of atmospheric greenhouse 

gases. Currently o 13C and 0180 o f atmospheric C02 are 

measured in nearly al l of the NOAA Global Cooperati ve Air 

Sampl ing Network, including flask sites, ta! I towers, and 

airc ra ft. Sampl es from 13 sites are a lso ana lyzed for o 13C 

of atmospheric CH4 , with plans to expand this measurement 

to the full network when fund ing permits. A system to 

measure oD in a tmospheric C H4 , as well a s isotopes in 

water vapor extracted from the NOAA flasks, is a lso in the 

testing phase. Planned future ana lyses include isotopes of 

atmospheric CO and N20. 

J13C of Atmospheric C02 

A current "flying carpet" plot of o 13C of C02 is shown in 

Figure 2.5. These data are key to the separatio n of fluxes of 

atmosphe ric C02 between the terrestrial biosphere and the 

ocean. Plants discriminate against 13C02 during photosynthesis by about - 18 per mi l (o/oo). This is a relatively 

large effect compared with the few-per-mil fractionation 

that occurs when C02 goes into and out of the s urface 

ocean. A reconstruction o f net terrestrial biospheric and 

oceanic fluxes is shown in Figure 2.6 from the CCGG twodimensional (latitude, he ight) transport model [Tans et al., 

1989]. Several key observations can be made from this 

figure. The temperate latitudes of the northern hemisphere, 

. 

J 
Site 

TABLE 2.3. PrO\ isional 2000 and 200 I Annual Mean Mi\ing and Isotopic Ratios 

from the Global Cooperative Air Sampling Network 

co, 

(μmol mol ) 

Cit, 

(nmol mol· ) 

CO 'J,O SF0 

(nmol mol ) (nmol mor ) (pmol mor ) 

li" CIL 

("0.) 

Code Location 2000 2001 2000 2001 2000 2001 2000 2001 2000 2001 2000 2001 2000 2001 

ALT 

ASC 

ASK 

AZR 

13,\L 

B\H:. 

BM\\ 

BR\\' 

13SC 

CBA 

CGO 

CllR 

CRZ 

EiC 

Gl'>ll 

llBA 

ll l.,:-; 

ICE 

IZO 

Kl:.Y 

KUl\I 

K/D 

Kt'.1'-1 

Ll.F 

\lllD 

\llD 

MLO 

:-.\tB 

N\VR 

PSA 

PrA 

RPB 

SEY 

Slll\I 

Si\10 

SPO 

SHI 

SUM 

SYO 

TAP 

TDF 

UTA 

Ul.Jl\I 

\\JS 

WLG 

Alert. Ntma\ut. Carmela 

\sccnsion Island 

Assckrcm. Algeria 

Tcrceira Island. A/ores 

Baltic Sea 

Bermuda (cast coast) 

Bcmrnda (\\CSt coast) 

Barro\\. Alaska 

Blad. Sea. Romania 

Cold Ba). Alaska 

Cape Grim. Ta~mania 

Christmas Island. Kiribati 

CroLct Island 

Easter Island 

l\ 1ariana Islands. Guam 

llalle) Ba). Antarctica 

Heg) hatsal. 1 lungal") 

I lc1111ac), Iceland 

lzaiia Obs .. Tencrile 

Key Bisca) nc. Florida 

Cape Kumukahi. l lawai1 

Sal) Taukum. Kazakhstan 

Plateau Ass\. Kuakhstan 

Par!.. Falls. \\'iscom,m 

;\lace I lead. Ireland 

Sand Island. ;\I id" a) 

1\launa Loa. I l<maii 

Gobabeb. '\amibia 

Ni\\Ot Ridge. Colorado 

Palmer Station. Antarctica 

Point Arena. Cali fornia 

Ragged Point. Barbados 

1\ lahc Island. Seychelles 

Shemya Island. Alaska 

American Samoa 

South Pole. A111arctica 

Ocean Station \I 

Summit. Greenland 

Syo\\a Station. A111arctica 

Tac-aim Pen .. Rep. of 

Korea 

3'0.6 

367.8 

369.8 

369.9 

374.6 

372.0 

369.6 

371.-1 

[ I 

[] 

370.6 37 1.6 

370.5 371.7 

370.8 372.2 

377.7 377.7 

l J 372.1 

366.9 

370.0 

366.8 

366.2 

369.3 

368.5 

[ ] 

[ l 

368.1 

371.0 

366.7 ! J 

37-1.2 [ l 

370.1 371.7 

370.2 371.7 

371.2 373.2 

369.9 37 1...J 

371.5 373.3 

369.1 371.2 

373.1 37-1.-1 

370.0 371.8 

369.5 

369.6 

[] 

370.3 

366.9 

[] 

369.1 

368.3 

370.5 

368.2 

366.8 

370.6 

I I 

366.9 

373.3 

371.5 

3 71.:! 

[) 

372...J 

368.6 

376.8 

371.2 

(] 

372.3 

369.8 

368.6 

371.8 

ll 

[ l 

376 . ..J 

Tierra dcl Fucgo. Argen11na 366.8 [ ] 

\Vendmcr. Ctah 371.3 372.2 

Ulaan Uul. 1\1ongolia 371.2 372 . ..J 

Nege' Desert. Israel 

l\ h. \\ aliguan. P.R. of 

China 

371.2 372.7 

370.3 l J 

1829.0 

1717.2 

1779.3 

1801.8 

1861.3 

1799.6 

1806.8 

18..J0.8 

1905. I 

1825.6 

1708.I 

1736.0 

1706.3 

1708.1 

1753.9 

1706.2 

1872.8 

182..J.6 

1782.2 

179..J.O 

1775.2 

18-15.1 

1816 . ..J 

1865.8 

1820.2 

1786.2 

1762.9 

[] 

1790.1 

1707.2 

[ l 

1770.8 

1725.6 

1824.2 

171..J.5 

1706.9 

1828.6 

I I 

1706.3 

1855.7 

1707.5 

1799.2 

1830.7 

1827.0 

1807.8 

1829.7 

171-1.3 

1779.7 

[ l 

[ l 

1796.0 

1798.6 

1837.6 

1909.0 

1826.4 

1706.2 

[] 

[] 

1705 . ..J 

1756.I 

[] 

[ l 

1828.5 

1780.0 

1789.0 

1776.0 

18-15.3 

1816.2 

1856.5 

1819.8 

1788 . ..J 

176..J.3 

[ l 

1793.9 

1706.3 

1809.0 

1767.0 

[] 

1827.2 

1712 . ..J 

1705.i> 

1828.3 

[] 

[] 

1851.9 

[I 

1802.5 

1829.7 

1823.8 

[ l 

126.1 

72.1 

102.9 

111.6 

176.9 

12..J.8 

67.0 

103.3 

[ l 

[ l 

119.3 118.2 

125.3 118.1 

125 . ..J 126.7 

239.3 233. I 

125.3 125.2 

-19.1 -18.7 

74.6 [ l 

51...J [ l 

59 . ..J 6-1.2 

78.9 88.3 

-19.2 ! l 

194.8 [ J 

121.5 125.7 

99.8 I 01.8 

112.6 111.1 

9-1.6 100.6 

1-16.7 ( l 

131.5 127.4 

1-13..J 11'.!.3 

120.9 128.4 

105.0 

89.2 

[] 

111.2 

-17.3 

[ l 

91.9 

77.9 

129.5 

5-1.7 

109.I 

93.4 

[] 

119.2 

-18.3 

126.3 

93.0 

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132.6 

58.6 

-15.9 -18 . ..J 

129.0 128.2 

[ l [ l 

-16.7 [ l 

219.I :!07.8 

-18 . ..J 

120.9 

1-18.9 

1-19.0 

133.0 

[] 

120.7 

15..J.6 

1-16.2 

(] 

315.5 316.2 

315.0 315.7 

315.8 316.6 

315.7 [ l 

316.5 [ l 

315.8 316 . ..J 

315.8 316 . ..J 

315.2 315.9 

316.7 317.3 

315.8 316.2 

31-1 .3 

315.9 

31..J . ..J 

31..J.7 

315.7 

31..J.I 

316.9 

315.7 

315.8 

315.8 

31..J.9 

I I 

[ l 

315.1 

316 . ..J 

I I 

[] 

316 . ..J 

316 . ..J 

316.5 

315.7 316 . ..J 

316.0 316.5 

315.9 316.5 

315.9 316...J 

314.3 315.7 

315.7 316.3 

315.7 316.3 

( l [ l 

315.7 316.3 

31..J.5 315.0 

[ l 

315.7 

315.3 

315.9 

315.1 

31-1.2 

315.6 

[] 

31..J.3 

316.5 

31..J.5 

315.9 

315.9 

316.0 

315.9 

317.3 

316 . ..J 

[] 

316.5 

315.7 

J 1-1.8 

316.3 

[ l 

[ l 

317.0 

( l 

316.5 

316 . ..J 

316.8 

l I 

4.-1..J ..J.64 

4.38 4.59 

..J.57 4.77 

-1.63 [I 

..J.75 [ l 

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..J.63 ..J.82 

..J.70 ..J.87 

..J.64 ..J.82 

..J.34 -1.5..J 

..J.-15 ( l 

-1.33 I I 

..J.36 ..J.54 

..J.51 ..J.72 

..J.32 ( l 

4.79 [ l 

-1.6..J ..J.8-1 

4.58 4.77 

..J.62 ..J.80 

..J.57 ..J.77 

-1.6..J ..J.83 

..J.62 -1.81 

..J.71 ..J.85 

..J.65 ..J.86 

..J.59 ..J.80 

-1.52 -1. 73 

[] ll 

..J.60 -1 .79 

..J.32 4.52 

[ l ..J.85 

4.56 -1.75 

-1.-1 1 I I 

..J.63 ..J.84 

..J.-10 ..J.58 

..J.33 

..J.66 

[] 

4.32 

..J.70 

..J.52 

4.85 

[] 

[) 

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-1.35 I I 

..J.65 4.82 

..J.64 -1.8..J 

-1.66 ..J.88 

..J.66 [ l 

-8.20 

-7.98 

-8.09 

-8.08 

-8.35 

-8. 18 

-7.97 

-8.09 

[] 

I I 

-8.20 -8.13 

-8.15 -8.16 

-8.22 -8.18 

-8.-16 -8.39 

-8.33 -8.20 

-7.97 

-7.99 

-8.00 

-7.95 

-8.03 

-7.98 

-8.30 

-8.17 

-8.08 

-8.10 

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l I 

[ l 

-7.87 

-8.0..J 

l I 

[ l 

-8.19 

-8.12 

-8.16 

-8.07 -8.08 

-8.23 -8.23 

-8.06 -8.14 

-8.30 -8.24 

-8.12 -8.12 

-8.08 

-8.06 

[ l 

-8. 10 

-8.00 

-8.08 

-8.06 

[] 

-8.13 

-8.00 

[ l -8.42 

-8.02 -8.01 

-7.98 ( l 

-8.20 -8.19 

-7.95 -7.97 

-7.99 

-8.18 

[] 

-8.00 

-8.31 

-7.98 

-8.17 

-8.16 

-8.17 

-8.1..J 

-8.00 

-8.17 

(] 

[ J 

-8.-10 

[ l 

-8.18 

-8.16 

-8.15 

[ l 

\\KT l\loody. Texas ll !l 11 l I [I !l [J [J ! I l l [J [ l 

7EP Ny-Alesund. Srnlbard 371.2 372.5 1831.4 1835.3 127.5 127.3 315.7 316 . ..J -1.66 ..J.84 -8.20 -8.24 

[ l --17.-17 

l l I I 

[I [I 

[I [I 

[) [ l 

ll l I 

[I I l 

--17.-13 --1 7.53 

[ l [) 

l l l I 

--16.9-1 [ J 

[I [J 

[I [J 

l l l I 

[ l [ l 

[] 

[] 

[I 

I I 

[ l 

[ l 

l I 

(] 

[ l 

I I 

--17.16--17.53 

I I I l 

[) [ l 

l J l I 

[ l [ l 

[] [ l 

--17.09 --17.20 

[] ( l 

--17.14 --17.23 

( l [ l 

l I [ l 

[I [ l 

( l [ l 

[] (] 

--17.02 --17.18 

--16.96 

I I 

[I 

[ l 

[] 

l I 

[] 

( l 

[) 

[ J 

[ l 

(] 

[I 

(] 

--17.-15 

[ l 

[ l 

[ l 

(] 

[ l 

[ l [ l 

I J I I -------- --- ------------ ------------ --- --- Square brackets indicate insunicicnt data to calculate the annual mean. 

33 
370 ,,....... 

~ 360 

a. 

N 350 0 

u 

E 

a. 

a. 

........... 

N 

340 

3 

2 

(o) GLOBAL MIXING RATIO AND TREND 

(b) GLOBAL GROWTH RATE 

is not included in the model. Plants with the C-3 photosynthetic pathway (the majority of plants) discriminate 

against IJC02, whereas C-4 plant discrimination is much 

smaller and thus more oceanlike in its effect on isotopic 

ratios. When this land conversion effect is included, the net 

land curve will be near zero. Importantly, this implies that 

there must be a sink of C02 in the living tropical biosphere 

because deforestation is clearly contributing to a source of 

C02• The impact of land conversion on the isotope record 

is the subject of one of CCGG's recent publications 

[Townsend et al., 2002]. 

0 

(..) 0 - -------------------------------

A key challenge to keeping these data useful for the 

modeling community is maintaining a stable and precise 

isotopic scale over time. Measurement precision needs to 

be extremely high, at least ±0.0 I %0 (I cr), in order to keep 

the global uncertainty in the above deconvolutions to less 

than 0.5 x 10 14 moles of carbon. This requires constant 

calibrations and the maintenance of a large suite of 

calibrated cylinders that are measured periodically to detect 

and distinguish between any observed instrument drift and 

possibly long-term change occurring in the suite of 

calibrated cylinders. In addition, the laboratory maintains 

several closely monitored intercomparison projects with 

other laboratories in which both laboratories analyze the 

same air-flask sample. Intercomparison projects are 

important because they can alert laboratories to analytical 

problems that can be addressed in near-real time. SIL also 

plays a key role along with laboratories in Japan, Australia, 

United States, and Germany in an ongoing effort to 

establish an international standard for isotopes in atmospheric greenhouse gases. 

79 80 81 828!8411519&117118119 80 91 92 93114 95 91197 91198 00 01 l'EM 

Fig. 2.4. (a) Globally averaged mixing ratio and long-term trend and (b) 

growth rate of atmospheric C02 as measured by the CMDL Global 

Cooperative Air Sampling Network. 

a land-dominated region, are always a sink of carbon for 

both ocean and land, with the land sink larger than the 

ocean sink. In the tropics, both land and ocean are almost 

always a source of carbon. The land source is overestimated and the ocean source underestimated in this 

analysis because conversion of C-3 forests to C-4 pastures 

Spatial and Temporal Patterns of Terrestrial 

Discrimination 

Measurements of C02 and o13C are used to deduce 

meridional patterns in oceanic and terrestrial C02 uptake in 

a simple two-dimensional inverse model. The input to the 

TABLE2.4. Summary of Measurements of the WMO Primary C02 Standards Expressed as 

μmo! mor1 in Dry Air (ppm), September 1996-August 2001 

Cylinder Difference 

Serial CMDL SIO Old Scale (mano - old)* 

Number N (ppm) (lcr) (ppm) (lcr) (ppm) (ppm) 

110 12 246.68 0.10 246.82 0.52 246.78 --0.10 

102 17 304.39 0.11 304.43 0.18 304.41 --0.02 

Ill 19 324.01 0.15 324.04 0.13 324.03 --0.02 

130 13 337.27 0.10 337.29 0.12 337.28 --0.01 

121 II 349.39 0.08 349.35 0.12 349.36 0.03 

103 18 353.35 0.10 353.18 0.12 353.24 0.11 

139 14 360.90 0.06 360.82 0.14 360.84 0.06 

105 16 369.38 0.12 369.32 0.16 369.34 0.04 

136 15 381.34 0.12 381.24 0.17 381.26 0.08 

146 15 389.54 0.11 389.47 0.20 389.49 . 0.05 

IOI 17 396.35 0.15 396.17 0.20 396.22 0.13 

106 13 412.09 0.14 411.91 0.25 411.96 0.13 

123 15 423.06 0.16 422.88 0.29 422.93 0.13 

107 21 453.13 0.19 452.76 0.40 452.90 0.23 

132 21 521.39 0.16 520.99 0.80 521.10 0.29 

*Difference between CMDL manometric values and values determined with the old scale. 

34 
_7.2 

_7.6 

g 

X' 

-= _a. a 

-EL4 

Fig. 2.5. Three-dimensional representation of the latitudinal distribution 

of the carbon isotopic composition of atmospheric carbon dioxide in the 

marine boundary layer. The measurements of stable isotope ratios were 

made at the University of Colorado INST AAR on air samples provided 

by the CMDL Global Cooperative Air Sampling Network. The surface 

represents data smoothed in time and latitude. The isotope data are 

expressed as deviations of the carbon-13/carbon-l 2 ratio in carbon 

dioxide from the VPDB-C02 standard in per mil (parts per thousand). 

model is smoothed over time and does not include highfrequency variability that exists in the data. This allows 

correlation of the high-frequency variations in C02 and 

o13C in order to check model-derived patterns of surface 

discrimination. In a manner similar to that of Bakwin et al. 

[1998b], changes in C02 and o13C are related to isotopic 

discrimination of a source or sink using a time-varying 

background of C02 and o13C. The observed C02 mole 

fraction is defined to be the sum of contributions from some 

regional background concentration and regional fluctuations 

due to biospheric sources and sinks and fossil fuel 

emissions. A similar equation is defined for 13C using the 

product of C02 and o13C, which, to a good approximation, 

is conserved [Tans et al., 1993]. 

c = c bg +elf + cbio (I) 

K = (K)og + (K)IJ + (K)o;a , (2) 

where C refers to C02 mole fraction and '5 refers to o13C. 

The subscript bg refers to background, .ff to fossil fuel, and 

bio to terrestrial biological contribution. Terms with no 

subscript refer to the observed atmospheric values. For 

each sampling site, the data are fitted with a curve 

consisting of a second-order polynomial and two harmonic 

functions [Thoning et al., 1989]. This "smooth curve" 

represents a regional average for either C02 or o13C x C02 , 

so the background components in equations ( 1) and (2) are 

defined by the smooth-curve fits. Then, if the molar 

emission ratio (R) of CO to C02 for fossil fuels is known, 

Cf/ can be determined according to equations (3) and (4): 

35 

I 

1 

0 

-1 

1 

0 

-1 

-2 

~-3 

Q)-4 

>. 

3 

0 2 

E 1 

54° N - go0 N 

-

17° S - 17° N 

"'" 0 

.I 

- - - - - _ =-:-:-:_ _ - - - :.. - --- - - - .... '.'.:":> 

(:, - 1 

1 

1-~...--~~~--+-~--- --1~~ ~+--~--~-+-~--t 

53 S_.::... 18 §.--.._ 

0 - ----==- --- -- --

-1 r--,__,~~-.;.-~---~-, 

-2 

-3 1- ~---~--+--~-------l 

1 go0 S - 54° S 

o ---- --- -1 

1992 1994 1996 1998 2000 

Fig. 2.6. Reconstructions of net CO, fluxes between the atmosphere and 

the terrestrial biosphere (green) and the ocean (blue) as well as the total 

net flux between the atmosphere and the Earth's surface from pC02 

(red), in major latitude zones. Dashed lines represent source/sink 

reconstructions using values for terrestrial discrimination that are 

consistent with CCGG observations. 

(3) 

CIJ = (CO - COhg)IR . (4) 

As with C02, C0&11 is defined to be the smooth-curve fit 

to the CO data. With this model, changes in CO due to OH 

photochemistry and biomass burning are neglected. 

However, Bakwin et al. [ l 998b] showed that changes in 

CO:C02 emission ratios of 15% and the inclusion of OH 

consumption had very little effect on the calculation of b&;,,. 

A value for R of 20 ppb CO/ppm C02 is assumed. Values 

for <'i_r1 are taken from a zonally and annually averaged data 

set of o13C of fossil fuel emissions for 1992 [Andres et al., 

1996]. For a given site, values from the four nearest 1 ° 

zonal bands are averaged to calculate bf/· . Equations (I), 

(2), and (4) are then combined to give equation (5): 

(5) 

Superscript R denotes the residual difference between the 

data and smooth curve. The right-hand side of equation (5) is 

plotted against the left such that the slope of the line is '5010 • 

Figure 2.7 shows '50;

0 for the subset of continental sites 

with more than 3 years of data available for May, June, 
July. August, and September. Fluctuations in summertime 

data arc more I ikcly lo be re lated to biosphcric 11uxes. and 

thus calculated discrimination \'alues are less scnsitiYc to 

the fossil fuel correction. Analysis was restricted to 

continental sites because they arc the most likely to satisfy 

the assumptions implicit in equations ( I )-(5). Specifically. 

the equations do not account for l1uctua11ons about the 

smooth curve resulting from oceanic exchange processes. 

At the continental si tes used here it is likely that most 

oceanic nuxes ha\c been mixed into the atmosphere to the 

extent that they arc captured by \'ariations in the smooth 

curve, and the remain ing nuctuations arc mainly a result of 

terrestrial processes. Note that other sites, during certain 

times, may also satisf) the assumptions of equations (I )-(5). 

Ohw \aries from about 30 to - 2-1°00 (Figure 2.7). The 

a\ erage of the 14 sites used is 26.0 ± I. 9°00 (I <J between 

sites). When data from all continental sites are binned as 

one site, Ohio 24.5 ± 0.2°00. This second a\ cragc is 

heavier than the first because sites with more data. and 

especially those \\ ith larger residuals. like the tall tower 

sites IT"!, HUN, and LEF. are gi,en more weight. These 

'alues of oh,,, correspond to isotopic discrimination 'alues 

of 18.0 and 16.5°00, respecliYely, for the 1-1 sites and all 

continental sites. 

Fung el al. [ 1997], using a Simple Biosphere l\lodcl 

(SiB2) coupled to a general circu lation model (GCM), 

found that discrimination changed from I 0 lo 20°00 bet\\ een 

30° and 50°N. Lloyd and Farquhar [ 1994] used a di ffcrcnt 

approach lo calcu late discriminati on values ranging only 

between I 5 and 16.5°00 O\ er the same latitudes. The map of 

discrimination used in this study to calculate the terrestrial 

carbon flu x from CM DL atmospheric obsc1 Hlliu11:, [ Ciais el 

al .. I 995a] ranges bet\\CCn 18 and I 9~oo over the same 

latitudes. The a\'erage discrimination 'alues CCGG 

inferred from obscr\'ations are less than the Ciais e1 al. 

[I 995a) model. although about half the sites agree quite 

-20 

MJJAS 

-22 

,,......, -24 11 ~ ~t:tj E -26 

'-

~ ~1 ~ ~ ~ 

~ Q) -28 a... 

~ ........... 

0 -30 

'l5 

'O 

-32 

-34 

20 30 40 50 60 

NORTH LATITUDE 

Fig. 2.7. Isotopic composition of biosphcric sources at the continental 

stations of 1he C1\IDL Global Cooperati\e Air Sampling Nel\\orl- for 

i\1ay through September. Bars to the right of the S)mbols (site codes) 

denote estimated unccnainl). 

36 

\\ell. The data show no meridional gradient in contrast to 

the Fung el al. [ 1997] result. About half the sites studied also 

agree reasonabl) well with the Lloyd and Farquhar [ 199-1] 

model. \\ ith the other sites sho\\ ing higher discrimination. In 

the CCGG analysis, the origin of the air sampled has not been 

accounted for, "hich ma) explain some of the discrepancy 

between the models and CCGG calculations. 

A Global Data Set for 0180 of Atmospheric C01 

The o1s0 of atmospheric CO~ has great potential as a tool 

to separate net photosynthetic and respiratory fluxes of co~ 

by land plants. The oxygen of CO~ can exchange with 

O\ygen in leaf water and in soil "atcr. Because leaf water 

is typically enriched in 180 relati\e to 160 due to 

C\ aporation of \\'ater from leaves, the 0180 of atmospheric 

CO, that has been in contact "ith leaf water (the 

pho~osynthctic nux) is enriched relatiYe to 01so of 

atmospheric C01 that has been in contact \\ ith soi I wa ter 

(the respiratory nux). Several papers have recently 

explored the potc111ial of this tracer technique using GCl\ ls 

with isotope physics included in the carbon and water 

cycles [l'akir el al., 1994; Miller el al., 1999; Peylin el al .. 

1999]. One major hurdle to the further de\ clopmcnt of this 

tracer is that air samples collected "\\et." that is. when the 

air is not dried during the sampling process, may experience 

post-sampling equi libration of oxygen in co~ with oxygen 

in the water vapor in the tlask. It was demonstrated that 

this can occur" hen air humidities are high [Gemery el al .. 

1996]. In the past, all 11 ask data for 8180 of atmospheric 

CO~ between the latitude bands of 30 N and 30°S ha' e been 

nagged as bad. CCGG has kno" n that this approach 

eliminates some good data but has been unable to discern 

which samp les were good data and \\hich were not. With 

the addition of several Al RKITs at tropical sites. which are 

sampling systems that dry air during sampling. data needed 

to compare sampling systems and generate a data set of 

1)180 of atmospheric CO~ \\ ith global CO\Crage arc nO\\ 

arnilable. An example of this is shown in Figure :!.8, "hich 

compares sampling systems used in parallel at Cape 

Kumukahi. Hawaii. Note that C\ aeuated Oas ks compare 

well" ith the dried nasks. an important obsenation because 

the Pacific Ocean shipboard 11asl,.s arc e' acuatcd Oasks. 

l\lultiycar records of 01so of atmospheric co~ at dried sites 

also allow assessment of the range of the expected 

\"ariability in moist, tropical sites and selection of the 

erncuatcd and undried data accordingly. The new, filtered 

data arc shown in Figure 2.9 as annual means for each si te 

plotted as a function of latitude. 

2.3. !\1ETHANE 

2.3.1. I:'\ SITU METHA:'\E MEASU RDIE;'\TS 

Quasi-continuous measurements of atmosphe ric methane 

continued at Mauna Loa and Barro\\ obscn atorics at a 

frequency of four ambient measurements each hour. The 

relative precision is 0.07°0. Details of the measurement 

techniques and analysis of the in situ data through early 

1994 were published in 1995 [Dlugokencky el al .. 1995]. 

Daily a\craged methane mole fractions (in 10"1 mol 11101' 1

• 
-15 D 

-2 

Cl 

0 

D 

Cl 

D MAKS (undned) v Ev'lc. , ,·,_J 

• AIRKIT {dned) 

95/1/1 961111 97/ 1/1 98/111 9911/1 00/1/1 01/111 0211/1 

Dale 

Fig. 2.8. Comparison of li180 of atmospheric CO! from three different 

sampling systems at Cape Kumukahi, Hawaii: dried, evacuated, and 

undried. 

nmol mol" 1

) for 2000-2001 are plotted in Figure 2.10 for BRW 

and MLO. The data were edited for instrument malfunction 

using a rule-based expert system [Masarie et al., 1991), and 

they were selected for meteorological conditions. Brieny, the 

BR W data are constrained to the clean-air sector, whi ch 

includes wind directions of 20°-110°, and wind speeds >I 

m s· 1

• MLO data are constrained to 0000-0659 local time, 

which is typically a period with downslope winds. In situ data 

are available at hourly, daily, and monthly time resol ution from 

the CMD L World Wide Web page (www.cmdl.noaa.gov) or fip 

lile server's "pub" directory (ftp.cmdl.noaa.gov). 

90'5 30'S [Q 30''1 90'~ 

. 00 f -,.- - T 

o.oof 

,., 

~ -i.00~ 19~3 

0 

2.00 l ~ 19n7 '() 

..., l.J>< 

~ '"JCJ1 

-301 -1.0 -0.8 -0.6 -0.• -0.2 0.0 0.2 0.4 0.6 0.8 1.0 

- ~E tAT 'JOE 

Fig. 2.9. Latitude distribution of li180 of atmospheric C02 from NOAA 

data. Annual a\·erages from sites "here samples are collected "dry" are 

shown as solid red squares. Annual averages from the Pacific Ocean and 

South China Sea shipboard samples collected in 3-L flasks are shown as 

solid blue circles and green triangles, respectively. The latitude 

distribution for each year shown is represented by a cunc fitted to "dry" 

records only. 

37 

a ,,....._ 1950 Ci 

\-~~ JJ .. j,l ,,;,.If,\,.} \lJ ~.t jQ E 

" 1900 

0 

E 

c 1850 '-' 

. 

I 

0 1800 

b 

Ci 1800 

~~ E 

" ~ 1775 

0 

E 

c 1750 . 

I 

u 1725 

2000 2001 

YEAR 

Fig. 2.10. Daily mean CH, mole fractions (in nmol mol-1

) for (a) Barrow 

and (b) Mauna Loa, for 2000 and 2001. 111e data arc constrained for 

wind regime (sec text), and they ha\c undergone a quality control step to 

ensure that the analytical instrument was working optimally when they 

were obtained (Masarie el al., 1991 ]. 

2.3.2. MEASUREl\I ENTS OF METHANE I DISCRETE 

SAM PLES 

During 2000-2001 the determination of the global distribution of atmospheric methane continued from 4 7 sampling 

sites of the CCGG Global Cooperati ve Air Sampl ing 

Network. Sampling was started at one new site during this 

2-yr period. A new tower measurement and sampling 

program on the KWKT tel evision transmitter tower in 

Moody, Texas, began in February 200 I. North-south 

sampling transects of the Pacific Ocean (and in the South 

China Sea) by ship have been suspended. Because of the 

importance of these measurements in studies of the global 

methane cycle, it is hoped that sampling can begin again in 

the future. Sampling a lso ended in 1999 at Maldives (KCO) 

and Malta (GOZ). Provisional annual mean va lues for 2000 

a nd 2001 are given in Table 2.3. Complete data records and 

monthly means can be obtained through 200 I for each site 

from the CMDL World Wide Web page (www. 

cmd l.noaa.gov) or ftp file server's "pub" directory 

( ftp.cmdl.noaa.go v). 

Globally averaged CI-1 4 dry-a ir mole fractions are plolled 

in Figure 2.1 I a for the period 1983.5 through 200 I (see 

Dl11goke11cky et al. [I 994a] for details on calculation of 

global and zonal averages). During this time, CI-1 4 

increased from about 1615 nmol mor 1 to about 1750 nmol 

11101" 1. The instantaneous growth rate for g loba lly averaged 
,.---.... 

' 1725 0 

E 

0 1675 E 

c 

v 1625 I 

u 

,.---.... 0 

' L 

>- 15 

I 

0 10 E 

0 5 E 

c 

I 

0 

u 

1985 1990 1995 2000 

YEAR 

Fig. 2.11. (a) Globally mcragcd methane mole fractions. The solid line 

is a dcscasonaliLcd trend curve. (b) Instantaneous Cl 14 growth rate for the 

global m erages. The gro\\1h rate is calculated as the derivative of the 

solid cune in (a). 

CH4 is plotted in Fig ure 2. 11 b: it ha s decreased from about 

1-l nmol moi- 1 y( 1 al the start of the record to approximately 

Lero in 2000 and 200 I. with significant intcrannual 

variabi lity. An allempt has been made to explain the large 

variations in g rowth rate. The increased global growth rate 

in 1991 appears lo have been dri ven by CH 4 sink chemistry 

in the tropi cs after the erupt ion of Mt. Pinatubo in July 

1991. Dlugokencky et al. [ 1996] showed that S02 emilled 

duri ng the eruption. and subsequent sulfate aerosol 

produced by oxidation o f the S02, affected tropical 

photochemistry, which temporarily decreased the photochemical Cl 14 de struction rate. The decreased global 

growth rate during 1992 was dri ven by a decrease of 0.3 ± 

0.8 nmol mol"t in the northern hemisphere. Dlugokencky e1 

al. [ 1994b] suggested that the decreased growth rate in 1992 

could, only in part, be explained by decreased emissions 

from natural wet lands. B. Walter (personal communication, 

2000 ) used a process-based mode l to show that lower-thannormal temperatures and precipitation in high northern 

ll"et land regions during 1992 resulted in decreased Cl 14 

emissions from wetlands. Such a change in wetland 

emissions would have been temporary: there is now 

evidence in the measurements that a separate step-li ke 

decrease in high northern emissions occurred during 1992 

(sec later in this section). During 1998, there \\as a large 

positi\·e anoma ly in global groll"th rate that corresponded to 

an increase in the imbalance between sources and sinks of 

2-l Tg Cl-14 (I Tg = 1012 g). Dlugokencky et al. [2001] 

38 

attributed this to increased emissions from wetlands in the 

high-northern and southern-tropical latitudes resulting from 

warmer and welter-than-normal conditions. 1Val1er [ 1998] 

and Walter mid Heimann [2000] used an adaptation of a 

process-based model that included soi l-temperature and 

precipitation anomalies to calculate decreased emissions for 

1998 of I 1.6 Tg C H4 from wetlands north of 30°N and 13 

Tg Cl-1 4 for tropical wet lands compared with the average 

emissions calculated for 1982-1993. Nearly all ( 11.5 Tg 

CH4 ) of the tropi cal emission anomaly was in the southern 

tropics (equator to 30°S). 

The observed long-term decrease in growth rate is 

consistent with o ur previous s uggestion that atmospheric 

CH4 is approach ing steady state [Dlugokencky el al., 1998], 

if it is assumed that the CH4 lifetime has been constant over 

the time period of the mea surements. In Figure 2. I 2a 

annual global Cl 14 emissions are plotted for the period 

1984-2000. They were calculated using the measured 

global Cl-14 burden and rate of increase with a constant 

life ti me of 9 years [Monl::ka et al .. 2000] in a mass-balance 

equation [Dlugokencky et al., 1998]. Other recent studies. 

though. suggest that the Cl-1 4 lifetime may not be constant. 

Krol et al. [ 1998] and Karlsd611ir and Isaksen [2000) 

suggested that global hydroxyl radical (OH) is increasing. 

with a resulting decrease in Cll 4 lifetime of about 0.5% yr- 1 

during this measurement period. If con firmed, CH4 

emissions must be increasing, also by 0.5% yr" 1

• Contrary 

600 

550 

500 

600 

. 

I 

u 550 Q"l 

f500 

0 

b 

1985 1990 1995 

YEAR 

e Source 

T Sink 

2000 

-

-

Fig. 1.12. Global annual emissions (circles) and sinks (triangles) for 

methane calculated using (a) a constant lifetime of 9 years and (b) 

smoothly \·ar) ing lifetime determined by Pri1111 e1 of. [200 I]. The dashed 

lines arc linear fits to the emissions with I cr confidence limits. 
to these studies. Pri1111 er al. [200 I] suggest that global 0 11 

has decreased by an a\erage rate of 0.64 ± 0.60°0 y..- 1 O\er 

the period 1978 to :moo. Further. they state that OH 

increased b) 15 ± 22°0 from 1979 to 1988, and then 

decreased to le\ els in 2000 that were I 0 ± 2-l~o lo\\'er than 

those in 1979. The impact of the Pri1111 el al. [200 I] 011 

changes on Cll4 lifetime is quite large. and the resulting 

changes in global Cll 4 emissions arc plotted in Figure 

2. I 2b. CCGG has not yet determined "hat combination of 

changes in sources could explain the near!) 100 Tg Cl 14 

decrease in globa l emissions bet" ecn 1991 and 2000. 

Figure 2. I 2a suggests that a potentially huge change has 

occurred in the global Cl-1 4 budget: that is. in 2000 it is 

obscn ·cd that for th e first time in the CCGG record the 

global sink was larger than global emissions. This indicates 

a net decrease in the global burden o r Cll 4 • No one can yet 

explain. C\ en qualitati\ el). the changes in Cl-1 4 source-sink 

imbalance that ha\ e occurred O\'er the past decade to cause 

a net decrease in global Cll 4 burde n. Without an 

understanding of the processes causing this change, it is not 

possible to guess. much less predi ct,\\ hat \\ill happen to the 

Cl 14 gro\\'th rate in the future. 

One possible change that may ha' e tipped the balance to 

a net global Cl 14 decrease is in emissions of Cl-14 from the 

fossil fuel sector 1n the former So' iet Union (FSU). In 

Sch11ell el al [2001. pp. 33-3-l]. a speculati\e scenario is 

described that ma) ha\ e contributed to the obscr\'cd 

decreasing burden o r atmospheric methane . E' idencc for 

this scenario comes from two recent studies of C!-14 

emissions fro111 Russia. Reshet11iko1· el al. [2000) estimated 

24-40 Tg C!-1 4 emissions from the Russian gas industr) 

during the late 1980s and early 1990s. Dediko1· el al. 

( 1999]. using 111eas11rements from an extensi\c program in 

1996 and 1997 to determine losses from Russian gas 

production and trans111ission facili ties. estimated a 3.6 Tg 

y(1 Cl-1 4 emission during that time. The dra111ati c decrease 

in emissions suggested by these studies is not supported by 

CCGG mcasure111ents. but an abrupt decrease in emissions 

from high northern latitudes is consistent "ith changes in 

the obs en ed Cll 4 latitudinal gradient. Differences in C 11 4 

calculated for polar latitudes (53.1 °-90 1 = PNH: 53 .1 °-

900S = PSll ) are plotted in Figure 2. 13. From 1984 through 

1991. the di ffercnce in zonal a\ erage increased. In 1992. 

there was a do\\n\\ard step change in the difference of 

about I 0 n111ol mo1' 1

. \\'hich continued do\\ mrnrd after 

1992. It is unlikely that this step change is due to a natural 

source such as wetland emissions or a permanent change in 

the sink. It is almost certainl y an anthropogenic sou rce that 

can be altered quickl y: fossil fuel exploitation is the most 

likely source. During 2000. the FSU produced 28% or the 

\\'orld's natural gas and about 10°0 each or coal and oil. 

Coal. oil. and natural gas production relati\ e to 1990 for the 

FSU arc plotted as a function of time in Figure 2. 1-l. 

Bct\\'een 199 1 and 1997. product ion of natural gas 

decreased b) 15%, or about 60 Tg Cl 14 • Combined with the 

la rge decreases in oil and coal production, it is concei\able 

(but not pro,ed) that these changes are responsible for 

atmospheric Cl 14 sources and sinks coming to steady state. 

39 

150 

........ 

0 140 E 

0 

E 

c 

~ 130 I 

VJ 

Cl.. 

I 

I 

z 120 

Cl.. 

110 

1985 1990 1995 2000 

YEAR 

Fig. 2.13. Annual (filled cirdc;) and \\eek I) (;olid cun c "ith I cr 

confidence limits) differences in Lmmll) mcraged Cl I, mole fractions in 

the latitude zones 53. 1 -90 N (PNll ) and 53.1 °-90 S (PSI! ). Trends in 

the differences an: plouccl for two periods as dashed lines: 1983.5-1991 

(0.+-1 ± 0.36 nmol 11101'1 )r'1

) and 1992-2000 (-0.94 "' 0.32 nmol 

mot ) ( ). The mean dtlforencc for the entire period 1s 133.9 nmol 

mot . 

2.3.3. A n1osP11 rn1c o' cH~ ~cE t 998 

l NST AA R's S IL has been measuring 811C in atmospheric 

C 114 at 6 si tes since 1998. and has recently increased that 

number to 13 sites. Partitioning atmospheric Cl 14 into its 

sources and sinks is possible through globa l measurements 

of its stable carbon isotopic ratio. 811Cll4 • in addition to its 

e Cool 

c 1 j i t ::: oa Q t • • •O< 

.J I 

"::;) 1 . (, 0 • • • a. • • • 0 0 .9 • i en • • • C> • • • • • • 08 ::: 0 • 

.Q 0.7 ::: 

• u ::: I ::: I ::: 0 I 

t.:: 06 • • • • • 

1985 '990 4995 2000 

YEN~ 

Fig. 2.14. Production of coal. natural gas. and oil in the fonncr So"iet 

Union relati,·c to 1990. Production in 1990 was 332 x Io• tonnes oil 

cquhalenl for coal. 684.6 x 10• tonnes oil equirnlc111 for natural gas. and 

570.5 x Io• tonnes oil. 
atmospheric mole fraction. Biological sources. such as 

wet lands. ha,·c a characteristic isotopic compos1t1on 

(typicall y -60°00) that is more depleted in the hea\ y isotope. 13C, than thermal sources like natural gas (-40°00), which in 

turn. are more depleted than biomass burning sources 

(-25°&,). The measured isotopic ratio of atmospheric Cl 14 

(-47°&,) is a composite of these sources. but it is also 

in ll ucnccd by the enrichme nt in 13C content (+5°00) that 

results from the destruct ion of methane by 011. which is 

slightly more rapid for ~CI 14 than for uCH4. 

An automated system was designed for the ana lysis of 11C in atmospheric methane [Miller e1 al.. 2002). Since 

January 1998. pairs of llasks were ana lyzed on a weekly 

basis from six sites (SPO, CGO. SMO. MLO. N\VR. and 

BR\V) of the Global Cooperative Air Sampling Network 

(sec Table 2.3 for site acronym defi nitions). In January 

200 I. a new automated llask manifo ld with a capacity of 16 

fl asks and multiple reference tanks was built and insta lled. 

This has allowed an expansion of the number of sites 

measured from 6 to 13. The new si tes arc ALT. ASC. AZR. 

KUM. MllD. TAP. and \VLG. The CCGG standard scale is 

linked to a scale ma intai ned by the Un i,ersity of California. 

Irvine (UC I). Air tanks calibrated at UCI arc used to 

establish the CCGG suite of worki ng reference tanks. A 

program \\hereby both CCGG and the UC I laboratories 

measure o13C in sma ll cylinders collected at N\VR 

commenced in summer 2000. Preliminary analysis 

indicates good agreement between the laboratories. 

Figure -2. 15 strnws the seasonal variations of o13C and 

CH4 at BR\V. The seasonal minima for o13C at BRW occur 

d uring Seprcmhcr or October :rnrl are curiously offset in 

time from either the seasonal Cl 14 maxima or minima. The 

timing of the seasonal cycle o f CH4 indicates th at it is 

dri,·cn. in large part. by seasonal \ariations in 0 11, the 

primary sink for CH4 in the atmosphere. The seasonal cycle 

of o13C. on the other hand. is dri\en most strongly by 

E -47.0 

'-- ! -47.5 ·: + 

~ -48.0 ... + + .. 

'O 

-:0 1850 a. 

a. 1800 I .. 

u 1750 

... + + 

+ 

+ 

• + 

+ 

•+ + 

.. 

1700'--~~~~~~~~~~~~~~~~~~~ 

1998 1999 2000 2001 

Fig. 2. 15. 811C (top panel) and mole fraction (bouom panel) of 

atmospheric Cl!" at Barrow. Alaska (BR\\'). from 1998 to 200 I. Pluses 

arc a\ crages of sample pairs collected sequentially on the same day. The solid cun cs arc smooth fits 10 the data [ Tlto11i11g et al.. 1989 ]. 

emissions from wetlands. The growth rate of o 11C during 

the summer is negati \ e. which is consistent with the 

addition of isotopic;lly light CH4 (more negative olJC) that 

is characteristic of wetlands emissions. This occurs despite 

the increasing act i\'ity of OH during the summer. which. in 

the absence of other processes, would result in a posith e 

o u C growth rate. The late summer minima in o11C arc 

probably the comb ined result of OH concentrations that arc 

reduced relati\c to th e middle of summer and wetlands 

emissions that arc still significant. 

Durin!l 1998 at BR \V the CH4 minimum \\'as less 

pro oun~ed than in other years, and the minimum in o13C 

\\'as more pronounced (sec the smooth-cun c fi ts in Figure 

2.15 ). Dl11goke11cky el al. [200 I] hypothesiLed that the 

growth rate anomaly in CH4 associated with the highcrthan-norma l seasonal minimum \\'as a result of two factors: 

increased Cl 14 emission from borcal \\'et lands in Canada and 

Siberia, and large emissions of CH4 from pcatland fires in 

Siberia. \Vith a two-box model of' the atmospheri c Cl 14 , this 

hypothesis was tested against the Cl 14 and o11C 

observations. It was found that the combination of 

anomalous wetland emissions and fire emissions fitted the 

observations better than either emission anomaly on its 

own. 

2.4. CARBON MONOX IDE 

2.4.1. MEASU L\ E~TS O F CA RBO ~ M ONO XIDE 

During 2000-200 I the study of the global distribution of 

CO in the lower troposphere continued using air samples 

collected through the CM DL Global Cooperati\c Air 

Sampling Nct\\'ork, in situ measurements at BR W and 

M LO. and air samples collected as part of the Measurement 

of Pollution in the Troposphere (MOPITT) validation 

program. Rates of drift in CM DL CO standards were 

quantified. and procedures fo r revision of the data were 

developed and implemented. In the air sampling network. 

the conversion on the last llasks to glass pistons wi th Tellon 

0-rings allo\\'cd CO to be measured at all active sites in the 

network. In situ measurements at BR\V and at MLO each 

had un ique problems. Improvements to the ruggedness of 

the air sampling units used aboard aircraft provided much 

greater success in 'ertical profi les at remote sites. The four 

verti cal air sampling sites established for the validation of 

MOP ITT provided monthly to biweekly profi les. Profiles 

were also determi ned over southern Africa as part of th e 

Southern Africa Fire-Atmosphere Research Initiative 2000 

(SA FARI 2000). 

Flask Meas urem ents 

Provisional annual mean CO mole fract ions for 2000 and 

200 1 are presented in Table 2.3. These va lues represent a 

correction to the CMD L CO scale (described in section 

2.4.2). As discussed previously [No1·elli el al .. I 998a], a 

high degree of intcrannual variation occurs in tropospheric 

CO (Fi gure 2.16). The sharp decline in global CO during 

1992 has been attributed to the effects of the June 1991 

eruption of Mt. Pinatubo [Bekki el al .. 199-l], and as the 

effects of the eruption diminished in 1993. CO returned to 
220 

220 

200 

180 

:0 

a.. 160 

..!;: 

0 

(j 

140 

120 

100 

80 

70 

-:;;- 60 Q. 

~ 

0 

u 50 

Pt. Borrow 

Cope Gri 

1990 1992 1994 1996 1998 2000 2002 

YEAR 

Fig. :!. 16. Tim..: series of tropospheric CO mixing ratios from Pt 

Barro\\. Alaska. and Cape Grim. Tasmania. Triangles are the mean ofa 

pair of flasks: the solid cur.es arc smooth lits to the data. 

pre\ ious le\ els. co mole fractions determined in nask 

samples showed strong cnhancemcnts beginning late 1997 

through 1998. In the southern hemisphere the anomaly \\as 

largely con fined to the tropics during late 1997. when 

strong fires in Indonesia burned agricultural areas, forests. 

and peat swamps. In the northern hemisphere a "eak 

summer minimum in 1998 was followed by high CO 'alues 

throughout the fall. The enhanced CO is attributed to 

extreme and '' idcspread forest burning during the summer 

and fall of 1998. Fires in Siberia detected by Advanced 

Very High Resolution Radiometer (A l IVRR) burned late 

into the autumn. lnterannual \ariations in the CO time 

series are probably related to variations in large-sca le 

biomass burning. 11'01mrn el al. (2002] reported that twothirds of the interannual CO 1·ariability in the e.\tratropical 

northern hemisphere can be explained b) boreal biomass 

burning. Measurements from the air sampling network 

show that afte r the high CO observed during 1997 and 1998. 

mi\ing ratios returned to pre-1998 le\ e ls in 2000 and 200 I 

(Figure 2. 16). 

!11 Situ ftfeas11re111e11/s 

Quasi-continuous measurements of CO (3--1 samples per 

hour) continued at BR\V and MLO. Both sites had minor 

problems. The instrument at BR\\/ \\as o ff line during midSeptcmber-No1 ember 2000 because of a loss of standard s 

during shipping. ~leasurements at MLO were hindered by a 

series of bad Il g lamps in the instrument. which often 

limited acceptable data to 1-2 samples per hour. In spite of 

these problems, CO determined from the in si tu instruments 

agreed well with nask samples. At MLO the annual mean 

CO mole fractions determined from nask measurements and 

41 

from thl! in situ instrument (selected for downslope 

conditions) agreed well. even during periods when the 

instrument's Ilg lamp 11as marginal. lligh co rrelation 

between the nask and in situ measurements was found at 

both sites. and there is no sign ificant offset between the two 

measurements (rigure 2.17). llowe\er. the scatter is greater 

at M LO than at BR \\I (r 0.973 and 0. 997, respeeti\ cly). 

The residuals from a function approximating the annual 

oscillations and trend [ Tho11i11g et al .. 1989] \\'ere used to 

examine CO at BR\V. Using a transport model and 

estimates of emissions from fires burning in eastern Russia. 

Brulmiler el al. (in preparation, 2002) sho\\ed that the high 

le' els or CO seen at BR \V during fall 1988 are consistent 

\\'ith the transport or emissions from fires in eastern Russia. 

0 

a. 

~ 

0 

0 

, 

·n 

.f 

(a) 

0 

! 

0 

(J 

~ 

·;;; 

(b) 

;50 

120 

90 

;/ 

... . . ., 

:.-' 

A• .. . 

60~~~~~~~~~~~~~~~~~~~~~ 

60 90 · 20 1~0 180 

r·a .. co (pp!>) 

150 

// ·25 

./. 

/ 

,.. - 100 .r· •;~ 

/ ' . . -"'· 75 . ,,. •• 

·r . . ,.,. <~· 

50 

•I ~ 

50 75 I CO 125 ·50 

;:- 0~1( CO (pD::>) 

Fig. ::!.17. Comparison of flask to in sill! measurements at (a) Pt. Barro\\ 

and (b) J\1auna Loa. The relationship bcmecn these measurement;, is 

de tined "ith an onhogonal linear regr..:ssion. BR \V: y = 0.087 <= 0.987) 

- 0.989 (er 0.008) r: J\ILO: y = -2.583 (::: 1.485) - 1.006 (= 0.017) x. 
Vertical Profiles 

With funding from the NASA Earth Enterprise System 

(formally the Earth Observing System), CMDL established 

four sites where the vertical profiles of CO and C l-1 4 are 

determined o n a regular basis (Table 2.5). The 

measurement program has two goals: ( I) It will provide 

vertical distributions of CO and C l-14 for the va lidati on of 

MOPITT radiances and mixing ratios. MOPITT is a nadirviewing, gas fi lter correlatio n radiometer that determines 

the column distribution and total abundance of CO and 

column abundance of Cl-1 4 . (2) It will use these data to 

better understand the distributions of trace gases above the 

boundary layer and provide additional constraints on trace 

gas budgets. The data collected by this program provide a 

unique view of CO and other trace gases as a func tion of 

altitude. 

The portable air sampling equipment developed at CMD L 

is used on chartered aircraft to collect air sampl es at 

altitudes of up to 8 km above sea level once o r twice per 

month. Flights are scheduled such that the aircraft is about 

halfway through its de scent as the sate llite passes overhead. 

Ana lysis in Boulder includes the s uite of gases measured by 

CCGG: CO and Cl 14, and also C02, 1-1 2, N20, and SF6• In 

addition to the long-term sites, profiles were measured over 

South Africa, Botswana, and the western Indian Ocean as 

part of the SAFARI 2000 campaig n. Preliminary 

comparison of the CMD L profiles with the MOPITT 

retrievals are within the MO PITT specifications. Other 

flights in Colorado, Oklahoma, Cal iforni a, and South Africa 

were used to va lidate measurements made by two MOPITT 

simulators de ve loped at the University of Toronto and at the 

National Center for Atmospheric Resea rch/ Atmospheric 

Chemistry Di vision (NCAR/ ACD). More than 110 flights 

were conducted as part of this program. Regular sampling 

at the fou r MOPITT sites builds time series that define the 

trends and seasonal cycles of CO and the other trace gases 

at altitude (Figure 2. 18). 

2.4.2. CO REFERENCE GASES 

Nine CO standards were prepared by CM DL using 

gravimetric methods during late 1999 and early 2000. Mole 

fractions assigned to CMD L working standards re ferenced 

Table 2.5. MOPlTI Validation Sites 

Latitude/ Maximum 

Site Longitude Altitude (km) Environment 

Poker Flats, AK 65. l

0 N/147.5°W 7.S HNH background 

continental 

Harvard Forest, 42.5°N/7 l .2°\V 7.9 NH polluted 

MA continental 

Molokai, HI 2 l .4°N/l 57.2°W 7.9 Background NH 

oceanic 

Rarotonga. 2 l.2°S/l 59.8°\V 5.0 Background SH 

Cook Islands oceanic 

Southern Africa• 20-30°N/22- 35°E 8.4 SH background and 

polluted oceanic 

and continental 

*SAFARI 2000 campaign (not a permanent site). 

42 

160 

150 . '.D 140 

0.. 120 ~ 

0 100 u 80 

60 

140 

120 

"'.Ci' 

Q. 100 0.. 

0 80 u 

60 

120 

,.-.... 100 J::J 

0.. 

Q. 80 ..__.. 

0 

(J 

60 

40 

2.5 km . :t. 

• I- .• • • • i -J. • • • fl-

. .-·.·r · -.. ti. ... ~ • -i ·. ·· • • . ~ """ . ~ .. , .... ... .&. ._ •• .... - ·. _ ,. 

x-~ .t. • ~ 

f 

• 

• 

... 

" 

1999 

4.5 Km 

6.5 Km 

r:\· " t \ 

/---/. " t 

/ • " v 

2000 

YEAR 

2001 

Fig. 2.18. CO time series from Molokai. Ha\\ aii. binned for each I 000 ± 

500 m altitude (typically 2-3 samples; each sample is plo1tcd as a solid 

triangle). In the top panel. open circles are the flask results from MLO. 

against the new grav imetrics were signifi cantly larger than 

those previously assigned based upon the original CMDL 

CO sca le [Novelli et al., 199 1, 1994]. Mole fractions 

assigned to the working standards using dynamic dilution of 

a National Institute of Standards and Technology (NIST) 

9.7-ppm standard in 2000 confirmed the higher CO levels in 

the new standards. Although frequent intercomparison of a 

suite of standards mainta ined at CM DL did not suggest drift 

in the standards, comparison of ca libratio ns of working 

standards referenced to three sets of gravimetric standards 

(prepared in 1989/1992, 1996, and 1999/2000) did indicate 

a change over time. A re-evaluation of the CO scale, 

extending back to the first set of gravimetric standards, plus 

confidence in both the original scale and the 199912000 

gravimetri c standards, lead to the belief that both the 

secondary and working standards have c hanged over time. 

Calculation of linear drift rates of ±0.3 ppb yr' 1 between 

1992 and 1999/2000 are consistent w ith the results from a 

set of gravimetric standards prepared in 1996, and with 

comparisons with several other laboratories [Novelli et al., 

I 998b; Masarie et al., 200 I]. Thus, there is consistent 

evidence that many of the CMDL standards have dri fted 

upward. 

Calibration procedures were based upon the analysis of 

six to eight standards with mixing ratios between SO and 

200 ppb; calibration curves were generated using area 

response and the CO mixing ratio assigned to the standards. 

Their relationship was defined using both a quadratic and 

•' 

j 

J 

I I 
third-order pol) nomial cun e [.\'oi·e/li et al .. I 998a]. The 

original set or "orking standards used bemeen 1990 and 

mid-1 997 were al I cal ibrat cd aga inst the 1992 and the 

1999 2000 !!.ra\ imetric standards. and in man) cases a lso 

agai nst the gra\ i metric standards prepa red in 1996. From 

calibration s. a rate or change in the 11orking standard was 

determined. These ra tes were then appli ed to the mole 

frac tion assigned to each standard in 1992, and new 

cal ibration cun es were genera ted. Combi ned \\ ith the 

archi\ ed sample area responses. each sample anal) ted 

through June 1997 was assigned a ne\1 mol e fraction. (In 

mid- 1997 the CO anal) ti cal system was changed to the 

\l easurcments of Atmospheri c Gases Influenc ing Climate 

Change (MAG ICC) system. and a second se t o f working 

standards was installed.) 

All CO calibrations for high-pressure cylinders 

(standards). whi ch 1\erc also made against the original set 

of working standa rds. required re visio n. A similar approach 

to that described above for flask measurements ''as used for 

the cylinders. First. the cali bratio n cun·cs were recalculated based upon the corrected standard CO n ilucs. 

Arc hi 1 ed responses from the calibrations were then 

combined with the re 1 ised cun es to assign new CO mole 

fractions to the standards. The se t of working standards 

used o n 1\IAG ICC we re corrected. and the sample CO 1 a lue 

was reca lculated. Table 2.6 compares re ' ised mol e 

fractions of SC\ era I standards (calculated as described 

abo,·c) to mol e fractions determined by direct calibration 

using the 1999/ 2000 gra1 imetric standards as the reference. 

A histogram o r the di ffercnces bet '' een mi\ ing ratios 

assigned to a number of tanks during 2000 and mixing 

ratios ca lculated by the correction procedure (Figure 2. 19 ) 

shows that the calculated CO mi xi ng ratios de termin ed by 

the correction are generally somewhat greater than those 

measured. The mean bias o f the correc ted mole fractions is 

-0.9°o (0.8 ppb) re lati1e to the measured mo le fractions. 

The tendency toward mo re negat i 1 e differences is sho\1 n in 

the negative skewness (-0. 7 1 ). This offset suggests that the 

rates of drift assigned to the working standard s may. in 

general. have been oYcrestimated by 0.1-0.2 ppb yr· 1

• 

2.5. NIT ROUS OXIDE A:\D SULFUR HEXAFLUORIDE 

Measurements of N20 and S F6 from all sites in the CCGG 

Global Coopcrati1e Air Sampling Network continued during 

2000 and 2001 on the MAGICC analysis system. Annual mean 

mole fractions arc g iven in Table 2.3 for N20 and SF 6. 

Tank ID 

10-l208 

01790 

01783 

7 1607 

68734 

3873-l 

TABLE 2.6. Comparison of Measured and 

Re,iscd CO 1\lixi ng Ratios 

;>.teasurcd CO 

(ppb) 

-l9. I (0.-l) 

5-l.0 (0.7) 

69.2 ( 1.0) 

1-l0.8 (0.8) 

167.4 (0.6) 

200.6 (I.I) 

Calculated CO 

(ppb) 

49.5 (0.5) 

5-l.7 (0.8) 

71.2 (0.8) 

1-ll.7 (1.3) 

168.5 (0.8) 

:!O:!.-l ( 1.7) 

Values in parcn1heses arc lcr of the mean. 

43 

0.5 

'J.-l 

.-.J 

. ' 

c 0.3 - ·~ 

02[ 

- .._. 

2 - ·~ _r ·. -:: 

L. . o · -'< 

oJ d· .. 

I "'r - .... 

-6 -~ -2 0 2 ~ 6 

C "e'cnce 

Fig. 2.19. Histogram of the dilll:rence bemeen CO mole frac tions 

assigned to standards b) measurement and the 1999 2000 grm imetric 

s1andards and mole frac tions assigned b) the data re' ision procedure. 

C111DL \\Orking standards used in the correction are not included. The 

dashed cun e is a Gaussian lit to the data. 

2.6. i\I EASU REl\IE i\TS O.'\ TALL TOWERS 

The CCGG ta II -towers program began measu rements of 

CO, m o le fractions o n a 610-m-tall TV transmitter tower in 

No;th Carolina (NC. si te code ITN) in June 1992. CCGG 

obscrrnt io ns at this site were discontinued in June 1999 due 

to loss of the lease with the tower owner. Measurements 

were sta rted o n a 44 7-m-tall TV t01\er in Wisconsin ( WI. 

site code LEF) in October 1994 and arc ongoing. Site 

characteristics and data from the ITN and LEF were 

discussed by Bakwi11 et al. [ l 998a]. In February 200 I 

measurements were begun on a 505-m-ta ll TV tower near 

Moody. Texas (T X. site code \VKT). Surfa ce winds often 

indicate transpo rt of air into the interior of the eastern 

United States from the Gulf of 1\ l cxico. especially in 

summer. so the WKT site may represent an upwind end 

member for samples obtained O\ er the eastern United States 

during many periods. 

The time series of daily mean C02 mixing ratios at the 

hi!!.hest mea surement level on each of the towers is s hown 

in-Figure 2.20. Of note is the \cry weak drawdO\\n ofC01 

in summer at W KT compared with ITN and LEF. WKT is 

in a region o f relath cly dry g raz ing lands with very hot 

summers. Jul)-August 2001 11as partic ularly hot and dry: at 

Waco high temperatures in e:-.cess of 34°C were recorded 

each day from July 3 through August 26. 11 ith o nly 25 mm 

o f rain recorded during this period. This \\ Cather condit ion 

affected a large region of the southwest United Stat es and 

apparen tl y resu lted in low ac ti vity by vegetat ion and soils 

in the area. This is reflected in the d iurna l cycle of C01 

measured a t \VKT ( Fig ure 2.21 ). During August 200 I the 

accumulation o f C01 in the s ha llow nighttime stab le layer at 

TX \\as much less than at \\I I. and during the daytime the 

\ertical grad ie nt o f C02 from 9 111 to 457 m at TX was 

negligible. 
390 

- 370 

360 

350 

~BO • 

370 

• 360 

350 

f'.Oo~h CRr&•r.:. 

1496m) 

\'fisconson 

(396m) 

--~-- . 1993 1994 1915 1996 1W7 1998 1999 2000 2001 2002 

I ig. 2.20. Dail) mean CO, mole fractions at the top measurement le,·els 

on the "\onh Carolina. Te:-.as. and Wisconsin tO\\ er>. Hea\) Imes sho\\ 

smooth ctm·c fits to the NC and \VI tower data [ Tho11i11g et al .. 1989]. 

and thin lines show Ml3L reference cunes [GLOBALl 'IEW-CO .. 2001] 

for the latitudes of the "\C and \\ I towers. 

Variations in the growth rates of CO~ at the ITN and LEF 

tO\\ers general!) lead those in the marine boundar) layer 

(MBL) and display slightly greater amplitude (Figure 2.22). 

Gro\\ th rate ,·ariations at the U.S. tower sites arc more 

simi lar to the MBL curve than arc those at the CCGG nask 

sampling site in Mongolia, suggesting that vegetation 

changes on the orth American continent had a greater 

innucncc on MBL gro\\th rates during the period of 

obscn at ions than did those in Eurasia. 

One aim of the to\\ er program is to pro\ ide data that can 

be used to test and reline models of the carbon cycle at 

global and continental scales. A key finding from recent 

global model studies has been the existence of a "rectifier 

effect" by which CO\ ariance between atmospheric transport 

August2001 

W1SCO"ISif\ I ~ 

4() , I Xm 

;t'"' 

2 2 30 ,..,,. '""' t 2 

2 """' "L 20 2 1 1 

3 10 2 3-3 3 • ( 2 3 3 • • • • • s 

f-4...-f2 ~ w. - ~ &~~ t t--i-i 6 . • 

Texas .,, 

f' 20 l_l ,,,.. 

~ i ~ ·~~ ··~ 10 ~!~~~ • ,..,,, 

t1 0 

3&11 

6-G 6 & 6 

~.t~ &-6 6-e-- 6 

0 12 15 18 21 24 

Ho.Jr(UD 

hg. 2.21. :V1ean diurnal cycles for each measurement le' el on the 

Wisconsin and Texas tO\\ers for August 2001. For each day the a\erage 

\·alue for the top measurement le\el (plotted as a number) has been 

subtracted from all data in order to remo' e synoptic 'ariability. 

44 

3 

<!) 

.._, 

0 

n::: 2 

..c 

.._, 

~ 

0 1 I.... 

(.'.) 

N 

0 0 

u 

Nonh Carofoa 

Wisconsin 

MBL 

Mongolia 

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 

Fig. 2.22. Gr0\\1h rate from smooth-cune lits [T/11mi11g er al .. 1989] to 

daily mean CO, mole fractions at the Nonh Carolina and Wisconsin 

tO\\Crs and the CCGG na.,k site at L laan Uul. i\longolia. and from the 

:\1BL reference cune for-10"\/ [GLOB.ILl'IW-CO-. 2001]. 

and su rface 1luxes of co~ lead to mean hori1ontal and 

\ertical gradients of C02 mixing ratios [De1111111g et al .. 

1995]. In order to balance the global atmospheric C02 

budget. models that ha\e a strong rectifier effect require a 

northern hemisphere C02 sink that is larger than seems 

reasonable based on current understanding of the global 

carbon cycle [La11· ancl Si11111101ul.1. 1996: De1111i11g et al .. 

1999). At IT~ surface exchange of C02 is measured 

[Berger et al .. 200 I: K.J. Da' is et al.. The annual cycles of 

CO~ and O exchange O\ er a northern mixed forest as 

obsen ·ed from a very tal I to\\ er, submitted to Global 

Change Biology, 2002). as \1ell as the dynamics of the 

atmospheric boundar} layer (ABL) [l'i el al., 2001). 

Therefore the strength of the rectifier forcing for this site 

can be eYaluatcd. The obscn at ions are compared "ith 

output from the global tracer transport model of Denning el 

al. [ 1995]. "hi ch exhibits a strong recti lier effect. The 

model underestimates the diurnal CO\ ariance and the 

resulting difference between ABL and free troposphere (FT) 

CO~ "hen compared "ith the obsen at ions. At seasonal 

time scales. ho,,e,·cr, the model O\erestimates the 

cornriancc and A BL-FT C02 difference. The seasonal 

CO\ ariance is responsible for the bulk of the predicted 

rectifier forcing on the global scale. ll ence, the rectifier 

forcing in the model appears to be too strong. There are 

uncertainties in this analysis regard ing seasonality of 

transport between the continental and marine boundary 

layers. representativeness of the single obsen ing site. and a 

bias toward fair-weather obscn ing conditions. This work 

has been submitted for publication (C. Yi et al.. Is the 

simulated forcing of the co~ rectifier effect 100 strong?. 

submitted to Geophysical Research Leffers. 2002). 

In collaboration '' ith scientists at Colorado State 

University, CCGG has made progress in the use of the 

tO\\Cr data to constrain regional-scale carbon cycle 

simulations. The \\Ork couples a revised version of the 

Simple Biosphere l\lodel (SiB2.5) "ith a nested-grid 

regional transport model, the Regional Atmospheric 
l\lodeling System (RAMS). Ph ysiological properties of the 

vegetat ion and phcnology were specified from satellite 

imagery. Encouraging results ha\'e been submitted for 

publicat ion (I. Baker ct al.. Simulated and obsened nuxes 

of sensible and latent heat and C02 at the \VLEF-TV to11er 

using S i82.5 . submitted to G/ohal Change Biology, 2002: 

A.S. Denning et al.. Simulated and obser\'ed 1ariations in 

atmospheric CO , O\'er a Wisconsin forest, submitted to 

Global Change Biology. 2002). This work represents the 

first step toward an in\'erse modeling scheme for th e 

regional-scale carbon cycle. 

2.7. DATA l:\TEGRATIO:'\ (GLOBALVIEW) 

The Cooperati\'c Atmospheric Data Integration Project 

for carbon dioxide, establis hed in 1995 , continues its effort 

to improve the temporal and spatial CO\'erage of 

atmosphe ric CO, observations by integrating existing 

obsen·ations made by different laboratories into a 

coo perati ve global network. Twenty laboratories in 13 

countri es now participate in this activity, contributing their 

up-to-d ate. high-precision C02 record s from land-s urface. 

aircraft. ship, and tower sites (see http ://www. 

cmdl.noaa.gov/ccgg. global\'iew/ co2). Data from this 

cooperati ve netwo rk are used to deri\e GLOBALVIE\VC02. a globally consistent data product for use with carbon 

cycle modeling stud ies [GLOBALVIE\V-C02, 2 001). 

GLOBAL VI E\V-C02. which is updated annuall y. contain s 

no actual data . The product consists of smoothed time 

series deri\'ed direc tl y from o bse rrntions as well as 

statisti cal summari es of atmospheric variability, and 

a\'e rage diurnal and seasonal patterns. Since it was first 

introduced in 1996, more than 2500 Internet requests (- 37 

per mon th) for the data product have been made from more 

than 50 countri es. Inte rest 111 GLOBA LVIE\V-C0 2 

continues to increase (Fig ure 2.23 ). In 1997 the a\'crage 

number o f accesses per month was 14. In 2000 the ave rage 

increased to 53 per mo nth. and in 200 I it increased again to 

mo re than 70 inqu iries per month. 

15G 

125 

¥ lOC 

0 

t 

>-

.0 75 ,, 

,, 

5 

,,. 

c 5r w 

2': 

0 

19 % 1997 •998 ' 99? 2000 2C01 2002 

Fig. 2.23. !\umber of Internet requests for the GLOBAL VIEW-CO, data 

product. ll1c dotted line is them era II a1 erage since 1996. 

45 

Assessi ng the le \'e l or comparability among actual 

observations made b y different laboratories continues to be 

a primary focus o f this acti1 ity. The challenge is to ensure 

that s patial and temporal patterns among obscr\'ations from 

the cooperati\'c global network are due to C02 sources and 

sinks as affected b y atmospheri c mixing and tran sport and 

not due to inconsistencies among internal calibration scales 

and potential systemal ic errors introduced when sampling 

the atmosphere. The level of traceability of each 

laboratory's int ernal C02 ca libration scale to the absolute 

WMO CO, mole fraction scale must be determined to 

properly assess comparability. Period ic cyl inder-air 

("round-robin") intcrcomparison experiments end orsed by 

the \VMO and International Atomi c Energy Agency ( IAEA) 

are used to make this assessment. Participat ing laboratories 

compare the ir measurements of C02 and other trace species 

and isoto pes in dry air made on a set of circulating hi ghprcssure cylinders. These experiments arc critical for the 

assessment of each laboratory's ability to make highprecision measurements and maintain the ir internal 

calibration scales. Re sults from the 1995/1996 cylinder-air 

comparison suggest that measurements made by laboratories 

contributing to GLOBAL V I E\V-C02 are comparabl e to 

ll'ithin 0.2 μmo t mo i- 1 with re spect to calibration [Peterson 

et al., 1999 ). Preliminary results from the most recent 

rou nd-robin experiment ( 1999/2000) suggest a slight 

impro\'ement in the number of laboratories with agreement 

al the 0.1 ~tmol moi- 1 le1el. Current scientifi c objectives 

require a global network precision of 0.1 tm ol mo1' 1 among 

northern hemisphere obsen at io ns and 0.05 μm o l mo1' 1 

among southern hemisphere observations [ IVMO. 198 1 ). 

Allaining this level of compa rabilit y among atmospheric 

observations with ex isting technology requires laboratories 

to maintain a level o f traceability to the \VMO scale 

sig nifi can tly heller than 0.05 μmol rn o1' 1

• Although the 

cylinder-air results suggest there is considerable ll'Ork yet to 

be done. ii ha s been demonstra ted that this le\ el o r 

agreement is att ainable. 

Results from three \VMO-cndorscd cylinder-air roundrobin inlercomparisons ( 199 1/ 1993. 1995/1997, and 

1998/ 2000) suggest that the l\leteorological Service or 

Canada (MSC) has maintained traceabi lity of its internal 

calibration scale to the \Vi\10 C0 2 mole fraction sc al e to 

within 0. 03 μmot mo1' 1

. Ho11 el'er. it cannot be concluded. 

based on these results alone. that atmospheric measureme nts 

made by MSC and NOAA (ll'hi ch maintains the \VMO C02 

scale) are comparable to this same lcl'cl o f ag reement. 

Add itio nal errors may be introduced into meas urements of 

atmospheric air when ambient sampl es arc coll ec ted. dried. 

stored , extrac ted. and analyzed. Cylinder-air comparisons 

arc ex pressly designed to exclude these po tential sources or 

error. To complement the periodi c cylinder-air 

comparisons. laborato ri es arc establishing ongoing nask-air 

intercomparison ( ICP) experime nts ll'hcrcb y laborato ries 

can more direc tl y compare atmospheric measurements. 

CCGG has o ngoing ICP activiti es ll'ith the Commonwealth 

Scientifi c and Indu strial Research Organization (CSIRO. 

Austral ia); MSC (Canada): Nationa l Institute for Water and 

Atmospheric Re search ( II \VA, New Zealand): and CM DL 

Ha loca rbo ns and o ther Atmospheric Trace Species group 

(ll ATS). 
The effecti veness of a flask-air ICP experiment depends 

on several essential features. First, participants must view 

the ICP activity as an additional level o f quality control 

whereby measurements are routinely scrutinized. Potenti al 

problems identified by a collaborating laboratory should not 

be viewed as an embarrassment but as proof that the ICP is 

working effecti vely. Second. the ICP acti vity is an ongoing 

long-term program o f routine (at least weekly) comparisons 

of atmospheric samples. Third, the ICP experiment must 

include supporting measurements (e.g., control samples) 

that can be used to narrow possible causes when differences 

are observed. Fourth, the ICP activity should have minimal 

impact on dail y operations. This is acco mplis hed only if 

participating laboratori es have advanced data management 

tools in place. Analysis of ICP samples and processing and 

data exchange between laboratories must be automatic and 

routine. Finally, ICP results must be summarized automatically and made readily available to participants. 

Timely feedback improves the likelihood that potential 

problems are detected early (Figure 2.24). 

.. ' 

J Ao Edl 

- F- Tools .._, 

At this time, only the ICP experiments with CSIRO and 

MSC include the essential fea tures described above and are 

proving to be valuable tools to monitor measurement qua I ity 

and assess comparability. The MSC-NOAA fla sk-air ICP 

experiment, begun in late 1999, is modeled after the longtime CS IRO-NOAA experiment [Masarie e r al., 2001] 

whereby both laboratories routinely analyze the same 

a tmospheric ai r sample. MSC and NOAA independently 

co ll ect samples of air week ly at Ale rt, Nunavut, Canada, 

using their respective flasks and sample collection 

strategies. Station personnel collect at approximately the 

same time one pair of MSC flasks and two pairs o f NOAA 

flasks. All flasks are shipped to MSC in Downsview, 

Ontario, where one of the two NOAA fla sk pairs is first 

ana lyzed by the Carbon Cycle Research Laboratory (CCRL) 

a t MSC for C02, CH4, CO, N20, and SF6 before being 

shipped to Boulder and analyzed a second t imc by CCGG 

for the same suite of trace gases. 

Figure 2.25 shows C02 measurement differences (MSC 

minus NOAA) from analysis of the same ai r in flask 

..J.IJJl!.I 

J 

j-.... 

.:0-Beck• 

l@J t-t!f>://www.ard.noaa.oovl«<R~l<*o_noaajq>/aro_noaajoyoll;.Nm 

... · @&J 1::1 1.a- llJF- (;f1tstary I · _. ~ • !!l 

~ ~'""'nu;;; -. 

- CSIR.O/NOAA Flask Air I nterCom 

~ Parison II Cape Grim, Tasmania 

~ [ Archive] rnfilfil [Help] l.Qy_if) :!.! 

ySIP.O/ NON, J ::l 

Fl:.1<t. !\or 1·1 • .; Ct.-ro~u1i>"<!n CS I RO and NOAA 

::Ji;'il '.;rim, -ocrnoniJ Flask Air I ntercomParison )70 

/ Cape Grim, Tasmania 

.,,J .... r; JO:!> DATE Sun Oct 14 04:41:57 2001 

• 

~ JOO .r- C02 (ppm) DIFFERENCES (C 

.:i. 

~r J;.5 , .. i·;r YEAR MEAN STDBV 

1992- 2001 0.0406 0.1766 

J!'" ~:1<\ 1992 0.1788 0.2316 

" 1.0 I 1993 0 . 1150 0 . 1138 ll I 1994 0.1989 0.1726 E 

~ o.~ 

-- 1995 0.0456 0 . 2445 

1996 0.0503 0.1301 

:T .~:1c.: . :•. ." ... '· :1- --.... . ·• 1997 0 . 0264 0 .1247 

'-' 0.0 --,.• : .... . ..., ,- ~ 1998 0.0271 0. 1198 --< 

--._ .. J ___ : __ __ ·L-~-- -:~ -- 1999 -0.0331 0.1265 

~ -{,.~ 2000 -0.0243 0.2063 

il ' ; I • 2001 -0.0286 0 . 1056 

g _,_o . l . , 

t!'fa:" n~4 ~·' ·.;~r. 1:\i)(l "'~ Flask Air InterComParison 'T.i.t! Cape Grim, Tasmania 

DATB sun Oct 14 04:41:57 2 001 

., I §1 .1 I §1 ~ lll• tmmet A 

Fig. 2.24. Up-to-date flask-air intercomparison results available to participating laboratories'' ith restricted \V\V\V page access. 

46 
r ' • T r ..,.. ... r T'" • 

c :o 

0.0 c_ 

:·· o 3 -

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -~~~.c· - .;•;•:!J-;.r - - - - - - -

·a··"'h I ~\ = - ;;;.s ~ 0 

-C ?0 

c :o'------'-----------'~---~-~-

1996 ~:::o 2:··c2 

f-i!!. 2.25. Ditlen::nccs (i'.ISC minus NOAA) between independent 

m;asure111ents of the sa111e air in flask samples collected at Alen. Nunm ul. 

Canada (open squan::s). Also plotted is a s111ooth cur\'e litted to the 

dillerences between indi' idual 111casurc111c111s. Tl1c 111can dillerences (i'.ISC 

111inus NOAA) detcnninoo fro111 111uh iple imercomparisons of air in highpressure cylinders are shown as solid hourglass S)111bols. Tl1c dotted and 

dashed lines about the zero dillerencc line idemify ±0.05 and .r.0.1 μ111 01 

11101"1 target le\els. 

sampl es collected at Alert. The a\erage difference is 0. 10 ± 

0.1~ μmol mo l" 1 (n = 104). ll igh-frcqucncy (4-6 \\'k) noise 

in the differences is small and enables us to better pinpoin t 

\\'hen systematic changes in th e distribution occur than in 

1hc CS IRO-CMD L comparison. This informatio n is used by 

MSC and NOAA to re-examine experimental changes that 

ma y have inadvertentl y introduced errors. i.e .. errors that 

we nt undetected by conventional internal quality assurance 

procedures (sec sect ion 2.2.2). Results from the cylinderair round-robin experiments are also s hown in Figure 2.25 

and clearl y demonstrate that the maintenance of direct 

traceabi lity to the \VMO C02 mole fractio n scale does not 

guarantee comparability among a tmospheric obserrntio ns. 

Note that. without first establishing traceabil ity, exclusion 

o f calibration as a possible cause for the o bserved 

differences in flask measurements wo uld not be possible. 

Both components of qua lity control arc essent ial. The 

probable causes or the observed differences between MSC 

and NO AA may be narrowed to erro rs introduced during 

sampl e coll ection, storage. extracti o n, and anal ysis at e ith er 

o r both laboratories. MSC and NOAA arc currently 

working together to und erstand the causes of these 

differences. 

2.8. l:\\'ERSE l\tODEL ~G 

Predi cting the response of the cl ima te system to 

anth ropogenic emissions or radiati' ely acti ve atmospheric 

trace species. such as C02 and Cl 14 • is complicated by 

important contributions to the budgets of these species from 

terrestrial biospheric and oceanic processes. In the case of 

the terrestrial biosphere . interannual \'ariability in 

paramet ers s uch as temperature and precipitatio n ma y lead 

to significant interannual variability in sources of these 

47 

gases (e.g., Bo11sq11e1 el al.. 2000: Dl11goke11cky el al .. 

200 I]. Future attempts to manage carbon resen·oirs depend 

c riti cally o n the abil ity to understand and quantify the 

behavior of terrestrial and oceani c carbon sources and sinks. 

Two approaches currentl y being used toward this end are 

prognostic models of oceanic and terrestrial processes, and 

ill\ erse models. The latter techn ique. long used for 

geophysical proble ms such as se ismology. acoustic 

tomography. and satellite data retrieva ls, is an attempt to 

reconcile pred ictions from a prognosti c mode l with 

observations of th e trace spec ies in a global network. Early 

attempts " ·e re designed to obtain the interhemispheric 

!!.radient of CO, flux es [Tans el al., 1990: £111ing and 

Afa11sbridge, 1991: Ciais e1 al .. I 995a,b: Bo11sq11e1 el al., 

1996: lmr and Si111111onds. 1996]: howe,·e r. with the 

expansion o f the C02 observational network , att empts ha ve 

been made 0\ er recent yea rs to obtain flux distribution s 

over contine ntal scales (e.g., Fan e1 al .. 1998: Bo11sq11e1 el 

al .. 2000]. Results of the recent TRANSCOM Ill model 

intercomparison s uggest that the network is currentl y still 

too sparse to a llow accurate resolution of conti nental-scale 

fluxes. The add it ion of more obscr\'atio n sites. especially 

over continenta l and tropical regions. would impro,·e the 

accuracy of current flux estimates. In additio n, it appears 

that the current gene ration of transport models needs 

impro,·ement so that subgrid-scalc processes. such as 

boundary layer transport and convecti ve transpo rt. are 

accurately represent ed and do not introduce biases. 

Ongoing work by CCGG is focused on development o f an 

operational inverse calcul at ion for flux retri evals at 

continental scales. The mass balance te chn ique used for 

these ca lcul ations is described in detai l by Bm/J11·iler el al. 

(2000]. A modificatio n to the technique allows the 

propagation o f spatial flux patt erns (basis. o r response 

functi ons, used to quantify the effect of each source region 

at an y particular location) for an arbitrary number of 

months. resulting in potentially more accurate and stable 

so lutions. In practi ce. it has been found that response 

functi o ns need not be calcul a ted for more than about 6 

mon ths, and suffi c ient accuracy may be achi eved with o nl y 

~ months. Th is modifi ed \'crsion of the mass balance 

tech nique may be ru n using constraints such as scmiempiri cal ocean flu x esti mates [Takahashi el al .. 1999] 

a nd/or terrestrial flu x estimates inferred from satell ite 

observations of greenness. e .g.. the Ca rncgie-A mesStan ford Approach (CASA) model [Ra11derso11 el al .. 1997]: 

ho\\·cver. the flu x estimates described here \\'ere calculated 

without the use of such prio r constraints. The latter strategy 

allo\\'s for the e\ aluation of fl ux estimates against th e scm icmpirical ocean fluxes and satellite-deri\'ed esti mates of 

terrestrial fluxes. 

Estimates of ca rbon flu xes \\'ere calculated for 11 

terrestrial and I I oceanic regions, correspondi ng to those 

used in the TRANSCOM Ill model intercomparison. The 

tra nsport mode l used is Tracer Model Version 3 [TM3. 

Hei111a11n, 1995] with nine verti cal levels and a ho ri zontal 

resolution of 8° latitude by 10° longitude. The model's 

transport is dri, en by European Centre for Medium-Range 

Weather Forecasti ng (ECMWF) re-a nal ysis \I ind fields for 

the years from 1979 through 1993. In versio ns for the years 

afte r 1993 are typica ll y run using wind field s of all 15 years 
to d efine a ra nge of flux estimates. Flux estimates are 

calc ulated at mo nthl y interva ls so that seasonal cycles may 

be resolved. 

The C02 o bservations used to constra in the in versions are 

a subset o f the G LO BA LV IEW-C0 2 d ata set, consisting of 

both actua l and extended records at I 14 network sites 

distri buted g loball y. The maj o ri ty of the statio ns used 

re flect the behavio r o f C02 in the marine boundary layer. 

The un resolved va ri ability, or model-d ata mismatch, is 

assumed to be 0 .5 p pm for oceani c sites and 2.0 ppm for 

con tinenta l sites. The larger e rror for continen ta l sites is 

intended to re n ect the greater diffi culty of mo de ling 

continental boundary layer processes. 

Ca rbo n nux estimates calculated for the period fro m 1979 

to 1999 show considerabl e interannual variability in both 

summertime uptake and spring/ autumn respiratio n. The 

average uptake over North Ameri ca for th is period is about 

0.8 Gt C y( 1

, and the net g lobal uptake is partitio ned 

unequa ll y between the land and oceanic regions, with mo re 

uptake over land regions. The average upta ke b y oceans is 

estimat ed to be 1.0 Gt C y( 1 compared with a net upta ke of 

2.0 Gt C y( 1 fo und by Takahashi et al. [ 199 9). It is 

inte resting to note that the estima ted terrestrial uptake in 

bo real continental regio ns is smaller than that suggested b y 

CASA and larger in temperate regions. Whether th is bias 

exists in the CASA model or in the inverse calcul ations is 

c urre ntly under in vestigation. Because of the relative 

sparseness o f the observat io nal netwo rk in tropical 

continen ta l and oceani c regions, n u x estimates tend be 

extreme ly noisy in the trop ics and average to zero. T his is a 

re n ecti o n o f the lack o f constrain ts in these regio ns. T here 

is a clear need for mo re o bservations in th ese regions. 

Fig ure 2 .26 shows estimated terrestrial ca rbo n nux 

anoma li es for 1981 th rough 1999. For each year, nuxes 

were esti mated using a ll 15 years of ECMWF wind fi elds. 

A lthoug h this approach was taken because wind fi e lds are 

not ava ilable past 1993 , use o f multip le yea rs of 

meteorology for the same n u x estimates p rovides a means 

to estimate the importance of interannua l variabi lity in 

transpo rt processes. This issue is of specia l importa nce, 

considering that it has been fairly co mmo n pract ice in 

in verse calcul atio ns to use onl y I yea r of meteorology 

cycli cally. In ord er to calculate the a noma lo us carbon 

nuxes, an average seasonal cycle was subtracted from the 

time se ri es of tota l land nux esti mates. The upper and 

lower lim its on 12-mo runni ng means of the nux anomalies 

re n ect a nnua l average behavior of the anoma lies. Altho ugh 

the run ni ng mean anoma li es are sensitive to transport 

d iffe rences at a level of abo ut I Gt C yr·', the monthly 

ano malies may range by as much as about 3 Gt C y(1

• It is 

the refore hig hly desirable to use wind fi elds for the 

app rop riate year when doing these sorts o f calcu latio ns. 

The smoothed nux anomali es in Figure 2.26 show 

extended periods of posi ti ve anoma ly (net emission from 

the terrestrial biosphere) as we ll as perio ds o f net uptake. 

S ignifi cant positive anoma li es o ccur after the El N ino o f 

1982- 1983 as we ll as after the 1987 - 1988 El Nino. The late 

1980s are a period of exte nded net emissio n from the 

terrestri al b iosphere, whil e the ea rly 1990s are a period of 

uptake. A large positi ve anomaly occu rs in 1998 both for 

the terrestrial biosphere and the oceans (not shown). 

48 

10 

- Filtered Residu al 

-12 M. nth Rur• ning l.1eon 

5 

-5 

Total Land Ca rbon Flux 

B 1 82 83 84 85 86 87 BB 89 90 91 92 93 9 4 95 96 97 98 99 

Fig. 2.26. Estimated terrestrial carbon flux anomalies for 1981 through 

1999. For each year, fluxes were estimated using all 15 years of 

ECM WF wind fields. The shaded purple region shows upper and lower 

limits on the anomalous carbon flux for each month of the inversion 

calculated by subtraction of an average seasonal cycle. The red lines 

show upper and lower limits on 12-mo running means of the flux 

anomalies and reflect annual average behavior of the anomalies. 

Comparison to glo bal temperatu re and precip itatio n fie lds 

( not shown) suggests that the a nomali es track trends in 

these variables. 

Pl a ns to improve the current generation of inversions 

inc lude the use of the NCAR Mod e l o f Atmospheric 

T ra nspo rt a nd Chemistry (M ATC H), whi ch m ay be run at 

hig her resolutio n with mo re current w ind fi e lds from the 

National Centers for En vironme nta l Pred ictio n (NCEP) reanalysis d ata set; use o f a mod ifi ed Ka lma n fil ter to allow 

for error propagation ; and use of additiona l observational 

constrai nts such as isoto p ic measuremen ts. In the fu ture, 

mo re measuremen ts may become avai lable, w hic h wi ll 

result in sig nifi cant improvements in n ux est imates. 

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49 

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50 

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Rei .. 101. 5885-5894. 1997. 
3. Aerosols and Radiation 

3.1. AEROSOL MO:\ITORl\'.G 

L. At--lJIU \\'S(EDITOR). D. DfLl.\.I. D. JAlKSO\,. A. Jn 11 KSO'-. 

J. Oc;IU -.:. P. SllERID.\\.. A'-1> J. \\'E\.lll IL 

3. 1.1. SCIE:\TIFIC B ACKGROU\'.D 

Aerosol part icles affect the radiat i\e balance of Earth 

both directl y. by scattering and absorbing solar and 

terrestrial radiation. and indirectly. through their action as 

cloud condensat ion nuc lei (CCN) with subsequent effects 

on the microphysica l and optical properties of clouds. 

Evaluation of climate fo rcing by aerosols, defined here as 

the perturbation of the Earth's radiation budget induced by 

the presence of airborne panic I es. requires kno\\ ledge of 

the spatial distribution of the particles and their optical and 

cloud-nucleating properties. and su itab le models of 

radiative transfer and cloud physics. Obtaining a predicti\e 

relationship bet\\ccn the aerosol forcing and the physical 

and chemical sources of the particles additionall) requires 

knowledge of regional- and globa l-scale chemical 

processes. physical transformation. and transport models for 

calculation of the spatial distributions of the major chemical 

spec ies that control the optical and cloud-nucleating 

properties of the particles. De\cloping and 'alidating these 

various models requires a di,·erse suite of in situ and remote 

obsen·ations of the aerosol particles on a \\ ide range of 

spatial and temporal scales. 

Aerosol measurements began at the CM DL baseli ne 

observatories in the mid- I 970s as part of the Geophysical 

Monitoring for Cl imatic Change (Gf\ICC) program. The 

objeeti\ e of these baseline measurements was to detect a 

response. or lack of response. of atmospheric aerosols to 

changing conditions on a global scale. Since the inception 

of the program, scientific understanding of the beha\'iOr of 

atmospheric aerosols has impro' cd considerabl y. One 

lesson learned is that residence times of tropospheric 

aerosols are generally less than I "eek. and that human 

activities primarily inOuencc aerosols on regional 

cont inental scales rather than global scales. In response to 

this increased understanding. and to more recent findings 

that ant hropogenic aerosols create a significant perturbation 

in the Earth's rad iati\ e balance on regional scales [ Cliar/.1011 

et al .. 1992 : ,\'RC 1996]. CMDL expanded its aerosol 

research program to include regional aerosol monitoring 

stations. The goals of 1his regional-scale monitoring 

program are to (I) charactcriLe m1:ans. \ariabilities. and 

trl!nds or climate-forcing properties of different types of 

aerosols, and (2) understand the factors that control these 

properties. 

No single approach to obsen ing the atmospheric aerosol 

ca n JHOI ide the necessar) data for monitoring all the 

rele\ ant dimensions and spatial temporal scales required to 

e\ aluate climate forcing by anthropogenic aerosols. In situ 

obsen auons from fi\ed surfac1: sites. ships. balloons. and 

aircraft can pro\ide \l'r) detailed characterizations of the 

atmospheric aerosol. but on limited spatial scales. Remote 

sensing methods from satellites. aircrali. or the >urfacc can 

determine a li111ited set of aerosol properties from local to 

51 

global spatial sca les. but they cannot pro' ide the chemical 

in formation needed for linkage "ith global chemical 

111odels. Fixed ground stat ions are suitable for continuous 

obscn at ions O\ er extended time periods. but lack 'ertical 

resolution. Aircraft and balloons can pro' ide the \ ertical 

dimension. but not continuously. Only" hen systematicall) 

combined can these 'arious t) pes of obsen at ions produce a 

data set where point measurements can be extrapolated \\'ith 

models to large geographical scales. \\ here satell ite 

measurements can be compared "ith the results of largescale models, and where process studies ha\ e a context for 

drawing general conclusions from experiments conducted 

under speci lic conditions. 

Measurements of atmospheri c aerosols arc used in three 

fundamentally different "ays for aerosol 'climate research: 

algorithm de\ elopment for mode ls and remote-sensing 

retriernls, parameter characterintion. and model 'alidation. 

Laborator) and field process studies guide the de\'clOpment 

of parameteri zation schemes and the choice of parameter 

'alues for chemical transport models that describe the 

relationship bet\\cen emissions and concentration fie lds of 

aerosol species. Systematic sun eys and monitoring 

programs pro' ide characteristic 'alues of aerosol properties 

that are used in radiati\ e transfer models to calculate the 

radiati\e effects of the aerosols. and to retrte\ e aerosol 

properties from satellites and other remote sensing 

plat forms. And finall~. monitoring programs JHO\ ide 

spatial and temporal distributions of aerosol properties that 

are compared with model results to 'aliuate the model;,. 

Each of these three modes of interaction between 

applications and measurements requires different l) pes of 

data and entails different measurement strategics. Ogren 

( 1995] applied the thermodynamic concept of "intensin·· 

and ··cx tenSi\c·· properties of a system lO t.:mphasiLe the 

re lat ion ship bel\\ een measurement approach and 

applications of aerosol obs1:n·ations. 

ln tensi\e properties do not depend on the amount of 

aerosol prest.:nl and arc used as parameters in chemical 

transport and radiati1e transfer models (e.g., atmospheric 

residence time and single-scatte ring albedo). E\tensi1 e 

properties \ary strongl) in response to mi\ing and remo\al 

processes and are most common I) used for model 'alidation 

(e.g .. mass coneclllration and optical depth). lntensi\e 

properties arc more difficult and expensi' e to measure than 

extensi' e properties because the) generally are defined as 

the rat io of t\\O e\tensi\e properties. ;\s a result . different 

measurement strategics arc needed to meet the data needs of 

the \arious applications. l\leasurements of a fe\\ carefull~ 

chosen c.\tcnsi\e properties. of" hich aerosol optical depth 

and species mass concentrations are prime candidates. arc 

needed in many locations to test the ability of the models to 

predict spatial and temporal 'ariations on regional to global 

scales and to detect changes in aerosol concentrations 

result ing from changes in aerosol sources. The higher cost 

of detcr111ining i111ensi\e properties suggests a strategy of 

using a limited number of highly instrumented sites to 

characteri7e means and \ ariabilities of intensh e properties 

for different regions or aerosol t) pcs. supplemented \\ 11h 

suncys b) aircraft and ships to charactcriLe the ;,patial 
\ariabilit) of these parameters. Cl\IDL's regional aerosol 

monitoring program is primari l) focused on the 

charactcri7ation of intcnsiYe properties. 

C:\IDL's measurements pro\ ide ground truth for satellite 

obscn at ions and global models. as \\ell as 1-.c) aerosol 

parameters for global-scale models (e.g.. scaucring 

erliciency of sulfate particles and hemispheric backscattering fraction). An important aspect of this strategy is 

that the chemical measuremcllls arc linhd to the physical 

measurements through simultaneous. size-sclecti\ e 

sampling that al101\s the observed aerosol properties to be 

connected to the atmospheric cycles of specific chemical 

::.pccies [e.g .. Q11i1111 e1 a/ .. 2002). 

3. 1.2. E:\PERntE:\TAI. :\I ETllODS 

[,tensiYc aerosol properties monitored b} Cl\I DL include 

condensation nucleus (CN) concentration. aerosol optical 

depth (o). and components of the aerosol extinction 

coefficient at one or more \la\elengths. i.e .. total scattering 

(CJ,rl· back11 ard hemispheric scauering (<Jb,rl· and 

'.1bsorption (cr.r). /\t the regional sites. siLe-resol\cd 

impactor and tilter samples (submicrometer and 

supermicrometer Sl/C fractions) are obtained for gra\ imetric 

and chemical (ion chromatograph) analyses. All sizeselecti\ e sampling. as 11ell as the measuremellls of the 

components of the aerosol e:-.tinction coefficient at the 

regional stations. is performed at a 1011. controlled relati\ e 

humidity (<40°0) to eliminate confounding effects due to 

changes in ambient relatiYe humidity. Data from the 

continuous sensors arc screened to eliminate contamination 

from local pollution sources. At the regiona l stations. the 

screening algorithms use measured 11 ind speed. direction. 

and total particle number concentration in real time to 

pre\ ent contamination of the chemical samples. /\t the 

baseline stations. algorithms use measured 11 ind speed and 

direction to exclude data that are likely to ha\C been locall) 

contaminated. 

Prior to 1995. data from the baseline stations were 

manuall} edited to rcmO\e spikes from local contamination. 

Since 1995. an automatic editing algorithm has been applied 

to the baseline data in addition to manual editing of local 

contamination spil-.es. For the baseline stations. Barro\1. 

Alaska (BR\\). i\1auna Loa. Ha11ai i (\!LO). American 

Samoa (Si\10). and South Pole. Antarctica (S PO). as 1\·ell as 

for Sable Island (\VS/\). data are automatically remo\ ed 

when the wind direction is from local sources of poll ution 

(such as generator~ and bu i I dings) as 11e11 as 11 hen the I\ ind 

speed is less than a threshold \ alue (0.5-1 m s·

1

). In 

addition. at i\ILO data for upslope conditions (1800-1000 

UTC) are excluded because the airmasses do no1 represent 

.. background.. free tropospheric air for this case. A 

summary of the data-editing criteria for each station is 

presented in Table 3.1. 

Integrating nephelome1ers arc used to determine 1he light 

scattering coefficient of 1he aerosol. These instruments 

illuminate a lhed sample 1·olume from the side and obscnc 

the amount of light that is scattered by particles and gas 

molecules in the direction of a photomultiplier tube. The 

instrument integrates O\ er scattering angles of 7 - I 70u. 

Depending on the station. measurements are performed 

rABLE 3.1. Data-l.:.d1ting Summar) for NOAA 

Baseline and Regional Stations 

Station [d11111g Clean Sector 

South Pole a.b.c 0 \\ () < 110 . 330 

Sa111oa a.h.c () \\[) 165 . ~l.\5 

\launa Loa a. b. c. d 90 \\ D < 270 

Barro" a. b. c () \\'D <. 130 

Sabk bland a.b.c 0 \\D < 35 . !-5 

Southern Great Plain;. a 

Bondi Ille a 

a: i\lanual rc111m al or local conta111ina1ion ;,pike;,. 

b: ,\u10111a1ic rc111m al of data nlll in ckan sector. 

c: ,\uto111a1ic rc11101al or data for JOI\ \\ind speed;>. 

d: Rcmm al of data li.)r up;. lope" 111d condition;.. 

\\ D: \\ind direction. 

\\ () 

\\ () 

\\ D 

360 

360 

360 

a1 three or four wa\ elengths in the Yisible and near-infrared. 

NC\\ er instruments allo1\ determi nation of the hemispheric 

backscattering cocfficienl by use of a shutter to pre\ cnt 

illumination of the portion of the instrument that ) ields 

scattermg angles less than 90 . J\ particle filter is inserted 

periodical!) into the sample stream 10 measure the light 

scattered b) gas molecules. '' hich is subtracted from the 

total scattered signal to determine the contribution from the 

part icles alone. To calibrate 1hc instruments the sample 

1olumc is filled 11ith CO, gas. \1hich has a kno\1n scattering 

coefficient. 

The aerosol light absorption coefficient 1~ de1cr111111ed 

11 ith a continuous light absorption photometer. This 

instrument continuous!) measures the amount of light 

transmitted through a quartz filter '' hile particles arc 

deposited on the filter. The rate of decrease of 1ransmissi\ it). di\ ided b) the sample flo\1 rate. is directly 

proportional to the light absorption coeflicicnt of the 

particles. Newer instruments (particle soot absorption 

photometers (PSAPs). Radiance Research. Seattle. 

Washington) are calibrated in terms of the difference of 

light extinction and scattering in a long-path extinction cell. 

for laboratory test aerosols. Older instruments at the 

baseline stations (acthalometers. \lagee Scicnti fie. 

Berkcle). California) 11crc calibrated by the manufacturer 

in terms of the equi,alent amount of black carbon (BC) 

from ''hi ch the light absorption coefficient is calculated. 

assuming a mass absorption efficiency of the calibration 

aerosols of I 0 m~ g· 1• 

Particle number concentration is determined '' ith a CN 

counter that exposes the particles to a high supersaturation 

of butanol 1·apor. This causes the particles to gro11 to a si7e 

''here the) can be optical I) detected and counted. The 

instruments in use ha\e lower panicle-siLe detection limits 

of I 0-20 nm diameter. 

Summaries of the extensi\ e measurements obtained at 

each site arc gi1en in Tables 3.2 and 3.3. Table 3.4 lists the 

intcnsi\e aerosol properties that can be determined from the 

direct!) measured c\tCnsi\ e properties. These properties 

arc used in chemical transport models to determine the 

radiati\c effects of the aerosol concen1rations calculated b) 

the models. In\ ersel). these properties arc used in 
Catcgol") 

Location 

Designator 

Latitude 

Longi1ude 

Elcrn1ion (m) 

Responsible instinne 

S1a1Us 

Sample RH 

Sample size frac1ions 

Op1ical measurements 

i\ licrophysical 

111casuremcn 1s 

Chemical measurements 

Categor: 

Location 

Dcsigna1or 

Latitude 

Longi1udc 

Eleva1ion (m) 

Responsible insti1u1c 

Collabora1ing ins1i1u1e(s) 

S1a1us 

Sample Rl l 

Sample size fractions 

Op1ical mcasurc111cn1s 

i\ licrophysical 

mcasurcmcn1s 

TABLE 3.2. CMDL Baseline Aerosol i\lonitoring Stations (Status as of December 200 I) 

Baseline Arctic Baseline Free Troposphere Baseline ~ larine Baseline Antarctic 

Point Barrow i\launa Loa American Samoa South Pole 

BR\\' i\ILO Si\10 SPO 

71.323°1' 19.539°1' 1-l.232°S 89.997°S 

156.609"\\" 155.578"\\' 170.563°\\' 102.0"E 

8 3397 77 2838 

G IDL C:-.IDL GIDL Cl\IDL 

Operational. 1976: Operational. 197-1: Opera1ional. 1977 Opera1ional. 197-1 

major upgrade. 1997 major upgrade. 2000 

RI I < -10°-o Rl l < -10% Uncontrolled Uncontrolled 

D < l11m.D < IOpm D < I 11m. D < 10 11m Uncon1rolled Uncon1rolled 

cr,r (31..). cr,.,r (3).), cr,r ( I),) cr,r (3),). cr,.,r (3),). cr,r ( IA.). Ii (6).) None cr,r (-1),) 

CN concemra1ion CN concen11111ion CN concen11111ion CN concentra1ion 

~lajor ions. mass None None None 

TABLE 3.3. Ci\lDL Regional Aerosol Monitoring Sites (Status as of December 200 I) 

Pcnurbcd i\larinc 

Sabk Island. Norn Scoiia. Canada 

\\/SA 

-13.933°N 

60.007° \\' 

5 

Ci\IDL 

AES Canada. NOAA Pi\IEL 

Opcra1ional. Augus1 199:!: 

inac1ive. April :woo 

Rll < -10% 

D < I pm. D <- 10 pm 

cr,r (3),). cr,.,r (3),). cr,r (I),) 

CN concc111ra1ion 

Pcnurbcd Co111incn1al 

Bond\ ille. Illinois 

BND 

-I0.053°N 

88.372"\\' 

230 

C\IDL 

Pcnurbcd Co111incn1al 

Lamont. Oklahoma 

SGP 

36.605° 1 

97.-189°\\1 

315 

OIDL 

Uniwrsi1y of Illinois. Illinois S1a1c \\'atcr Sun e) DOE ARi\I 

Opcra1ional. July 199-1 Opcra1ional. Jul) 1996: 

chemis11J added. FebrnalJ :moo 

Rll < -I0°·o Rll < -10% 

D < I pm. D < 10 ~1111 

cr,r (31..). cr,.,r (3),). cr,r (I).) 

CN conce111ra1ion 

D < I pm. D < I 0 pm 

cr,r (31..). cr,.,r (3),). cr,r (I),). Ii(?}.) 

CN. 11(D) concc111ra1ion 

Chemical measuremen1s ~lajor ions. mass ~ lajor ions. mass Major ions. mass 

AES. A11nospheric Em ironmenl Sen ice: Pi\! EL. Paci fie :-. larine Ell\ iron men I Labormor): DOE ARi\I. Depar1men1 of Energy1 A1mospheric 

Radiation i\leasuremcnt. 

TABLE 3.-l. Intensive Aerosol Properties Deri,ed from the CMDL Network 

Propcnics Descrip1ion 

a The Angs1rom exponent. defined by 1he power-la" cr,r oc !.."''. describes 1he "a'cleng1h-dcpcnclcnce of sca11crccl light. In 1he ligures. 

c"1 is calculaicd from mcasurcmcms al 550- and 700-nm \\a\elcngths. Si1ua1ions where 1he sca11ering is dominaied by submicrome1er 

panicles typically ha'e ,·alues around 2. "hereas "hen 1hc sca11cring is domina1ecl by panicles larger than a fc" micromclers in diamclcr. 

'alues arc close 10 0. 

fl\, The aerosol single-sca11cring albedo. defined as cr," (cr,r - cr,r). describes 1he rela1i' e contributions of sca11ering and absorp1ion 10 1he w1al 

ligl11 extinction. Purely scallering aerosols (e.g .. sulfuric acid) have Yalues of I. \\hcrcas \cry slrong absorbers (e.g .. elemental carbon) 

hmc rnlucs around 0.3. 

g . b Raclia1ivc 1ransfer models commonly requ ire one of 1wo imegral propenies of 1he angular dis1ribu1ion of scauered ligl11 (phase func1ion): 

1he asymme1ry fac1or g or 1he hemispheric backscauer fraction b. The asymmetry factor is the cosine-\\eigh1ed average of 1he phase 

func1ion. ranging from a 'alue of - I for em irely backsca11ered light 10 - I for en1irely forn·ard-scauered light. The hemispheric back scalier 

fraction bis defined as cri..r cr,r. 

/(RI-I) The hygroscopic gro\\1h fac1or. defined as cr,r (RH = 85) cr,r (RH = -10). describes 1he humidity dependence of scallering on relative 

humidi1y (RI I). 

a The mass scaucring efficiency for species i. defined as 1he slope of 1he linear regression line relating cr," and the mass concemrmion of 1he 

chemical species. It is used in chemical 1ranspor1 models 10 e\alua1e 1he raclia1i'e dTcc1s of each chemical species preclic1cd by the model. 

This parame1cr has 1ypical uni1s of m~ g·'. 

53 
algorithms 10 inte rprete satellite remote-sensing data to 

determine aerosol amo unts based on measurements of the 

radiati\'c effec ts of the aerosol. 

3.1.3. A:"i:'\UAL CYCLES 

The annual cycles of aerosol optical properties for the 

four baseline and three regional stations are illustrated in 

Figures 3.1 and 3.2. respectively. The data are presented in 

the form of box and whisker plots that summarize the 

distributi on of values. Each box range s from th e lower to 

upper quartiles with a central bar at the median rnlue, while 

the whiske rs extend to the 5'11 and 95'11 percentiles. The 

statistics are based on ho urly averages of each parameter for 

each month of the year; a lso shown are th e annual statistics 

for the ent ire period of record . The ho ri zontal li ne across 

each plot represents the annual median, so measurements 

above and below the medi an can easily be disce rned. The 

a nnual cyc les for the baseline stations are based on data 

throug h the e nd of 200 I, except at SMO, where scall ering 

measureme nts were made only from 19 77 10 199 1 and CN 

from 1977 lo 1997. In general, changes in long-range 

transport patterns dominate the annual cycles of the base I ine 

stations. 

Figure 3. 1 shows that, for BR \V. the high va lues of CN, 

cr,r, and cr,P arc obscr\'cd during the Arctic haze period when 

anti-cyclonic acti\'ity transports pollution from the lower 

latitudes of Central Europe and Russia. A more stable polar 

front characterizes the summertime meteorology. High cloud 

co verage and prec ipitation scavenging of accumul ation-mode 

(0.1 - to 1.0-μm diameter) aerosols account for the annual 

min ima in cr,P and crap from June to September. In contrast, 

C N ni lues ha ve a secondary maximum in the summer. whi ch 

is thought to be the result of sulfate aerosol production from 

gas-to-parti c le co11\'ersion of dimethyl sulfide (OMS) 

oxidation products from local oceanic emissions [Radke et 

al .. 1990). The aerosol single-scallering albedo displays lilllc 

annual ,·ari abi lity a nd is indi cati ve of highl y scallcring 

sulfate and seasalt aerosol. A September minimum is 

obser\'ecl in Angstrom exponent (a) when cr,r and 

acc umulatio n-mode aeroso ls are also lo\\ but when primary 

production of coarse-mode seasalt aerosols from open water 

is hig h [Q11i1111 et al., 2002: Delene and Og ren. 2002). Quinn 

et al. (2002) ha\e also shown. based on their chemical 

a nalysis of the submi cromet cr aerosol particles al BR\V. that 

seasalt has a dominant rol e in co111rolling sca11 ering in the 

winter: non-seasalt sul fa te is the dominant sca11ere r in the 

spring: and both components contribute lo scallering in the 

summer. 

For M LO. the highest cr,r and cr,r \'a lu es occur in the 

springtime and result from the lon g-range transport o f 

pollution and mineral dust from Asia. However. li11le 

seasonal ity is seen in CN concentrations at MLO. indi cating 

that the small est pa rti cles (<0.1-μm diameter). ''hi ch 

usua ll y dominate CN concentration. are 11 01 enriched during 

these lo ng-range transpo rt e\"ents. At SPO. both the aerosol 

cr,P and ,; d ispl a) seasonal cycles. 1\·i1h a cr,r maximum and 

an cl minimum in austral winter assoc ia ted 11 ith the 

transport o f coarse-mode seasalt from the Antarctic coast to 

the interior of the co111inent. The summertime 

peaks in CN a nd a are associated with fine-mode sulfat e 

aerosol and correlate ll'ith a seasonal sulfat e peak found in 

the ice core, presumably from coastal biogeni c sources 

[Bergin e1 al .. 1998). Al SMO. aerosol extensi\'e properti es 

display no distinct seasonal va riation. At BR \V and MLO. 

albedo va lues abo\'e 1.0 are clue 10 instrument noise at 

low aerosol concentration. These high albedo \'alues 

arc not present in daily ave raged data. Furthermore, these 

hig h albedo values are not present if data arc 

excluded where cr,P is below I tvtm·'. Hence. the high 

albedo \'alues result from an instrument detection limitatio n 

problem. 

Based o n only 4-7 years of measurements, the annual 

cycles for the regiona l stations (Fi gure 3.2) are less certain 

than those of the baseline statio ns. The proximity of the 

regional sites to North Ame ri can pollution sources is 

apparent in the res ults, \\'ith monthly median va lues o f cr,r 

that are up to 2 orders o f magnitude higher than va lues from 

the baseli ne stations. The Bondville, Illinois, site (BN D), 

situated in a rural agricultural region. displays an aut umn 

high in <iap and a loll' in rv0 that coinci de w ith anthropogenic 

and dust aerosols emitted during the har\'est [Delene and 

Og ren. 2002). As evident in the lower <isp and crap values. 

the Southe rn Great Plains sit e (SG P), Lamont. Oklahoma. is 

more remote than BN D. SGP ha s a similar but less 

pronounced annual c ycle with late-summer highs in cr,P and 

<iap· and a corresponding minimum in rv0 [Delene and 

Ogren. 2002: Sheridan el al., 2001). Lilli e seasonal 

va riabi lity is observed in aerosol properties at Sabl e Island. 

Nova Scotia (\VSA). Val ues of a tend lo be hi gher in the 

summe r and very likely re sult from transport of fine-mode 

s ulfate aeroso l from the contine111 and lower coarse-mode 

production of parti cles with lower summer wind speed s 

[Delene and Ogren. 2002). 

3.1.4. LO;";G-TERi\1 TRE:\DS 

Fig ure 3.3 s hows long-term trends in CN concentration 

and cr,P for the baseline observatories. and Figure 3.4 shows 

long-term trends in a for the baseline obsen ·atories and <iop 

and {V0 for BR \V and M LO. The mo nthl y means are plotted 

along with a linear trend line fi11 ecl 10 the dat a. Al BR\V. 

the aerosol properties exhibit an annua l decrease in cr,r of 

about 2°0 yr·

1 si nce 1980. This reduction in aerosol 

scatterin g has been a11 ri buted to decreased anthropogeni c 

emissions from Europe and Russia [Bod/wine . 1989) and 

is most apparent during March ll'hen the Arctic haze effect 

is largest. The corres ponding decrease in the A ngstrom 

exponent over the same tim e pe riod po ints to a shift in the 

aerosol size distribution to a larger fract io n of coarscmodc scasalt aerosol. S1one [ 1997) noted a long-t erm 

increase in both s urface tempe ratures and c loud co,erage 

a l BR \V for 1965- 1995 that de rives from c hanging 

c ircul atio n pa11ern s and ma y account for the reduction in 

cr,r by enhanced sca1·eng ing of accumulation-mode 

aerosols. 

In cont rast 10 the reduction in cr,r at BR\V. CN 

concentrations. " ·hich a re most scnsiti,·e lo particles ,1·i1h 

diameters <0. 1 μm. have increased si nce 19 76. There is an 

offset in CN concentration startin g in 1998 that corresponds 
BR .'. 1'J76 _l4'1Q1 

•o ' ' ' ' ' ' ' ' ' • • ' ' l ·~ .. ~ ~ H ~@LU dlil 

·~ TilllG"i' l! i l~i 

::. ::~ ~ ffi rrr n ~ ~ ~ ~ 1 

,,,I L • ~ ~ I 

f ··:r T T~.~~PQ: ·~ -~)C~ r T T T 

:-. ':.' l ~ ~ * ~4 ! ~ ~ ~ ~ ~ ~ 

\ TIT~ -- ·· ' "·~ ~ ~ ~ ~ I -t > L L - -

~~i ' ' ' ' 'i''o '•,•J-.>co: ' T T r I 

-~ H ~ $ ~ ~ Q $ ~ + ? ~ + * ~ l 0 .~ ~ ~ ~ - .L -

rig. 3.1. 130\ and "h1skt'r plots of annual C) cles shm1 ing ;,tau sties for condensation nuc ki (C;'\) conccntrallon. Angstrom e\ponent (cl). 

and total scattcring coefficient (O»rl at baseline 'tat ions BR\\. \ILO. s;..10. and SPO: and for absorption coefficient (<J,rl and single 

scattering albedo ((o .. ) at BR\\' and \ILO. Statistic;, representing the entire period are gi1en in the last column(/\'\'\). 1--.ach bo'\ ranges 

from the 25'1 to 75•h quartiles. and the horizontal line represents the median 1aluc. The "hiskcrs c.\tcnd 10 the s•h and 95•h quartile>. 

55 
!:'.::>: '996-20C1 !''.!:': 1996-2001 

15f T , • r .,. ~ ~ ~ 

~~ ·:: ~ ~ H H ~ I '" :' ~ '. p H ~ ~ ~ ~ ~ ~ : 

.', S.\: 9~5 L000 ','. SA: '995-2000 

';GP !996 2CC1 S'.;P '99€-200' 

JA\.; \'AR '.':.."' Jul C:EP :.J'J A~,~~~ O.S .,,~'\ 1.1AR \'AY ... UL 5FP '.0\J A~~! 

,,, • ~ .. , .. ,,. ,,,, J . "' H ~ , .. , .,,. . . j 

~ ~! w ~ uil ~ ~l 3"~~ . ~ n n : J ~ .':SA: l'l95 2000 \';SA: ' 995-2000 

~ :!! H ~ ~ ~d ~ i ~ H ~ j j l~t ~ ~ ~ ~ H ~ ~ ~ ~ H ~ l SGP: i996 2001 SGP '9'1o 20~l~ 

~ '.~ [llij i ~ d . - ~ ~ 30 ~~ ~ ~ '. H r~ ~ ~ n P lJAf'. '}I.I"( '.'1-Y •L;::> :'\.v. ,,.,, ,., " · '.'/.- '.'~ Y JI" -c::r ~~-, t-·.·. 

Fig. 3.2. Bo:-. and whisker plots of annual cycles for regional sliltions at B'\D. \\'SA. and SGP sho"ing statistics for absorption coefficient (a.,). 

Angstrom C\ponent (a). total scaucring cocflicicnt (IJ,0 ). and single-scauering albedo (<l\.). Statistics representing the cmire period are g iwn in the last 

column (,\;.;'\). The bo\C'> and" hiskers arc as 111 Figure 3.1. 

56 
BRW Condensotion Nuclei (cm- '} 

1400 orrrrrrnm"'""="f1TTITm1"' ' 1'mn-nntpnnn •rmn=ifi==mrn'""1'"""="""' 

MLO 

SMO 

SPO 

1200 ~ 

1000 

800 

600 

400 

200 

1000 

800 

600 

:: .... ~~~~~- ~ 500 

400 

300 

200 

300 

200 

100 

Condensation Nuclei (cm- ') """'""'"'"'""""''l""'"'l"ffrf'mmT rn 111 n1 '1'1'111rt=ljcrr=rrrrhrnm'""''I1'"'"~,,,... 

Condensation Nuclei (Grri- ') "'m111m11 1""'"""J m111m11m111w11 m111 m11""""1''l'~'m111m11mn1Titfl'"iiTfllTT rt'11'1' l'f1\1'1'n'""'"""'""'"""mm"""' 

BRW "' ,""I ,, ,, ,,,;,~~ .~ .. ~~.~~.\~ \~~ ... ~~.;,~ :~:~~J.t Mm";.1~"" 25 f20 

15 ~ 

10 >-

5 

MLO 

4 

SMO 

1.5 

1.0 

0.5 

1977 1980 1983 1986 1989 1992 1995 1998 2001 

Fig. 3.3. Long-tenn trends for baseline stations of monthly averaged condensation nuclei concentration (left panels) and total scattering coefficient at 

550 nm (right panels). A simple linear fit is given for the scattering coefficient but is omitted for the condensation nuclei because instrument changes 

make a trend I ine inappropriate. 

to a change to a new CN sampling inlet. Similarly, the step 

increases in CN concentration in late 1991 at MLO and 

1989 at SPO are due to replacement of the CN counter with 

a butanol-based instrument with a lower size detection 

limit. The reason for the decrease in CN and increase in a 

at SMO is not readily apparent, but it could stem from 

changes in long-term circulation patterns. 

Previous reports describe the aerosol data sets: for BRW, 

Bodhaine [1989, 1995]; Quakenbush and Bodhaine [1986]; 

Bodhaine and Dutton [1993]; Barrie [1996]; Delene and 

Ogren [2002]; for MLO, Bodhaine [ 1995]; Delene and 

Ogren [2002]; for SGP, Delene and Ogren [2002]; Sheridan 

57 

et al. [2001 ]; Bergin et al. [2000]; for SMO, Bodhaine and 

DeLuisi [1985]; for SPO, Bodhaine et al. [1986, 1987, 

1992]; Bergin et al. [1998]; and for WSA, Mcinnes et al. 

[1998]; Delene and Ogren [2002]. 

3.1.5. SPECIAL STUDIES 

Comparison of Aerosol Light Scattering and Absorption 

Measurements at Mauna Loa, Hawaii 

CMDL has measured both aerosol light scattering (since 

1974) and aerosol light absorption (since 1990) at MLO. In 

spring 2000 new light scattering and absorption instruments 
BRW BRW 20 

1.5 

MLO MLO Absorption Coefficient (I /Mrn) 1"TT"l"'t"l't"l lTM'iili ll lj i il i i ii ii ilj i iiiiiiil i l I' '' ''''' ' 1• ••t'1'T'l"10"f'M' 

0,8 

0 .6 -

0 

SMO Angstrom E.xponeri ~.,~.~~0/ 700 nm} 4 ~~TITJ","TTTTITfTI'"rrrr mrmm'"""mrrrmm"'"''""'"""'"' BRW s;ngle-scatte6ng Albedo 1.00 ~tiiiiihiifOlllPliiilji ; J j I 'f'm't't"t't'l'H l" 

3 

2 0 _90 

V__ ·' V'" .1 I!.\ II' 4 .r!Yd lf"U IJ ,, r .... 'Y 

\ UJj,JUj,llo1Ll.iUJJ.J111•• 1111 ••'· 11 ....... 1 ... 11111t1 •1,, ......... 1LLUJ .LlU .. U.L.u.1.ut 

0 

-1 

0.85 

SPO AngstfOm Exponent (550/700 rim) 4 "'""'~""'""~"'' rnm""'f'm''ITttTttt'ffmlTI 

MLO 

3 

2 

0 

-1 llu.IJl,1..1..U.ll .. li.uJJ..UJll ! , 1 1u (' 1 1 1 I 1 u 11 1 n r 1 .! I !J t I I I I I I I I!! I II h I I I u!J..uJ.U.UtiJl.iU i1JLl1 u.l.11 

1974 1977 1980 1983 1985 1989 1992 1995 1998 2001 

Fig. 3.4. Long-term trends for baseline stations of monthly averaged Angstrom exponent (550/700 nm) (left panels); and absorption coefficient and 

single scattering albedo .at BRW and MLO (right panels). Simple linear fits to the data are shown. 

were installed at Mauna Loa (within 2 m of the old 

instruments). Prior to the upgrade, light scattering was 

measured with a three-wavelength nephelometer (MS 

Electron, Seattle, Washington), and light absorption was 

measured with an aethalometer (Magee Scientific, Berkeley, 

California). This original sampling system did not include 

size or relative humidity control of the aerosol sample. The 

new instruments are designated MLN (Mauna Loa New) to 

distinguish them from the collocated MLO instruments. The 

new system obtains measurements at two size cuts by using a 

valve to switch between a 10-μm and 1-μm impactor. 

58 

Relative humidity is maintained at no more than 40% by 

heating the air sample as necessary. Table 3.5 lists the 

instruments and their period of operation at Mauna Loa. 

It is important to assess how measurements from these 

instruments compare in order to maintain data consistency for 

the entire measurement period. The MLO and MLN systems 

were operated simultaneously for approximately 1 year 

(spring 2000-spring 2001). One year of simultaneous light 

scattering and 3 months of light absorption (the aethalometer 

broke in August 2000) measurements from the collocated 

instruments are compared here. 
TABLE 3.5. lnstrnment lll\ cntory at Mauna Loa Obsenatory 

Instrument 

1\IRI nephelomcter 

1\IRI ncphelometcr (operating at one 

\\mclength because ofmstnnnent 

problem,) 

1\ IS Electron nephclomctcr 

1\lagee Scientific acthalomc1cr 

TSI ncphclomc1cr 

(model number 3563) 

Radiance Research paniclc soo1 

absorption photomc1er (PSAP) 

:-. tRI. \lc1eorolog) Research Inc. 

Period of Operation 

1974-,pnng 2000 

Summer 1982-spring 1984 

Sprmg 199-1-~pring 200 I 

1990-prc:.cnt 

Spring 2000-prcscnl 

Spring 2000-prescnt 

The comparison procedure was as folio\\ s: 

• Select data for the overl ap period. i\lay 2000 through 

April 200 I. 

• Estimate the absorption coerficient for the 

aethalometer using cr,r - 10 m~ g·

1 x [BC]. 

• Appl) quality-control edit corrections to data sets 

(e.g .. remo\ e spikes and contaminated data ). 

• For the MLN data set. use onl) 10-μ m si7c cut data. 

• Correct the MLN PSAP data for (a) scattering b) 

parti cle~ \\ ithin the filter and (b) spot size. Also. 

remO\ c low transmittance data (e.g .. transmittance 

<0.5. per Bond el al. [ 1999]). 

• Calculate hourl y averages or scattering and 

absorp1ion coefficients. 

• Determine the least-squares I inear fit and correlation 

coefficient for the data sets. Perform the regre ssion 

for both a calculated and forced-to-Leroy-intercept. 

Figure 3.5 shows that. on an houri) ba sis, there is 

excellent correlation between the ncphclometcr measurements (R~ = 0 .94 ), and the instruments agree fairl y well (the 

slope is I. I). This agreement is also seen \\ hen the data are 

separated for upslope (polluted) and dO\\ nslope (cleaner) 

condition s. Because the t\\O instruments appear to be in 

good agreement. the old ncphelometer was removed during 

annual ma intenance in May 200 I . 

The comparison between the PS/\P and the aethalomctcr 

(Figure 3.6) was O\er a much shorter time period: i\la) 

2000-carl y August 2000. In early August the acthalome ter 

feed sprocket \\ as replaced. and after the rep lacement, 

measurements from the two instruments became completely 

uncorrelated (R2 = 0.02). Prior to the feed sprocket 

replacement, the absorption measurements show that the 

PSAP measured absorption coefficients - 3 times higher 

than the aethalometcr although the instruments \\ere fair!) 

well correlated (R ~"' 0.6). The difference between the two 

in struments suggests that the assumed BC absorption 

efficiency o f JO ~ g·1 may not be appropriate for Mauna 

Loa. Additional comparisons bet\\Ccn the PSAP and 

aethalometcr arc planned to resolve this discrepancy. 

Determination of Ille Light Absorption Efficiency of 

Grapflilic Carbon in Indian Ocean Aerosols 

Carbonaceous particles in the atmosphere arc generall) 

thought to contain up to two major classes of ca rbon: 

S1a1ion Comments 

\ILO 

\!LO 

Four "a'clcngths. no si7c cu1 

One \\a\elength (550 nm). no size cut 

\ILO 

;..!LO 

TI1ree \\a\ eleneths. no :.i/C cut 

Broadband. no ~'>i7e cu1: specific absorption of 10 ~ g·' used 

10 com en [BC) 10 cr,. 

Three wa\cleng1hs. 101al and back scalier. l- and !0-~1111 

Si/e CUIS 

l\ILl\ 565-nm \\U\Clcnglh. I- and 10-μm Si/e CUIS 

59 

E 

~ 

a. 

100 

75 

50 

t5 25 

0 

y = 1.10x 

R2 = 0.94 

............... : .. ·· 

. ......... .......... . . . ...... . • • t ~..,..,. 

. :-.-". .. . . . 

0 25 50 75 100 

cr,P (Mm-1) MLN 

rig. 3.5. Comparison of scancring measured by 1hc nc\\ ncphclometer 

(cr.0 \IL:\) \\ith scanering measured b) the old nephelomc1cr (cr .• :-..tLO) 

for 550-nm \\a\clcnglh. spring :!000-spring 2001. TI1c solid blad. line 

sho\\S 1hc Iii "hen the 1·-in1erccp1 is forced through 1hc origin: the 

dashed line is 1hc I: I line. 

2.0 

0 1.5 _J 

:iE 

.,. 1.0 E 

~ a. 

0 0.5 

0.0 

y = 0.39x 

R2 = 0.56 

0.0 

.... ............. ...... ..... ..... ..... ·' ....... .. ·" 

_.,.,/ ..... ,.. . . ..... 

0.5 1.5 2.0 

l·ig. 3.6. Comparison of absorption measured b) the PSAP (cr . l\ILi\) 

\\ ith absorp1ion measured h) the ae1halome1er (cr, 0 t\I LO). l\la) 2000-

J\ugusl '.!000. The solid hlad. line sho"s the tit "hen the y-in1ercep1 is 

forced 1hrough 1he origm: 111<: dashed line is the I: I line. 
organic carbon (OC) and black carbon (BC. also called 

elemental carbon. EC). Visible light absorption b) 

atmospheric aerosols is t)pically dominated by particles 

contain ing BC. The mass measurement of BC in 

atmospheric aerosol samples has most often been performed 

by thermal evolved gas analysis [e.g .. Cac/iier el al., 1989] 

or thermal optical rcllectance (TOR) methods [e.g., Chou· el 

al., 1993). The light absorption coefficient (CJ,p) of aerosol 

samples has been determined with optical (usuall) filterbased) instruments. such as the aethalomctcr [e.g .. 

Bod/wine. 1995), the PSAP lc.g., Bond el al., 1999], or 

photoacoustic techniques [e.g .. Amo/I el al., 1999). All or 

these measurement techniques depend direct!) on the 

amount of aerosol sampled for the analysis. and al l ha\·e 

associated measurement uncerta11111es. artifacts. i ntcrfercnces, and other problems that must be taken into 

account. 

A measure of the effic iency with \\ hich atmospheric 

aerosols absorb visible radiation is desirable for model 

inputs and other applicat ions. The aerosol light absorption 

efficicnc). a. is defined as 

(I) 

where CJJr is total absorption (in Mnf 1), and 111 , is the mass 

concentration of absorbing carbon (in μg nf3). The parameter a has also been called the specilic allenuation cross 

section, the spcci fie absorption coefficient, and the BC mass 

absorption coefficient in previous studies. Over the past 

l\\ o decades. reported \·alues of a IHt\ e ranged from I to 

25 m2 g· 1

• Most of the \ ariabilit) in a has been a1tributed 

to differences in aerosol composition, shape, size. mi:-.ing 

state (i.e., internal \S. c:-.ternal), and amount of scallering 

materia l present. The chall enge for researchers is to 

determine what portion or the va riability in a is caused by 

instrument uncertainty or di ffercnces in measurement 

methods and \\ hat portion is due to rea l differences in the 

sllldied aerosols. 

A ne\\ method of determining the a of graphi 11 c carbon 

(GC), a specific and dominant component of BC, is reported 

here. The PSAP instrument was used to obtain the Oar of 

aerosol samples co ll ected during the Indian Ocean 

Experiment (INDOEX) in early 1999. The PSAP is a filtcrbascd instrument in \\ hich aerosol paruclcs are con11nuousl) 

deposited onto a !iltcr. A transmittance measurement is 

made through the particle deposit and simultaneously 

compared \\ ith an identical measurement through a second. 

particle-free filter. Through careful calibration of the fa\\ 

transmittance signals against deri\·cd absorption from an 

extinction cell/nephclometer system [Bond el al .. 1999]. a 

measurement of suspended-state aerosol absorption 1s 

obtained. 

For the analysis of GC mass, CM DL collaborated wi th 

colleagues at the Institute for Tropospheric Research (I FT) 

in Leipzig. Germany. The Raman instrument used in this 

study to quantify GC mass \\as a Bruker IFS 55 

spectrometer equipped \\ ith a FRA-106 Raman module in a 

backscallcr configuration. Calibration of the Raman 

spectrometer for GC mass on the PSAP filters was 

performed as documented in ,\/er1es el al. [2002) using a 

commercially arnilablc carbon black standard (Monarch 7 1. 

60 

Cabot Corporation. Boston, Massachusetts). The 

atmospheric concentration of GC can then be calculated 

from the GC filter mass. using the \ olume of air sampled 

through the PSAP filters. 

This in\ estigation has two adrnntages over pre\ ious 

studies. First. the GC responsible for I ight absorption and 

not the thermographic EC is used. Thus. a quanti liable. 

dominant component of light absorbing carbon is obtained. 

Second. the correlation between Oar and 111 .. is anal)led from 

identical aerosol samples (i.e., the same particles). so any 

\ariability between samples does 1101 come from exami ning 

different populations of particles in the two analyses. 

The INDOEX lntensi\e Field Phase (IFP) \1as conducted 

during February and March 1999. The site for Cl\IDL surface 

measurements \\as the Kaash idhoo Climate ObscrrntOr) 

(KCO), on the island of Kaashidhoo in the Republic of 

Maldives. During this period of the \\inter monsoon, dry 

winds from the northeast sweep over the area. These winds 

bring \Cry polluted air from India and Southeast Asia O\er 

the Maldi\es. The INDOEX aerosols haYe been found to 

contain signilicant fractions of BC [Ra111a11a1hw1 el al .. 

200 I]; probable sources of these aerosols include biomass 

and biofucl burning, \chicle exhaust, industrial releases, and 

other anth ropogenic emissions. 

Figure 3. 7 shows a time se ries of o,r plotted alongside 

GC concentration. O\erall. there \\aS good agreemelll 

bel\\ccn the l\\'O parameters over the course of the IFP. The 

initial portion of the e:-.pcriment (through DOY 70) \1as a 

period or highe r aerosol concentrations at KCO punctuated 

by l\\O rai nfall e\ents that remo\ed aerosols from the 

atmosphere. From DOY 71 through nearly the end or the 

IFP, light absorption coefficients \\Crc relati\·el) IO\\Cr. but 

still SC\ cral times larger than at typical rural. 

midcontinental sites in the Un ited States [Delene anti 

Ogren, 2002]. In Figure 3.7. each symbol represents the 

analysis of one PSA P filter. When high concentrations of 

aerosols were present. filters "ere changed up to fi\ e times 

per da) to pn:\·cnt the PS/\P fi lter transmittance 

measurement from dropping belO\\ 0.5. During cleaner 

periods (e.g., the rainfall e\ents), fi lters were changed as 

infrequently as once per day. 

50 

E 

~ 40 

c 

0 30 

a. 

0 1l 20 

"' 

10 

40 50 

• absorption 

o Graphitic Carbon 

60 70 80 90 

Day of Year, 1999 

M" 

5 ·e 

4 

Cl 

:1. 

c 

0 

3 -e 

u "' 

2 ,g 

:c 

0. 

~ 

C) 

Fig. 3.7. Time series of absorption and graphuic carbon measured al 

KCO durmg February-.\ larch 1999. 
Figure 3.8 sho\\ S a jP plolled against GC. In this analysis. 

the PSA P fi hers were grouped according to the ir ti Iler 

loading, and one ob' ious out lier "as remo' ed from the 

··Medium Loading·· category. The PSA P manufoclllrer·s 

manual states that absorption measurements should be 

reliab le as lone. as the tilter transmillance (Tr, or / / 11) 

remain s abo\ c (l.5. The calibrations recommended by Bond 

et al. ( 1999]. ho\\e\cr. were performed using PS Al's "ith 

Tr va lues maintained abO\e 0. 7. so this grouping or lightly 

loaded filters is the only one in whi ch the Bond e l al. [ 19991 

PSAP calibration corrections can be applied reliably. The 

slope o r the linear least squares regressio n line through the 

lightly loaded filt ers equates 10 an a. or 9.7 m2 g·

1

• w ith a 

\Cl') s mall offset and an R2 value of 0.86. The fil ters "it h 

hig her GC loadings show regression slopes bet\\ een roug hl y 

9.0 and 10.-1 , but "ith significant _1 ·-intcrccpts. These /ero 

offsets may be due to uncertainties in the nonlinear filter 

loading corrections used in th e PSA P instrument. Whi le 

GC c u;rcntly is thought to be the major aerosol absorber of 

'isible ra di atio n, other forms of carbonaceous material 

{e.g .. amorphous C. organic CJ need to be studied in a 

si milar manner to quantify th eir contributions to 'isible 

lig ht absorption by aerosols. 

Jn Situ Aero.rnl Profile Measurements m •er the Southern 

Great Plains Cloud and Radiation Testhed (CART) Site 

The objecti' e of this project is to obtain a statisti cally 

sig nifi cant data set of in sit u meas uremen ts or the \ertical 

di tribution of aerosol properties (e.g., ligh t scall eri ng and 

absorpt ion). The measuremen ts will be used to answer the 

fol lo\\ ing scien tifi c q uestions: 

• I lo" do aerosol properties 1 ary th roug hout the year'> 

• Unde r what conditions can surface-based 

measurements of these prope rti es be used to 

calcul ate the di rect aerosol radiali\c forcing from a 

measured aerosol optical d epth (and "hat conditions 

inhi bit s uch ca lculations)? 

• 11 01' do local and regional perturbations (e.g., fires) 

influence the Ycrtical profile characteristic s? 

• 11 011 do data from these fli ghts compare 11 ith ot her 

mea su rements of atmospheric c haracteristi cs, e.g., 

aerosol optical depth (AO D)? 

T he data arc obtained on an instrumen ted light aircraft 

(Cessna C- 172N) over the Southern Great Plains (SG P) 

CA RT site in Lamont, Oklahoma. The aerosol instrument 

pa c kage o n the airc ra ft is similar to the o ne operating at the 

surface SGP site. The aircraft fl ew 225 profile fli ghts 

between March 2000 and Decembe r 200 1. For each profile 

11 ight, the Cessna fl ew nine lei e l legs O\ er (or near) the 

SGP sit e. The legs 11ere llo11n at altitudes of-167, 6 10, 915. 

1220. I 525. I 830. 2440. 3050. and 3660 m abO\ e sea k:\ c l. 

and lliuhts 11erc made se1·cral times each 11cek. Aerosol 

data w;re collected at I I lz and a1 eraged O\ e r the duration 

of each Ici ci flight segment (- JO-min a1eragcs for the four 

highest lc1·cls. -~5- rnin~ a1·crages for the fi,e lo\\CSl le1cls). 

Aerosol optical p rope rti es obtained for each le' el leg 

include a,r· a b,r· and a,r coefficients. From these c\tensl\C 

properties the following intcnsi 1·e aerosol optical properties 

11ere d eri1 cd: (V.,. h, and 0. All measurements o n the 

a ircraft 11erc made at I011 humidity (Rll ::= 40°'0). 

6 1 

60 

50 

E 40 

~ 

c: 

.Q 30 

c. 

(5 

IJ) 

.Q 20 

"' 

10 

0 

0 

o Light Loading (1.0 >Tr> 0.7) 

Wedium Loading (0. 7 >Tr > 0.5) 

• Heavy Loaduig (Tr < 0.5) 

: y = 9.69x + 0.21 

. R2 = 0.86 

y = 10.37x + 3.14 

R2 = 0.84 

y = 8.97x + 8.80 

R2 = 0.67 

2 3 4 

Graphitic Carbon (mg m ·

3

) 

5 6 

Fil!. 3.8. Comparison of GC and absorp11on coct1icicnt measured at 

KCO during Fcbrual')-i\1ard1 1999. The solid darl.. line 1s the lit lO the 

hea\) loading data: the gra) line i., the lit to the medium loading data: 

and the dashed black line is the lit to the light loading data. One outlier 

has been remo1 ed from the "\l edium Loading" data set. 

There is good agreement (R2 - 0.82) bet11ccn lo11cst level 

leg and surface extincti o n {a0 " a 0 r + a,r) 1alues. 

indicating s ubmicromctcr aerosol (predominantly scattering 

aerosol) in the 150 m abo1c th e surface is 11cll-mi xed. 

M uch of the va riability in the parameters measured at the 

su rface sit e appears to be captured b ) the \\eckly profiling 

fl ights. T he comparison is not as good (R2 = 0.-19) for 

single-scalle ring albedo and is due to measured differences 

in ~bso rption bc111ccn the surface and the 101\cst nig ht 

le' el. These obsen cd di ffcrcnccs appear to be rea l because 

side-b y-side tests o f the 111 o PSA Ps s ho11 good agreement 

(11 ithin 8°0). Comparison of other deri' ed properti es at the 

lo11cst lli uht lcYcl 11 ith surface p ropert ies are e .\cellent for 

backscall;r fraction and green-blue Angstrom e\pone nt. but 

Jess so for the green-red Angstro m e .,.ponenl. 

Figure 3. 9 s ho11 s the medians and ranges {as indicated b y 

percentiles) of a rcprcse111 ati1e e'>; tensi\C aerosol optica l 

property {extinction) and a rcprcscntati\c intcnsiYc aerosol 

optical property {sing le-scallering albedo) at STP. low RI I. 

and D < I μm, o btained al the su rface and during 1erti cal 

profi lin g flights. The line in the center of the box 

represents the med ian. ll'h il e the edges of the box g ive the 

25'h and 75•h perce ntiles, and the 11 hiskcrs c"tcnd to the 5•h 

and 951h percen tiles. In general. the 'alucs for extc nsi1·c 

p rope rties (extinction . absorption, and scallering 

coeffi c ients) \ary b) up to a factor of 3. 11 hilc the medians 

for intcnsi1 c aerosol properties (single scau ering a lbed o. 

backscaller fract io n. and Angstrom exponent) arc much less 

\ariable (less tha n 10°.o ,·ariation). Figure 3.9 suggests that 

the median \'alueS Of the e.\tensiYe properties lend to 

d ecrease ll'ith altitude from the surface upwa rd. Such 

beha' ior is expected as distance fro m the ground-based 

sources or aerosol parti cles in creases. The median rnlues of 

the intc nsi,·c properties do not display a strong d epende nce 

11 ith altitude. 
o~~ ......... ~~~~~~~ 

0 20 40 60 80 100 0.60 0.70 0.80 0.90 100 

e.ctinctlon (Mm-') single scotterinq albedo 

rig. 3.9. Statistical bo:1. and "hisker plots of, enical proliks of 

C\tinction (1.:ft) and albedo (right) O\ er the SG P site. \l arch 2000-

\larch 2001. Black plots arc from aircraft nights: grn) ploh arc 

surface measurements. The bo:1.cs and "his~crs arc as 111 I tgurc 

3. I. 

f\ lorc ind icat i\e of the O\erall \'ariabil it) of the aerosol 

arc the ranges of the parameters. as ind icated b) the 

percenti les in rigure 3.9. ExtensiYe properties can differ b) 

up to 1 o rders o r magnitude between flighb and c1 en 

bet\\een individual le\els of the same flight. The intensi\c 

properties. \\ hile still displaying a range of \alues. \ ary at 

most by an order o r magnitude (i.e .. green-red Angstrom 

c:1.poncnt. le\ cl 3660 m) but more common I) b) less than a 

facto r of 2. The parameter ranges display diffc rent 

tcndeneies "ith height. Extcnsi\e properties become less 

niriable at higher altitudes. due to consistently IOI\ 

concentrations of aerosol particles. Coll\ crscl). intensi\e 

properties become more \ariable \\ith altitude for a similar 

reason: lo" concentrat ions of aerosol partic les result in 

more noise" hen calculating the \'alues of these parameters. 

0.3 

c 

0 

<( 

0::: 

en 0.2 

0::: 

The surface measurements arc reprcsentati' e of the 

frequenc) distributions aloft. particular)) for i111cnsi1 e 

properties such as albedo (Figure 3.9). Ho\\e\er. the 

correlations (not sho\\'n) bet\\ een column a1 erage and 

surface \'alues are IO\\er (e.g .. C\tinction R2 = 0.65: albedo 

R2 = 0.30) than correlations between lowest flight le\'el and 

surface 'alues. Thus. while surface aerosol measureme111s 

are statistically representa ti1 e of the air aloft. the) ma) not 

be reprcscntati\'e of day-to-day 'ariations in the colu mn. 

Measurements from the profile flights can also be 

compared with measurements by remote sensing 

instruments located at SGP. i.e.. the Cimel sun sky 

rad iometer and the multi-tilte r rotating shado\\ band 

rad iometer (ti IF RS R). A ftcr incorporation or corrections 

for supermicromctcr. upper tropospheric. and stratospheric 

aerosol particles. comparison in Figure 3.10 of aerosol 

opti cal depth (AOD) calculated from aircrali measurements 

with AOD obtained from the remote sensinl!. instruments 

shows fair correlation (R! == 0.5. Cimcl; R2 == 0.8. MFRSR). 

although the aircraft AODs arc lower than those dcri,·ed 

from the radiation instruments. "ith an offset in the range 

of-0.03 or -0.04. 

Long-term surface measurements can represent a 

statistical distribution of aerosol properties aloft. llo11c\er. 

day-to-da) 1 ariabi lit) bet\\ ecn the surfact:: and alo ft ma) not 

ah1ays be captured and caust::s a poor re lat ionship bet\\een 

surface and column a1 crage quantities. Compa rison of the 

in situ and remote sensing instruments shows fair 

correlat ion for AOD although the aircraft AOD is 

consistently lower than that o f the remote sensin g 

instruments. 

Measurements of Aerosol Optical Properties from a 

Surface Site in Korea (ACE-Asia) 

An intt::nsi,·e field campaign knO\\ n as the Asian Paci fi c 

Regional Aerosol Characterintion l:.xperiment (ACE-Asia) 

too-k place in Apri l 2001 in eastern Asia. The goal of ACEAsia was to gather data for regional c limate models as well 

o CIMEL 

LL 

~ 

"'O 

c: 

y = 0.96x + 0.03 

R2 = 0.50 

• MFRSR 

01 :01 

---Linear (CIMEL) 

Linear (MFRSR) 

('Cl 0.1 ...J 

w 

:E 

u ••• . 

0 

0 0.1 0.2 0.3 

Aircraft AOD 

Fig. 3.10. Comparison of aerosol optical depth (AOD) measured on aircran \\ith t\OD dcri\<.~d from Cimel and 1\IFRSR remote scn.,ing in~.irumcms at 

the SGP site. for I> larch 2000-\larch 2001. 

62 
as to understand better the interactions bt:tween aerosols 

and radiation. gas phase species. transport. and c louds. 

This large field stud) was a multi-platform. international 

effort \I ith scientific measurements being recorded from 

land-based sites. ships. a ircraft . and satellites. Scientists 

from Korea. United States, Great Britain. Ch ina. Japan, and 

Australia \\'Orkcd together lo characteri Le aerosol radiati Ye. 

chemical. and size properties. These aerosol properties. as 

11 ell as their co1 ariance. strongly inlluence the Ea rth 's 

radiative balance. The p rimary s urface site was located at 

the Upper Air Meteorological Observation Facility near the 

sma ll town of Kosan o n Chcju Island. South Korea. The 

sit e is strategica lly located between seYeral major aerosol 

source regions. Depending o n wind cond it ions. the 

scientists obsen cd anthropoge ni c aerosol from Japan. 

Korea. and China: large dust outbreaks from northern 

China: re lati1ely clean marine a ir: or e1en local crop 

burning. 

As part of this effort. CMDL conducted in situ 

measurements or the aerosol opti cal properties as "ell as 

250 absorption Jttennq 

a 

200 

-: 

E 

50 !if 

0 

't:J 

lij 100 

~ 

0 

50 

1~ J\ ~J J.,J«• \,...._ 

0 

95 100 105 110 11 5 120 

Day of year. 2001 

1.0 

\j ~\ ~~~~~ (1( 1'1 '~·~ c 

c 

0 

u 0.8 ro 

~ 

2 

<I> 0.6 E 

e 

<.> 

.E 

.D 0.4 :::> 

(/) 

absorption ltlE'"lf 1 

0.2 

95 100 105 110 115 120 

Day of year, 2001 

full column measurements of solar radiation at Kosan. The 

ground-based measurements included aerosol scallering 

coefficient as a func tion of particle siLe. \I al'elength. and 

rela1i1·e hurnid it). and the aerosol absorption coefficient as 

a function of siLe. These obsen at ions pro1 ide a direct 

measure of the s urface aerosol e\linction of 1 isibl e 

radiat ion. For full column measurements o f the atmosphere. 

radiometers from Ct\IDL measured the total, direct. and 

diffuse (sca ttered light by aeroso l) solar radiation. These 

observations can be used to deri1 e the /\OD. or a mo unt o f 

solar radiatio n allenuatcd by aeroso ls. and the aerosol 

forc ing efficiency. 

The aerosol scatt ering coeffic ient \\'as highly 1 ariablc 

duri ng the campa ign. ranging bet\leen 20 and 250 Mrn·1

. 

Spring in Korea is kno\l n as the d ust season when 

southeasterly "inds bring dust to the region from the Gobi 

Desert. Several such e1·ents. note part icu larly day of year 

(DOY) 101 - 10-1 a nd DOY 11 0. are apparent from the data 

(Figure 3. 11 ). On these da) S 01er 60°0 of the aerosol 

scallering was in the total size mode. as indicated by the 

1.0 

b 

total r'11~r 

0 

/~ N'~~ ~ J'f \ it,~\/ 'O 

Q) 0.9 .D 

-ro 

CJ) 

c 

t~\ ·~ 

"" 0.8 ro 

u 

(/) 

Q) 

gi 0.7 

·u; 

0.6 

95 100 105 110 115 120 

Day of year, 2001 

4.0 

d 

3.5 • 

3.0 ~· ~:-. • ~ 2.5 

.. ;;::-- ·~~ Y· ~-i~· 2.0 ~ ) • • • 

1.5 

. ~ 

1.0 

95 100 105 110 115 120 

Day of Year, 2001 

Fi g. :i 11. Time 'crie' of aerosol mea<,urcmcnh from Ko,an during ACE-rhia in 2001: (a) total absorption and \Cnttering coefficit:nts. (b) 

total and 'ubmicrnmcter single-scat1ering albedo. (c) 'ubmicromctcr fraction of aerosol ah,orption and 'cattering. and Cd) 1otal acrm,ol 

hygro,copic gro" th factor. All values are reported for a wa' clength of 550 nm. 

63 
lo" 'alues or the ratio of the submicromeler to total aerosol 

scaltering coefficients (Figure 3.1 l c). The aerosol si nglescaltcring albedo during the dust e\ cnts declined slightly to 

- 0.80 for total aerosol and as lo" as 0.63 for submicrometcr 

aerosol (Figure 3. 1 lb). Most of the aerosol absorption 

during the campaign was in the submicromcter particles. 

The aerosol hygroscopi c growth factor. /(RH) 

o,r(RH=85)/o,r(RH=-IO). a measure of the increase in 

scattering due lo aerosol \\atcr uptake. was rclati,ely high 

during the dust e\ ents. ranging from 1.5 to 2.5 (Figure 

3.1 Id). The low single-scattering albedo and high 

hygroscopic growth factor indicate th e aerosol at the site 

was composed of not onl) dust but also vcr) like!) of 

absorbing elemental and hygroscopic species wch as 

sulfate. oxidiLed organics. and scasalt. 

Mean aerosol optical properties from Kosan as well as 

from two other anthropogenically perturbed sites are gi\'cn 

in Table 3.6. Although all three sites rccei\'e anthropogenic 

aerosol, there arc significant differences in the aerosol 

opt ical properties bet\\ecn the si tes. demonstrating the 

importance of long-term, regional measurements at a variety 

of locations. Kosan. South Korea. and Kaashidhoo. 

Republic of \ laldives. are anthropogenicall) perturbed 

marine sites. and Bonch illc, Illinois. is an anthropogenically 

pt:rturbcd continental site. Thi: aerosol scattering 

coefficient from Kosan is higher than from either the 

Kaashidhoo or the Bond\ ille sit.e. indicating a high aerosol 

loading in eastern Asia during the spring. Kosan and 

Kaashidhoo ha\'c higher light absorption coefficients than 

Bondville, consistent \\ ith a larger contribution of 

combustion aerosol (e.g .. from biomass burning or limited 

pollution control on 'chicles and industries). Consistent 

11 ith the higher absorption coefficients at Kosan and 

Kaashidhoo, those sites have lower single-scattering albedo 

\alues than Bondi ill e. "ith Kaashidhoo being significant!) 

IO\\er than Kosan. The ./!Rll) 1alue at Kosan was 

significant I) higher than at Kaashidhoo or Bondi ille. The 

.f!RH) at Kosan did not correlate well with scasalt aerosol. 

but was probably high due to extensi1e mixing with 

polluted air masses containing sulfates and nitrates from 

both China and Korea as well as cloud processing. At 

Kaashidhoo the aerosol \\as more rc flectiH of the source 

TABLE 3.6. Means and Standard De\ iations of Aerosol Optical 

Properties of Anthropogenically Influenced Aerosols at 550 nm 

Aerosol Kosan Kaashidhoo Bonth1llc 

Property (KOS) (KCO) (B'Dl 

a ,r• 92 (53) 73 (28) 5-l (43) 

CJ. ri* 12 (8) 16(9) -l (3) 

(l) 0.87 (0.05) 0.82 (0.03) 0.92 (0.06) 

/(Rill 2.2 (0.5) 1.7 (0.1) 1.7 (0.-l )+ 

Fa,0 ! 0.61 (0.16) 0.67 (0.08) 0.86 (0.09) 

Fa.sr; 0.83 (0.09) 0.8-1 (0.06) 0.92 (0.38) 

KOS data for April 2001: KCO data for 1111d-rebruary-;-,1arch 1999: 

ll'D data for all of2000. 

*Values an: for total (D < I 0 ~tm) aerosol. 

"i"Rood. per;onal communication. 2002. 

!Fa,r and Fa. are the submicrometcr fraction<. of aerosol scattering 

and absorption. rcspecti1el). 

emissions. 11 hi ch were high in black carbon and. 

periodically. dust and had undergone little cloud processing. 

The strong inversion layer present during the INDOEX 

sampling at Kaashidhoo pre,ented significant processing of 

the aerosol in the boundar) layer. 11 hereas the frontal 

systems present during ACE-Asia promoted strong 'ertical 

mixing between th e boundary laye r and lower free 

troposphere and hence faster aerosol cloud processing. The 

similarit) of the _/(RH) 1alues at KCO and BND is most 

likel) coincidental and not from a similar aerosol 

composttton. Finally. at all three sites. the absorbing 

aerosol was concentrated in the submicromcter aerosol. as 

suggested by the high 1alues of the submicrometer fraction 

of absorbing aerosol (Table 3.6 ). I I owe\ er. Kosan and 

Kaashidhoo had lower values of the submicrometer fraction 

of scattering aerosol than Bomh il le. most likely due to the 

presence of seasalt and or dust at those 1110 sites. 

The sunpholometers gi,·c a measure of the direct solar 

irradiance in se\en narro11 band wa\'elength channels. 

Preliminary data from these instruments (screened for 

clouds) gi\'c a measure of the AOD. On clays with the 

highest pollution. the AOD for 500-nm radiation 11as as 

high as 0. 7. and on days \\ ith clean marine air the 1 aluc 

dropped to a lo\\ ofO.I. During the major dust e1ent from 

DOY I 0 I to I 04 the AOD was 0.-15 to 0. 7, indicat ing 

relati\ely low sunlight levels from a hea1y loading of 

aerosol. Figure 3.12 sho11 s both the i\OD at 500 nm 

and the aerosol Angstrom e:-.ponent, a measure of the 

aerosol size, for a 3-mo period from March 31 to Jul) 9. 

200 I, at Kosan. 

Systematic Variation of Aernwl Optical Properties 

Aerosol optical properties measured 0\ er se\'eral years at 

BND, SGP. WSA, and 13R\V ha\e been analy7cd to 

determine the importance of the 1ariability in aerosol 

optical properties to direct aerosol radiati\e forcing 

calculations and to in\ estigate 11 hcther systematic 

relationships ex ist bet11 een 1 arious aerosol optical 

properties. i.e .. Gar· w0 • b. a. and aerosol radiati1 e forcing 

(t1F o), and the amount of aerosol present (measured as O,rl· 

Systematic relationships among aerosol properties can be used 

lo check for consistency among measured and modeled 

000 

-040 

04 ·120 

00 ·160 

90 110 130 150 170 190 

Day of year. 2001 

Fi g. 3.12. Aerosol optical depth measured at 500 nm and aerosol 

Angstrom e'ponent from the -112 862-nm 11 a1 elcngth pair. \larch 

31-Jul) 9. 200 I. at Kosan. 
climatologies. Also. systematic relationships can be used in 

model parameteriLation to reduce uncertainties resulting from 

insufficient kno" ledge of aerosol properties. The performance 

of different models can be ernluated "ith measurements. and if 

models predict the parameters that arc obscr\'ed. the 

measureme111s can be used to rnlidate the models. 

Kno\\ ledge concerning systematic relationships among 

aerosol properties can be useful in reducing uncenai111ies in 

remote)) sensed data because the) can be used to make belier 

9 

8 

-

E 

::?. 7 

c 

·~6 

:t 

Q) 

85 

c 

0 

'e-4 

0 

<fl 

.D 

-:: 3 .r: 

Ol 

:.J 

c2 

ro 

Q) 

::?. 

-.-BND - • · SGP ·· +·· WSA - •· BRW 

Maximum Standard Error 

BND: 0.26 SGP: 0.32 

WSA 0.29 BRW: 0.09 

... 

• • 

.. ·:..-.. -· =-·• -•-.•/ _ .... -.-......... ,,, .. ,,... .+· 

/ " .+· / .. ,• .+·" 

(a) 

1 / .. . • ... -.. . +' -.. .... ..... .... 

0 • 

0 ~ ~ ~ w 100 1~ 140 

Light Scattering Coefficient (Mm·') 

____.__ BND - e- SGP · · + · · WSA - • · BRW 

0.17 

Maximum Standard Error (c) 

c 0.16 BND: 0.0008 SGP: 0.0014 0 

tl WSA: 0.0010 BRW: 0.0008 ~ u. 0.15 

~ 

iii 

u 0.14 <fl 

'°"' u .. \ ro \ co 0.13 • • ,!,1 

Q; ' .r: 0.12 ... .. a. ' <fl • ····•· 

• . E 

' Q) ····'-'*·· I 0.11 c 

Q) 

ro ...... .. I ::?. 0.10 • ............ •••••••••• .... ....... 0.09 

0 20 40 60 80 100 120 140 

Light Scattering Coefficient (Mm'') 

assumptions about unkno"n aerosol properties. Remer and 

l\a11/i11a11 [ 1998) illustrated the importance of using a dynamic 

model where aerosol properties 1 ary with aerosol load for the 

in1ersion of remote sensi ng data. The reason to use a dynamic 

aerosol model is to represent systematic changes in one aerosol 

propert) as another propert) changes. Because of their 

importance and usefulness. systematic relationships among 

aerosol optical properties were irn-estigated at the four surface 

sites. Figure 3.13 shows systematic relationships among lo\\· 

1.00 

0.98 

0 

'O 

~ 0.96 

~ 

Ol 

c 0.94 ·~ 

~ 

~ 0.92 

di 

O> 

~ 0.90 

c 

ro 

~ 0.88 

0.86 

0.84 

-21 

-22 

N 

E 

~ -23 >. 

u 

c 

Q) 

·c:; 

~ -24 

Ol 

c 

·~ 

~ -25 c 

ro 

Q) 

"2 

-26 

-27 

____.__ BND - •- SGP · · + · · WSA - • · BRW 

•••••• • 

. ... ..... I ~ ............. :* .' 

• . ............ ,,.:e- .... .. .. .. ..... •.. / ...... • / 

" I 

• 

/ 

• 

Maximum Standard Error 

BND: 0.003 SGP: 0.002 

WSA: 0.002 BRW: 0.002 

{b) 

0 20 40 60 80 100 120 140 

Light Scattering Coefficient (Mm. 1

) 

--.- BND - e- SGP .. + .. WSA - • · BRW 

I I 

I I 

• 

Maximum Standard Error 

BND: 0.24 SGP: 0.17 

WSA: 0.19 BRW: 0.13 

.... _. .......... _.. .....

.. ... " . .. . .... :-f'. ·•·· ' \ _.,,, ...•. . I ·i· ..~ ... ... 

0 20 40 60 80 100 120 140 

Light Scattering Coefficient (Mm.

1

) 

(d) 

Fig. 3.13. (a) \lean aer,)sOI light absorption coetlicien1 (a .). (b) mean single-,ca11ering albedo (<Q). (c) mean hemi;,phcric backsca11er fracrion (b). and (d) 

mean forcmg dfa:1cm:) (J.F 0). all \Cr,us the aerosol light scanering coetlic1e111 (a.,). for BND. SGP. \\'SA. and BR\\. Plots are ba>ed on all \alid houri~ 

a\eraged aerosol measuremems (>50°0 I-min data \\ithin 1he hour) for s~slcm;, \\ilh TSI 3563 ncphclomcler>. TI1e mean \alues \\Crc calculmed m·er 10-

l\ Inf a,.. bins. TI1c ma\111111111 >landard error (sample standard de' iation square root of 1hc number of poi ms) al each 'lat ion i> gi,cn in th.: lC\l bO\cs. 

65 
relati\<! hu1111dit) (<40°-o). aerosol op11cal properties (<Jw 

cu.,. b. and t:.F 8). and the aerosol load (measured as a," al 

550-nm \\a\ckngth). The mean aerosol optical properties 

\\ere calculated O\cr <J,r intenals of 10 i\lni"1. and the 

corresponding ma\lmum standard error for each station is 

gi\ en in the graph. The standard errors are considerably 

smaller than the changes O\ er I 0-;\.1 m 1 bins. ''hi ch implies 

a high le,el of significann: lo the relationships. The a .r 

does not increase as rapidly as the <J,r. resulting in a 

systemati c increase in w,, as <J,r increases al all four 

stations. All four stations also sho\\ a systematic decrease 

in h as <J,r increases. In terms of iJ.F 8. the relationship 

bel\\ecn band <J,r acb 10 offset the rcla1i0nship bel\\'ecn cv,, 

and <Jw The h-<J,r relationship results in a decrease in the 

magniwde of th.: J.F o as <J,r increases. \\ hilc the <V, -<J,r 

relationship results 1n an mcrease in the magnitude of the 

D.F o as <J,r increases. For SGP and \\SA. the b-<J,r 

relationship ts more important and results in a decrease in 

the magnitude of D.F'o as <J,r increases. For BND. the w,,-

<J,r relationship is more important for <J,r kss than 40 Mni"1 

and results in an increase 1n the magnitude of D.F o as <J,r 

increases: hO\\C\er abO\c 40 :1.1m·1

. the b-<J,,. relationship 1s 

more importalll and resulh in a decrease in the magnitude 

of J.F o as <J,r increases. Similar!) al BR\\. the rclati\ c 

importance of one relaltonship compared '' 11h the other 

determines ho\1 .:c.F·8 changes as a,P increases. 

Figure 3.14 illustrates two systemati c relationships. one 

bCl\\'een o and <J,r and the other bcl\\Ccn submicrometcr 

scallcring fraction R,r and a. The strong relationship 

bel\\'cen R,r and a 1nd1cates that a is scnstll\C to changes 1n 

the rclati\e amount ofsubmicromctcr scatterirll! aerosol. Al 

B'\D and SGP ct decreases as <J,r drop-, bel~'' 30 :--1111· 1

. 

'' hereas at \\Si\ and BR\\' a increases as <J,r drops belO\\ 

30 i\tm·' (Figure 3.14a). AbO\e 30 \Im all four stations 

shO\\ a fair!) constant ci '' ith increa-,ing <J,r· This 

systemati c relationship suggests that during lo\1 aerosol 

concentration c\ cllls. the continental sites ( BND and SGP) 

ha\e more relati\CI) larger particles present. '' hile the 

marine sites (\\'SA and BR\\') ha\e more rclati\el) sma ller 

particles present. The u-<J,r relationship at BND and SGP is 

consistent with the relationship bet'' cen the Angstrom 

e\poncnl and aerosol optical thi ckness (dcri,cd from 

Sun 'sk) scanning spectral radiometer measurements) for the 

mid-1\tlamic region of the eastern United Stales [Remer and 

Ka11/i11a11. 1998]. It is interesting lo note that ''hi le the u-

<J,r relationship is different bet\\'ccn SG P and WSA. the 

::,.F 'o-a,r relationship is 'cry similar. This suggests that the 

J.F 'o-<J,r relationship 1s not inlluenced b) changes in the 

submicrometcr to total aerosol fraction but rather b) 

changes in the submicromeler aerosol s11c distribution (h-

<J,r relationship) and the aerosol composition (tu, -a,r 

relationship). 

Systematic relationships e'\isl bel\\ ccn \ arious aerosol 

properties (<JJp• rv,,. h, D.Fo, and a) and <J,r nnd also bet1,een 

ct and submicromcter scauering fraction R,r (Figure 3.14b). 

These systematic relationships arc qualital i\ely similar 

among th e four stations: ho\\ c\ er, the quami1a1i\ e 

rela1ionships arc d1ffcrcn1 at each station. \\'hich is 

1ndicati'e of the occurrence of di fferent aerosol types and 

si7c distribution'> al each station. S) stcmatic relationships 

66 

2.2 

2.0 

1.8 

c 

Q) 

c 

8.. 1.6 x 

w 

E 

e 

iii 

Ol 

c 

-:! 

c 

Cll 

Q) 

~ 

Q 

ro 

a:: 

Ol 

c 

1.4 

1.2 

1.0 

0.8 

0.6 

1.0 

0.8 

~ 0.6 

rl 

(/) 

E 

..6 04 ::l 

!/) 

c 

Cll 

Q) 

~ 

0.2 

00 

-BND .. . .. SGP .. ... WSA -•· BRW 

·•··• .. 

.............. .... ..... 

• 

• 

Maximum Standard Error 

BND. 0.02 SGP: 0.06 

WSA: 0.03 BRW: 0.02 

• 

I 

• '· ·. I 

I .•. .. I • 

It. • . •. . :< :. -.. . ... .. .•. 

0 20 40 60 80 100 120 140 

Light Scattering Coefficient (Mm 1

) 

-.-BND • SGP + WSA • BRW 

- . • 

(a) 

(b) 

• • • 

• 

• 

• 

00 0.5 

• 

1.0 

• • 

• 

• 

• 

• 

Maximum Standard Error 

BND: 0.008 SGP· 0 015 

WSA 0.020 BRW: 0.015 

1.5 2.0 25 

Angstrom Exponent 

3.0 

I 1g. J.14. (a) \kan \ngstri;m e\poncnt (a) 'cr·rns aerosol light 

sca11ering coeflicicm (O ,) and (b) submicromcter scallering 

fraction tR,r) 'crsus \ngstr(im c\poncnt. for B'- D. SGP. \\'Sr\. 

and BR\\. Plots arc based on all 1alid houri) a1craged aerosol 

n11:asurcmcn1s t >50°0 l-1111n data 1111hin the hour) for systc1m 11 ith 

T'i I 3563 nephelo1m:1e rs. The " 1 alues 11 ere.: ca lcu latc.:d 01 er I 0-

\ Im a. bins. and the mean R 11as cakula1c.:d from 0.::>5"'\ 

e'\pom:lll bin>. The ma\imum standard error (sample standard 

de1 i;111on -,quarc root of the number of poi111s) al each station ,., 

g11 en 111 the te:-1 bo\C,. 
and the regional. yearly. week I). and dail) \ilflations 111 

optical properties can be used 10 check for cons1stcnq 

bet\\ ccn climatologies based eitha on obsen at ions or 

models. The e\ist.::ncc of S)Stematic changes in aerosol 

optical propcrtie;. '' ith changes in aerosol conce111ra11on 

indicate that care should be taken "hen us111g a' erage 

\alues 111 algorithms to retrien: aerosol properties. such as 

opti cal depth. rrom satellite data. An algorithm that uses a 

static representati on for aerosol optical properties "ill h:l\ e 

a systematic bias in deri\ ed rnlucs. 

3.2. SOL.\I~ A '\'D ll ER~L\L AT\IOSl'll ERIC 

RADIATIO'\ 

B Bollll.11'\I ([L>JIOK). G. \'\DrRSO'\. G. ( IRBIU1ll. I· Dl 1 Jo'\. 

B. 11 I I. I I R. D. J It f..SO'\. D. LO\l,J \It f..rR. D. '\J I ~O\. 

R. SJO'\I. R. Tin SKll. \'\)}'\. \\'OOJl 

3.2.1. RADL\TIO:\ :\IEASliRE\IE:'\TS 

l11trod11cti1111 

The C\I D L Solar and Thermal Atmospheric Rad1a11011 

(ST \RJ project pro1 ides support mg 111tim11a11011 for 

baseline cl1111ate monitoring ac1i1 ili.::s and i1l\ estigates 

trends and 'ariations in the obsened surface radia11011 

budget. L:nerg) associated" ith the l::arth·s radia11011 budget 

is not only responsible for maintaining the thermal state or 

the planet but also causes atmospheric and oceanic motions. 

l::xpectcd trends in surface radialion quantities at globall) 

remote sites caused b) anthropogenic acti111ies are near or 

bel011 the le' el of detectabi lit). on the decadal 11me scale. 

I lowc1 er. there arc gaps in lhe !..no\\ ledge of basic 

climatological 1ariabili1y in the global surface radia11on 

budget such that STAR mcasuremcnls can c:on1nb11le 10 a 

rundamental understanding of atmosphenc and cl11natolog1cal processes. These contributions include delln11ion of 

diurnal and annual cycles and eftects of cloudiness. actual 

\ar1a11011 on daily to decadal 11mc scales. major 1olcanic 

eruptions. une\pectedly high concentrations of 

anthropogenic pollution in the ,\retie. cons111uen1 \ anations 

on narrtl\\ band 1rradiancc (e.g .. OLOlh~ and ultr<l\ 1olc1 ( L \') 

changes). and possible anthropogenic modilication to 

cloud1nes-.. The ST AR group also makes remote sensing 

measurements of \'arious atmospheric constituents that arc 

potcnt1all) responsible for \ ariations in surface rad1at1011 

quantities. pan icularl) aerosol optical depth. In addition 10 

the research conducted by Ci\IDL and the locall} 

maintained data archi1 cs. ST,\R measurements contnhutc to 

sci era I global databases. Databases that arc global in 

e\lcnt arc needed 10 e1 aluatc radiation and en erg} budgets 

Ill diagnoses or the climate. STAR obsenations also 

contnbute 10 satellite-based projects by helping 1 en f) po1111 

estimates and thereby allo" 1ng in ten cning rcaturcs of the 

atmosphere 10 be deduced. 

i\ nw_1or goal of the monitoring program 1s to obtain a 

record of surface radiation parameters that 1s as long and 

complete as possible and that can be c\am1ned for all scale;. 

of natural and modi lied 1 ariabilit). Of particular intere-,1 is 

lhe dc1erm111a1ion of the magnitude. representatneness. and 

possible consequences of any obsen cd change-,. ro this 

end. the ST,\R group maintains continuous surface 

67 

radiation budget obscn allons at se1 era I globall) di1 crse 

sitt:s. along "ith 'arious ancil lar) obscn·a11ons. The 

folio\\ ing describes those projects and changes since the 

pre1 ious C.\/DL 511111111111:1 Repon f Sc/111ell e1 al .. 200 I]. 

B<neli11e ,\/011itori11g Site\ 

Surface radiation measurements ha\ e been made at the 

four principal Ci\IDL baseline obscnatories (BR\\'. i\ILO. 

S\10. and SPO) since the mid- I 970s. \\ ith some 

measurement series going back 10 1957. The different 

en1 iron men ts and obscn ing cond i11 ons at the sites resulted 

in sume11 hat different measuremen t programs e\ oh ing at 

each site. The basic measurements made at all 'iites include 

the do\1 nward components o f solar radiation: global. 

diffuse. and direct. Broadband thermal infrared (IR) 

irradiance measurements 11cre added 01er the past 15 years. 

L.;p11 ard solar and therm:il IR are measured at sites \\here 

the surrounding terrain is rcprcsentati\ e of a larger regional 

area. such as at SPO and BR\\. for at least pan of the ) car. 

The records acquired at thcsc sites constilllte some of the 

longest kno\\ n series :n·ailable by the Lnited States for 

solar radiation research. The ra\\ data are routine!) 

1ransmi11ed from the field s11cs 01 er telephone Imes or the 

Internet 10 the cenllal data processing facilit) in Boulder. 

"here data editing. linal cal1bra1ions. graphical mspcction. 

and archi' ing arc perrormecl. as discussed in section 3.2.9. 

Other Meas11re111e11t Sites 

Boulder Atmospheric Ob.l'erwlfory (BAO Tower). Obser1ations of up\\'elling and do\\ nwelling solar and thermal 

1rradiances began in 19h5 at the top of a 300-m-tall IO\\Cr. 

kno\\11 as the Boulder Atmospheric Obsen ator~ (BAO). 

"h1ch 1s located near l::rie, Colorado. '\early continuous 

obsenations of these quantities \\Cre made \\ith houri) 

resolution until 1992. 3-min resolution until 1998. and lm1n resolution 1hcrcar1cr. Tin. up1\ clling data pro' idc a 

unique 'ie\\ of surrounding agricultural land. making the 

data more reprcsentati\ e than I) pica I surface-based solar 

radiation budget obsenauons. This s11e has cnntnbuted 

data to the \\'orld Climate Rcsearc.:h Program (\\'CRPJ 

Baseline Surface Radiation !\ct\\ork (ASR'\). Applications 

of data from this site "ere described 111 the 19%-1999. and 

earlier. C.\IDL S11111111e11:1· Reports [e.g .. Sc/111ell el al .. 20011. 

Since 1990. obscn at ions or direct solar and do\\ nwclling 

solar irracliances ha\ c also been madc near the base of the 

IO\I er. i\lcasurcmcnts of acrosol optical depth 11 ere added 

in the past 2 years. as \\Crc ohscnations of the direct solar 

beam \\ ith an all-\\·cather absolute ca1 ii) radiometer. 

Kll'ajalei11. Ohscn at ions of direct solar and do\\ 11\\·elling 

solar and thermal IR irracliance be1rnn on K\\ajalein in 1989. 

K"ajalcin is a small. < -t-km~. isla~1d in the tropical \\Cstern 

Pacific. Data obtained at this location arc 1 irtually free of 

an) ertects of the island and therefore arc often taken as 

rcpresematiYc of the open ocean 111 that regwn. Data from 

K\1ajalcin ha\e been used as ol'.ean1c repre,entatnc b} 

01111011 [1993). fl'hi1lock I!/ al. [1995). and Bishop el al. 

[ 1997). and arc currellll) be111g used b) the Cloud and 

Earth's Radiant Energ) S)stem (CLRl-.S) and the l::uropean 

Centre for :'lledium-Rangc \\ cather l·ort:cash (FCi\l\\'F) 

global circulation model (GC\I). <\ub-,1a111ial upgrades to 

the K\1ajalein radiation measurements 11c1-c carried out 
in the past 2 years because a corrosive marine environment 

requires that much attention be g i,en to the instrumentation. 

The Kwajalcin si te is a panicipant in the BS RN program 

and receives 111ueh of its fundin g from the Natio nal 

Aeronautics and Space Administration (NASA), which ha s a 

large interest in CMD L's radiation 111ea-suremen t activities 

in general. 

The inst allation of a new permanent stairway to the 

Kwajale in measurement platform was completed. new 

tables for sensors and the solar tracker were constructed. 

and all equip111e nt was re located during August 2000. 

Bermuda. Observations of downwelling solar and 

thermal JR began at the NASA Tracking Station at th e east 

e nd o f Bermuda in 1990. The rather small size and low 

relief of t his island , located in the lower midlatitude 

westerlies. has minimal innuence o n the irradiancc measu rements. although some c louds of orographi c origin arc 

known to exist there in the summer months under certa in 

synoptic meteoro log ical cond ition s. Data from Bermuda 

ha ve been submitt ed to the BSRN data archive and we re 

used by Whillock e1 al. [ 1995] and Bishop el al. [ 1997]. and 

currentl y b y the CERES program in satellit e comparison 

and validation stud ies and b y ECMWF and Geophysical 

Fluid Dynamics Laboratory (GFDL) in their GCM testing. 

The monitoring site was 111oved in 1998 from the NASA 

Tracking Station (32.2670°N. 64.6670°\V) near the east end 

of the island to the top of Prospect Hill near th e center of 

the island (32.3009°N, 64. 7659°\V). The site is ably tended 

by the Bermuda Biological Station for Research and is also 

funded largely by NASA. 

Basic il1eas11re111e11ts 

Broadban d irradiance. The basic broadband measurements c urrently conducted at each o f the four baseline 

observatori es for the past 26 yea rs include nor111al direct 

and downward broadband solar irradiance and downwa rd 

solar irradiance in the 0.28-μ111 to 2.8-μm band. Downward 

broadband thermal irradi ance 111easure111ents were added 

at a ll sites in 111ore recent years as well as upwelling 

irradiance 111easure111ents at SPO and BR \V. The current suit e 

of measurements at all sites is shown in Table 3.7. Data are 

sampled at I Hz with I-min averages recorded on computer 

media. Preliminary data from all CMDL radiati on sites are 

generally available. graphi cally. within a couple of days of 

acquisition in the Radiation section of the CM DL web site. 

and subsequently as descri bed in sect ion 3.2.9. The Ci\JDL 

S11111111a1:r Report for 1998- 1999 [ Sch11ell et al .. 2001: page 

59] shows different example sum111ari es of the 24-yr record of 

total solar irradiance collected at SMO using the single 

pyranomctcr technique. 

Filter wh eel NIP. The wideband spectral direct solar 

irradiance measurements are made w ith a filter wheel 

normal incidence pyrhcliometcr ( F\V N lP). One of the 

appl ications of these data is to compare them with a highspectral-resolutio n radiative transfer model [Bird and 

Riordan. 1986] that is based on Beer's law and is intended 

for use at the surface only. Th e aerosol optical depth and 

precipitable wa ter arc adjusted within the mod el to obtain 

the best mat ch with the FWN IP obsen <1l ions. This provides 

a low-precision but relati ve ly stable estimate of mean 

visible aerosol optical d epth and water vapo r at the four 

baseline observatories. The accuracy of the method for 

obtaining aerosol optical depth and water vapor is li111ited 

by the dependence on the absolut e values of the extraterrestrial solar spectrum and instrument calibration. unlike 

o ther typical applications in sunphotometry. The updated 

d ata records from these observa tions are shown in Figure 

3.15 through near the end of2001. The accuracy of the data 

is on the order of 0.03 opti cal depth units. or abo ut 2 lo 3 

times poo rer th an sun photometer-derived val ues and should 

only be used when sunphotometer-derived d ata are not 

a vailable. 

MLO apparent tra11 s111issio11. The transmission for direct 

broadband solar irradiance through the at111ospherc abo\'c 

M LO is monitored as a quantit y known as the apparent 

transmission. This qua ntity is comput ed as the average 

TABLE 3.7. Measurement T ypes Made at Each Station. 2000-200 I 

BR\V Bennuda BAO f\I LO 

Broadband lrradia11ce (11111i/ orhenrise 110/ed) 

Direct solar beam x x x x 

Diffuse solar x x x x 

Total dO\\ n\\'ard solar x x x x 

Reflected solar x x 

Downward IR x x x x 

Upward IR x x 

01/ier .\leas11re111e111s 

Spectral optical depth x x x x 

All-sky d igital imagery x x 

UV-B x x x x 

High-resolution spectral UV x• x 

Wideband direct solar irradiance (F\VNIP) x x 

x 

x 

x 

x 

x 

x 

St-.10 

x 

x 

x 

x 

x 

S PO 

x 

x 

x 

x 

x 

x 

x 

x 

BR\V. Barro\\'. Alaska: BAO. Boulder Atmospheric Observatory (Erie. Colorado): l\I LO. 1\ launa Loa. llawaii: SMO. American Samoa: S PO. Soulh 

Pole. Antarctica. 

* lnstrnmcnl localed in Boulder about 16 km wesl of BAO. 

68 
0.30 

0.25 

0.20 

..c: 

c. 0.15 

a.> 

0 

ca 0.10 

(J 

+:; 

a. 0.05 

0 

0.00 

-0.05 

-0.10 

1976 

BRN M...O 

1981 1986 1991 1996 2001 

Veer 

Fig. 3.1 5. Aerosol optical depth anomalies, monthly averages from wideband filt er wheel NIP estimates. 

of three s uccessive ratios of direct sola r irradi ance, where 

each ratio is the quotient of the irradiance at an integer 

airmass divided by the irradiance at the next smaller integer 

airmass. as first de fined by Ellis and Pueschel [ 197 1 ). The 

apparent transmission measurement is inherently stable over 

time because it is independent o f a radiometer calibration 

va lue and is therefore also quite sensitive to small changes 

in transmission that can be due to aeroso ls, ozone, or water 

vapor. 

S tudies by Bod/wine et al. [ 198 1] and D111ton et al. 

( 1985] have shown that aerosols tend to dominate observed 

changes in the monthl y a ve rages of apparent tra nsmission 

such that the majo r observed excursions in the record, 

shown in Fig ure 3.16. are due to aerosols. The major 

observable features in Figure 3. 16 are the effects of several 

volcanoes. particularly Agung in 1963, El Chi ch6 n in 1982, 

and Pinatubo in 199 1, and an annua l osc illation caused 

primarily by the springtime transpo rt of Asian dust aerosol 

over the site [Bod//(/ine et al., 198 1 ]. Figure 3. 16 is 

complet e through 200 I and shows that the recovery from 

the eruption o f Mt. Pinatubo required several years. The 

fact that the Mauna Loa apparent transmission record took 

several years to recover from Pinatubo is evidence of the 

sensiti vity of the measurement , because it is known from 

other measurements by CMDL and others that the optical 

depth of Pinatubo in 1995 was already ve ry low, on the 

order of 0.005 a t 500 nm. Dutton and Bod/wine (200 I] 

have used the M LO transmission record to deduce the 

max imum possible change in certai n solar radiation budget 

quantities that could have occurred over the length of the 

record. The long-term atmospheric transmission was con69 

g 

~ 088 

~ g 086 

~ 

084 

082 

• t.\ontht/A~ 

l - &-month rumng meW\ 

08'-~~~~~~~~~~~~~~~~~~~~-' 

1958 1963 1968 1973 1978 1983 1988 1993 1998 

Year 

Fig. 3.16. Apparent solar transmission observed at l\1auna Loa. 

vc rted to net solar irradiance at MLO by comparison to 

more recent accurate measurements of surface irradianee. 

and assumptions about the constancy of underl ying 

renectivity and extraterrestrial solar irradiance. The 42-

yea r time series o f the deduced net solar irradianee at the 

level of M LO is shown in Figure 3 .17 [DI// ton and 

Bod/wine, 2001]. The maximum sustained solar radiative 

forcing from varying atmospheric transmission over Mauna 

Loa, determined from deduced net solar irradiance c hanges 

at 3.4 km above sea level (ASL), was less than - 0.3 W nf2 

over the last 40 yea rs. In other words, the o nly linear trend 

that could have existed in net sola r irradiance at the level of 

Mauna Loa but no t have been detected would be between 0 

W m·

2 and - 0.075 W 111·

2 per decade, thereby also 

e liminating the possibi lity o f any positive tre nd. This work 
.;- 2 2 

E 0 0 

~ ·2 VI 

. SI -4 -4 ftj 

§ ~ ~ c 

~ 

"' .a .a -~ e ~ ·10 8 -10 

/}_ -12 -12 

~ ·14 -14 

58 63 68 73 78 83 88 93 98 

Year (·1900) 

I ig. 3.17. !'\et solar 1rradiance \ariation; at the height of \launa Loa 

because of diangcs in atmospheric transmis>ion o\·er i\ launa Loa. 

pro\ ides a longer histor) nnd more nccurate determination 

of ac1t1al obsen ed 'nrintions in radiati\ e forcing as related 

10 potcn11al clilllrtte change than an) other kno\\"n d1rectl) 

obsen ed radiation record. 

/111pru1•e111e11ts in Diffuse Solar lrradiance Jfe11rnre111e11t~ 

Total do" n\\ el ling solar irradiance is the primary input 

component of the Enrth·s energy budget. One step 111 the 

imprO\ emenl of the instantaneous surface-based solar 

irradiance mensurelllcllls "as the BSRN recomlllcndnt ion 

for using the combinat ion of the separately mensured direct 

and diffuse irradinnce. "hi ch incorporates the high I) 

accurate direct bealll llleasurclllcn1 capabi liti es de\cloped 

O\ er the past four decades and greatly reduces the cosine 

response error inherent in the single-instrument fln1-pln1e 

recei' er or the p) ranometcr. This lllethod of measuring 

total solnr irradiance led 10 impron:ments discussed by 

0'111111ra el al. [ 1998]. 8111'1 el al. [ 1999]. and .\liclwlsky el 

111. [ 1999]. This rccommendntion lrns plnct:d ne\\ requirclllcnts on the nt:cessar) documented nccuracy of diffuse 

measurements. Although accttraC) specifications for direct 

solar irradinncc are rather easil) determined. there are 

difficulties for the diffuse component because no relerence 

standards exist. This has resulted in some recent 

modifications in the \\"a) in \\ hich STAR is making diffuse 

1rradiance measurements. both in the type of instruments 

used and the ndjus1men1s for therlllal offsets induced in 

certa in diffuse p) ranomelers. The specifics of ne"· diffuse 

solar measurements and adjustments 10 older data arc gi,·en 

b) 01111011 el 111. (200 I]. \\ ith thest: changes. 11 is esllrnatcd 

that diffuse irradiance is currcnth measured 10 "ithin about 

5 W nf~. This results in accuracies 10 within about 8 \V m·2 

for total solar 1rradiance 1\ hen determined from the 

combined diffuse and direct mt:asurements. STAR is 

in\'ohed in ongoing national and in1crna1ional efforts 10 

promote the de\ elopmcnl or international reference 

standards and further imprO\ e the absolute accurac) of solar 

diffuse measurements. 

Each CMDL BSRN site 1\as also equ ipped 10 monitor 

diffuse sk) radiation "ith a tracking-disk-shaded black and 

\\ hite pyranomc1er 10 augment the diffuse sk) 

mcasureme111s made with singlc-black-de1ector-l) pe 

70 

p) ranometers. The addition of pyranometers with black and 

\\ hite detectors enables more thorough monitoring of Lerooffset effects. Solar trackers nt each site \\ere modified 10 

t:nable installation or the additional shaded blac" and \\ hite 

detector p) ranomeicrs . 

Thermal IR Irrndi1111ce ,Heas11re111e11t /111p ro1•e111e11ts 

Although there ha1c been subs1an1ial reduc ti ons in the 

uncertaint) of thermnl IR measurements in the past I 0 

years. from near!) ~ 30 \\' m ~ in the late 1980s 10 about ~ 5 

\\' 111·2 no" (based on experiences in Ci\IDL and clse11 here). 

there still appears 10 be room for further imprO\ emenls and 

the po1en1ial for the establishment of a measurement 

reference standard. o, er the past 2 years. ST AR has 

become in\'olved in the efforts of BSRN and the World 

Radiation Center (\\/RC) in Da,os. S1,itzcrland. 10 \\Ork 

lO\\ ard these potential imprO\ ements. This wor" is th rough 

the establlshmelll of ne\\ radiance measurement cnpabilitics 

that rel) on absolute. self-calibrating. sky-scanning 

instruments that could C\ cntually determine a "orld 

reference group similar 10 that used 10 es1abl1sh the \\oriel 

Radiometric Reference (\VRR) for solar direct beam 

obscnations. C\IDL. \1or"1ng with BSRN. hclpt:d orgnni/c 

and par11cipa1ed 111 the International P) rgeometer and 

Absolute Sk) -scnnning Radiometer Comparisons (IP ,\SRC1 and 11 ). in the central United States during September 

1998 and in the •\retie at Barro\1 during \larch 200 I. 

rcspecti,ely. \\here this process 10 establish such 

capabiliti es and reference slandnrds began [Pliilipo11a el al .. 

1998]. 1 he results of the first of these comparisons and the 

operation of the s"y scanner suggest thnt an absolute 

longwa\ e 1rradiancc measurement made rout incl) m the 

field can achie' c the accurac) of c lose 10 ± 1-2 \V m·2 

[Pliilipo11a el al .. 200 I]. 

3.2.2. BASELL\E Sl'RFACE RAD IATIO:'\ :\'E r\\ORK 

The STAR group has the prinrnr) management role in 

BSRN nnd has cnrried out the duties of International Project 

Manager for the past 7 years. BSRN is intended not onl) 10 

suppl) the in1erna11onal elinrnie resenrch communit) "ith 

the best possible surface irradiance data from a globall) and 

clima1ologieally di\erse long-term network. but also to keep 

nd1 ancing the state of the art in impro' ements or those 

measurements so that research uses of 1hc dnta cnn continue 

to be C"\panded. Support of the U.S. BSR0. program comes 

from sc,cral agencies. l\OAA Nnt ional Weather Sen ice 

('\1\\'S). NOAA Oceanic and Atmospheric Rt:st:areh (OAR). 

NASA. and the L...S. Department of Encrg) Atmospheric 

Radiation i\1ensurement (DOE, AR\ I), and is funded 

in1erna1ionnll) by more than 15 participating countries that 

operate surface BSR'\ stations and contribute lechnicnl 

e.\pcrts to the group·s effort~. The BSR:-.: data arc being 

utilized 111 major sa1elli1c and GCM research programs 

mentioned earlier. The program \\"as concei' eel in 1988. 

began operations in 1992. and ts intended 10 operate 

indefinitely until there arc no further cx1cnsi' c research 

needs for such data. Acti' itics or BSRN are further 

summari1cd b) Oh11111ra el al [ 1998]. The BSRN program 

is part of \\ CRP and the Global Energy and \\ ater Cycle 

E:-.pcriment (GE\v EX). 
3.2.3. SOLAR RADIATIO:--: CA LIBRATIO'> FACILITY 

SR F Radiometric Standards A ctii1ity 

Self-calibrating ca' ity radiometers (referred to as 

cavit ies) arc the basic references for all CM DL broadband 

solar radiation mea surements. Long-term performance of 

the se sensors is checked and documented through reg ular 

comparison s with peer ca\ ities from other pri\'ate and 

pub I ic sector groups and agencies as \\'Cll as other countries. 

Also, the CMDL reference cavities are periodicall y 

compared \\'ith the World Standard Group (WSG) 

radiometers that are kept al the World Radiation Center in 

Da rns, Switzerland. NOAA has participated in these 

periodic co mparisons since they began more than 30 yea rs 

auo. These International Pyrhel iometer Comparisons (I PCs) 

a;.e sponsored by the World Meteorological Organization 

(\\IMO). The most recent intcrcomparison. IPC IX. was 

conducted at the World Radiatio n Center in Da\'OS from 

September 25 to October 13, 2000. CM DL. as a WMO 

Reg ion IV radiation center. participated in the comparison 

\\'ith three NOAA Solar Radiatio n Facility (SRF) cavities. 

TM 167502. AH F28553. and A \\'X32448. The SRF 

reference ca,·1t1cs were compared with the \\ISG 

radiometers, and ratios o f measurements from these ca1 ity 

radiometers to the World Radiation Reference (\\/RR) were 

established. The ratios for the three SRF references that 

participated in IPC IX are listed in Table 3.8. Res ults of 

recent annual comparisons o fCMDL reference caYities with 

peer ca' ities at the National Renewable Energy Laboratory 

(NREL) in Golden, Colorado, are also listed. The NREL 

p) rhcliometer comparisons (/\PCs) fH01·ide an annual check 

o f the NOAA rel'erences with NRE L references. 

SR F Special Projects 

A self-cal ibrating ea1 ity radiometer equipped 11 ith a 

calcium Ouoride window was deployed at the Cl\I DL BAO 

BSRN site in Auuust 2000 and has operated continuously 

since installation.- Additional installations at o ther CMDL 

BSRN sites are pl anned. Other special projects during the 

2000-2001 period inc luded a comparison of a CMDL 

reference radiometer with refere nce radiometers of the 

Australian Bureau of Meteorology during May 2000. The 

comparison was conducted at Alice Springs, Australia. after 

Cl\IDL participation in the Biennial BSRN Meeting held in 

Melbourne. Austra lia, in early f\ lay 2000. SRF also 

completed speci fi cation and procurement of solar radiation 

monitoring hardware and sensors for a number of interTAB LE 3.8. Ratios of Measurements from Three SRF 

Reference CaYity Radiometers to f\ leasurements 

from WSG and Peer Radiometers, Obtained 

During Pyrheliometer Comparisons 

Pyrheliometer 

Comi:>arison T;\1167502 Al-IF 28553 A \\'X 32+18 

IPC VIII ( 1995) 0.99869 0.99756 

\:PC 1998 0.99783 

:NPC 1999 0.997.J I 1.00086 

IPC IX (2000) 0.99966 0.99733 1.00038 

\:PC 200 1 0.9970.J 1.00073 

7 1 

national projects during 2000-200 I. These projects 

included ACE-Asia. BSRN sites (Algeria, South Africa, and 

Russia). and Global Atmospheric \Vatch (GA \V) baseli ne 

si te s (Algeria, Argentina. Brazil, and Indonesia). Support 

for 1·arious Cfll DLSTAR group rield campaigns (a lbedo 

measurement. sunphotometry. ACE-Asia. and ARM) was 

also pro1·ided. A report of the SRF historical maintenance 

of radiometric references, characterization. and calibration 

of sensors used at CM DL monitoring sites \\'as published in 

March 2000 [1\'elson. 2000). Collaboration was undertaken 

with other authors on publicati ons inl'estigating p yranomcter zero-offset effects and utilization of broadband 

pyranometer data to model UV irradiances [e.g .. D1111on et 

al .. 2001]. 

3.2.4. MO'>ITORl:"G AEROSOL OPTICAL DEPTll 

BRW and SPO 

Backgro1111d. Atmospheric aerosols affect the Earth's 

radiation budget directl y through interactions with solar and 

terrestrial radiation and indirec tl y as cloud condensation 

and ic e nuclei. While the impact of aerosols is probably 

most pronoun ced downwind of midlatitude industrial 

complexes [e.g .. Charlson et al.. 1992). high-latitude 

regions are also sensiti\'c 10 1 ariations in atmospheric 

turbidity. This is especiall) true in the Arctic 11 hen 

airborne pollutants and dust from Eurasia are transported 

poleward. and \\'hercas aerosols tend to have a cooling 

effect at 1011 and middle latitudes. their radiati1·c effects are 

less certain at hi uh latitudes. The effects of high surface 

albedo in conj11n~tion with lo\\' solar angles may cause a 

wa rming instead [Cacciari et al .. 2000). The focus of the 

Cf\lDL aerosol program is to characteri ze the means, 

l'ariability, and trends of' aerosols regiona ll y. A further goa l 

is to understand the factors that control the distribution of 

aerosols and th ei r radiative properties. 

,\'eed for 111011itori11g. In 1998 the Sc icnti fie Co mmittee 

on Antarctic Research (SCA R) recognized the importance 

o f polar aerosol chara c teri zat ion and recommended the 

establishment of an international network of solar 

spectrophotometers to monitor aerosol optical depth (AOD) 

al high southern latitudes. Such a network no1v exists, and 

some- participating countri es also maintain sites in the 

Arcti c. thus prol'idin g a polar perspective. Cl\lDL has 

monitored aerosol properties at two po lar sites (BR \\I and 

S PO). since the mid- I 970s. An overl'iew of these actil'itics 

is gi,en b y Stone (2000) and references therein. Historically. ground-based in situ properti es o f aerosols ll'ere 

derived with nephelometer measurements [e.g .. Bodl/(/ine. 

1992 . 1996). In recent yea rs a strategy \\'as adopted to 

relate chemical and physical properties by means or 

simultaneous size-selecti1·e samp ling, allowing obser\'ed 

aerosol properties to be correlated with atmospheric cycles 

of specific chemical species [Og ren, 1995). In additio n. 

CMDL has monitored effecti1e l'isible (500-nm) aerosol 

optical depth at BR\\/ and SPO. The derivation utilizes data 

from p yrheliometers filled with moderately wideband filters 

[D1111011 and Christ.I" 1992). While not a precise measure. 

the Iona time series ha l'e been \aluablc for the definition of 

seasom~l cycles and for the documentation of episodi c 

perturbations caused by the presence of volcanic aerosols. 
Figure 3.18 highlights the extreme increases in 'isiblc 

clltinction at polar latitudes, which \\ere caused b) the 

eruptions of El Ch ichon and Pinatubo in 1983 and 1991. 

rcspccti\ cl). A ft er major eruptions. 'olcanic aerosols are 

dispersed globall) b) strawspheric \1 inds and then deca) 

cllponentiall). O\er polar regions. ho1\e\er. dec ay times 

tend to be longer [Sro11e er al .. 1993. 199-t]. The prolonged 

lifetime of \Olcanic aerosols at high latitudes may result 

from unusual processes that occur 1\ ithin the polar \Ortcx. 

Aerosols may persist if dynamical processes f:I\ or 

'aporiLation at high altitudes and regeneration or particles 

at 101\er altitudes [llof111c11111 and Rosen. 1987] . Also. natural 

elimination processes ma y be suppressed because mixing 

\1 ithin the polar \Ortex is minimal. A limited number of 

spectral obscn at ions of aerosol extinction at BR \V I\ ere 

used to deri\'C so me understanding of composition and siLe 

distributions of' olcanic aerosols [D11ffo11 er al .. 198-t: Sw11e 

er al .. 1993): hO\\C\er. quantifying the direct or indirect 

radiati\ e forcing by 1 olcanic aerosols is not yet possible 

because continuous obsen ational records arc lacking. 

On an annual basis. Arctic haze [D11uo11 er al .. 1989] and 

Asian dust. and occasionally smoke from forest fires. 

inlluence the BR\\' record [Sro11e. 2002]. In recent decades. 

significant \ ariability in the concentration of ha ze during 

spring at BR \\I has been obsen·ed. Bodlwi11e and Durum 

[ 1993] do cumented a dowrrn ard trend of Arctic hue during 

the 1980s 11 hen emissions of haLe-forming pol lutants in 

Eurasia may ha' e decreased. Ho,1·e, er. a dclin it i' e 

explanation for the trend ha s not been gi\ en. While 

emission rates arc certain to inlluence th e distribution of 

hue. changes in atmospheric transport ma) also be a factor. 

Atmospheric circulation in this region has undergone 

'[.25 BARROW 0 

0 

Lt) 

%20 Cl) 

c 

.15 

a 

0 

g .10 

~ 

~ Cl) .05 

> :;:: 

(J Cl) 

ffi .00 

1975 1980 1985 1990 1995 2000 2005 

YEAR 

fig. J.18. Time serie, of dli:cti1 e 1 isible aerosol optical depth ( \OD! 

deri1ed from lilt..:n:d p~Theliometric measurement> mmk at BR\\ and 

SPO. T11 o-~ear smoothed 1·alues are sho11 n to highlight the periods of 

increased \OD flillo11 ing the em pi ions of El Chichon and P111atuho. 1 he 

dashed line:. represent 1he long-1em1 a1 erage hacl.;ground cond1t 1tm~ at 

each site. 

n 

significant shifts in recent decades [Stone. 1997: Sro11e e1 

al .. 2002]. In the future. closer attention ''ill be gi\ en to 

the role of transport as it affects the c10lution of specific 

aerosol t) pes (i.e .. haLe. dust. smoke. or' olcanic). 

At SPO. intrusions of seasa lt aerosols arc obsened when 

storms reach the high plateau from surrounding oceanic 

regions [Bergin er al .. 1998: Bocllwi11e. 1992]. Although the 

direct radiati\'e impact of such aerosols can be studied 

theoretically [e.g .. Cacciari er al .. 2000]. \erilication or 

re su lts will require more continuous monitoring o f aerosols 

in conjunction \I ith mea surements of the surface radiation 

budget. The indirect effects of aerosols (i.e., their role in 

influencing cloud morpholog)) ha s yet to be ill\ estigated 

and ''ill a lso require corrclat i1 e studies using high!) 

rcso l\'cd data sets. 

Ne11• projects. To address the aforementioned needs. 

C!\IDL has enhanced its monitoring programs at BR \\I and 

SPO to include continuous measurements of spectral AOD 

during sunlit periods using photometers titted with 

narro\\ band (I 0-nm) I-in-diameter interference filters. 

Because background \alues of Arctic and Antarctic optical 

depths are small (see Figure 3. 18). the determination of 

spectral AOD at BR \V and SPO requires extraordinary care 

to produce high-quality data sets. The main features of 

the se ne\\ programs include the follO\\ ing: 

• Deployment of four-channel. sun-tracking photometers to measure extinction at nominal "a' elengths 

centered at -t 12. 500. 675. and 862 nm (368. -t 12. 

500. and 865 nm prior to July 2000). 

• One-minute acquisition of ra\1 1 oltagcs. 

• Acquisition of ancillary da ta to assure data quality. 

• Merging of photometri c data \1 ith station pressure 

and temperature to account for Ra) lei gh scattering 

using the method of Bncllwi11e er al. [ 1999]. and IO 

correct airmass for refraction at lo\\ solar angles. 

• Thermal!) controlling instruments to \I ithin ± 1°C of 

established set points to assure tilter stability and 

longc,·ity. 

• Merging of daily OLOne and l\O: data to account for 

absorpt io n by the se constituents. 

• Performing pre- and post-season ca librations at 

1\1 LO. with the Lang le) method. to document and 

correct for any tilter degradation. 

• Careful screening of data '' ith an interacti,·e. 

graphical ed itor to e liminate cloud contamination. 

and by reference to independent radiation data. 

Preli111i11a1y results. Prelimi nary processing of data from 

S PO beginning January 2000 and from BR \\I beginning 

!\larch 2000 indicates significant contrasts in aerosol 

concentration as well as in spectral sig nature. Time series 

of 1-min-resoh·ed AOD arc no\1 being generated for 

detailed ill\estigations of the direct and indirect radiati\'c 

forcing of aerosols. In addition. it is possible to 

characterize , ·arying t~ pcs o f particles. thus pro\ iding a 

basis to parameterize aerosols in c limate models. Figure 

3.19 shows a time series of spectral AODs and deri\'ed 

Angstrom exponents (a) during ;\,larch-April 2000. Values 

of a arc defined b) a power la1\. ''here AOD oc },->_ In this 

case. Angstrom ellponents ''ere deri,ed for the channel 

pairs labeled in the lo\\ er panel. Generali). Angstrom 

exponents are irl\'erscly proportional to mean particle size. 
... 

:I: 

.... 

a.. 

w 

c 

0·25 ~-58 54 (. 02 --12 23 ) --50_0_ 0_.0_96- (.0_1_7_) --86-5- 0.-0-52- (-.0-1_4__, ) 

I ( 

...J 

<( 

(.) 

la.. 

0 

-I 

0 

CJ) 

0 

cc 

w 

<( 

.... 

z 

w 

z 

0 

a.. 

x 

w 

:E 

0 

cc 

.... 

CJ) 

~ 

z 

<( 

0.2 

0.15 

0.1 

0.05 

0 

75 

II 

f 

v 

I 

f t

i i ij I i 

'

1

• ~l . "' ~ ·l \\ ~ t. i ~\\~ f ~~~ 

i ~ ~ J fi f ·~ '/\ ~ '\ >. 

'w I 

80 85 90 95 100 105 

75 80 85 90 95 100 105 

DAYOF YEAR (Un 

Fig. 3. 19. (a) Time series of I-min spectral aerosol optical depth derived from measurements made with the CMDL SPOl-A four-ch annel 

sunphotometcr at Barrow, Alaska, during March-April 2000, and (b) Angstrom exponents. calculated for the channel pairs indicated in the legend. 

1\lcans and (standard de\ iations) for the period arc also given in the respective legends. 

Similar time series from SPO (no t shown) reveal less 

va ri ability. The 500-nm opti cal depths at SPO are in the 

range 0.01 5-0.025, and A ngstro m expo nents are 

significantl y larger than at BRW, ind icating the dominance 

of sma ll parti c les at S PO. 

Previo usly, the main features o f the a nnua l aerosol cycle 

at the surface a t SPO were establis hed with the combination 

o f nephe lomcter data and derived va lues o f Angstrom 

expo nent to infe r partic le size spectra. Clea r sig natures 

disting uish modes o f coarse (sod ium) and small (sulfur) 

particles, whe re peak sodium concentratio ns are assoc iated 

with the rapid, po leward transport of seasalt from oceani c 

regions, princ ipa lly the Wedde ll and Ross Seas. Bergin et 

al. [ 1998] showed how in situ aerosol measurements fro m 

South Pole cou ld be corre lated with records of chemi cal 

species captured in firn samples to study past climate. In the 

futu re, corre lating surface and columnar properti es o f 

aerosols will lead to better inter pretatio n o f the firn data in 

terms of past climate forc ing. According to Bergin et al . 

[ 1998], the possibility ex ists to resolve, o n a seasona l basis, 

a record of aeroso l properties dating fro m I 000 years ago. 

73 

Mo reove r, the natu ral (e.g., seasalt, biogenic, o r volca nic) 

sig natu res should be disting uishable from anthropogenic 

ones. 

Goals. The large spati a l and te mporal differences 

observed in polar records of aerosols hi ghlight the 

importance of assimilatin g similar data from o the r sites to 

better charac teri ze polar aerosols spatially and tempo ra ll y. 

Init iall y, e ffo rts should focus o n establishment of 

" background" va lues o f AOD in bo th po la r regions, from 

which futu re perturbations, whether from volcani c activity, 

anthropogeni c facto rs, o r ot her fac to rs, can be refere nced. 

As evidenced in Fig ure 3. 18, the high la titudes are c urrently 

experi encing a period o f volcani c qu iescence; no major 

e ruptions have occurred in recent years, a nd AOD values 

are below histo ri cal min ima (dashed lines indicate the lo ngte rm background). The re fore, the opportu nity to establish 

base line values o f spectral AOD and deri ved prope rties, 

s uch as size s pectra [e.g., King et al., 1978], now exists. 

Once natu ra l seasona l vari a tio ns are understood over broad 

spatial scal es, climate forc ing by po la r aerosols can be 

assessed with g reate r confidence. O nly through int er-
national cooperation can adequate information be prO\ ided 

Lo modelers ch al lcngcd to impro\ e aerosol parameterizations as called for b) the lntergo' crnmcntal Panel 

on Climate Change (IPCC) [l/011ghto11 et al. :!001). Abo. 

the remote sensing communit) "ill benefit from these 

efforts because 'a lid retriernls of surface and atmospheric 

properties require that accurate corrections be made to 

account for c.\Linction by aerosol particles in the 

atmosphere. 

Steps ha' e been taken b) researchers from sc\ era I 

coun tries Lo coordinate their polar acti' ities in this regard. 

Participating countries include Italy. Australia. Germany. 

Japan. United States. Russia. England, and France. 

Although a 'ariety of photometers ha\C been used and the 

data records are of' ariable length and continuiL). there is 

agreement that an archi' e of polar AOD data \\ill pro\ ide 

the basis for bctler characterization or polar aerosols 

spatiall) and tcmporall). Once these data arc assimilated, 

analyses in conjunction "ith model studies should pro\ ide 

the means to more accurately quantify the peculiar radiati' e 

effects of aerosols at high latitudes. The immediate 

objecti\e of this group is to coll\ enc a \\Orkshop to set 

goals for future collaborations and to establish such an 

archive that may be modeled after the Baseline Surface 

Radiation Net\\ ork protocols [ Oh11111ra et al .. 1998]. 

Ber11111t/(I, BAO, Boulder, {I/Id Kwaj(l/ein 

Routine monitoring of aerosol optical depth continued at 

Bermuda, BAO. Boulder. and Kwajalein "ith multi-tilter 

rotating shado\\ band radiometers ( M FRSRs) and tracking 

sunphotometers. M FRSRs were first installed at Bermuda in 

February 1996, BAO in August 1996, Boulder David Skagg' 

Research Center (DSRC) laboratory in Jul) 1999. and 

Kwajalein in April 1996. Data are do\\nloaded b) telephone 

and stored in the STAR data archive. With the intent of 

eventually replacing all MFRSRs with tracking 

sunphotometers, the MFRSRs at BAO and K\\ajalein \\ere 

rcmo\'ed in August 2000. Optical depth data analysis for all 

stations is performed routinely by first finding mornings and 

afternoons that produce acceptab le Langley plots so that a 

time series of V0 \'alues (instrument ca libration constant) ma) 

be formed. This V0 time series is then smoothed, and a nc\\ 

V0 is calculated from the smoothed time series for e,·cry I -

min data point in the data set. These ne" V0 values along 

with the I-min direct-beam irradiancc data arc used to 

calculate new total optical depth \alues. Fina II), aerosol 

optical depth is calculated by subtracting other components 

of optical depth, such as that due to Rayleigh scattering. 

o7onc absorption. and absorption by other gases. 

3.2.5. MLO AND BOULDER UV SPECTRORADIOi\IETERS 

Solar radiation measured at the Earth's surface depends 

on the absorption and scattering of the atmosphere, the 

Earth-Sun distance, and the irradiance of the Sun. The UV 

porti0n of the spectrum is controlled primarily by Rayleigh 

scattering by air molecules. scattering by clouds, and 

absorption by oLone. Under clear-sky conditions, at a given 

site and for a gi,cn solar zenith angle (SZA), \'ariations in 

UV arc strongly correlated (inversely) with 'ariations in 

total ozone. As part of the Network for the Detection of 

Stratospheric Change (NDSC) a UV spectroradiometer 

74 

(labeled UVL) \las installed at i\ILO (19.533"N. 

155.578°\\'. 3.4 km) in Jul) 1995. This imtrument operated 

until June 1997. and a ne\\ instrument (UV3) \\as installed 

in No, ember 1997 and continues in operation at i\ILO to the 

present. 

To pro' ide an additional site for these studies. a UV 

spectrorad1omcter (UVL. the same instrument initially 

installed at i\1 LO) "as installed at the Boulder laborator) 

(39.991 °N. 105.261 ° \V. 1.62 km) in June 1998. This 

instrument was replaced \\ith a ne\\ instrument (UV-t) in 

September 1999. Finall). the UV-t instrument \las replaced 

\\ ith another ne\\ instrument (UV5) in August 200 I. Of 

note is the fact that UV5 participated in an instrument 

comparison at the Table l\lountain. Colorado, research site 

during June-July 200 I. immediately before it "as installed 

in Boulder. This instrument has continued in operation at 

Boulder to the present. All of these instruments (U\' L. 

UV3. UV4. UV5) were constructed b) the National lnstillltc 

of \\'ater and Atmosphere (NIWA) group at Lauder. Ne\\ 

Zealand. under a cooperati\c program agreement "ith 

Ci\I DL. The 'arious spcctroradiometers used at M LO and 

Boulder are sutrnnari/ed in Table 3.9. The goal or this 

program is to stud) the relationship bct\\een UV and OLone 

and to determine long-term trends. if an). in UV. M LO and 

Boulder arc both e.\ccllcnL sites for this study because of the 

prc,alcnce of clear skies and the collocation of Dobson 

oLone spcctrophotomctcrs. 

Data analysis is accomplished through the use of sofL\\arc 

provided by the NI\\ A-Lauder research group. This 

soft \\'arc runs on 18M PC-t) pc machines and is designed to 

read the ra\\ monthly data files, appl) calibrations. and 

calculate a UV spectrum for each ubscr\'ation. The program 

asks for instrument name (such as UVL). year. month. and 

block number as input "hi le running. and therefore it is 

neccssar) to kno\\ \\ hich instrument 11 as located at a 

particular location and time in order to process the data. 

The program a utomal ica II y ca lculates cerla in i ntcgratcd 

spectra such as UVB, UVA. and erythema, and has the 

capabili ty of calculating any special action spectrum. such 

as deoxyribonucleic acid (DNA) or 'itamin D. The 

erythema spectrum (.\/cKi11/ay and Dff!ey. 1987] is 

important because it represents the response function of 

human skin to UV radiation. and it is used in stud ies of 

sunburning. The 'itamin D spectrum (,\Jacla11ghli11 et al .. 

1982] is important because exposure to sunlight causes the 

photosynthesis of' itamin D in human skin. In this report 

TABLE 3.9. UV Spectroradiomcters at MLO and Boulder 

lnstrnmcnt 

UVL 

UV3 

UVL 

UV-I 

uvs 

,\/LO 

Boulder 

Date 

Jul) 1995-June 1997 

NO\ ember 1997- preseni 

June 1998-September 1999 

September 1999-August 2001 

August 200 I present 
results arc presented only for crythema because at the time 

of this writing there is no general agreement among 

researchers on the correct 'itamin D spectrum for use in 

these calculations. 

UV data from M LO were presented by Bod/wine et al. 

[ 1996. 1997). ,\fcKen::.ie el al. (200 l ), and briefly in Cl/Dl 

S11111111ar1· Reports Xo. 23. 14. and 15 (llof111w111 et al .. 1996, 

1998: Schnell el al .. 200 I). The UV irradiances measured at 

1\1 LO arc much larger than at low-altitude midlatitude 

locations. primarily because of less Rayleigh scattering. but 

also because of lower column ozone in the subtropics. 

Boulder can be considered a midaltitude site. since it lies 

about ha lf-way between MLO and sea le\el. llere the 

complete data set is presented, selected for clear mornings at 

M LO, and clear mornings and afternoons at Boulder. Clear 

mornings occur at M LO appro:-.imatel) 60% of the time. 

pro' iding an excellent site for solar radiation measurements. 

Clear skies occur less often. and UV data tend to be noisier, 

at Boulder. Clear afternoons are accepted in addi tion to clear 

mornings at Boulder in order to increase the number of data 

points. All processed spectral data arc a\ailable from the 

solar radiation division of the CM DL program. 

In sl r11111 e11talio11 

The UV L spectroradiometcr "as desc ribed b) McKen::.ie 

et al. [ 1992) and Bod/wine el al. [ 1997). Briefly. a diffuser 

designed to minimiLe cosine error and machined from 

Tellon is mounted as a horizonta l incidence receptor to 

'ic" the "hole sky. For UVL. stepper-motor-driven 

gratings cover the spectral range of 290-450 nm in a single 

scan with a bandpass of about I nm. The newer instruments 

(UY3, UV4, and UV5) cover the range 285-450 nm with a 

bandpass of about 0.8 nm, and use fiber opt ic cables to 

transmit the light from the sensor to the spectrometer. A 

complete forward scan for UYL requires about 3 min. The 

UV3, UY4. and UV5 instruments do a backward scan and 

then a forward scan centered at the desired SZA, and 

therefore require about 6 min for a complete measurement. 

All instruments are programmed to perform scans eYery 5° 

of SZA during daytime hours, starting at 95° SZA in the 

morning and ending al 95° SZA in the afternoon. During 

midday for 2.5 hours the sampling inten al is changed to 

once C\ e ry 15 min because the SZA changes slowly during 

that time. 

Absolute calibrations of the spectroradiometcrs arc 

performed at approximately 6-mo inten als with I 000-\V 

FEL lamps traceable to NIST standards. A dedicated 

calibration bench is set up at MLO for these calibrations. 

The Boulder instrument is calibrated by NOAA ·s Surface 

Radiation Research Branch (SR RB) "·ith a portable I 000-\V 

lamp calibrator. Weekly stability calibrations arc 

performed at both sites with mercury lamps for wa\ clength 

calibration and 45-\V standard lamps for long-term stability 

checks. The long-term accuracy of the spectroradiomctcr 

systems is expected to be better than :::5°·o. 

Data A nalysis 

For the followi ng analyses, UV spcc trorad iometer data 

for 45° and 65° SZA were chosen for clear mornings at 

l\ILO during the July 1995-0ctober 2001 time period. This 

gives approximately 6.5 years of data, and includes ozone 

values in the range of about 200-350 Dobson units (DU). 

75 

For l3ouldcr data. 65 ° SZA and the period July 1998-

0ctobcr 2001 were used, co,ering an ozone range of about 

220-400 DU. Note that 45° and 65° are the smallest SZAs 

attained year round at the M LO and Boulder sites. 

rcspecti,ely. The 65° SZA data are used for comparisons 

between MLO and Boulder. Clear mornings at MLO and 

Boulder were determined in the same manner as in previous 

studies: that is. a day \\as accepted as a clear day at MLO if 

the sk) was cloudless from da" n through the time of the 

desired scan, and if Dobson ozone data "ere a' a ilable for 

that morni ng. At Boulder, generally, the sky had to be clear 

at the time of the scan, Dobson ozone data had to be 

a\ ailable, and clear afternoons were also accepted. The 

Dobson ozone obsen·ation closest to the time of the UV 

scan was used. Figures 3.20 and 3.2 1 show M LO ozone and 

UY erythcma data for July 1995-0ctober 200 I for 45° and 

65° SZAs. respectively. Figure 3.22 shows similar data for 

Boulder for June 1998-0ctobcr 2001 for 65° SZA. 

Erythcmal radiation data were obtained from the 

spectroradiometcr data for both sites by appl) ing the 

crythema l weighting function of McKinlay and Diffey 

[ 1987) and integrating over wave length for each scan, as 

discussed by Bod/wine et al. [ 1997). The ill\ erse 

relationship of UV erythcma and ozone at both sites is 

apparent. 

350 36 

Ozone 

300 +----~,-----__ --~.,.-. ___ ..... ,,_----, ..;.,...· ~:--+ 32 ::-

=>!=)_ 

- 250 : /-'<?-.._ ~ .· :. :-·. ~ ;t'1".i..,,. •• ----. ...!_.·"":" ~ ~~ ., .i_ h.~ ': ~Fi. ... - 28 .., 

~ 

SlA ='5' 

50 +-----~--~ -~--~--~---+ 12 

1995 1996 1997 1998 1999 2001 2002 

Year 

Fig. 3.20. Ery thcmal irradiance at 45 SZA (boHom) and toial o7one 

(top) for clear-sk> mornings at MLO O\Cr the time period July 1995-

0ciobcr 200 I. 

350 9 

Ozone 

JOO ;- --~-- ----~ -r- -..~-+ 8 

[ 250 ,,:,, :o :k~?::.. : ,; /,;.-1-* '.·~';?:.' .(~,~ ~ · ,,{=~'~">. 1 'e 

~ ~i~! ':\~ "~.f :;; . :0 . ~ 

200 ;- -------,...- ~--..:;i=;=---;.~ -ra~ c -~i ·::. E:.IJU"'~ · . =~. E 

Do: 150 +---__,_,,_, '.!- - ., -~~·:~ < -~i.t_.,1,.,~~~~~!; : \~.: ::-~ J~-:f~ ;~.:~~- sw€. ~-;~:: __ ~~f),:-~ ~-:~e· j~· .... -~_::··. ~:f.;;:. C' 

• ,... :! 

100+-- ~;-.---+- --~ ~------+--t- 43 

SZA =65' 

50 -

1995 1996 1997 1998 1999 2000 2001 2002 

Year 

Fig. 3.21. El) the ma I irradmnce at 65 SZA (boHom) and 101al ozone 

(top) for clear-sk} mornings al MLO O\cr 1he time period July 1995-

0ctobcr 200 I. 
~o~+--~~--~~~~~~~~~~~~~~~~~~ 

Ozone 

Jso+-~~~~~~~--~~---~-'-'-',-, ~s .. -

e •·.· .. · .. =· t:: .... S ~ JaJ +---"'~~ .... --->--~,_,;,..,., __ , ~ .. -. ~~--+--,.,~='--'-i~..-;·c...-,. ~ ~ 5 :sJ t". . ': '::., . \ . . . . -~-. ! c Erythema E 

~ M0+-ZA -~-.--~~~--.-J-.. ~~---.•. -(·-·, ... ~~_-., --'---.--+5 € 0

° 15J :· ·:., ->'" • • • •• '.:.· 4 w" ,.,, ... . ' ~ ·. ·" ~~-'-' . . : . ·. -- ~~.:: ':: =:.~ .. :::: .. _-<.: .... -£ '· ." 

.,., · ... ·~·:.:-::~) 

SJ+----------~-----------2 

'Cl 

19;3 1939 :OJI 

Fig. 3.22. El)themal irradiancc at 65° SZA (bottom) and total ozone 

(top) for clear-sky mornings and afiernoons at Boulder O\er the time 

period June 1998-0ctobcr 200 I . 

Figures 3.23 and 3.24 show the relationships between UV 

crythema and ozone at MLO for November 1997-0ctobcr 

2001 for 45° and 65° SZAs, respectively. correspond ing to 

the most recent instrument configuration. Figure 3.25 

shows the relationship between UV erythema and ozone at 

Boulder for the time period June 1998-0ctober 200 1 for 65 

SZA. The radiative amplifi cation factor (RAF), defined as 

the percent change of UV (erythemal) irradiance di\ idcd b) 

the percent change of total ozone. was calculated for both 

sites, using the power-law formu lation of J\fadronich 

[1993]: RAF -nln(/)/6 ln(03) , where I is UV irradiance. 

The RAF is simply the slope of a straight-line fit on a loglog plot. The data for Roulder arc subject to more scatter 

because of more variable sky conditions than at MLO. The 

scatter in the Boulder data can be reduced signifi cantl y by 

plotting the ratio of erythemal to 340-nm irradiance against 

OLone. Since OLone effects are essentially absent at 340 nm, 

this reduces the effects of aerosols, clouds, and other atmo>-

pheric variations. 

SZA :45• 

RU': 1 22 

f = 1~4651_, 1171 

R1 •09.! 26 

10 +-~---~-~---~----~------< 

200 350 

Dobson Ozone (DU) 

rig. 3.23. Power law regression between el)·themal irradiance at .J5 

SZA and Dobson total ozone at MLO O\cr the time period No,·ember 

1997-0ctober 200 I. The graph is plotted on a linear sca le to facilitate 

reading the units. The exponem of the power law function ( 1.22) gi,·cs 

the RAF. 

76 

7 , 

SZA = 65' 

RAF= 1 16 

250 

Dobson Ozone (DU) 

300 

y : 3173 4X I 15.lt 

R' = 09441 

350 

Fig. 3.24. Po\1er lm1 regression between el)·thcmal irradiance at 65' 

SZA and Dobson total O/one at MLO o\·er the time period No,cmbcr 

1997-0ctober 2001. The graph is plotted on a linear scale to facilitate 

reading the units. The e\ponelll of the power la1\ function ( 1.16) gi' es 

the RAF. 

SZA = 65' 

RAF= 0 97 

200 250 300 350 

Dobson Ozone (DU) 

y = 930 99x 

R' = 043 

400 450 

Fig. 3.25. Power la\1 regression between Cl) thcmal irradiancc at 65° 

SZA and Dobson total O/Onc at Boulder o\·er the time period June 1998-

0ctober 200 I. The graph is plotted on a linear scale to facilitate reading 

the units. The exponent of the power h111 function (0.97) gi,es the RAF. 

Figure 3.26 shows the RAF at MLO as a function of 

wave length for SZAs of 45° and 65° . In general the RAF 

decreases with increasing wavelength. and the ozone 

dependence is negligible for 340 nm. It is clear from the 

figure that the RAF is consistently larger for larger SZAs. 

Figure 3.27 shows the RAF al MLO as a function of SZA 

for SZAs in the range 15°-85° . The apparent break in the 

slope of the data for SZAs <35 is most likely caused b) the 

fact that smaller numbers of data points are avai lable for 

SZAs of 15°-35 ° because these smaller SZAs arc not 

reached during winter months. which means that somewhat 

different ranges of ozone data are used for those data points. 

Co11 c:/11si o11s 

• Erythemal irradiance calculated from UV s pectra at 

M LO and Boulder is in\'erse ly correlated '' ith 

Dobson total ozone. 

• No significant trend in UV irradiance may be 

in ferred because of the limited time period. 
i6 

'° ..I 

t 

~ 4+-~~~.,.._~~~~~~~~~~~~~~~~~-< 

e:. F45'l ~ 

2+-~~~->,~'--~~~~~~~~~~~ ~ 

· ..... 

290 295 300 305 310 315 320 325 330 335 340 345 

Wavelength (nm) 

l· ig. 3.26. l:r)1hema RAf as a function ofwmclength at 1\1LO for 45 

and 65 S/ ·\s for No' em her 1997-0ctober 200 I. 

16 

¥ 

..J 12 

iii 

~ 

0 

0.. 

;;:- 08 

~ 

04 

5 15 JS 45 65 75 85 

Solar Zenith Angle (

0 ) 

Fig. 3.27. Er)thema RAr as a function of SLA at 1\1LO for No, ember 

1997-0ctobcr 2001. 

3.2.6. BROADBA~D UV 

As part of the \arious programs being operated b) the 

CMDL STAR group, broadband UV instruments (Yankee 

UVB- 1) ha\e been in use at MLO. BR\V, BAO, 13crmuda. 

Kwajalcin. and Boulder. These instruments ha\c been 

compared at 'arious times with the M LO UV 

spectroradiomctcr that was instal led at M LO in July 1995 

I Bod/wine et al., 1998). The calibration of the broadband 

instrument, reporting in erythemal units, is strongly 

dependent on total o7one because the erythcmal response 

defined for human skin is significantly different from the 

spectral response of the broadband instrument [Bod/wine et 

al., 1998). When a broadband instrument is placed in the 

field, it is necessary to know the calibration as a function of 

07onc to determine accurate erythemal irradiance. 1 lowe\ er. 

the manufacturers of broadband instruments do not general I) 

prO\ ide information on the ozone dependence of the 

calibration. Because of these uncertainties the broadband 

measurement program "as suspended on December 3 I. 2000. 

and the only instruments remaining in operation are those at 

M LO and Boulder, the locations of UV spcctroradiometers. 

77 

3.2.7. RADIATl\' E EFFECTS OF A~ EARLI ER SPR ~G 

S:\0\\1\IELT I~ NO RTHER~ ALASKA 

Regiona l climate models fail to adequately simulate the 

complicated feedbacks that arc peculiar to the Arctic . 

Empirical analyses of data from BR W and other Alaska 

North Slope sites pro\ idea better physical understanding of 

climate change in this region. In particular, data from BR\V 

re,·eal important factors that determine the annua l cycle of 

snow cover there and the radiati\ e perturbations caused by 

variati o ns in surface albedo. What modelers refer to as a 

··temperature-albedo feedback" is C\aluated in response to 

an advance in the date when the sno\\ melts in spring on the 

North Slope. The timing of snO\\ me lt is found to have a 

significant innuence on the net surface radiation budget 

(NSRB) and temperature regime there. 

Trend analyses of climate records from seYeral northern 

A laskan sites sho\\ 'ariations on seasonal to decadal time 

scales. Time series ha\e been correlated " ith synopticscale atmospheric circu lation patterns to understand the 

interaction of dynamical and radiati\ e processes. D1111on 

and Endres [ 1991) and Ci\!Dl S11111111w:1· Report .\'o. 25 

[Sch11ell et al .. 2001: pp. 65-67] gi'c a historical O\'crvicw 

ofCMDL's monitoring ofsnowmelt at BRW. The detection 

and a11ribution of climate change in the 'icinity of BR \V are 

discussed in se\eral published papers [e.g .. Stone. 1997. 

200 I: la11Ti111ore et al., 200 I: S1011e et al., 200 I, 2002). 

O nl y the main results arc summariLed here. 

A trend toward an earlier disappearance of snow in spring 

(i.e., melt date} in northern Alaska has been documented. 

Corre lated variations in the ti ming of sno\\ melt are revealed 

in several independent records. Since the mid- I 960s the 

spring melt has ad,anced by about 8.0 (±4.0) days over a 

significant region of northern Alaska, as shown in Figure 

3.28. Earlier spring sno\\ melt is, in part, the consequence 

of decreased sno\\ fall in "inter, folio\\ cd by warmer. 

cloudier spring conditions (e.g., Sto11e et al .. 2002). 

In turn. changes in snO\\ fall. temperature, and cloudiness 

are attributed to variations. or shifts, in regional circulation 

patterns. as is illustrated in Figure 3.29. Back-trajectories 

[llarris and Kahl, 1994) were used in the analyses. For 

example, snowfall. measured in units of water equi\alent 

precipitation (\VEPC}, is reduced \\hen the ad,ection of 

relati,ely warm, moist air from the north Pacific Ocean is 

blocked by a hig h-pressure system cen1ered nort hwest of 

BRW during win te r (Figure 3.29b \ersus 3.29a). Warm 

s prin g conditions prevail if there is more frequent now from 

the south, as indicated in Figures 3.29d and 3.29f versus 

3.29c and 3.29e. The combination would resul t in an earl ier 

melting of the snow pack during May-June. 

One consequence of an earlier melt is the increase in the 

NSRB that tends 10 warm the near-surface air through an 

albedo feedback. Table 3.10 contrasts the NSRB and 

temperatures for 3 earl) 'ersus J late yea rs of snowmelt at 

BRW. An early melt enhances the gain of radiant energy at 

the surface, warming the air in turn. In this case. a 2-wk 

ad,ance in the melt date in June increases the NSRB b} 

25•,o. "ith an associated rise in temperature of about I 0 . 

After an early melt, slight warming persists through August 

on a\'erage. 
200 Jul20 

195 ISAKTOAK [0.80] 

190 COOPER Is. [0.74] Jul10 

8185 

_. 180 .r Jun 30 

175 

; 170 Jun 20 

Q 165 i 160 Jun 10 

155 

150 May30 

145 

140 May20 

{a) 

1965 1970 1975 1980 1985 1990 1995 2000 

·140 

·160 Beaufort Sea 

(b) 

Fig. 3.28. (a) Analyses of six independent time series of measured or 

proxy melt dates (day of year) compared with the 1966-2000 CMDL 

BRW record (in red). Five-year smoothed time series and linear fits arc 

shown. Each is cross correlated with the BRW record with coefficients 

indicated in brackets for individual sites that are labeled and color-coded. 

The dashed analysis (unlabeled) is for an ensemble average of the 142 

station-years, non11alized to the BRW timeframe. (b) Map of Alaska's 

North Slope showing the location of sites making up the e nsemble [from 

Sr one er al., 2002]. 

This last result supports theoreti cal predictions of a 

posi ti ve feedback due to diminished snow and ice cover in 

the Arcti c a s a result of g lobal warming. T his temperaturealbedo feedback is expected to enha nce warming over the 

northern high latitudes (e.g., Serreze et al., 2000). The 

CMDL BRW observations are found to be representative of 

northern Alaska and establish baseline conditions for 

eva luating future cl imate change in this sensitive region o f 

the Arctic. Also, the time series will be useful for verifying 

regiona l c limate model simulations and for val idating 

remote sensing a lgorithms being developed to monitor 

surface temperature and a lbedo needed to estimate the 

surface radi ation balance [Key et al., 1997). Continued 

monitoring of the snow cycle at BRW and the factors that 

determine it is essenti al. The timing of the spring melt on a 

pan-Arctic scale will influence not onl y the regiona l ene rgy 

78 

budget (temperature regime) but also biogeochemical cycles 

that affect the sources and sinks o f metha ne a nd carbon 

dioxide, imposing other potential cl imate effects [e.g., 

Oechel et al., 1995; Myneni et al., 1997). Already, the 

c hanging Arctic cl imate is affecting indigenous people who 

depend on fi shing and hunting grounds that are being 

modified [Morrison et al., 2001]. 

3.2.8. UV VARIABILITY IN T H E ALASKAN ARCT IC 

Objectives 

With support from the Arcti c Research Initiative (ARI) in 

1997 and 1998, a network of three UV meters was installed in 

Alaska, at BRW and at the NWS o ffices at Nome and St. Paul 

Island. The objective of this network is to provide information 

on the geographical distribution and temporal trends of UV 

radiation at c limatically di verse sites in the Arctic. 

Methods and Results 

This network was mainta ined with support from ARI in 

FY 2000 and 200 l , and inc luded annual calibrations at the 

manufac turer. In addition, LI-COR sensors and data 

acquisition systems we re installed at Nome and St. Paul 

Island to measure both downwe lling and upwell ing 

photosynthetically active radiation (PAR). The data from 

the upward and downward sensors can be used to provide 

information on changes in albedo to aid in the assessment o f 

UV va riability. Further in formation about the instruments, 

site descriptions, or requests for data access can be obtained 

from CM DL's website (http://www.cmdl.noaa.gov/star/ 

index.html). 

Table 3. 11 provides an overview of the monitoring 

periods fo r 1998-200 l at the three sites. T he table also 

provides in formation on the number o f days with good and 

bad data, calibration dates at Biospherical Instrume nts Inc. 

(BS I), and comme nts. With the exception o f Barrow and 

Nome for 2000, there has been less than a I 0% loss in data 

during the monitoring period each year. In 2000, the losses 

o f data at BR W and Nome were due to a PC ma I fun ct ion 

and not to instrument fa ilure. Unfortunately, since data are 

downloaded onto a PC, there is no way to retri eve lost data. 

Of a ll three UV meters, the BR W instrument has 

exhibit ed the best stability, with a ±4% drift or less on four 

of the channels (305, 320, 340, and 380 nm). The stabi lity 

of any one channel is evaluated by comparison of calibration factors, whi ch are provided after the instrume nts 

undergo an absolute calibration each wi nter by the 

man ufacturer. Unfo rtunately, there is a significant drift in the 

3 13-nm channe l for all three instruments, where the 

ca libration factors have changed by as much as 40% from one 

year to the next. Therefore, until the problem is resolved and 

data are corrected, any interpretation about dose rates at 3 13 

nm is not possible. As noted in Table 3. 11 , a channel was 

c hanged in the UV instrument at St. Paul for 1999 and 2000. 

The replacement o f any channel makes an evaluation of 

stability problematic. In addition, when the St. Paul 

instrument was returned to the manufacturer in Decembe r 

1999 fo r calibration, the di ff user was found to have leaked . 

This would affect a ll channe ls within the instrument's 

housing and therefore invalid ate a comparison of calibration 

factors from th e previous year. Although Nome had only 
Late Melt Date at BRW 

43% (1.73) 

) 

34% (2.09) 

Fig. 3.29. A\'eraged, 1500-m back trajectories relatiYe to BRW and corresponding 850-hPa gcopotential height fields for (a) Octobcr-Februa!) 1987. 

1993. and 1999. (b) October-February 1990. 1996. and 1998. (c) :>.larch-April 1987. 1993. and 1999. (d) i\tarch-i\pril 1990. 1996. and 1998. (e) Ma) 

1987. 1993. and 1999. and (f) 1\tay 1990. 1996. and 1998. sho\\ing the multi)ear. seasonal a'cragc. 5-da) air no" from source regions indicated as 

lightly shaded areas. The percent frequenc) of transport and merage transit time from each source region (in days) are indicated in the legends. In each 

panel the upper left legend relates lo n ow from the Arctic source region. and the Im, er lefl legend relates to llow from the North Pacific source region. 

The thickness of trajectories is proportional to their frequency and their lengths in\'crscly proportional lo a\'erage speed along track. These a\'eragc 

trajectories represent the mean now of all indi\'idual trajectories from the respective regions O\'er each period indicated in the upper right-hand legend. 

The late melt dates at BR \V were due to higher October-Febrna!)' sno" fall (measured as water cqui,a lcm precipitation (\\'EPC)). follo\\ed b) cool 'cir) 

spring weather conditions, compared with early melt date years. A more detailed explanation is given by Sto11e et al. [2002 ]. 

the 320-nm channel replaced in December 1998, an analysis 

of the calibration factors shows a significant drift in the 

305-n111 channel (up to 18%) from one year to the next. 

Detailed information about th e replacements of channels 

can be obtained from CM DL. 

Despite the calibration issues, the data can be used to obtain 

a prel iminary overview of the variability in UV at different 

79 

latitudes in Alaska. Figure 3.30 pro\'ides a summary of the 

monthly a\·erage da ily total energy (J m·2 nm- 1

) for all three 

sites. Data for the 3 l 3-n111 channel are not included because or 

the large changes of the calibration factors for that channel. In 

addition, for the No111e and St. Paul instruments. the 340-n111 

channel was substituted with a PAR channel, which is an integrated measurement across the 400- 700 nm spectrum. 
TABLE 3.10. Comparison or Net Surface Radiation Budget 

and 2-m Air Temperatures for Late Versus 

Early Years of Snowmelt at BR\V 

Late t.lclt Date Early Melt Date 

Years Sampled ( 1992. 1999. 2000) (1990. 1996. 1998) 

Melt date (DOY) 164 (0.8) 150 (0.8) 

NSRB (MJ m·') 

June 306 (2) 385 (7) 

1\ lay-August 860 ( 17) 970 (43) 

T,m {°C) 

June 0.9 (0.59) 1.8 (0.36) 

July-August 3.3 (0.62) 3.6 (0.87) 

DOY. day of year: NSRB. net surface radiation budget (in units of 

total radiati\'e energy): T,m. air temperature at 2 111 above ground lewl. 

Standard deviations are gi' en in parentheses. 

There fore. there is no 340-nm chan ne l fo r either Nome or 

St. Pa ul. Monthly averages were computed if there were 18 

days or more per month with good data. 

An annual variability in UV levels is clearly evident for 

all three sites, with maximum values for all wavelengths in 

May or June (Fi gure 3.30). Nome has th e highest UV levels 

at 305 and 320 nm for all three years compared with BR\V 

and St. Paul. Barrow is at the highest latitude of the three 

sites, and therefore would receive much less solar radiation 

O\ er the course of the year, even \\'hen the Sun is above the 

hori zon for 24 hours per day. St. Paul is usually under the 

influence of low-le\'el stratus clouds, which would block more 

incoming UV radiation. Nome has many days that are 

spectacularly clear. The anomalously lo\\' UV levels at 305 nm 

at St. Paul in the year 2000 are most likely due to a reduced 

sensitivity in that channel over the monitoring period, which 

necessitated its replacement in December (see Table 3.1 I). 

In 2000, two Ll-COR PAR sensors were installed at both 

St. Paul and Nome. A PAR sensor measures in the 400-700 

nm solar spectrum. At both sites, one sensor faces upward 

(to measure downwe lling or incident PAR) and the other 

sensor faces downward (to measure upwe ll ing or reOected 

PAR). Table 3. 12 summarizes the monitoring periods for the 

Ll-COR sensors at St. Paul and Nome. Of the 338 days of 

data for St. Paul for 2000-200 I, 212 were found to be good. 

The remaining 126 days had a downwelling PAR offset of 5 

W ni"2 or greater, which wi ll be corrected later using a linear 

regression technique. This will enable all the data to be 

evaluated for 2000. At Nome, data were obtained for 232 

days during 2000-2001; 225 of these were considered good 

days. The remaining 7 bad days were due to missi ng data. 

To investigate whether the Ll-COR downwe lling PAR is 

equivalent to the measurements obtained by the BSI PAR at 

T ABLE 3. 1 I. Site S ummary o f UV Monitoring at Barrow, Nome, and S t. Paul. for 1998-200 I 

Stan of monitoring 

End of Monitoring 

Good days 

Bad days(% loss) 

Calibrations at BSI 

Comments 

Stan of monitoring 

End o f monitoring 

Good days 

Bad da)S (% loss) 

Calibrations at BSI 

Comments 

Stan of monitoring 

End of monitoring 

Good da)S 

Bad days(% loss) 

Calibrations at BSI 

Comments 

1998 

t. lay 15 

Oc1. 27 

158 

4 (2.5%) 

April 30. 1998: 

Dec. 17. 1998 

Diffuser replaced in 

March 1998 and 

recalibrated April 1998 

June 11 

Oc1. 24 

134 

5 (3.6%) 

April 28. 1998 

320-nm channel replaced in 

Dec. 1998 

June 6 

Oc1. 25 

135 

7 (5%) 

April 30. 1998 

320-nm channel n:placcd 

in Dec. 1998 

1999 2000 2001 

Barrow 

Feb. 3 Feb. 8 March 29 

NO\. I Oct. 16 Oct. 3 1 

244 213 

5 (2. J

0 'o) 24(10. 1%) 

Dec.9. 1999 Dec. 12.2000 

PC malfunction 

Some 

Feb.24 Feb. 9 Feb.9 

Oct. 28 No\'. 6 NO\. 9 

226 237 

10(4.2%) 30 ( 11 .2%) 

Feb. 16. 1999: Dec. 1999 Dec. 12. 2000 

22 days los1 because of 

PC malfunction 

St. Paul 

t.larch I 1\larch 7 Feb. 27 

Oct. 1-1 NO\. 3 NO\. 7 

21 1 231 

16 (7%) 7(2.9%) 

Feb. 16. 1999 Jan.25. 2000: Dec. 12. 2000 

380-nm channel bad from 305-nm channel 

March I to June I 0. 1999 replaced prior to 

Dec. 2000 calibration 

80 
3.0E+02 

1.1E+04 2.0E+02 

5.5E+03 1.0E+02 

O.OE+OO O.OE+OO 

May-98 Sep-98 Jan-99 May-99 Sep-99 Jan-00 May-00 Sep-00 

2.0E+04 ~320nm 

5.0E+02 

1.6E+04 4.0E+02 

1.2E+04 3.0E+02 

8.0E+03 2.0E+02 

4.0E+03 1.0E+02 

O.OE+OO O.OE+OO 

May-98 Sep-98 Jan-99 May-99 Sep-99 Jan-00 May-00 Sep-00 

1.4E+04 3.5E+02 

1.2E+04 3.0E+02 

1.0E+04 2.5E+02 

8.0E+03 2.0E+02 

6.0E+03 1.5E+02 

4.0E+03 1.0E+02 

2.0E+03 5.0E+01 

O.OE+OO '-------------------~ O.OE+OO 

May-98 Sep-98 Jan-99 May-99 Sep-99 Jan-00 May-00 Sep-00 

Fig. 3.30. Monthly average of daily total energy (J ni"2 nm·') for 1998-

2000 for Barrow. Nome, and St. Paul. The 305-nm channel is plotted on 

the right scale. 

Nome and St. Paul, a linear regression was applied with the 

I-mi n solar noon values obtained from each instrument. At 

St. Paul, both the LI-COR sensor and BS I PAR compare 

very we ll , with an average difference between the two 

instruments of onl y about 4% (compari ng only the 2000 

data). However, at Nome, the Ll-COR PA R measurements 

are 65% below those obtained by the BSI PAR during 2000, 

and the sensitivity of the Ll-COR sensor appeared to be 

decreasing in 200 I. Fortunately, the Ll-COR downwelling 

PAR at Nome and St. Paul track the BS I PAR (r2 = 0 .99 at 

81 

TABLE 3.12. Summary ofLI-CO R PAR 

Sensors at Nome and St. Paul 

Stan of monitoring 

End of monitoring 

Good days 

Bad days(% loss) 

Comments 

Stan of monitoring 

End of monitoring 

Good days 

Bad days (% loss) 

Comments 

2000 

St. Paul 

March 29 

Nov. 20 

2001 

March 19 

Nov. IS 

108 104 

126 (54%) 0 (0%) 

From Nov. 20, 2000, to 

March 19, 2001, the 

downwelling PAR was 

turned otT and sensor 

returned for repair 

April 11 

Aug. 29 

147 

Nome 

April 22 

Dec. 31 

78 

7 (5%) 0 (0%) 

From Aug. 29, 2000, Although the upwelling 

to March 29, 200 I, the PAR sensor was reupwelling PAR was deployed on March 29, 

turned otT and sensor 200 I, it was incorreturned for repair rectly installed until 

April 22 

both sites), so the Nome LI-COR downwel ling data were 

easily corrected using the equation obtained from the linear 

regression a nalysis. 

When a ratio of the re Oected fl ux density to the incident 

fl ux density is taken, one can obtain the a lbedo o f the 

surface. In the Arcti c the surface albedo can vary from less 

than 0.05 to more than 0 .9. Figure 3.3 1 provides a 

preliminary a nalysis o f albedo fo r Nome and St. Paul for 

2000 a nd up to the last day of processing in 200 I (Jul y 8). 

The albedos were calc ul ated with data from sunrise to 

sunset (or for solar zenith angles between 0° and 85°). 

Days s howing a n offset were not inc luded in the analysis 

for this report. In 2000 the range of albedos at Nome was 

0. 03 to 0.52 ; at St. Paul, the range was 0.03 to 0.95. St. 

Paul shows much lower albedos for the March-April period 

in 2001. At fi rst, this was thought to be due to an 

instrument malfunc tion. However, upon examination of the 

meteorological observations for St. Paul, the albedos in 

Figure 3.31 are representative of both snow depth and 

snowfall amounts that were reported in both years. St. Paul 

had snow depths of more than 0.6 m (2 ft) th roughout 

March a nd into mid-April in 2000. On ly on May I d id the 

snow depths decrease from I 0.2 cm ( 4 in) to a trace, thus 

the dramati c decrease seen in the albedo for St. Paul in 

earl y May 2000. In contrast, 2001 was a very dry year for 

St. Paul, with little to no snow accumu lation from January 

th rough April. This is reflected in the low albedo values, 

with the exception of a peak on March 27 , whi ch is most 

likely due to the fac t that St. Paul received 1.5 cm (0.6 in) 

of snow that day. The next few days had trace amounts of 

snowfall , and a lbedo was seen to decrease. Even a small 
0.8 

.g 0.6 

- t'-.brre 2CXXl 

- t'-.brre 2001 

- St. Paul 2CXXl QI 

..c < 0.4 - St. Paul 2001 

O.~ ~~~~~ ~.:!. .... ~_,.... ::! .. "-d 3115 31'29 4112 4126 5'10 5'24 ff7 &'21 7/5 7/19 812. 8'16 8/30 !¥13 

Day 

Fig. 3.31. Daily average albedo for Nome and St. Paul for 2000 and 

2001, calculated with data from sunrise to sunset. 

snowfall of 1.5 cm was enough for the albedo to increase 

threefold. At Nome the instrument did not operate correctly 

when it was installed in the early part of 2000. If it had, it 

is quite likel y that measured albedos would have been as 

high as those seen for St. Paul because snow depths were 

greater than 0.6 m (2 ft) prior to April 4, but then 

plummeted to 12.7 cm (5 in) in less than 2 weeks, with little 

to no additional measurable precipitation after April 22, 

when the a lbedo reached its minimum leve ls. The large 

amount of missing data for the beginning of 200 I at Nome 

is due to bad weather that made it impossible for the site 

operator to install the repaired sensor, and when the sensor 

was insta lled in late March, it was erroneously inverted 

until April 22. Had the sensor been insta ll ed sooner and the 

inversion discovered earlier, more than likely the measured 

albedos would have been as high a s St. Paul in 2000 

because Nome received substanti a l snowfall that spring. 

The two peaks, on May 9 and again on May 25, are the 

result of two snowfa ll events, with more than 5.1 cm (2 in) 

measured each time. 

Figure 3.32 shows the annual variability of daily total 

column ozone (Dobson units) obtained from the Total 

Ozone Mapping Spectrometer (TOMS) for the three sites 

for 1998-2000. Not shown on this plot is the ozone 

obtained from the Dobson spectrophotometer, w hich is 

located at BRW. A linear regression analysis between th e 

Barrow TOMS and Dobson ozone indicates that for all 3 

years both data sets are highly correlated, with r

2 = 0.98. 

However, TOMS consistently overestimates total column 

ozone by an average of 3.4% (averaged over all 3 years) and 

as high as I 0%. As can be seen in Figure 3.32, for a ll three 

sites the maximum levels of ozone occur in February or 

Mar~h and then decrease over the course of the summer, 

with minimum levels of ozone occurring in August, 

September, or October. Note the lower maximum ozone 

levels at all three sites in February and March 2000 as 

compared with 1998 and 1999. Low leve ls of ozone were 

also found during the SAGE III (Stratospheric Aerosol and 

Gas Experiment) Ozone Loss and Validation Experiment 

(SO LVE) in earl y March 2000, when scientists from the 

United States, Canada, Russia, and Japan measured ozone 

losses as high as 55% across much of Scandinavia and north 

central Siberia. 

In conclusion , these three sites can be used to evaluate 

long-term trends in UV and ozone, and the data can be used 

by researchers doing impact-related analyses as well as by 

the satellite community to improve algorithms used to 

estimate UV. This is important because of expected ozone 

losses over the next 20 years or more due to a cool ing 

stratosphere in the Arctic reg ion, with potential impacts on 

human health and on the marine and terrestrial ecosystems. 

3.2.9. DATA PROCESSING 

Solar radiation data are currentl y be ing monitored by 

STAR at 11 sites: the four CMDL baseline observatories 

(BRW, MLO, SMO and SPO); three BSRN sites (BAO, 

600 

550 

,----------------------------St. Paul TOMS 

500 

-

g 450 

-

Q) 400 

c: 

2 350 

0 

300 

250 -

- NomeTOMS 

- - - - - - - --Barrcm TOMS 

2001--------------------------' 

Jan-98 Apr-98 Jul-98 O::t-98 Dec-98 fvBr-99 Jun-99 Sep-99 Dec-99 fvBr-00 Jun-00 Sep-00 

Date 

Fig. 3.32. Daily total column ozone from the Earth Probe Total Ozone Mapping Spectrometer (TOMS) for St. Paul. Nome. and Barrow, 1998-2000. 

82 
Bermuda. and Kwajalein): two UV monitoring sites (Nome 

and St. Paul. both in Alaska): Kosan. Korea: and CivtDL's 

headquarters al the DSRC in Bo ulder. Thermal (IR) 

rad iation is also monitored at all these sites with the 

exception of St. Paul and No me. 

Five meteorological data streams (wind speed, wind 

direction. pressure. temperature, and relative hu midity) are 

moni tored by the ST AR group al the BS RN sites. Pressure. 

temperature, and relati\'e humidity are monitored at Kosan. 

Temperature measurements are made al BR \V to be used in 

conjunctio n ,,·ith a new IR sensor, and pressure is meas ured 

for use w ith sunpho tometer data at S PO. 

Sunphotometers have been installed a l BR \V. M LO. SPO. 

BAO. Kwajalein, Boulder. and Kosan. Data from the 

s unpho1ome1ers. as well as the meteorological and radiation 

data. are collected by Campbell Scient i fie data loggers. 

Windowed. cavity radiomete rs are operating at two sites 

(BAO and Bo ulder). Data from these instruments arc 

collected by custom programs and stored locally o n a PC. 

Multi-filter rotat ing shadowband radiometers (l\IFRSRs) 

continue to operate al Bermuda. Kosan, and at Boulder. 

MFRSR data arc collected and stored locally o n a PC. UV 

data are mon itored at BR\V . in addition to Nome and St. 

Paul. BS ! instruments are used 10 collect the UV data and 

store the data onsite on a PC. 

The M LO Auto mated Solar Dome data are collected by a 

custom program on a PC running at that site. Also at MLO. 

data are monitored on a precision fil ter radiometer (P FR), 

\\'hi c h is a tracking sunphotometer used for optical depth 

measurements. The PFR data arc collected by a Campbell 

Scicnti fie data logger. All-sky images arc made '' ith 

Yankee Environmental Systems (YES) Total Sky Imagcrs at 

three sites (BAO. BRW. and Boulder). These data arc 

collected and processed by YES proprietary so ftware. All 

data that arc collected on the Campbell data loggers are 

transfe rred to CM D L O\'cr telephone lines. with the 

exceptio n of data fro m S PO. Ca lls to the data loggers arc 

made at regular int ervals \'arying from 2 to 12 hours 

depending on the site being called. All o ther data are 

retrieved via the l111erne t. Some of the Internet connections 

are. ho\\'ever, made over telephone I in es. 

Each morning all data from all sites arc permanently 

sto red on o ne of the CMDL servers in Boulder. The data 

are then loaded into archive fil es. A ll archive files for a ll 

projects have exactl y the same format. Uniformity among 

the arc hi\'C fil es has si mplified da ta access. Plots and lists 

of the data are avai lab le to CM DL scientists from the 

archi\'e files. Modifications can be made at field sites after 

data review. 

Currently the solar and thermal radiation. meteorology, 

and sunphotometer data a rc being edited usi ng qualitative 

and quantil ati\'e methods. CMD L is a contributing member 

of the BSRN net\\'ork. The rad iatio n and meteorology data 

are sent to the BSRN database in Zurich. Switzerland. 

Access 10 the data for people outside CM DL is arnilablc 

from BSRN. or from CM DL directly upon request. 

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B. Forgan. C. Frohlich. R. Phrhpona. A. llcimo. G. Konig-Langlo. 

B. l\lcArthur. R. Pinker. C.11. Whitlock. and K. Dehne. Baseline 

Surface Radimion Nc1work (BSRN) WCRP: Ne\\ prec1s1on 

radiomclr) for climate research. 8111/. Am. ,\feteorol. Soc .. -9. 

2115- 2136. 1998. 

Philipona. R .. C. Frohlich. K. Dehne, J. DcLuisi. J. Augus1ine. E. 

Duuon. D. Nelson. B. Forgan. P. No\'olny. J. llickcy. S.P. Lo\e. 

S. Bender. B. " lcAnhur. A. Ohmura. J.11. Se)mour. J.S. Fool. "I. 

S hiobara. F.P.J. Valero. and A.W. Slra\\a. The BSR1' 

p)rgcornctcr round-robrn calrbra1ion e'perimen1. J. Atmos. 

On!anit Tec/11101 .. 15. 687-696. I 998. 
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Stifler. P. Wendling. N. Wo<id. S.A. Clough, E.J. Mlawer, G. 

Anderson. 11.E. Re\ercomb, and T.R. Shippen. Atmospheric 

longwave irradiance uncertai c11y: Pyrgcomctcrs compared to an 

absolute sky-scanni ng radiom eter. AERI, and radiati ve transfer 

model calculations. J. Geoph_1·s . Res .. 106. 28.129-28.141. 200 I. 

Quakenbush. T.K .. and B.A. Bodhaine, Surface aerosols at the 

Barro\\ G~ICC observatory: C>ata from 1976 through 1985, NOAA 

D{l/a Rep. ERL ARL-10. 230 pp., NOAA Air Resources Lab .. 

Sil, er Spring, MD, 1986. 

Quinn, P.K., T.L. Miller. T.S. B ates, J.A. Ogren, E. Andrews, and 

G.E. Shaw. A three-year record of simultaneously measured 

aerosol chemical and optica l properties at Barrow, Alaska, J. 

Geophys. Res., in press, 2002. 

Radke, L.F., C.A. Brock, R.J. Fe r ek. and D.J. Coffman, Summertime 

Arctic hales. Eos Tt-a11S. AGU. 7/(43}, 1264, 1990. 

Ramanathan, V .. et a l., Indian Ocean Experiment: An integrated 

analysis of the climate forc ing and effects of the great lndo-Asian 

ha7e, J. Geophys. Res., 106. 28.371-28,398, 2001. 

Remer, L.A.. and Y.J. Kaufman, Dynamic aerosol model: 

Urban/industrial aerosol. J. Geop hys. Res .. 103, 13.859-13.871. 1998. 

Schnell, R.C.. D.B. King, a.-.d R.M. Rosson, (Eds.}, Climate 

Monitoring and Diagnostics L aboroto1:i• S11m11w1:i· Report No. 25 

1998-1999, 154 pp .. NOAA Environ. Res. Labs., Boulder, CO. 

2001. 

Serrezc. ~LC .. J.E. Walsh. F. S . Chapin Ill , T. Ostcrkamp, M. 

DyurgerO\. V. Romanovsky, 'W.C. Oechcl, J. Morrison, T. Zhang. 

and R.G. Barry. Observational C\ idence of recent change in the 

northern high-latitude environment, Clim. Change. 46, 159-207, 

2000. 

Sheridan, P.J .. D.J. Dclene, and J .A. Ogren, Four years of continuous 

surface aerosol measurements from the DOE/ARM Southern Great 

Plains CART site, J. Geophys . .Res., 106, 20,735-20,747, 200 1. 

Stone, R.S., Variations in Western Arctic temperatures in response to 

cloud radiative and synoptic-scale influences, J. Geophys. Re.1· .. 

102, 21,769-21,776. 1997. 

85 

Stone, R.S., Climate monitoring at Barrow, Alaska, and South Pole: 

An overview of U.S. studies of polar surface radiation balance 

and aerosols. Proc. 8'h Workshop Italian Research on Amarctic 

Atmosphere. Bologna. Italy, Oct. 20-22. 1999. edited by M. 

Colacino and G. Giovanelli. pp. 83-98, Ital. Phys. Soc., Bologna. 

Italy. 2000. 

Stone. R.S .. Factors that determine "hen the seasonal snowmelt 

occurs in Northern Alaska. Proc. 2nd Wadati Con/ on Global 

Change and the Polar C/im{lfe, Tsukuba, Japan, arch 7-9. 2001. 

pp. 87-90. 2001. 

Stone, R.S., Monitoring aerosol optical depth at Barrow. Alaska, and 

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Proc. 9'" Workshop Italian Research on Antarctic Atmosphere. 

Rome, Italy, Oct. 22-24, 200 I, Ital. Phys. Soc., Bologna. Ita ly. in 

press. 2002. 

Stone. R.S., J. Key, and E. Dutton, Properties and decay of 

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spring snowmelt in northern Alaska as an indicator of climate 

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4. Ozone and Water Vapor 

J. HARRIS (EDITOR). G. CARBALGH. D. CHAO. i\I. CLARK. R. E\'r\:-.:S. B. Jo11:-.:so:-.:. 

ill. o-. Elli .. S. 01 n1 ."s. D . QUl'ICY. D. SllER~IA:-.: . B. \/ASEL. H . VO~l~L. A>.D B. \\1\1 Sii 

4.1. CO:\'TINU l:'\G PROGRA:\IS 

4. 1.1. TOTAL 0 Z O:\'E 0BS ER\'AT IO:\S 

Total ozone observations conti nued throughout 2000 and 

200 1 at the 16 stat ions that constitute the U.S. Dobson 

spectrophotometer netll'Ork (Table 4 .1 ). Of the 16 stations. 

CMDL personnel o perated five. the National Weather 

Service (N\VS) operated five, two are university stations, 

and fo ur arc foreign cooperative stations. All sta tion 

instruments are either ful ly automated or semiautomated, 

except for the one at the Peruvian site. In additio n, a Bre\\'er 

spectrophotometer was operated o n a nearly contin uous 

basis at Boulder. 

The automated system at Ha ute Provence. Fra nce. \\'as 

finally made operational in August 2000. but was not full y 

re liabl e until December of that year. Observations at 

Tal laha ssee are contin uing at Florida State Uni versity until 

th e new \VS office is completed in January 2002, but due 

to personnel problems. observations are not made 

consistently. and the data record is not very useful. Several 

months of data \\'ere lost from the Uni versity of Alaska. 

Fairbanks. because of a failure in the 20-year-old controll er 

unit. The replacement parts we re 'ery difficult to obtain. 

The dome at the Nashville (Old ll ickory) site \\'aS 

rei nsu lated by a local contractor. 

Ne\\ computers and programs were installed at a ll the 

si tes. and a new protocol "as established for data transfe r. 

l\lany sites transmit observational data daily. a lloll'ing 

prelimi nary ozone val ues to be arnilable in near-real time. 

Provisional da il y to tal ozone amounts applicable to local 

apparent noo n for the stations listed in Table 4.1 were 

archi1·ed at th e World Ozone and Ultraviolet Data Centre 

(\VOU DC). Canada. in O::one Daw for 1he World. Table 

4.2 I is ts the monthly mean total ozone amounts measured at 

the stations in the network for 2000 and 200 1. 

Observations of total column ozone 11 ith the Dobson 

spectrophotomete r at South Pole Observatory (SPO) with 

the Sun as a li ght source are limited to less th an half o f th e 

yea r. Moon observations are infrequent due to adverse 

winter weather conditions and limited obsen·ing periods. 

Opt ical measurements with the Dobson spectrophotometer 

cannot be made at all during twilight periods. To belier 

define the year-round column ozone measurements. 

integrated column ozone amounts from the ozonesondes are 

used to supplement the Dobson data during the dark and 

tll'ilight months (Figure 4.1 ). This new data set has been 

analyzed with a recently de1·eloped techn ique [Harris el al .. 

200 l) for describing long-term column ozone changes. The 

dec line in ozone (expressed as residuals) at S PO began in 

the 1970s (Figure 4.2) and has persisted through most of the 

record since then. Gro\\'th rates 11ere mostl y negati1e 

(Fig.ure 4 .3) throughout this period. ll'ith the la rgest dec lines 

in the 1970s and mid- l 980s. The overall !!.roll'th rate 

(decline) ll'as -8.1 ± 0.5% decade· ' . Even th o~gh humanprod uced. ozone-destroying halogen compound s have begun 

TABLE 4. 1. U.S. Dobson Ozone Spectrophotometer Station Net\\'ork for 2000-200 I 

Station 

Bismarck. 1 orth Dakota 

Caribou. i\ taine 

Wallops Is .. Virginia 

Si\10 

Tallahassee. Florida 

Boulder. Colorado 

Fairbanks. Alaska 

Lauder. 1c11 Zealand 

!LO 

ash1 ille. Tennessee 

Perth. Australia 

SPO 

Haute Pro,·ence. France 

j\ tarcapomacocha. Peru 

BR\\' 

Fresno. California 

I Ian ford. California 

Period of Record 

Jan. I. 1963-present 

Jan. I. 1963-present 

July I. 1967-prcscnt 

Dec. 19. 1975-presenl 

i\ la) 2. 1964-1 o'. 30. 1989: 

No1. I. 1992-present 

Sept. I. 1966-prcscnt 

1\ larch 6. 1984-present 

Jan. 29. 1987-present 

Jan. 2. 1964-present 

Jan. 2. 1963-present 

July 30. 1984-prcsent 

Nov. 17. 1961-prcscnt 

Sept. 2. 1983-present 

Feb 26. 200 1-prcsenl 

June 6. 1986-present 

June 22. 1983-:--tarch 13. 1995: 

i\larch 15. 1995-presenl 

Instrument No. Agency 

33 NOAA 

34 NOAA 

38 NOAA . • ASA 

42 NOAA 

58 NOAA. Florida State Uni,ersity 

61 NOAA 

63 NOAA. Uni,crsit) of Alaska 

72 NOAA. National lnstilllte of \\'ater and Atmospheric Research 

76 NOA/\ 

79 NOAA 

81 NOAA. Australian Bureau i\lctcorolog) 

82 NOAA 

85 NOAA. Centre National de la Recherche 

Scicntifiquc. Unil'ersity of Riems 

87 NOAA. Sen icio Nacional de 1-ktcorologia e Hidrologia 

9 1 NOAA 

94 NOAA 

86 
TABLE 4.2. Provisional 2000 and 2001 Monthly Mean Total Ozone Amounts (DU) 

Station 

Bismarck. North Dakota 

Caribou. i\laine 

Wallops Is .. Virginia 

Si\10 

Tallahassee. Florida 

Boulder. Colorado 

Fairbanks. Alaska 

Lauder. Ne\\ Zea land 

i\ILO 

Nasln ilk. Tennessee 

Penh. Australia 

SPO 

l laute Pro\ ence. France 

l\larcapomacocha. Peru 

BR\\' 

llanford. California 

Bismarck. North Dakota 

Caribou. Maine 

Wallops ls .. Virginia 

Sl\10 

Tallahassee. Florida 

Boulder. Colorado 

Fairbanks. Alaska 

Lauder. Ne" Zealand 

l\ILO 

Nasln illc. Tennessee 

Perth. Australia 

SPO 

llautc Provence. France 

I\ larcapomacocha. Peru 

BRW 

Han ford . California 

Jan. 

31-l 

328 

[2-1-1] 

# 

30.J 

272 

258 

308 

276 

270 

322 

290 

329 

[3.J2] 

323 

2-16 

305 

279 

2-18 

298 

268 

265 

332 

2-19 

305 

Feb. 

353 

369 

318 

2-17 

320 

259 

267 

309 

250 

267 

(262] 

322 

381 

[365] 

297 

2-18 

# 

335 

[-110] 

26 1 

252 

289 

258 

233 

325 

(250] 

[358] 

326 

j\ larch Apri I 

3-18 

356 

339 

2-16 

337 

391 

253 

:m 

305 

266 

[2-16) 

25.J 

[.J03] 

318 

371 

[39-1] 

3-18 

2-12 

330 

.j 17 

260 

267 

319 

265 

331 

[2.J6) 

-123 

31-l 

3.J 1 

387 

[327] 

2-19 

F 

311 

393 

272 

288 

318 

269 

[2-18] 

[2-19) 

396 

299 

380 

[.J02] 

3-1 2 

2-1.J 

I: 

330 

390 

271 

283 

[282] 

267 

365 

252 

407 

3-13 

:\lay 

:!000 

336 

359 

336 

252 

301 

389 

279 

278 

313 

282 

[237] 

2-17 

390 

305 

JOO/ 

(3-16] 

3+1 

2-13 

328 

297 

287 

278 

21-l 

3-12 

[2-16] 

-103 

315 

June 

327 

3-1 1 

[311 ] 

252 

310 

336 

303 

271 

298 

29-l 

245 

335 

306 

(296] 

(325] 

317 

239 

31-l 

338 

279 

338 

272 

223 

333 

3-10 

30-l 

300 

335 

[312) 

257 

302 

326 

319 

265 

301 

311 

[231] 

2-13 

[31-1) 

303 

299 

3-18 

315 

238 

:; 

297 

325 

270 

316 

293 

2-19 

322 

316 

30-l 

Aug. 

293 

318 

302 

256 

298 

296 

331 

26.J 

29-1 

31-l 

[226] 

259 

287 

298 

292 

[307] 

308 

245 

F 

290 

309 

35-1 

271 

311 

301 

[298] 

292 

293 

Sept. 

287 

30-1 

286 

260 

27-1 

290 

362 

25-1 

281 

320 

[295] 

262 

290 

282 

282 

285 

253 

270 

311 

3-16 

263 

29 1 

327 

3 15 

278 

Oct. 

287 

292 

279 

259 

273 

339 

364 

25-l 

26-l 

29-l 

186 

292 

258 

[285] 

280 

294 

[293] 

259 

279 

330 

357 

251 

29 1 

33 1 

139 

278 

271 

NO\. 

312 

280 

278 

259 

282 

[339] 

329 

25 1 

26-l 

27-l 

287 

285 

25-l 

273 

282 

275 

267 

t/ 

276 

[321] 

328 

239 

273 

168 

286 

26-l 

Dec. 

332 

33-l 

303 

2-17 

302 

285 

238 

293 

276 

322 

295 

25-l 

276 

318 

267 

296 

301 

232 

269 

(289] 

238 

286 

287 

Monthly mean OLonc \alucs in square brackets arc dcri\ed from obser\'ations made on fewer than 10 days per month. 

- . no data: 11. data are too sparse for meaningliil monthly a'crages. 

10 dec line Yery slow ly in the stratosphere. ozone amounts 

have nol shown any sign of recovery 10 their pre- l 970s 

lcYcls. This is expected because al the South Pole there is 

more than enough c hlorine and bromine in 1he stratos phere 

10 destroy mos! of lhe ozone in lhe 14- 10 22-km allitude 

range during the spring (see section 4.1.5 ). 

4.1.2. Ui\IKEllR OBSERVATIONS 

Umkehr obscr\'alions made wi1h the Automated Dobson 

Network instruments continued in 2000 and 2001 at 

Boulder. Colorado: llaule Provence. France: Lauder. Ne"' 

Zealand: l\launa Loa Observatory (M LO). Ha\\'aii: Pe nh, 

Western A ustralia: and the Geophysical Institute. University 

of Alaska. Data processing has been completed for 

87 

Boulder. Haute Provence. La uder. and the Geophysical 

lns1 itu1e through September 200 I. and the Ycrtical profiles 

arc a\'ailable from \\IOUDC. P rocessing has a lso been 

completed through June 200 1 for M LO. Problems al Perth 

ha\'e yet lo be rcsoh·cd. 

4.1.3. CALIBRATIO:'\ OF DOBSO\' 

S PECTROPHOTOl\IETERS 

Seven Dobson ozone spectrophowmelers in the CMDL 

network, as we ll as eight ot hers, were cali brated during 

2000 and 200 I. Table ~.3 I is ts al 1 the instruments 

calibrated and 1he result ing ca libration difference expressed 

as a percent ozone difference. This perce nt difference is 

between the ozone calcu lated from the tes1 and from the 
400 

~ 

:::> 

0 

~ 300 ., 

c 

0 

N 

0 

0 200 

0 

t100 

1960 1970 1980 

Dote 

1990 

0 

2000 

Fig. 4.1 . Monthly mean (0 ) and model (solid line) total ozone at SPO. 

The model accounts for the seasonal. quasi-biennial. solar. and detrended 

temperature dependencies in the data. 

50 I T 

... . 

-' ... ~ 

:::> I ~· \ .. :~~ :~ : ·t.t': Cl Ot .... 

0 . :;) 

:'S! 

., "' t t .· er: -50 ., 

c 

0 

N I 

0 

100 ~ · . . . ' 

l L 

1960 1970 1980 1990 2000 

Dote 

Fig. 4.2. 0Lone residuals(+) at SPO after removal of known variations. 

and the tendency cune (solid cun•e) found from the filtering of the 

residuals. The dashed curves show the 95% confidence limits about each 

point on the curve. 

standard instrument, using the measurements based on the 

most common observation type (ADDSGQP). The value is 

then averaged over μ (optical path length through the 

atmosphere, calculated from solar zenith angle) va lues of I, 

2, and 3, and normalized 10 a tota l ozone va lue of 300 

Dobson units (DU). This number represents the instrument 

measurement status before any repair or calibration 

adjustment is made. The table a lso lists the loca tion of the 

calibration and the standard instrument used. The Boulder 

station instrument is normally compared with the standard 

whenever intercomparisons are made. The MLO station 

instrument is compared with the Primary Standard (0083) 

each summe r. The Primary and Secondary Standards are 

88 

10 

5 

'- 0 0 

., 

>-

......... 

:::> 

a -5 

- 10 

- 15 

1960 1970 1980 1990 2000 

Year 

Fig. 4.3. Instantaneous gro\\1h rate of total column ozone (solid curve) at 

SPO, found by differentiation of the tendency cune shown in Figure 4.2. 

The dashed curves show the 95% confidence limits estimmed with a 

bootstrap method. 

compared twice yearly. These instruments arc maintained 

to within ± I% of the Primary Standard. 

CMDL participated in international Dobson spectrophotometer calibrations at the South African Weather 

Bureau in Pretoria, South Africa, in 2000 and at Lauder, 

New Zealand, in 200 I as pa rt of its role as the World Center 

for Dobson Calibrations. The J apanese regional standard 

f)ohson instrument was calihrated at M LO during AugustSeptember 200 I. 

4.1.4. SURFACE Ozo 'E 

Observations of surface ozone were continued at each of 

the four baseline observatories, Barrow Observatory 

(BRW), MLO, Samoa Observatory (SMO), and SPO, as 

well as at Niwot Ridge, Colorado; Westman Islands, 

Iceland ; and Arrival Heights, Antarctica. In June 2000 a 

TEI Model 49C ozone analyzer was installed at Summit 

Station, Greenland. Data from BRW, MLO, SMO, and SPO 

have been processed th rough 200 I. The monthly mean data 

for the four sites are given in Table 4.4 for 2000 and 200 I. 

Revised data for 1998 and 1999 for BRW and data for 1999 

at M LO are also included. For M LO the average is based on 

downslope ( I 000-1800 UTC) data. The data system at 

SMO experi enced a number of outages after the 

meas urements were restarted in 1997 after about a 15-mo 

gap that included all of 1996 and the first 3 months of 1997. 

Most of the data for 1997 and 1998 have, however, been 

recovered from a backup paper c hart record. 

Trends have been computed for each of the lo ng-term 

data sets (Figure 4.4 ), by the methods described in Harris et 

al. [2001], modifi ed to remove effects of the seasona l cycle, 

surface temperature, and autocorrelation before the trend is 

fitted. As an example, Figure 4.5 shows the monthly 

surface ozone data and the mode l fit for M LO. 

The numerical trends are summari zed in Table 4.5. The 

standard errors are determined by a Monte Carlo tec hnique. 

At BR W surface ozone amounts we re generally increa sing 
TABLE 4.3. Dobson Ozone S p ectroph otom eters Calibrated in 2000-200 I 

lm1rument Original Calibration Calibra1ion S1andard 

S1:11ion Number Date Com:c1ion (0 o) Number Place 

:!000 

Tamanrassel. Alg1ma II Jul) 22. 1993 - 2.-1 65 Pretoria. South Afnca 

\ laun. Botswana (propo~ed) 15 NA NA 65 Pretoria. South Africa 

Lni\crsit) of'Jmrob1. Kcn)a 18 :-.tarch 7. 1995 -0.2 65 Pretoria. South Africa 

Seychelles 57 1988 2.0 65 Pretoria. South Africa 

Irene. South Africa 89 Febmal') 12. 1997 -0.8 65 Pretoria. South Africa 

Springbok. South Africa 132 Febnml') 11. 1995 Calibration broken 65 Pretoria. South Africa 

L,gos. •igeria 5703 Jul) 22. 1993 - -1.-1 65 Pretoria. Somh Africa 

,\dmunscn-Scotl. An1arctica 82 NA N'/\ 83 Boulder. Colorado 

](}()/ 

Bismarck. l\orth Oal-.ma 33 April27.1995 -0.7 83 Boulder. Colorado 

Caribou. :-.lainc 3-1 Oc1ober 5. 1995 -0.3 65 Boulder. Colorado 

Nash\ illc. Tennessee 79 October 3. 1995 +1.0 83 Boulder. Colorado 

Samoa -12 Febmal') 1997 -1.1 83 Lauder. NC\\ Zealand 

Lauder. 1

ew /.ealand 72 Febmal') 1997 +0.2 83 Lauder. NCI\ Zealand 

Perth. Australia 81 Fcbmal') 1997 +0.9 83 L,uder. C\\ /caland 

\lclboumc. Aus1ralia (regional standard) 105 Febmal') 1997 0.0 83 Lauder. 'Jc11 Lealand 

TABLE 4.4. Monthly Mean S urface Ozon e Mixing R a tios (ppbv) 

Ytoa1 J•111. Feb. !\larch April i\ lay June July Aug. Sept. Oc1. 1\0\. lJec. 

Barron 

1998* 33.3 29.2 23.5 26.7 22.6 16.3 2-1.-1 21.7 2-1.9 30.0 33.-l 30.7 

1999* 29.5 28.3 13.0 9.-1 23.3 :n.4 18.7 19.2 22.3 31.1 29.9 30.6 

2000 27.-1 27.2 19.3 10.0 t 1.3 2-1.4 17.9 19. 1 23.6 30.9 35.2 30.8 

2001 30.0 31.3 17.3 16.9 23.3 20.4 2 1.4 25.4 3-1.9 34.8 33.7 

.I fa1111a Loa (I 11011-I 800 UTCJ 

1999 -13.1 -18.5 48.-1 54.9 -I-I.I -11.6 -18.3 35.9 -16.2 39.4 38.5 36.0 

2000 -10.8 -13. I 46.9 53.8 -11.0 -15.5 36.2 37.2 33.1 33.6 -11.3 

2001 39.8 -10.I 49.-l 51.6 -16.7 37.2 3-1.9 39.0 33.8 -18.3 37.0 -11.7 

So111'1 Pole 

2000 26.5 19.8 19.8 2-1.3 28.7 31.4 32.3 3 1.8 32.0 27.5 29.1 32.0 

2001 27.3 21.6 20.5 23.7 28.0 31. 1 3-1.5 33.6 33.0 28.2 30.2 28.5 

Samoa 

1995 8.-1 7.5 5.9 12.0 18. 1 19.7 17.7 12.7 13.I 

1996 

1997 8.2 15.3 23.7 16.5 15.7 1-1.5 11.8 I I. I 10.6 

1998 6.8 6.7 7.7 13.5 15.3 16.3 21.8 17.5 15.0 13.6 10.2 10.6 

1999 9.1 7.3 7.3 17.6 13.9 16.9 16.2 15.1 13.8 8.2 

2000 5.0 8.4 -1.9 6.6 7.5 15.7 16.7 15.2 1-1.3 15.-1 11.7 9.6 

2001 7.8 8.3 5.9 9.3 17.6 13.3 15.2 18.9 19.I 16.8 I 5.5 10.9 

S11111111i1. Gree11/a11d 

2000 5.J.8 -12.8 -14.8 -14.4 41.3 43.0 

2001 -12.1 -1 2.2 -15.I -15.7 -19.9 49.3 -1 2.8 46.2 -11.9 -16.6 -11.9 41.6 

-. no data. 

*Data for 1998 and 1999 arc n:' iscd. 

89 
20 

~ 

> 

J:J 10 a. 

~ 

0 

:J 

't:I 0 'iii 

.. 

a:: 

.. 

c 

0 

N -10 0 

20 

~ 10 a. 

a. 

.. . .. .. 

.· : ..; . ~ 

1975 1980 1985 1990 1995 2000 

Dote 

• • J • ··. g _ .. oi:~ ~. . __ ~ Or~~:=-~--ti~~~~c:;;'~~:i'f.~~-;::.~_;::,.,c:::::~ 

a:: "' 

Q) 

c 2 -10 0 

i 

-20~~~~~~~~~~~~~~~~~~~~~ 

1975 1980 1985 1990 

Dote 

1995 2000 

(a) 

(c) 

20 

~ 

> • • : I • • # ..,. 

·:· :~ {/~::: ;, i.?jfs J:J 

a. 

a. 

~ 

0 

:J 

't:I 

'iii 

a:: "'

"' .· !-· ... 

c 

0 

N -10 - 0 

- 20 _ ~ 

1975 1980 

20 

~ 

~ 10 a. 

a. 

~ 

0 

:J 

't:I 

'iii 

a:: "' 

Q) 

c 

2 - 10 0 

. . : +•··'"" ~:: ... : ...• :,,. . r:: ........ 

-... ~ 

1975 1980 

· .. : ' .. · 

1985 1990 

Dole 

1985 1990 

Dale 

1995 

1995 

2000 

(b) 

., 

;, 

2000 ! 

(d) 

Fig. 4.4. Residual (+) and 1endency curve (solid curve) of surface ozone mixing ratios at (a) BR W, (b) M LO, (c) SMO, and (d) SPO. The solid curve is 

a smooth lit to the filtered residuals. The dashed curves give the 95% confidence interval for the lit at each point. 

r 

~ 

> 

J:J 

a. 50 ~ 

a. 

~ 

., 

c 

0 40 - N 

0 

30 

20 _ 

1975 1980 1985 1990 1995 2000 

Dale 

Fig. 4.5. Monthly mean surface ozone (0) and the modeled result (solid 

line) for MLO. 

90 

TABLE 4.5. Average Growth Rate and Standard Error in Surface 

Ozone Mixing Ratio (ppbv yr"

1

) at Four CMDL Sites 

Trend 

Standard error* 

BRW 

O.Q7 

0.04 

MLO 

0.1 5 

0.06 

*Determined by a Monte Carlo technique . 

SMO 

-0.02 

0.04 

SPO 

-0.01 

O.o3 

in the 1980s and early 1990s but have declined somewhat in 

recent yea rs. At MLO there has been an overall increase, 

but after relatively higher ozone amounts in the late 1990s, 

the past 2 years have had lower values. At SMO ozone 

mix ing ratios have remained relatively unc hanged. The 

signi Ii cant decline at S PO through the 1980s and early 

1990s has nearly recovered in recent years with little overall 

change now evident. A recent study [Cra11'.ford et al., 200 1) 
shO\\S that at SPO d uring the summer there is 'igorous 

photochemical production of oLone i1n oh ing the release of 

nitrogen oxides from the deposit of nitrogen-bearing 

compounds on the snow surface. This quite likel) has 

minimal impac t on the O\'erall tropospheric ozone burden at 

SPO (or O\er Antarctica) but does pla) a role in the 

reduction of the amplitude of the surface O/One seasonal 

cycle. 

4.1 .5. OZO:'\ESONDES 

Tab le -t.6 lists the CMDL ozonesonde sites for 2000-

200 I. Weekly ozonesondes we re launched at eight sit es. 

and daily OLonesondes were launched during three int ensiYe 

campaigns, the Texas Air Quality Study (TexAQS), To tal 

Ozone Measurements by Satell it es. Sondes, and 

Spectrophotometers at Fairbanks (TOMS1F), and Sou thern 

Great Plains/Cloud and Radiation Testbed (SGP CART). 

SMO and Fiji missed several weeks due to suppl) 

shortages. A critical task of the ozonesonde project is the 

testing of oLonesonde performance al CM DL and in field 

and laboratory intercomparison projects. The Jiilich 

Ozonesonde lntercomparison Experiment (JOS I E-2000) 

held at the Research Center in Jlili c h, German), in 

September 2000 pro' ided the venue for one such 

intercomparison. Resu lts arc described in section 4.2. 1. 

All the sites and campaigns used electrochemical 

concent ration cel l (ECC) ozoncsondes purchased from ENSCI Corporation and Science Pump Corporation. The 

OLoncsondes used a 2% potassium iodide sensing solution. 

CMDL average pump efficiencies were used to process the 

data [Joh11so11 et al .. 2002] . Pu mp efficienc ies are 

dctcrmi ncd 1n CM DL's en viro nmental c hamber by 

measuring OLonesonde now rates at ambient pressures 

between I 00 and 5 hPa with an oil b ubble nowmcter. 

About I 0-12 new ozoncsondes per year are selected 

randomly for ca libration in the environmental c hambe r to 

ensure that the average pump efficiency remains consistent. 

Ozonesond es are sometimes found by hikers. farmers. 

etc .. after the night and returned 10 CMDL \\here they are 

c leaned and recond itioned. and the pump efficiency is 

measured. The sondes arc the n c hecked for accuracy 

against a UV calibrator at su rface pressure before they are 

no" n again. The Boulder site is the on ly location routinely 

using reconditioned OLo nesondes. Despite the additional 

testing. the recondit ioned ozonesondes s ho" a relatively 

high fai lure rate above 20 km, "here the measurements 

appear to be too lo\\. In 2000 nea rly 20% o f the 

reconditioned ozonesonde nights showed this problem 

abo\c 20 km. For com parison a typica l failure rate at a site 

w ith new ozonesondcs is about 3- 10%. 

In 200 1 the fai lure rate for the recond itioned ozonesondes 

at Boulder was reduced 10 13%. The decrease may be 

related to an additional c leaning procedure, started on May 

I, 200 I. that invoh es pressure nushing of the ion bridge 

bet\\ een the cathode and anode ce lls of the ECC ozonesonde 

sensor \\ ith disti lled water ( 1-m col umn head pressure). 

Pri or to use of the nushing procedure, the sensor cells were 

on ly soaked for several days, filling up both the anode and 

cathode chamber with 5 mL of distilled \\ater. 

Q, erall. the successful Boulder ozonesonde nights 

compare very well \\ ith the Boulder Dobson spectrophotometer. measuring "ithin I. 7 ± 4.4°/o when the constant 

mixing ratio extrapolation method i~ used 10 compute the 

residual ozone above the burst a ltitude of the balloon, and 

1.6 ± 3.6% when the solar backscaller ultraviolet (SBUV) 

residu al tables fro m All.Peters et al. [ 1997] arc used. 

Since 1986 the ozoncsondcs nown at S PO have provided 

a detailed look at the yearl y ozone hole development. 

Ba I loonbornc ozonesondes are launched once per week 

throug hout the year, but the frequency is inc reased to two or 

more per week o nce the first signs of ozone depiction 

appear in late August, and then to C\ cry o ther day as the 

ozone hole minimum approaches. Figure 4.6 shows the 

typical pre-ozone-ho le profiles during the winter compared 

with the minimum total column OLOne observed in late 

September. The ma in ozone depiction layer at 14-21 km 

continues to show near-complete ozone destruction each 

TABLE 4.6. Summary of 2000-200 1 Ozonesonde Sites, Projects, and Tota l Number of Sondes 

2000 2001 

O/oncsondc Sites To1als Dates Totals Dates Project - ---

Stmion (11·eek/y) 

13oulder. Colorado 60 Full year 51 Full year NOAA long tem1 

MLO 46 Full year 61 Full year NOAA long tem1 

SPO 68 Full year 71 Full year NOAA lo:ig tem1 

Fiji 34 Full year 36 Full year PEM Tropics/SI IADOZ 

SMO 43 Full year 35 Full year PE~I Tropics/SI IADOZ 

Trinidad llead. California 47 Full year 44 Full year NOA/\ "I lcalth of the A1mosphere" 

1 unt~\ ille. Alabama 52 Full year 47 Full year NOAA "Health of the Atmosphere" 

Galapagos 50 Full year 50 Full year SOWER SI IADOZ 

!111e111i1·es (- dai(1·1 

I louston. Texas 27 Aug. 18-Scpt. 14 TexAQS 2000 

Fairbanks. Alaska 30 arch 20-April 25 TO\IS'F 

Lamont. Oklahoma 7 Aug. 27-Sept. I SGP CART 

PE:>-1 Tropics. Pacific Exploratory ~lission in the Tropics: SHADOZ. Sou1hem Hemisphere Additional Ozonesondes: SO\\ ER. Soundings of Ozone 

and Water in the Equatorial Region. 

91 
40 

35 

30 

~25 

~ 

~ 20 ::::> 

1-

5 15 

<{ 

10 

5 

0 

- 23 AUG 2000 251 DU 

- 29 SEP 2000 96 DU 

0 5 10 15 20 0 

OZONE (mPa) 

- 06 JUL 2001 271 DU 

-26 SEP 2001 100 DU 

5 10 15 20 

OZONE (mPa) 

Fig. 4.6. SPO ozonesondc profiles measured in (a) 2000 and (b) 2001 

showing the prc-o7onc-hole profiles in austral "inter and the minimum 

total column ozone profiles in late September. Total column ozone 

values (DU) arc given for the dates shmrn. 

year. Years 2000 (Figure 4.6a) and 200 1 ( Fi gure 4.6b) were 

similar in total column ozone minimums: 98 ± 4 DU on 

September 29 and 100 ± 4 DU on September 28, 

respectively. These minimums were about 7- 10 da ys earlier 

than the average minimum date observed at SPO. The 

recovery, howeve r, occurred muc h sooner in 2000 than in 

200 I because in 2000 the polar vortex deteriorated and 

shifted away from South Pole. Total column ozone was 

already at 259 DU on November 3, 2000, but did not exceed 

220 DU until December 8, 200 I (Figure 4. 7). 

JOO • • 

• 

350 

;,_, 

Cl 300 

.. 

c 

0 250 

N 

0 

c 200 

2 

0 150 

'-' 

Jul I Aug I Sep I Oct I No\' 1 Dee 1 Dec 31 

Fig . .J.7. SPO total column ozone (DU) measured by ozonesondcs 

during the development and recovery time period of the Antarctic ozone 

hole. The 1967- 197 1 measurements were made prior to the existence of 

the yearly ozone hole. 

92 

Twenty-seven ozonesondes were flown at I louston, 

Texa s, from August 18 to September 14, 2000, during the 

TexAQS 2000 field program. The project inc luded several 

g roups measuring gaseous and particulate a ir pollutants 

from ground instruments and aircraft platforms. The 

ozonesondes were launched every afternoon at 1500 loca l 

time during the campaig n. Figure 4.8 shows the average 

ozonesonde profiles (and I standard deviation bars) 

measured during the late-summer project in Houston . The 

highest surface ozone mi xing ratio measured by the 

o zonesondes during the 4-wk period was I 13 ppbv on 

Augu st 31 , 2000. Total ozone averaged 29 1 ± 12 DU , 

which differed by - 1. 0 ± 3% from the NASA To tal O zone 

Mapping Spectrometer (TOMS) total ozone measurements. 

Seven ozonesondcs were launched from the U.S. 

SGP/CART site near Lamont, Oklahoma, during an inte nsive 

measurement campaign from August 27 to September 1, 

200 I. Total ozone remained very steady during the week at 

302 ± 4 DU measured by the ozonesondes. For comparison, 

TOMS measured 297 ± 6 DU. 

4.1.6. ATMOSPHERIC WATER VAPOR 

Water vapor measurements with balloonbome frost-point 

hygrometers continued at Boulder, Colorado. In addition water 

vapor soundings were made at Kinma. Sweden, during January 

and March 2000 as part o f the SAGE Ill (Stra tospheri c 

Aerosol and Gas Experiment) Ozone Loss and Validation 

ppmv 

5 10 

35 

30 

......... 25 

E 

..)C. 

-

w 20 

0 

::> 

I- 15 i= 

_J 

<( 

10 

5 

0 

0 5 10 15 20 0 50 100 150 

OZONE (mPa) (ppbv) 

Fig. 4.8. Average of 27 ozone panial pressure (left panel) and ozone 

mixing ratio (right panel) profiles measured during the l louston 

(TexAQS-2000) campaign. The error bars represent I standard 

deviation. 
! 

Experiment (SOL VE) campaign. The long -term record of 

stratospheric water vapor measurements at Boulder 

[Olt111a11s et al., 2000) through 2001 has been analyzed with 

the technique described by Harris et al. [200 I). The 

technique is also brieny described in section 4.2.3. The 

autoregressive model was modified for water vapor to 

inc lude on ly the seasona l cycle as an explanatory variable. 

The residua ls from the model with the long-term variation 

added back (Figure 4.9) have been fitted after the data were 

filtered in the frequency domain to produce a tendency 

curve. The changes in this tendency curve, found by di fferentiation , give the instantaneous growth rate curve 

(Figure 4. 10). The growth rate shows relatively large yearto-year variations, including periods of significant negative 

growth, but the average growth rate has been positi ve. The 

deviati ons of approximately ±0.5 ppmv are around an 

average water vapor mi xing ratio of about 4 ppmv. The 

largest positive excursions in the growth rate ( 1982, 1987, 

1992, and 1997) occur several months prior to warm-phase 

El Nino/Southern Osci llation (ENSO) events. The average 

growth rate over the 20-yr observational record has been 

0.04 ± 0.01 ppmv yr" 1 or about 0.9% yr1

. The increase in 

stratospheric wate r vapor at Boulder is confirmed by a 

number of other data sets including those from the I la logen 

Occultalion Experiment (HALOE) instrument on the Upper 

Atmosphere Research Satellite (UARS) [Rosenlof et al., 

200 I). Several data sets predating the Boulder record also 

suggest that wa ter vapor may have been increasing in the 

stratosphere for several decades [Rosenlof et al., 200 I]. 

During the winter of 1999-2000 the Third European 

Stratospheric Experiment on Ozone in 2000 (THESEO 2000) 

SOL VE campaign launched several water vapor soundings 

from Kiruna, Sweden. During two of the sou ndings (January 

and March 2000) multiple water-vapor-measuring instruments were nown in proximity in both space and time. On 

the night of January 27, 2000, the Lyman-a hygrometer of 

the Forschungszentrum-Jii li ch and the cryogenic, chilledmirror hygrometer of CM DL were nown within 2 hours of 

3r 

~ 21 > 

E 

Q. 

Q. 

~ 

0 

1 I- " " ·;;; 

a:: "' 

> 

3: 0 

-1 L 

1980 

T 

1985 1990 

Date 

1995 2000 

Fig. 4.9. Water vapor mixing ratio residuals(+) for the 16-24 km layer 

over Boulder, Colorado. The solid curve is a lit to the filtered monthly 

residuals. The dashed curves represent the 95% confidence interYal 

based on the application of a Monte Carlo technique. 

93 

.._ 

0 

"' >-

0.5 

-;;- o.oi-~;-~--t t-if-lr?'---+--+- -+-+-+-1'---4

E 

Q. 

Q. 

-0.5 

- 1.0 .__ ___ ..._ _ __ _._ ___ __.. ____ ..__ _ _J 

t980 1985 1990 

Year 

1995 2000 

Fig. 4.10. The instantaneous (monthly) growth rate of water vapor (solid 

curve) in the 16-24 km layer over Boulder, Colorado. The dashed curves 

give the 95% confidence interval of the growth rate. 

each other. The resu lts agreed very closely in both absolute 

amount (d ifferences <5%) and replication of small 

structural features in the profile [Schiller et al., 2002). 

4.1.7. ATMOSPHERIC TRANSPORT 

The CM DL iscntropic trajectory model is used to 

understand better the role of transport in the distribution of 

trace species measured at the base I ine observatories, as well 

as those measured on ships, on aircraft, and at other 

experimental sites. The standard gridded meteorological 

data used as input to the CM DL trajectory model come from 

the European Centre for Medium-Range Weather Forecasts 

(ECMWF) through the National Center for Atmospheric 

Research (NCAR). These data usually become ava ilable 

about I month after collect ion. Sixteen years of 

meteorological data ( 1986-200 I) are now available on a 

CMDL se rver. The trajectory program is automated so that 

obtaining large volumes of trajectories (e.g., for a site 

c Ii ma to logy) is st ra i gh l forward. 

The trajectory input dat a are fairly coarse because of 

storage and processing constraints. The data have a 

hori zontal resolution of 2.5° latitude x 2.5° longitude. a 

vertical resolution of 14 levels (from surface to JO hPa), and 

a temporal resoluti on of 12 hours. Trajectories produced 

with these data are not suitable for diagnosis of mesoscale 

transport, but rather they track large-scale regional airn ow. 

The gridded winds are int erpolated kinematically to 

isentropic surfaces with the specification of arrival he ight, 

arrival pressure, or potent ial temperature. A desc ription of 

the isentropic model is on the web 

(http://www.cmdl .noaa.gov/ ozwv/traj/traj info.html). The 

method of wind interpolation to the isentropic surface is 

detailed in section 3.13.4 of S11111111my Report No. /I 

[llarris and Bod/wine, 1983). 

Trajectories for various sites of interest are provided in 

real time on CMDL's trajectory website (htt p:// 

www.cmdl.noaa.gov/ozwvllraj). CM DL scientists and 

co ll aborators arc encouraged to contact the project leader to 

request a new site be added to this group. These traj ectori es 

are made with meteorological data downloaded twice daily 
from the National Centers for Ell\ ironmental Prediction 

(NCEP). The differences between the ECMWF and NCEP 

data sets arc usually slight. but to amid confusion. it is 

recommended that the real-time trajectories be used onl} as 

a first look. Trajectories for publication should be based on 

the ECMWF data. 

A nc\\' feature on the website is the capability to plot 

trajectories from the observatory archives (http: \\ \1 \1. 

cmdl.noaa.gO\ OL\I \ traj siteplot.html). The archiYes contain ECL\I \VF traj ectories arriving at the obsen atorics for 

1986 through the last date of aYailablc data (I or 2 months 

prior to the present). Sc\cral arri\al altitudes arc provided. 

The user may obta in Postscript Ii !es and print the 

trajectories. Another ne\\ \\'cbsite (http: \\'\1 \1 .cmdl.noaa. 

go\/ ozwv traj tchentry.html) allows a scientist to format the 

input parameters for a set of traj ectory calculations and mail 

this information to the project leader. 

Trajectories have been used to i11\ estigatc the 

relationships of trace gas and aeroso l measurements to their 

sources and sinks. Some studies utiliLing trajectories at the 

C'MDL obscn atorics are cited in section 4.1 .7 o f Ci\IDL 

S11111111a1:1· Report No. 14 (Ho/11101111 et al .. 1998). More 

recently. llarris et al. ['.WOO] analpcd trace gas correlations 

during \I inter dark periods at BR W with the use of 

trajectories. These papers arc also listed on the web 

(http: \1'111\.cmdl.noaa.go\ 'ozw\ /traj papers. html). 

4.1.8. ST ~ATOSP ll ER C AEROSOLS 

The M LO lidar measurements of aerosol backscatter and 

tratospheric mesospheric temperature continued during 

2000 and 200 I. The frequency of measurements \I as about 

42 per year, similar to pre\ ious years. The record of M LO 

total stratospheric integrated aerosol backscatter since 1999 

is shown in figure 4.1 I. along with the record from the 

Boulder lidar. The same background levels and annual 

cycle continued and 11cre summarized b} Barnes and 

l!c~(i11w111 [200 I]. No aerosol increases from volcanic 

eruptions \\'ere identi ficd . 

., 

~ 

.. 0 

~ 

~ 

.. 

r: 

" u 

., 

°"' u 

m "' 

0 

., 

0 

<; 

<( 

't) 

J!! 

:! 

Cl 

"' 

~ 

0 

1999 2000 2001 2002 

Fig . .J.11. Lidar measurements of integrated aerosol backscatter (tABS) 

for the stratosphere. At 1'·1 LO the altitude range is 15.8 to 33 km: in 

Bou lder the range is tropopause to 30 km. 

94 

The Boulder lidar \1as installed in 1999 and operated 11 ith 

a single detector channel for all altitudes. IJccausc of the 

high-altitude 1ariability of the tropopausc. measuring the 

stratosphere pro1 cd to be a problem for the single channel. 

and a second detector was added and optimized for the 

troposphere in April 2000. Se\ era I Asian dust episodes 

were measured 11 ith this channel in spring 200 I. The 

Boulder data sho11 much more variability than the M LO 

data. The annual cycle of stratospheric aerosol abo1 e 

Boulder is in phase with that of l\I LO. peaking in th e 

winter, but has a much larger amplitude. Much of th e 

winter increase in the stratospheric aerosol layer above 

Boulder is due to the lo\\'ering of the tropopausc height 

(from 15 km in summer to I 0 km in winter). A 

stratospheric layer is much harder 10 idcnti fy abo1 e Boulder 

where there are often larger aerosol concentrations in the 

upper troposphere than in the stratosphere. The tropopause 

height at 1'1 LO ( 16 km in summer and 17.5 km in 11 inter) 

rnrics much less than that of Boulder. and the M LO 

stratospheric layer is always clearly defined because the 

upper troposphere generally has very small aerosol 

concentrations. The variabi lit} of the peak scattering ratio 

is larger at Boulder than at MLO (Figure 4.12). The peak 

ratio is usually sci era! kilometers above the tropopausc and 

may be a better quantity than the integrated aerosol 

backscatter (!ABS) for comparison of M LO and Boulder 

data. 

Work for a NOAA grant to make the rub} lidar 

stratospheric aerosol record available 10 researchers was 

completed in :mo I. The c111ire record since 1974 ll'as 

standardiLed and error estimates were included in the data 

files. The obsenations arc 11011 a\·ailable by anonymous ftp 

to the publ ic (mloftp.mlo.noaa.gov). Part of the work was 

completed by a local high school science teacher and high 

school student. 

One new measurement added lo the MLO lidar \1as 11ater 

1'apor. The Raman-shi fled wa1 c length due 10 water molecules was measured to obtain profil es from the station 

altitude lo approximately 14 km. The lidar is able to reach 

1.4 1-- Bould~ ML~ 

.2 

4iii 1.3 

0:: 

... 

QI 

~ 0 1.2 

-" "' 0 

Cll "' 

-" "' QI 1.1 

a.. 

1.J 

1999 2000 2001 2002 

Fig. -1.12. Lidar measurements of peak aerosol backscatter ratio for the 

stratosphere. The backscatter ratio is the total scattering (molecular + 

aerosol) di' ided b) the molecular scattering. A ratio of t .O is pure 

molecular scattering. 
altitudes above that of rad iosondes, and also measure 

aerosols simultaneously, whi ch is useful for cirrus cloud 

studies. A National Aeronautics and Space Administration 

(NASA)-funded program will use the lidar and sondes to 

va lidate water vapor, temperature, and ozone for the 

Atmospheri c Infrared Sounder (A IRS) satellite instrument 

to be launched in 2002. The measurement of water vapor 

profiles by lidar is limited by the weak signal in the cold, 

dry upper troposphere. New red-sensiti ve detectors and a 

new 74-cm-diameter mirror were installed to increase the 

water vapor signal. The optical support structure was 

extended to accommodate the long focal length o f the new 

mirror. The old ruby telescope was remounted at the same 

time to test new components. 

4.2. SPECIAL PROJ ECTS 

4.2.1. JOSIE-2000 

JOSIE-2000 was he ld at the Research Center, Hi lich, 

Germany, in September 2000, during two 9-day periods. 

The project, sponsored by the World Meteorological 

Organi zat ion (WMO), provided an exce ll ent opportunity to 

compare ozone pro fil e measurements from va rious 

ozonesonde groups, using slightly diffe rent ozonesonde 

preparation procedures, sensing solutions, or instruments. 

During JOSI E-2000, ozonesondes were tested in seven 

separate simulated flight conditions in an environmental 

chamber, with an ultraviolet (UV)-photometer as an ozone 

reference. The chamber accommodated four ozonesondes 

during each simul ation. Eight different groups parti cipated ; 

seven used ECC ozonesondes and one Japanese group used 

the KC79 ozonesonde. The test ing procedure was similar to 

the JOSIE-1996 campaign [Smit et al., 1998), where all 

participants brought their own ozonesondes and preparation 

equipment. 

Among the JOSIE pa rticipants, three different cathode 

sensor soluti on recipes were used , three pump-efficiency 

algorithm curves were used for data processing, and 

ozonesondes were from EN-SCI Corporation and Science 

Pump Corporation. CMDL used both Science Pump and 

EN-SCI ozonesondes. The only maj or difference for CMDL 

during JOS IE-2000 compared with JOSIE-1996 was the 

switch from the standard buffered I% Kl sensor solution, 

used by all ECC ozonesonde groups in JOSI E-1996, to 

unbuffered 2% Kl sensor sol utions. CM DL's measured 

pump efficiencies were nearly the same in both JOS IE 

campaigns. A comparison of the CMDL results at JOSIE in 

1996 and 2000 s howed that the unbuffered 2% KI sensor 

solution improved the stratospheric measurements, 

averaging about 6% greater than the UV-reference 

compared with 15% greater with the I% Kl. The agreement 

was not as good near the surface where the 2% Kl 

ozonesondes were about 8% too low. However, several 

calibrations in CMDL (in the laboratory and outside) 

comparing ozonesonde measurements to measurements 

made with surface instruments with UV techniques were 

consistently within ±2%. 

Figure 4. 13 shows one of the JOSI E-2000 simulations 

with both a model 2Z EN-SCI and Science Pump 6A 

ozonesonde. The profi le simulation, run in a sinusoidal 

95 

35 

30 

-

~ 25 -

Q) 

1J 

:l 20 ... 

-

<( 

c 

0 15 ... 

~ 

:l 

.§ 10 

Cf) 

5 

0 

- UV _reference 

2Z sonde 

6A sonde 

5 10 15 

Ozone (mPa) 

• d 

· 15 ·5 5 15 

% Diff. 

Fig. 4.13. Comparison of models 6A and 2Z ECC ozonesondes during 

JOSIE-2000 simulation experiments. Both ozoncsondcs used unbuffered 

2% Kl cathode-sensing solu1ion. The chart on the right shows the percent 

differences (UV minus sonde) between 1he UV-reference and bolh 1he 6A 

ozoncsonde (black c irc les) and 1he 2Z ozonesonde (squares). 

wave pattern, illustrates the general diffe rence observed 

between the two manufacturers of ECC ozonesondes. On 

average, the 6A model was about 4% lower than the 2Z 

model near the surface and nearly I 0% lowe r nea r the top of 

the profile. The UV-reference was approximately in 

between both ozonesonde profiles. 

4.2.2. DOBSO A D Ozo ESONDE MEASUREME TS 

AT FAIRBANKS D URI G TOMS3 F 

TOMS3F was a campaign to investigate the differences in 

total ozone measurements produced by ground-based and 

space-based instruments. The experime nt was prompted by 

differences as high as 4% between va lues reported by 

Dobson or Brewer stat ion s and the space-based TOMS. 

TOMS being higher. The difference is dependent on both 

total ozone and latitude. The campaign pe riod of March 

and April 200 1 coincides with high total ozone and low 
Sun, which appear to cause the differences. The experiment 

was funded primarily by NASA, and included CMDL, NASA, 

Meteorological Service of Canada (MSC), and University of 

Alaska, Fairbanks (UAF) instruments and personnel. 

Dobson Me" s11re111e11ts 

The Dobson instrument and the method of operation are we ll 

documented [Dobson, 193 1]. Briefly, the instrument measures 

the intensity differences of selected wave length pairs (called A, 

C, and D) in the UV by attenuating the more intense 

wavelength to match the intensity of the other. If the atmospheric ozone absorption coeffic ients for those wavelengths and 

the instrument extraterrestrial constant are known, the total 

ozone amount can be calculated from the difference in the 

intensity between the two wavelengths of a pair e ither on direct 

sunlight or light from the zenith sky. Normally, measurements 

on two pairs are made to reduce the effects o f other 

atmospheric constituents. Measurements using the A and D 

pairs on direct sunlight are considered the most accurate, and 

the results of other measurement types are normalized to the 

AD-pa ir type. Measurements using the C and D pairs on direct 

sunlight are used when the Sun is lower in the sky, i.e., higher 

solar zenith angles (SZAs). Measurements can also be made 

on the light scattered from the zenith sky, and ozone estimated 

from the results. If a series of measurements is made on the 

zenith sky as the Sun rises or sets (SZA changes from greater 

than 90° to 60°, or the reverse), the resultant time series of 

readings versus zenith angle has a characteristic shape that is 

related to the ozone distribution with height. This curve is 

called the Umkehr effect [Got::, 1931]. 

500 O AD083 

•8096 OS 

a 

475 0 

a ~ 

450 :::> 

0 0 

~ oj 8 c 

0 425 N 

0 

~ 0 0 I- ~ Q 400 0 

0 a ~ <> 

375 -iJ 

• 

350 

18 19 20 21 22 23 24 25 26 

March 2001 

During the TOMS3F campaign, measurements were made 

with both the normal Fairbanks station instrument, D063 

(an automated instrument), and the World Standard Dobson 

instrument, D083. D083 made measurements in the period 

March 20-April 3, 200 I; D063 made measurements 

throughout the campaign. This analysis concentrates o n the 

period when both instruments we re operational in 

Fairbanks, and stratospheric temperature data were 

available from the extensive bal loon ozonesonde campaign. 

D083 made 453 observations, 139 of which were AD-pair 

type, 138 were CD-pair type, and the rest were various 

zenith measurements. D063 made 656 observations over a 

longer period, 16 1 of which were AD-pair type, 131 were 

CD-pair type, and the rest were various zenith observat ions. 

Figure 4. 14 shows an overview of the total ozone 

measurements during the intensive measurement pe riod. 

Eight measurements of the Umkehr effect were made with 

both instruments operating coincident with ozonesonde 

flights. 

The measurements were reduced using the published 

instrument characteristics and ozone absorption in formation, and both the normal a lgorithm, which uses ozone 

coefficients based on a standard midlatitude ozone profi le 

assuming a -46.3°C stratosphere, and an a lgorithm from the 

actual stratospheric conditions measured by the balloon 

flights. The first discovery was a difference in the ozone 

calculated by the two instruments (A D-pair-type 

measurement), with D063 approxima tely 1-2% lower than 

D083 (Figure 4 .1 5). An investigation of quasi-simultaneous 

measu rements showed a calibration difference between the 

o AD063 e TOMSCorr'd :1: 8171 OS 

68007 OS D CMRSond1 IJ SBlN Sonde 

x 

a a 6. [J 0 

8 

g 

x 0 

0 8 

0 

27 28 29 30 31 2 3 4 5 6 

Ai>ril 2001 

Fig. 4.14. Total ozone measurements at Fa irbanks. Alaska. during the primary period ofTOMS3F. AD represents direct-Sun Dobson spectrophotometer 

observations from instruments D083 and D063; B are direct-Sun Brewer measurements; TOMS is the Total Ozone Mapping Spectrometer; and the 

ozonesonde totals are computed by the constant mixing ratio (CMR) residual method and by climatological averages based on solar backscatter 

ultraviolet (SBUV) satellite data. 

96 
~ 

5% 

~ 4% ::I 

.... 3% ti 

·= .... 2% 

• 

Cl) • .J::. 0 1% ---------------------------------------------------------------.-------------------------------- • • -.--------------------------------- •• 

• ~ • 0% 0 

0 

';'-1% () e -2% Cl) 

!E -3% 

"O 

c -4% Cl) 

() 

~ -5% 

Q. 

• • 

-6% -+-~~~~~~~"""T""~~~~~~~-....~~~~~~~---,.--~~~~~~~..-~~~~~~~~ 

350 375 400 425 450 475 

Average 0083 Ozone 

• 0083-8007 • 0083-8086 ... 0083-8171 

• 0083-0063 

--Average 0083-8171 

--------· Average 0083-8007 - · - ·-Average 0083-8086 

-------Average 0083-0063 

Fig. 4. 15. Average percent difTcrence between D083 (uncorrected for stratospheric temperature), and D063 (uncorrected) and the Brewer ins1rnmen1s, 

based on daily averages of direct-Sun observations, p < 3.2. 

two instruments that accounts for the differe nce at lower 

SZAs but not at higher SZAs. The unexpla ined difference 

is related to μX , whe re μ is the optical path length of the 

direct solar beam through the most UV-light-absorbing part 

of the atmosphere, and is calculated from SZA. μ is 

dimensionless and varies from l at SZA = 0° to approximate ly 12 at SZA = 90°. X is the total column ozone 

amount in Dobson units. Both factors control the UV light 

intensity as seen by the instruments at the time of the 

measurement. Investigations by scientists at UAF showed 

that this μX depende nce could be explained by scattered, 

off-band light w ithin the instrument. (The instrume nt is a 

doubl e prismatic monochromator. Multiple surfaces allow 

for multiple reflections, whi ch produce both spurious 

spectra and scattered white light in the optical path.) 

Because the D083 instrume nt, as we ll as the D063 

instrument, appeared to have some ~1 X dependence, a 

doubl e-grating monochromator Brewer 17 1 that has had the 

internal stray li ght measured independentl y was used as a 

re fe rence. This Brewer instrument's measured stray light 

was found to be very low. Because an apparent lac k of μX 

dependence of the CD-pair-type measurement in Figure 

4.16 was not ed as opposed to the μX dependence of the ADpair in Figure 4.1 7, a mode l was deri ved to evaluate 

internally scattered light using only the relationship 

between the C D- and AD-pair-type observations (Figure 

4.18). The physical alignment of several optical 

components during C-wavelength-pair measurements results 

in less scattered light in the optical path. 

97 

Considering the difference between the instruments ~1 

range: 3.2 or less), the average is approximate ly 3% between 

the Brewer B 17 1 results and Dobson D083 AD-pair results, 

5 

0 

-5 

-10 

-15 

x 

xx 

x x 

xx x>t<x 

x x x 

x 

0 l XX X ,JX xX 

{vx~ xx ~ X~ 00° Yx xx x~xx x~ xx x x ·.JI.. ><xx x &> x cf' o xx x x'I<:'"' o x x Q) xx 

o ~ ~x i ooo x oO o o o ~ f) _o x 0 o 8oQ 

xxx~<::Po ooo x rP oo 8 o xx 'O'/ 0 o l'.>o.. oo 0 CO 0000 00 00-0 

00 00 oo 

o 0 

0 O Raw Data 

0o 0 X Static 0 

800 1000 1200 1400 

Slant column 0 3 (DU) 

Fig. 4. 16. The difTerence between D063 CD-pair direct-Sun ground 

quartz plate observations and B 171 observations versus the slant column 

of ozone (μX). The open circles are the raw (reprocessed) Dobson data, 

and the crosses are the Dobson data corrected for the mean stratospheric 

temperature, known as the static correction. 
-10 

s 

e, 

..-

,...._ 

..- -20 

Cl) 

M 

c.o 0 Raw Data 

0 -30 Cl • Static 

x Dynamic 0 

-- Model 0 

-40 

800 1000 1200 1400 

Slant column 0 3 (DU) 

Fig . .J.1 7. The difference between D063 AD-pair direct-Sun ground 

quartl plate observations and the B 17 1 observations versus the slant 

column of ozone (μX). The open circles arc the raw (reprocessed) 

Dobson data. the fill ed triangles are the Dobson data corrected for mean 

stratospheric temperature, and the crosses arc the Dobson data corrected 

for both stratospheric temperature and known absorption nonlinearity 

arising from finit e slit widths. The solid cune is from a model that 

assumes 0.09% of the Dobson A-long light intensity is scattered into the 

Dobson A-short measured intensity. 

with Brewer measurements higher (Figure 4.15) using the 

normal analysis meth o d for Dob son measurements. A fte r 

the anal ysis incl uding the e ffect o f the co lder stratospheric 

temperature o n the ozone absorption co e ffi cients at the 

wavelengths used b y the Dobson instrume nt, the re rema ins 

an approx imate 2% difference. The wave len gths used by 

th e Brewe r instrument have been shown lo be indepe ndent 

of stratosphe ri c tempe rature, and Dobson-Brewer 

intercomparisons at sma ller ~tX (<900 D U) values and 

lower latitude sites w ith warme r stratosphe ric temper atures 

ag ree we ll. T he d ifferen ce at hig h e r ~tX can b e attributed to 

the effect of forward-scattered li g ht in the atmosphere in the 

Dobson instruments' fie ld of v iew, scattered light with in the 

Dobson instruments, o r a combination of th e two . 

Another co nc lusion of this campaign is that when 

selecti ng data. the μ X fac to r would be a bette r c riterion than 

the ~t value. Making such a cha nge in the selectio n process 

could h ave an effect o n trend analysis at high latitudes, so 

th e entire long -term data sets would have to be re-se lected. 

The Umkehr measurements with th e C-wavelength p air 

produced very similar o zone profiles from bo th instruments. 

though the profi les differed from the balloon profiles. The 

d ifferences can be attributed to the time difference between 

the measurements, the in formation content of the Umkehr 

measurement, and weaknesses in th e reduction algorithm. 

o11 e~ o11de Jifeas11reme11ts 

Thirty electrochemical concentration cell (ECC) 

o zonesond e instrume nts were Oown during the TOM S3F 

camp aign b etween Marc h 2 0 a nd April 25, 200 I. The 

o zonesondes provided verti cal profi Jes o f o zone con98 

1.08 

0 Raw Ratio 

1.06 -- Model 

0 

~ 1.04 0 

() 

1.02 0 

0 

oog~ 1.00 00 

800 1000 1200 1400 

Slant column 0 3 (DU) 

Fig . .J.1 8. The ratio between D063 CD-pair and AD-pair near-coincident 

obsen at ions plotted w rsus the slant column of ozone (~ X). The open 

circles are the ratios for the ra\\ (reprocessed) Dobson data, and the cun·e 

is from a model assuming 0.090-. stray light on the Dobson A-pair 

obsenation. and no stra) light on the C- or D-pair obsen•ations. 

ccntrat io n and an additi onal total co lumn ozone 

measurement for compa rison w ith the g round-based and 

sa tellite observations. The b alloo nbo rn e instruments were 

launched from the Uni ve rsity of Alaska, Fairbanks. every 

da y, with several d ays of two to three balloon Oig hts. 

Fig ure 4. 14 shows th at the ozonesondes measured slig htl y 

hig he r tota l ozone than th e other me thods, approximate ly 

4 .1 % hig he r than Dobson instrument D083 and 2% hig he r 

than TOMS measurements. Figure 4.19 shows th e ave rage 

ozon e partial pressure and mi x ing rati o meas ured during the 

campaig n. The most variability in the profiles was observed 

near th e o zone p eak, as indi cated by the standard d eviation 

ba rs. The ozonesondes showed very good prec ision up to an 

altitude of 34 km. 

The TOMS3F campa ig n was the first fi e ld project that 

used the EN -SCI Global Posi tioning System (GPS) interface 

board with ozon csondes. The o zonesondes used Va isala 

RS80-N radiosondes to measure pressure, temperature, and 

re lati ve humidity. whi le the GPS board collected latitude, 

longitude, and altitude data approximately every 5 seconds. 

The GPS altitude prov ided the location of the sonde , and 

thus w inds, during the entire flig h t. The GPS altitude 

proved to be very bene fi cia l in the correc tion o f the 

calculated geopotential height from the Vaisala p ressu re a nd 

temperature data. Below 25 km the two a ltitudes compa red 

very we ll, b ut abo ve 25 km the diffe rence (Vaisala 

geopotential - O PS altitude) was in th e range from - 200 111 

to + 1000 m. 

4.2.3. LONC-TERi\I TOTAL OZONE Tl{El\DS 

A new method was d eveloped to investigat e total ozone 

variations that a rc in the range of about 3 .5 yea rs to decad es 

[Harris et al., 2001]. The goal of the stud y was to c reate a 
35 

30 

25 ..--.. 

E 

~ --20 w 

0 

=> I- 15 

I-

_J 

<( 10 

5 

0 

0 5 10 15 20 0 

OZONE (mPa) 

ppmv 

5 10 

50 100 150 

(ppbv) 

Fig. 4.19. A\cragc OLonesondc partial pressure (left panel) mul mi,ine 

ratio (right panel) prolih::. measured during the TO:'\IS'F campaign al 

Fairbanks. Alaska. The error bars rcprc>cnl I standard de' iation. 

trend line that is some\\ hat flexible so that the recent 

decreases as wel l as the (probabl e) rcco,er) can be trac ked. 

The method combines traditional total ozone !rend-finding. 

i.e .. autoregressi\ C mode li ng (AR), techniques with trend 

analysis methods de veloped in CM DL by the Carbon Cycle 

Greenhouse Gases group . The intent was to first remove 

c:-.plained variations in the ozone. This step regresses total 

ozone to seasonal harmo nics. the solar cycle. quasi-biennial 

oscil lation (QBO) in equato ri a l stratospheric \\ inds, 

detrended tempera ture at I 00 and 500 hPa, and a cubic 

polynomial. The residuals of this fit are added back to the 

cubic function prior to the next step. Then a smooth curve 

is titted to the result ing data according to methods of 

Tho11i11g er al. [ 1989). "ith a filter chosen to remo' e pe riods 

in the data of fewer than about 3.5 years. The dcri\'ati\e o f 

this smooth ozone "tendency curve" is lhe o.wne gro'' th 

rate cun e. lntegra1io n of the g ro\\ th rate c urve gives the 

a\erage growth rate. Unce rta inties of the cunes and the 

gro'' th rate a\erage arc determined b) bootstrap techniques. 

First the method was applied to indiYidual station data 

from the Dobson total ozone network. These data arc 

archi,ed at \\IOUDC in Do\\ ns\ ie", Ontario, Canada. 

Figure 4 .20a shows total oLone monthl y means and the AR 

fit of explained 'ariation for Bismarck, North Dakota. 

Figure -L20b sho\\ s the total ozone tendency cun e '' ith 

99 

400 '-

~ 3~~ ~ 

300 ~ 

40 

20 

5' 

e. 

'iO 0 

'2 " 

"' ., 

Cl:~ -20 0 

~ ::> 

e. 

., 

'iO 

Cl: 

.c 

j 

e 

<.:> 

-40 ' 

10 

5 

0 

-5 

-10 

1960 

j \

1

(1!-, \1 1!11t1!i\!l1:1 l\tj H!!i _1 

b . 

... + + • +. '. 

c 

- / ' .... ' / / \ \ / ....... - ..... / ' / ' / ' 

' ,.. ' ' / \ 

- ' / 

1970 1980 1990 2000 

Fig. 1.20. Bismarck. 'lonh Dakota. total O/Onc data. (a) 0Lone month!) 

means (filled circles) and the AR lit (solid line). (b) Total oLone 

temlcnC) cun e (solid cune) with 95~o confidence limits (dashed 

cun es). Residuals combined "ith the cubic function from the AR fil are 

sho\\11 as plus signs. The points and the tendency cune ha\ e been 

adjusted so that the tendenc) cun·e starts m /era. (c) The grO\\ th rate 

cunc and 95% confidence limits. 

95% confidence limits for Bismarck. Residuals combined 

with the cubic fun ction from the AR fit arc also s hown. 

Fi g ure 4.20c sho\\ s the growth rate curve for Bismarck and 

the 95°0 confidence limits. A\eraging the monthly val ues 

a long this c un e gi\'cs an on:ra ll growth rate of 1.4 . 

decade·' for the period December 1962 through Decembe r 

2000. Bootstrap methods were used to determi ne a standa rd 

error (S.E.) of 0.2°·o decade·'. For the individual stations 

exami ned. total ozone decreases ranged from I to 2°10 

decade·' since the 1960s and from 2 to -l0o decade·! O\ er the 

period 1979-1997. 

Figure 4.21 a depicts the total 01one tendency curves for 

six midlatitude Dobson sites. The long-te rm Iota! OLone 

decrease is clearl y evident. wilh the ozone decli ne 

beginning in the early 1970s. Some of the stat ions share 

common fea tures (peaks a nd dips). The commo n features in 

the ozone tendency c ur\'es are accentuated in the growth 

ra1e curves for the four si mil ar midlatitude records 

(Ca ribou. Bismarck. Wallops Island. and Arosa) shown in 

Fi gu re 4.21 b. Whi le keeping in mind that the exact 

locations of ma'\ima and minima are some'' hal uncertain 
10 

S' 0 

Q. 

(ij 

~ -10 

Ql 

a: 

6 -20 

-30 

4 

-;::-

~ 

~ 2 

Ql 0 ~ ~ 

~ -2 

CJ 

-4 

2 

'C' 

& 

Ql 

a; 

a: 0 

~ 

~ -1 

CJ 

-2 

1960 1970 1980 1990 2000 

Fig. 4.21. Comparisons of lolal ozone tendency and gro\\1h rate curves. 

(a) Midlalilude tendency cunes for Bismarck, Nonh Dakota (solid red), 

Nashville, Tennessee (dolled green), Wallops Island, Virginia (solid 

green), Boulder, Colorado (dolled blue), Caribou, Maine (solid blue), and 

Arosa, Switzerland (dolled red). Tendency curves have been set lo zero 

on July 1967 (the beginning oflhe shortest record) lo aid lhe comparison. 

(b) Growth rate curves for four coherent midla1i1ude sites with the same 

colors as in (a). (c) Growth rate curves for the tropical sites. Samoa 

(red), Mauna Loa (green), and Huancayo (blue). 

because of the filtering process, it is noted that the 

coherence among these sites is maintained over their entire 

records. The growth rate curves for three tropical sites 

shown in Figure 4.2 1 c also have coherence, although the 

pattern is different from that o f the mid latitude curves. It is 

interesting to note that SMO's pattern leads that of MLO by 

more than I year. The two sites are separated by only 15° 

of longitude but lie on opposite sides of the equator. The 

causes for growth rate coherence are not known, though 

widespread meteorological and dynamical patterns are 

possibilities [Zerefos et al., 1994; Ziemke et al., 1997). 

Some consecutive cycles of the midlatitude growth rate 

curves match the solar cycle. This could be fortuitous or a 

hint at a possible secondary effect not accounted for by the 

fit to the solar index. 

100 

To further explore the total ozone growth rate coherence 

seen among the Dobson sites, CM DL obtained the TOMS/solar 

backscatter UV (SBUV) merged tota l ozone monthly data set 

(http://code9 I6.gsfc.nasa.gov/Data_services/merged/). These 

data cover all longitudes, and latitudes from 60°N to 60°S. 

Data are gridded 5° of latitude by I 0° of longitude and are 

avai lable with few data gaps from November 1978 through 

December 2000. In the data set there are 24 x 36 grid cells, 

each of which can be thought of as a separate site with a time 

series consisting of 266 months of data. Each of the 864 time 

series was processed in the same way that the Dobson station 

data were processed earlier. 

The results are compiled in Figure 4.22, which depicts 

the average growth rate in percent per decade over the 

entire grid. In this figure the cooler colors (green, blue, 

purple) denote re latively larger ozone decreases compared 

with the hotter colors (yellow, orange, red). In th e area 

near the tropics that is cross-hatched in white, the total 

ozone growth rate is not statistically different from zero. 

The greatest ozone loss rate (or negative growth rate) in the 

southern hemisphere (SI-I) is centered at 0°E and 50-60°S 

(>8% decade- 1). This may be a result of some asymmetry of 

the Antarctic continent and the preferred pattern of vortex 

breakup after the ozone hol e forms in the spring. The 

greatest loss rates in the northern hemisphere (N I-I) occur 

over Western Europe, Great Britain, Siberia, and the North 

Pacific (>3% decade1). 

The next step was to look at the tota l ozone time series 

averaged over 5°-latitude zones. Figure 4.23 shows the tota l 

ozone deviation since 1978. Th is plot is analogous to the 

tota l ozone tendency curves for the six sites shown in 

Figure 4.21 a. Again hot colors signify relatively more 

ozone. This plot shows a steady decrease in the high 

latitudes of the SI I. More than 35 DU of total ozone has 

been lost since November 1978 at 60°S compared with more 

than 15 DU at 60°N. The NI-I high midlatitudes have seen a 

slight recovery si nce the low point in 1995. The areal 

coverage of the region representing more than a I 0-DU loss 

has increased from about 40° and poleward in 1988 to about 

23° and poleward at the end of 2000. 

Figure 4.24 shows the instantaneous zonal growth rate for 

60°N-60°S. Seen in this plot are the growth rate evolution in 

time and the patterns of growth rate coherence. The 

instantaneous growth rate is not statistica lly distinguishable 

from zero over most of the warm colors (-2 to 2% decade1

) . 

Outside of this area, the largest loss rates (greatest negative 

growth rates) occurred in 1982, 1991 , and 1999 in both 

hemispheres. The largest loss rates of the time series (>9% 

decade1

) occurred in 1982- 1983 in the most southerly 

latitudes. Events that may have contributed to this decrease are 

the El Chich6n volcanic eruption, the declining phase of the 

solar cycle, and a very large El Nino event (peaking in early 

1983). Loss rates in 1991-1992 were very likely intluenced by 

the eruption of ML Pinatubo and possibly by the decline in the 

solar cycle. These reasons are not present during the high loss 

rates of 1999. It is interesting to note that the NI-I losses during 

1982 and 1999 peaked at 30°N rather than at higher latitudes. 

Finally, during 1995-2000 there was a positive growth rate for 

ozone (>2% decade"') in the high northern latitudes. Warm 

temperatures in the stratosphere and borcal fires may have 

contributed to this e!Tecl. 
-9 -8 -7 -6 -5 -4 -3 -2 

Growth Rate - %/decade 

-1 0 

Fig. 4.22. TI1e average total ozone growth rate in percent per decade for 

November 1978-December 2000. 

60 

40 

(I) 

"O 

" 20 § 

0 0 ., 

"' e E -20 

-40 

-40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 

Total Ozone Deviation (DU) 

Fig. 4.23. The total ozone zonal deviation in percent per decade since 

November 1978. 

60 

40 

-8 

~ " 20 

'" _, 

0 0 ., 

~ g-20 

-40 

-60 

1980 1985 1990 

Year 

1995 2000 

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 2 3 

Growth Rate - °lo/decade 

Fig. 4.24. The instantaneous zonal total ozone grm11h rate in percent per 

decade. 

101 

4.2-4. LONGITUDINAL AND TEMPORAL DISTRIBUTION 

OF DEHYDRATION IN THE TROPICAL TROPOPAUSE 

RECIO 

Balloonborne observations o f frost-point temperature and 

ozone at seve ra l equatorial locations provide an accurate 

data set of water vapor a nd ozone wi th high vertical 

resolutio n around the tropica l tropopause. Observat ions are 

a na lyzed here for San Cristobal, Galapagos, Ecuador, in the 

eastern Pacific; Juazeiro do Norte in northeastern Brazil ; 

alo ng a ship cruise in the we stern equatorial Pac ific; and 

Christmas Isla nd in the central equatorial Pacific. At San 

Cristobal, observations began in 1998 on a campaig n basis 

and are ongoing as part of Soundings of Ozone and Water in 

the Equatori al Region (SOWER) [Hasebe et al., 1999), with 

the most recent campaign in November-December 200 I. 

The observati ons are limited to ozone and wate r vapor. 

There is no direc t evid ence for the presence of ice particl es; 

however, supersaturatio n observed in most spring profiles 

combined w ith large temperature va ri ations during the 

observation period stron g ly suggest the presence of ice 

particles. Hi gh relative humidities we ll above ice saturat ion 

can force ice particle formatio n through homogeneous 

nucleation, and the subseq uent sedimentatio n of these 

particles would lead to the removal of wate r substance. 

Thus, the observations o f supersaturation w ith respect to ice 

imply dehydration, allowing a study of some of the 

c haracte ristic processes at the tropica l tropopause and of the 

regions that control the amount of water vapor entering the 

stratosphere . These processes are shown as a schematic in 

Figure 4.25 . 

• .. 

Large-scale ascent 

0 • Drying~rge:seale waves - - -

- _. • • ,. \.. ~ry g --Drying~ 

.... Cinus clouds 

Large-scale 

subsidence 

Deep convective regions Subsidence regions 

Fig. 4.25. Schematic of the transpon and dehydration processes across 

the tropical tropopause. The tropopause is indicated by the solid thick 

line; the tropopause transition region is indicated by thin lines above and 

below. Drying occurs at the temperature minimum close to the lapse-rate 

tropopause, induced by con\"cction, large-scale waves. and slow ascent. 

Breaking of large-scale waves is one of the sources of ozone in the 

tropopause transition region below the tropopause. The impact of the 

different deep convective regions on the transition region depends on the 

altitude reached by typical convection 11 ithin each region. 
Deep com ection in the western Pac i tic transports lo\\'er 

tropospheric air to th e tropopausc, dehydrating the air to 

\ Cry lo\\' mixing ratios. "hilc ma intaining high rclati\e 

humidit ies and low ozone concentrations [ 1'6me/ et al .. 

1995]. Do" n" ard mo tion in the lo" er stratosphere abo,·e 

regions of deep con\ection [Gage et al .. 1991: Slierll'ood. 

:WOO] ma) be respo nsibl e for the extremely steep gradients 

of water \apor and ozone obsened direct!) at the 

tropo pause. A\\ay from regions of deep comection. 

subsidence lo" ers the relati\ e humidity in the middle 

tropos phere: ho" e'er, the upper troposphere remains at 

high relath e humidities and low ozone \alucs indicati\e of 

the recent con,ectivc origin of the air. In regions where 

deep con,·ection does not reach the tropica l tropopau se or 

where subsidence pre\ ails, salllration and subsequent 

dehydration within the transition layer ma) still occur, 

dri' en only by slo". large-scal e a scent [ Vomel et al .. 2002]. 

Keh in wa' es and o ther large-sca le waves may contribute to 

the dehydration process in these regions [Fujiwara et al., 

200 I]. Not all equato rial regions sho" saturation, and some 

regions may no t participate at all in the dehydration of 

rising all". There is a strong seasonal cycle in the 

deh ydration process at the tropi cal tropopause. At San 

Cristobal. no ncom ective deh ydratio n was o bserved during 

the March campaigns. but not during the September 

campa igns. 

A transition region around the tro po pa use can be 

identified by the inc rease in re lati\ e humidity \\ ith altitude 

up to the tropopause [Vomel et al. , 2002]. in addition to the 

increase in 070ne [Folki11s et al.. 1999]. While wa' e 

breaking across the tropical tropopause and midl atitudc 

intrusions are sources for ozone in thi ~ transition region 

[Fujiwara et al .. 1998). the general up\\ard motion in the 

transition region dri' en b) the stratospheric extratropical 

pump [Ho/1011 e t al., 1995. and references therein) maintains 

a high relative humidity "ithin this laye r. The seasonal 

cycle of relati\ e humidity \\'ithin th e tran siti o n region is 

dri,en by the seasonal C)Cle of the stratospheric 

cxtratropical pump. In add itio n, the rclati\ e importance or 

different reg io ns for the dehydratio n process c hanges" ith 

season. Based on Ct-.IDL measurements from se,cra l 

equatorial sites. it appears that the zona l a\ c rage or the 

tropopause rclati' e humidity shows a seasonal cycle as 

well. Furthermore. the seasonal cyc le of the tropo pausc 

tempera ture s hows a rapid cooling bet\\ een Septembe r and 

December. The "ater 'apor mixing ratio of 6 ppm' , "hen 

ai r passed the tropi cal tropopause in September. is not 

found later at hig her altitudes when the nc\\ seasonal 

minimum at th e tropopausc is established (Figure 4.26). 

indica ting a secondary or continuing dehydration of this air 

th roug h December [ l'omel et al., 2002]. Since a\ eragc 

ve rti cal Yelocitics in the lower stratosphe re are signifi cantly 

larger during the northern winter. it appears that the 

northern ''inter mo nths play a stronger role than the 

northe rn summer months in the dehydrat io n of a ir entering 

the stratosphere. 

Considering that the tropopa use temperature in the 

equato rial eastern Paci tic during Septembe r is too 11·ar111 to 

allo\\ saturation and the presence of cirrus cloud s. reports 

o f sub,·isi blc c irrus in this region may indicate that these 

clouds are not ice c louds but rather a mixture o f nitri c ac id 

102 

30 

September 1998/99 

San Cristobal 

000 October 1964/ 65 

Trinidad 

25 November Trinidad 

1964/65 

November 1997 

Brazil 

s December ZOOO 

San Cristobal 

c, 

Q) zo -0 

:J 

:!:! 

.μ 

:.: 

15 

10 '--~--''----'----1--1.-L.1...L.LL~~-'-~-'--'--=o.....L--L...l...J 

1 10 100 

Mixing Ratio [ppmv] 

Fig. -1.26. De' elopment of the dehydration between September and 

December. The proliles at San Cristobal and Trinidad are the merage for 

all profiles of the month(s); the profile at Juazc1ro. Bralil. is a single 

profile. 

and water si milar 10 some types of stratospheric c loud s 

found in the winter po lar stratosphere. 

CMDL's analysis identified three different dehydration 

processes that can occur at the tropical tropopause. It also 

showed that 1101 all regions participate in dehydration of ai r in 

the tropopause transition region. Air entering the stratosphere 

\\ill most li ke!) ha\e experienced a mi xed history of the 

'ario us dehydration and mixing processes, making quantitatiYe 

modeling \Cry difficult. There is a regional preference as well 

as a seasonal pre ference for deh)dration. and the transport of 

"atcr 'apor into the stratosphere does not occur in a 

temporally and spatia ll y uniform manner. This is co ntrary to 

the analysis by Dess/er [ 1998], who suggested that theories 

including spatial and temporal pre fere nce ··arc no lo nger 

necessary.·· Newell 011cl Go11/cl-S1e1rnrt [ 198 1] suggested that 

air enters the stratosphere predominant!) o\·er the western 

Paci fie during the no rthern hemisphere \\'i nter and earl) 

spring. as well as O\ er the Indian Ocean during the mo nsoon 

season; the) called this phenomenon the "stratospheric 

fountain." I Iowe\·cr, the sharp gradients o f" ater 'apor and 

OLone at the tropopause in deep con' eeth e regions. as well as 

the offset bet\\ecn regio ns of deep con\'ection and regions of 

coldest tropopause temperatures [.\'ishida et al., 2000). 

indicate that the regions of deep conYccti on arc not 

necessarily "here air e111ers the stratosphere. The regional 

and seasonal pre ference for the dehydration process still 

needs to be quantified in detail. 
Deep convective regions play an important role as a source 

of air in the transition region below the tropopause. This air 

may be transported horizontally away from the area of deep 

convection before e ntering the stratosphere [Holton and 

Gettlemcm, 2001 ]. Furthermo re, overshooting deep convectio n 

may directly inject air into the lowermost stratosphere. If the 

tropopause temperature is cold enough, air in the transition 

region may be dehydrated further in nonconvecti ve regions. 

The extratropical stratospheric pump provides a zonall y 

averaged view, but there is no reason to assume that the 

vertical ascent in the lower tropical stratosphere is zonall y 

symmetric. CM DL's analysis has not addressed this issue, but 

studies showing descending motion above the deep convective 

regio ns in the maritime continent already indicate that there are 

important zonal asymmetries in the vertical ascent in the lowe r 

tropical stratosphere. It is plausible that cold tropopause 

temperatures also corre late with regions of stronger vertical 

ascent, which would not only imply a regional prefere nce for 

the dehydration o f air entering the stratosphere, but also a 

regional preference for the entry point. It is also important to 

point out that there has been a significant increase in 

stratospheric water vapor [Oltmans et al. , 2000) and, at the 

same time, a decrease in the tropical tropopause temperature 

[Zhou et al., 2001). These two trends are not easily 

reconcilable. They also show that the atmosphere that led to the 

formulation of the stratospheric fountain hypothesis has 

changed and that the conc lusions that are deri ved now will 

necessarily be diffe rent w ithout re futing the stratospheric 

fountain hypothesis. 

15 

10 

E 

~ ~ 

<!> 

-0 

::l 

...., 

...., 

::;: 

5 

J F M A M J J 

Month 

As a last point, the classifica tions "stratospheri c " and 

"tropospheric" for a ir that is respecti ve ly above and below 

the lapse-rate tropo pa use need to be questio ned . Air in the 

transition region has stratospheric sig natures, like higher 

ozone concentra tions and hig her vertical stabil ity tha n air in 

the middle troposphe re. A t the same time, this a ir has 

hig her values o f re lati ve humidity and typi cal tropospheric 

trace rs as we ll as the potential for cloud fo rma tio n. In this 

regio n there is a mi xture of both stratospheric a nd 

tropospheric air, and the questio n o f whethe r convection 

overshoots the tropo pause o r not sho uld be re placed by 

questions o f how deep convec tio n penetrates into the 

transitio n layer and how much nonconve cti ve and wavedri ven processes contribute to the makeup of the air in this 

region. 

4.2.5. Tropical Tropospheric Ozone 

Ozone vertical profile measurements o bta ined during 1995-

1999 from o zonesondes flown at Fiji, Samoa, Tahiti, and the 

Ga lapagos provide a pi cture o f ozone in the tropos phere over 

the tropical south Paci fie Ocean [ Oltmans et al., 200 I]. The 

seasona l variation at each of these sites is sig nificant. The 

seasonal behavior at the western Pacific sites is similar, with 

the Tahiti pattern typical (Figure 4.27). At sites in bo th the 

easte rn Pacifi c (i.e., Galapagos; Figure 4.28) and the western 

Pacific, ozone mi xing ratios are greatest at almost all levels in 

the troposphere during September-November and smallest 

during March-May. The vertical pro file has a re lati ve 

96 

90 

84 

78 

72 

66 

60 

54 

48 

42 

36 

30 

24 

18 

12 

6 

0 ppb 

A s 0 N D 

Fig. 4.27. Cross section of average ozone mixing ratios in the troposphere at Tahiti for 1995-1999. 

103 
96 

90 

Ill 

78 

72 

66 

........, 10 

E 60 

~ 51 

(i) 

" 10 :i 

...., 

::::; .1z 

< 

36 

5 JO 

2 1 

18 

I<! 

6 

0 ppb 

J F M A M J J A s 0 N D 

Month 

Fig. 4.28. Cross section of average ozone mixing ratios in the troposphere at Galapagos for 1998-1999. 

maximum at all the sites in the troposphere throughout the 

year; the largest mixing ratios are us uall y found near the 

tropo pause. This maximum is particularl y pronounced 

during September-November. On average, throughout the 

troposphere, the Galapagos site has larger ozone mixing 

ratios than the western Paci fi e sites. The enha nced ozone in 

the midtroposphere during September-November is 

associated with transport from the continents. In the 

western Pac ifi c this transport is usually from southern 

A fri ca (although I 0-day back traj ectories do not a lways 

reach the contine nt) but a lso may come from Australia and 

Indonesia. In the Gala pagos the ozone peak in the 

midtroposphere is associated with transport from the South 

Ameri can contine nt, and particularly from northern Brazil. 

High ozone concentrations within potentia l source regions 

and transport characteristi cs associated w ith the ozone 

mixing ratio peaks in both the western a nd easte rn Pacific 

suggest that these enhanced ozone mixing ratios result from 

biomass burning. In the case of the western Pacific sites, 

low ozone mi xing ratios in the uppe r troposphere are 

associated with transport that origina tes in the convecti ve 

western Pacific . In the Galapagos the lower ozone mix ing 

ratios in the uppe r troposphe re may be associated both w ith 

transport from the uppe r tropical troposphere in the western 

Pacific and a lso with convection in northern South America 

and Central America. 

104 

4.3. R EFERE CES 

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background aerosol over Mauna Loa Observatory, Geopl1ys. Res. 

Leu., 28, 2895-2898, 200 I . 

Cra\\ ford, J.1-1., D.D. Davis, G. Chen, M. Buhr, S. Oltmans, R. Weller. L 

Mauldin. F. Eisele, R. Shetter, B. Lefer. R. Arimoto, and A. 1 logan. 

Evidence for photochemical production of ozone at the South Pole 

surface, Geophys. Res. Leu., 28. 364 1-3644. 200 I. 

Dessler, A.E., A reexamination of the "stratospheric fou ntain"" 

hypothesis, Geophys. Res. Leu., 25, 4165-4168, 1998. 

Dobson, G.M.B., A photoelectric spectrophotometer for measuring the 

amount of atmospheric ozone, Proc. Roy. Soc., 43, 324-337, 193 1. 

Folkins. I., M. Loewenstein, J. Podolske, S.J. Oltmans, and M. Proffitt. A 

barrier to vertical mixing at 14 km in the tropics: Evidence from 

ozonesondes and aircrafi measurements, J. Geophys. Res., 104. 

22,095-22, 102, 1999. 

Fujiwara. M., K. Kita, and T. Ogawa. Stratosphere-troposphere exchange 

of ozone associated with the equatorial Kelvin wa\e as observed with 

ozonesondes and rawinsondes, J. Geophys. Res., 103, 19.1 73- 19.1 82. 

1998. 

Fuj iwara, M., F. 1-lasebe, M. Shiotani, N. Nishi, H. Vomel, a nd S. 

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3146, 2001. 

Gage, K.S .. J.R. McAfec, D.A. Carter. A.C. Riddle. G.C. Re id. and B.B. 

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177 1-1773. 1991. 
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Beil. Geophys .. 3 I. 119-154. 1931. 

1 larris. J.M .. and B.i\. Bodhainc (Eds.). Geoplrysical \fo11i1ori11g for 

Climatic Clra11ge .\'o. 11 S11111111m!· Repon 1981. 160 pp .. NOAA 

Erniron. Res. Labs .. Boulder. CO. 1983. 

llarris. J.i\I.. E.J. Dlugokencky. S.J. Oltmans. P.P. Tans. T.J. Corrna). 

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trace gas corre lations during Barro\\. Alaska. \\ i111cr dark periods. 

1986- 1997.J. Geophy1. Res .. 105. 17.267-17.278.1000. 

llarris. J.i\I.. S.J. Oltmans. P.P. Tans. R.D. hans. and D.L. Quine). A 

new method for describing long-tenn changes in total ozone. 

Geoplrys. Res. Lei/ .. 18. -1535-4538. 2001. 

I lascbc. F .. 11. Viimcl, i\I. Shio1ani. N. Nishi. S. Ohmans. T. Ogawa. and 

K. Gage. First resuhs from SOWE~ Paci lie. SPARC .\'e1nle11 .. 11. 22-

23. 1999. 

Hofmann. D.J .. J.T. Peterson. and R.:-1. Rosson (Eds.). Climme 

,\/011i1ori11g a11cl Diag11os1ic.1 Labormory \o. 1./ S1111111101!· Repor/ 

1996-1997. 166 pp .. 'IOAA Em iron. Res. Labs .. Boulder. CO. 1998. 

I lolton. J.R .. and A. Gcnelman. I loriLontal transpon and the dehydration 

of the stratosphere. Geopl1ys. Res. Lell .. 18. 2799-2802. 2001. 

llolton. J.R .. P.11. lla)11CS, i\1.E. i\lchll)rc. A.R. Douglass. R.B. Brood. 

and L. Plister. S1ra1osphcre-1roposphere c.\changc. Rei•. Geoplry.L 33. 

403-439. 1995. 

Johnson. 13.J .. S.J. Ollmans. H. Vomel. 11.G.J. Smit. T. Deshler. and C. 

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the sensili\ it) 10 oLonc of bulTered and unbulTcrcd ECC sensor 

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climatolog) for balloonsondc estimation of total column ozone. J. 

Geopl~n. Res.. JO:!. 8875-8885, 1997. 

l\ewe ll. R.E.. and S. Gould-Stewan. A stralOspheric fountain?. J. A111101. 

Sci .. 38. 2789-2796. 1981. 

Nishida. M .. A. Shimi1u. T. Tsuda. C. Rocken. and IU I. Ware, Seasonal 

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the GPS occuhauon 1cchnrque (GPS 'MET). J .111.!leorol. Soc. Japan. 

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Ohmans. S.J .. II. Vomd. D.J. Hofmann. K.11. Rosenlof. and D. Kley. 

The increase in stratospheric \\alcr \ apor from balloonbome. 

frostpoint hygrometer measurements al Washington. D.C.. and 

Boulder. Colorado, GeoplH's. Res. Lei/ .. 27. 3453-3456, 2000. 

Ohmans. S.J .. B.J. Johnson. J.i\1. Harris. 11. Vomcl. A.i\I. ll1ompson. K. 

Koshy. P. Simon. R.J. Bcndura. J.A. Logan. F. llascbc. M. Shiotani. 

V. \V.J.11. Kirchholl: M. 1\laata. G. Sami. A. Samad. J. Tabuadra\ u. 11. 

105 

Enrique1. M. Agama. J. Cornejo. and F. Paredes. 01one in the Pacific 

tropical troposphere from 01oncsonde obsen·a1ions. J. Geophys. Res .. 

106. 32.503-32.525. 2001. 

Rosenlof: K.H .. S.J. Ohmans. D. Kley. J.i\1. Russell Ill. E.-\\1. Chiou. 

W.P. Chu. D.G. Johnson. K.K. Kelly. I I.A. i\lrchelsen. G.E. 

Nedoluha. E.E. Remsberg. G.C. Toon. and \l.P. i\lcConnick. 

Stratospheric water \apor increases of the past half:centul). Geophys. 

Re.1. Le11 .. 18. 1195-1 198. 200 I. 

Schiller. C .. R. Bauer. F. Cairo. T. Deshler. A. Diimbrad .. J. Elkins. A. 

Engel. H. Flcntjc. N. Larsen. I. Le\'in. M. 1\Hiller. S. Ohmans. H. 

Ornrlez. J. O\arle1. C. Poss. J. Schreiner. F. Stroh. C. Voigt, and H. 

Vomcl. Dehydration in the Arctic stratosphere during the 

Tl IESE02000 SOLVE campaigns. J. Geophys. Rl.!s .. in press. 2002. 

Shemood. S.C .. A "stratospheric drain" mer the maritime continent. 

Geoplrys. Res. Lei/ .. 17. 677-680. 2000. 

Smit. 11 .G.J .. \\I. Strjter. i\I. lichen. D. Kie). D. Ciupa. 11.J. Claude. U. 

Kohler. B. llocgger. G. Le\ rat, B.J. Johnson. S.J. Oh mans. J.B. Kerr. 

D.\\'. Tarasid .. J. Da' ies. i\I. Shitamichi. S.K. Sri\asla\. and C. 

Viallc, JOSIE: TI1c 1996 Wl\10 imemational intercomparison of 

O/Onesondes under quasi !light conditions in the cm ironmcntal 

simulation chamber at Jlilich. Proc. of 1'1e XVIII Quadrennial O::one 

Symposium. L'Aquila. hal). Sep!. 12-2 1. 1996. edited by R. 13ojkov 

and G. Visconti. 971-974. 1998. 

Thoning. K.W .. P.P. Tans, and W.D. Komhyr. Atmospheric carbon 

dio-.idc at i\1auna Loa Obsenatory. 2. Analysis of the NOAA GMCC 

data. 197.J-1985. J. Geoplry;. Re.1 .. 9./. 8549-8565. 1989. 

Vomcl. 11.. S.J. Oltmans. D. Kley. and P.J. Cru11cn. Ne\\ C\ idencc for 

the stralOspheric dehydration mechanism in the equatonal Pacific. 

Geopl~n. Res. Lei/., 21. 3235-3238, 1995. 

Vomcl, H .. S.J. Ohmans. 13.J. Johnson. F. llasebe. i\I. Shiotani. 1\1. 

Fuji,rnra. N. Nishi. M. i\gama. J. Cornejo, 1-. l'arcdcs, and II. 

Enriquez. Balloon-borne obscr,ations of water\ apor and 01onc in the 

tropical upper troposphere and IO\\er stratosphere. J. Geophys. Res .. in 

press. 2002. 

Lercfos. C.S .. K. Tourpalr. and A.F. Bais. Funher studies on possible 

\Olcanic signal 10 the oLonc layer. J. Geoplry.1. Rei .. 99. 25.7-11-

25.7-16. 199-1. 

Zhou. X.-L.. 1\1.A. Geller. and i\1. Zhang. Cooling trend of the tropical 

cold point lropopause temperatures and its implications. J. Geophys. 

Rei .. 106. 1511-1522. 2001. 

/.icmkc. J.R .. S. Chandra. R.D. i\lcPeters. and P.A. Ne\\nmn. Dynamical 

proxies of column oLonc \\ ith application 10 global trend models, J 

Geoplrys.Res .. /01,6117-6129, 1997. 
5. Halocarbons and other Atmospheric Trace Species 

B.D. I I ALL (EDI I OR). J.11. BUTLER, A.O. CLARI...!:., G.S. DL IT01'. J. \\. ELKll\S, D.F. I IURST, 

D.B. Kl,G. E.S. KUM, J. Ll'-:D. L.T. LOCK, D. l\IONDEI L. S.A. 1\10,TLKA. F.L. MOORE. 

J.D. "'tr. E.A. RAY. P.A. RO\J \SllK11'. "D T.l\t. TJJO\ll'SO' 

5.1. 0\' ER\'IEW 

The mission o f the Halocarbons and other Atmospheric 

Trace Species ( llA TS) group is to study halocarbons and 

other trace gases that cause c hemical and radiative change in 

the atmosphere. The goal of I IATS is to measure and 

interpret the distributions and trends of these species in the 

troposphere, stratosphere. and ocean with the best analytical 

instrumentation available. The species measured include 

nitrous oxide (N20); many halogenated species, such as 

halocarbons, Ouorocarbons, pcrOuorocarbons (PFCs), and 

sulfur hexafluoride (SF1,); organic nitrates. such as 

peroxyacctyl nitrate (PAN); organic sulfur gases, such as 

carbonyl sulfide (COS); and hydrocarbons (l lCs). The 

halocarbons include the chlorofluorocarbons (CFCs); 

chlorocarbons (CCs}, such as CCl 4, CH1CCl3, CllCl3, 

C H2Cl 2, and C2C14; hydrochloroOuorocarbons (I ICFCs); 

hydroOuoro-carbons ( H FCs); methyl halides (Cl 13Br, Cl 13CI, 

and Cll 11); bromocarbons (Cll2Br2 and CHBr3); and halons. 

Three primary research areas involving these trace gases 

are stratospheric ozone depletion, climate change, and air 

quality. For example. the CFCs and N20 are major ozonedcplcting and greenhouse gases. The trace gns SF6 is a 

greenhouse gas with a large global warming potential , but its 

net warming is small because of its low concentration in the 

atmosphere. Short-lived halocarbons, PAN, and the llCs play 

an important role in g lobal and regional pollution. PAN is a 

major precursor of tropospheric otone in the remote marine 

atmosphere. Tropospheri c COS is a relatively stable sulfur 

molecule that contributes to the stratospheric aerosol layer. 

Resea rch conducted by ll ATS in 2000 and 200 1 included 

(I) weekly flask sampling and analysis of air from remote 

and continental-influenced sites, (2) operation of 

instrumentation for hourly. in situ meas urements of trace 

gases at the four CMDL baseline observatories, Barrow 

Obscn atory (BRW), Mauna Loa Observatory (M LO), Samoa 

Observatory (SMO). and South Pole ObserYatory (SPO), and 

at four continemal-influenced sites, (3) preparation and 

maintenance of trace gas standards, (4) participation on 

airborne campaigns with in situ gas chromatographs (GCs) on 

aircraft and balloon pa) loads, (5) i11\'estigation of oceanic 

processes that inOuence trace gas composition o f the 

atmosphere, and (6) measurement of man y trace gases in firn 

air from South Pole. 

Continuing programs \\ ithin HATS arc based upon m situ 

and flask measurements of the atmosphere from the 4 CMDL 

base I ine observatori es and I 0 coopcrati,·c stat ions (Figure 

5.1 ). Table 5. 1 lists the geographic locations and other usefu l 

information for al l the sites. There are currently 14 Oask 

sites and 8 in situ sampling sites in the llATS atmospheric 

sampling network. 

One of the hig hlig hts of this report is that the total 

equivalent c hlorine (Cl + Br) in the troposphere contin ues to 

106 

decrease at about I o,o yr'1 as a result of the Montreal Protocol 

[ UNEP. 1987]. Total cquirnlent chlorine in the stratosphere 

appears to have leveled off or peaked at most a ltitudes. The 

main reason for the decline in the troposphere is that methyl 

chloroform (Cll 3CCl 3) concentrations cominucd to decline to 

less than half of the peak levels present in 1992. 1-lo,,e,cr. 

atmospheric concentrations o f the halons and CFC-12 are st ill 

increasing because of pcrmilled production in the developing 

countries and the large bank of chemicals that exists in the 

developed countries. As a result or the halon increase, the 

total bromine in the troposphere and stratosphere is still 

increasing. Once atmospheric CH3CCl 1 is depleted, the trend 

in total equivalent chlorine may significantly change. 

requiring further observat ion. 

Other significant results include the g lobal increases in 

atmospheric N~O and SF<,, observed from both flask and in 

situ monitoring, the continued growth of the CFC 

replacements (HCFCs and llFCs), and the decline in the 

northern hemispheric concentrations of Cl-ICl 1 and C~Cl 4 as 

a result of the U.S. Clean Air Act. Carbonyl s ulfide 

distributions from both in situ and flas k measurements are 

described for the first time and show a strong seasonal 

cycle. A new fla sk station ''as added in 200 I at Trinidad 

Head, Ca lifornia . Airborne measurements were conducte d 

in the upper troposphere and lower stratos phere in the 

northern polar region during the 1999 and 2000 

Stratospheric Aerosol and Gas Experiment 111 (SAGE 111 ) 

Ozone Loss and Va lidation Experiment (SOLVE) conducted 

from Kiruna. Sweden. The rapid-sampling airborne gas 

chromatograph was also used to measured CFCs, halo ns. 

and chlorinated solvents in Russia along the trans-Siberian 

railway during June-Jul y 200 1 in a collaboration with 

Russian and German scie ntists. The construction of the 

next-generation airborne GC "ith electron capture and mass 

s pectrometric detection was funded by th e National 

Aeronautic s and Space Administration (NASA) Instrument 

Incubation Program to measure trace gases. includ ing 

hydrocarbons and organic nitrates, that influence 

atmospheric chemistry in the upper troposphere. An in situ 

GC system. equipped '' ith one mass selccti\c detector and 

two electron capture detectors. is being built for the ne'' 

U.S. West Coast sampling si te (Trinidad ll ead, California, 

or elsC\\hcrc on the U.S. West Coast) to monitor pollution 

originating in Asia and transported O\er the Paci fie Ocean. 

5.2. CONTINUl;\"G PROGRAMS 

5.2. 1. FLASK SA:\I PLES 

01'en•iew 

Arrangements were made in 2001 to add t\\O llC\\ stati ons 

to the sampl ing network. One of these is an additional 

remote site in the far southern hemisphere , located at 
90°N 

60°N 

30°N 

o· 

3o·s 

5o·s 

\I Cl.AV __ A'.I) 

• 

KW UKAHI 

.. • .. , 

.. .... . + RAROTC'•GA 

• "V.: OCE•·· CRu s;s, ,E~ sv."o 

'> 1-!ALOCARBON A:R SAMPLING NETWORK 

• ~ARBOtl CYCLE AIR SA'.'PL :~G ',, ·:.-.RK .t. C4R80 tl CYCLE TQ::[R '!~~SUf ••>·.·s 

+ CARBON CYCLE AIRCRAn SA•APLING S1TES 

90°N 

60°N 

30°N 

o· 

3o·s 

CROZET • .. 

5o·s 

go·s+===---="j==-==--,====--.-===~.---1---.---~~.---~~.-~~.-~~+90°S 

100°E 140°E 1 so· 14o·w 1 oo·w 5o·w 2o·w 20°E 60°E 1 oo·E 

Fig. 5.1. Geographic locations of stations in the CM DUI-IA TS nask and in situ networks, along wi1h CMDUCarbon Cycle Greenhouse Gases (CCGG) 

siations (N10 and SF6 collec1ed in glass nasks) and lower sites (triangles, future in silu halocarbon measurement). 

TABLES.I. Geograph ic and Network Information for HATS Network Sites 

Elevaiion LST - GMT 

Code Station La1i1ude Longi1ude (m) (h) 

ALT Alen, Nonhwest Territories, Canada* 82.45°N 62.52°w 210 .4 

BRW Point Barrow, Alaska 7 1.32°N 136.60°w II .9 

Ml-ID Mace Head, Ireland (University College) 53.33°N 9.90°w 42 0 

LEF WLEF tower, Wisconsin (CMDUCCGG) 45.95°N 90.28°w 470 -6 

HFM Harvard Fores!, Massachusetts (Harvard University) 42.54°N 12. 18°w 340 .5 

THD Trinidad Head, California (Humbolt State University) 41.05°N 124.15°W 109 -8 

NWR Niwot Ridge, Colorado (University of Colorado) 40.04°N 105.54°w 30 13 -7 

ITN WITN tower, Nonh Carolina (CMDUCCGG)t 35.37°N 77.39°\V 9 .5 

MLO Mauna Loa. Hawaii 19.54°N 155.58°\V 3397 -10 

KUM Cape Kumukahi, Hawaii 19.52°N 154.82°\V 3 - 10 

SMO Tuluila, American Samoa 14.23°s 170.56°\V 77 • JI 

CGO Cape Grim, Tasmania, Australia; 40.41 °s 144.64°E 94 + 10 

TDF Ushuaia, Argentina (WMO GAW station)§ 54.82°s 68.32°w 10 .3 

PSA Palmer Station, Antarctica' 64.92°S 64.oo•w 10 + 12 

SPO Souih Pole, Antarctica 89.98°s 102.00°E 2841 + 12 

F, nasks; I, in situ. 

*Cooperative site with Environment Canada. 

tSite's nask and in situ GC instrument closed down on June 12, 1999. 

tCooperative site with Commonwealth Scientific and Industrial Research Organizalion (CSIRO) and Bureau of Meteorology, Australia. 

§Began collecting data in November 200 I. 

'[Only glass nasks used. 

107 

Type 

F 

F, I 

F 

F, I 

F, 1 

F 

F, I 

F, I 

F, I 

F 

F, l 

F 

F, I 

F 

F, I 
Ushuaia. near Tierra de l Fuego (TDF), Arge111ina (Figure 

5.1, Table 5.1 ). This is a cooperati\e site with the 

Argentine government and is a Global Atmospheric Watch 

(GA \V) station sponsored by the World Meteorological 

Organization (\VMO). The second site. located at Trinidad 

Head, California (TllD). is considered a regional sampling 

site and has been established for ernluating reg ional-scale 

air quality. It is an1icipa1cd that Trinidad I lead \\'ill recei' e 

a mix of air from O\ er the remote ocean and from nearby 

forests and small IO\\ ns. It also may be useful for detecting 

air masses 1ranspor1ecl from Asia. Sampling al Mace Head, 

Ireland (to.II ID), was suspended for almost a yea r, as nasks 

began disappearing in transit. Bi\\'eekl y sampling at Mll D 

\\'as reinitiated near the encl of 200 I. Efforts 10 improve 

sampling frequency and precision at all sites Jiaye continued 

throughout 2000-200 I. 

Flasks brought into the laboratory are anal yzed on two to 

four instruments, depending upon the species being 

examined and the size of the individual sampling fla sk 

(Table 5.2). Analyses are performed by a gas chromatograph with electron capture detection (GC'-EC D) and/or a 

gas chromatograph with mass spectrometric (GC-MS) 

detection. Although all 300-ml nasks haYe been retired, 

there still remain some 850-ml nasks. "hi ch contain a 

margina l amount of air for all of these lo\\ -le\ el analyses. 

Most nask analyses are of samples from the network, 

although many arc from research cruises, firn air sampling, 

and other special projects. One hundred new electropolishcd. stainless-steel nasks were recently purchased 

from Lab Commerce (formerly knO\\ n as Meritor 

Corporation. San Jose. California) to supply the nc\\' sites, 

to upgrade nask quality and quantit) at o ld sites, and to use 

for s pecial projects. 

In 1996. 269 nasks from the network were filled and 

cleli\ered to the Boulder laboratory for analysis. This 

TABLE 5.2. Instrumentation for I !ATS 

Flask Analysis 

rrcqucnc) of 

lmtrumc111 Type Gases i\el\\ork Data 

OTTO GC-ECD N,O. CFCs (3), Weekly 

(three-channel. ccs (2). s r,, 

isothermal) 

LEAPS GC-ECD I la Ions (2). Cl l;CI. Scmimomhly 

(one-channel. Cl hBr. Cl IC!i to momhl) 

temperatureprogrammed) 

HCFC-:\IS GC-MSD llCFCs(3). HFCs( I). Scmimomhly 

(one -channel CFCs (3). halons(IJ. 

temperature- CCs (6). BrCs (3 ). 

programmed) c os 

llFC-:vlS GC-MSD 1 ICFCs (5). HFCs (2). Semimonthly 

(one -channel. CFCs (2). halons (2). to momhly 

temperature- CCs (6). BrCs (3). 

programmed) BrCCs(3) 

OTTO. not an acronym: LEAPS. LO\\ Electron A11achme111 Potential 

Species: BrCs. bromocarbons: BrCCs. bromochlorocarbons. 

number has increased each year. reaching a total of 415 in 

2000 (Figure 5.2). This in crease is the result of added sites 

and more efficient turno,cr o f flasks bct11cen Boulder and 

the fie ld sites. This was accomplished through imprO\ cd 

record keeping of nasks coming to Boulder and b) addition 

of fl asks to the network. Sampling success has steadily 

improYcd from that for 1996 at all sites (Table 5.3 ). This 

"as mainly the result of small leak repairs and rnl\'c 

replacements on flasks. "here necessary. These repairs 

greatly improved the agreement in flask pressure between 

simultaneously sampled pairs (Figure 5.3). 

GC-ECD Results 

CFC-12 continues to increase in the atmosphere: 

howc\ er, it may ha\ e le\ cled off in the northern hemisphere 

(Figure 5.-1). Mi.\ing ratios o f CFC-I I continue to drop 

steadily (Figure 5.5). The CFC-I I gro\\ th ra te (-1.75 ± 

0. 11 (95% C.L.) ppt yr' 1

, 0.7°'o yr' 1

) for 2000 through mid200 I docs not di ffcr from the rate cletcrm i ncd for 1997-

108 

450 

400 

350 

300 

250 

200 

1996 1997 1998 

Year 

1999 2000 

rig. 5.2. Number of flask pairs lilled and returned to Boulder each year 

from the HA TS station nct\\ork. 

TABLE 5.3. Percentage Sampling Success at Ct-.lDL 

Obser\'atories and Cooperati\ c Sampling Sites 

Sampling Station 1996 1997 1998 1999 2000 

Barro\\ . AK 69°,. 9-1% 88°. 870o 90% 

;..fauna Loa. HI 69% 83% 90% 96°,. 9-1% 

American Samoa 54% 67% 73% 88°0 88% 

South Pole 770,. 69% 77•. ss•. 81% 

Alert. Canada 52• .• 46% 67°0 67°0 65°:0 

'\iwot Ridge. CO 63°-o 92°0 870,o 7700 88°,. 

Cape Grim. Australia 60"·• 6900 85% 87% 85% 

\\ LEF tower. \\'I 12°. 35°0 69°0 n•. ioo•,. 

Hanard Forest. i\IA 46% 62°0 69% 69% 88% 

Kumukahi. HI so•,. 5-IOo 67°·0 69°'0 83% 

Palmer. Antarctica 8°0 65°0 s 1°·. 96°0 

i\lacc llcad. Ireland* 8•· 

'0 15°0 

WITN to\\ er. NCt 65% 62% 62% 38% 

Sampling success is dclincd as the fraction of llasks analy1ed relati\ e 

to the number expected (i.e .. one pair per \\Cek). 

*Sampling was discominucd temporarily in 2000 because of loss of 

flasks in shipments. 

tSitc \\as discontinued indefinitely in 1999. 
100% 96% 

90% 

80°/o ········ ················· ·· ·· 

70% 

60% ... 

50% 

1996 1997 1998 1999 2000 2001 

Year 

Fig. 5.3. Percentage of flask pairs agreeing'' ithin I psi in total pressure 

upon arrival in 13oulder. 

a. 

-3: 

c: 

.Q 

u 

ro 

u: 

Ql 

Ci 

~ 

~ 

0 

540 

535 

530 

525 

520 

515 

510 

1995 1996 1997 1998 1999 2000 2001 2002 

Year 

l"ig. 5.4. Recent measurements of CTC- 12 in the atmosphere. 

t\1casuremcnt; are monthl) a\eragc:. of GC-l:CD data: nonhcm 

hemisphere means (squares). global means (triangles). and southern 

hemisphere means (diamonds). 

274 

272 

270 

268 

266 

264 

262 

260 

258 

1995 1996 1997 1998 1999 2000 2001 2002 

Year 

rig. 5.5. R.:ccnt measurements of CFC- I I in the atmosphere shO\ling a 

stead} loss rate since 1997 (GC-ECD month!} means: S}mbob as in 

rigure 5.4). 

2001 (-1.73 ± 0.03 ppt )r" 1). CFC-113 and CCl4 arc also 

both decreasing, al about I 0 o yr·'. The globa l gro'' th rate 

ofN!O (Figure 5.6) during 1978-2000 \\as 0.74 ± 0.01 ppb 

) r· . \\ hich amounts to a mean of about 0.25% yr" 1

• During 

1999 through mid-200 I, the global gro\\ th rate ''as 0. 73 ± 

0.06 ppb )r" 1

, \\hich docs not differ from the 23-yr a1crage. 

Sulfur hexanuoridc (Figure 5.7) still appears to be 

increasing I inearl) in the atmosphere. \\ ith a gro\\ th rate of 

about 0.22 ± 0.0 I ppt yr" 1 since 1996. 

109 

The mixing ratios of halons arc still increasing slowly in 

the atmosphere, in spite or a ban on their production in 

de1 e loped countries as of 1994. The global gro\\ th rate or 

halon- 130 I (Figure 5.8) from 1999 through 2000 (0.06 ± 

0.07 ppt )r" 1

) docs not differ significant ly at the 95% 

contidencc lei el from the 1995-2000 average of 0.06 ± 0.0 I 

ppl yr" 1

, nor from thel995-1996 a1eragc o f 0.044 ± 0.0 11 

ppt yr" 1 reported in 8111/er et al. [ 1998]. The gro'' th rate of 

halon-1211 (Figure 5.9) seems to be slowing, ha1ing 

dropped from a steady ra te of 0. 16 ± 0.02 ppt yr" 1 in the late 

1980s and ea rl y 1990s to 0.094 ± 0.04 ppt yr" 1 for 1999 

through mid-200 I. 

320 

315 

310 

305 

300 

295 

1977 1982 1987 1992 1997 2002 

Year 

Fig. 5.6. Atmospheric hi!.to~ of l\ O since 1977 (GC-ECD monthl) 

means: s)lnbols a:. 111 Figure 5..1 ). A ne\\ GC-ECD instrument has been 

used since 1994. 

a. 

-3: 

c: 

.Q 

u 

ro 

u: 

Ql 

Ci 

~ ,., 

0 

5.5 

5.0 

4.5 

4 .0 

3.5 

3.0 

1995 1996 1997 1998 1999 2000 2001 2002 

Year 

Fig. 5.7. Recent histo~· of atmospheric SF. from C1\ IDL llask 

measur.:mcnts (GC-ECD monthly means: S}111bols as in Figure 5..1). 
a. 

~ 

c 

0 

u 

~ 

IL 

Q) 

0 

~ 

~ 

0 

2.9 

2.5 

2.1 

1.7 

1.3 0 

.. 

0 

0.9 L----- --------------' 

1987 1990 1993 1996 1999 2002 

Year 

Fig. 5.8. Atmospheric history of halon-1301 (GC-ECD bimonthly 

averages; symbols as in Figure 5.4). 

4.5 

a. 4.1 0.. 

-

c 

0 

n 3.7 <1l 

LL 

0 

~ 

Q.> 

.... 

('.:-

3.3 

2.9 ~ 

#~ 0 

0 

~ 

2.5 

1992 1994 1996 1998 2000 2002 

Year 

Fig. 5.9. Recent atmospheric history of halon-1211 (GC-MSD monthly 

means; symbols as in Figure 5.4). 

GC-MS Results 

Chloroj111orocarbo11s alternatives measurement program. 

Measurements of CFC alternatives and other trace gases 

were continued during 2000-200 1 from flasks collected at 

12 loca tions. In both years, three samples per month, on 

average, were filled and analyzed on GC-MSD 

instrumentation at 11 of the 12 sites. Fewer sampl es from 

MHD were col lected and analyzed owing to difficulties 

associated with s hipping. 

Tropospheric mixing ratios of HCFCs and HFCs 

continued to inc rease during 2000-200 I (Figure 5.10, Table 

5.4). Fairly linea r rates o f increase have been observed for 

HCFC-22, HCFC- 141b, HCFC-142b, and HFC-1 34a since 

1998. By mid-200 I, chlorine in the three most abu ndant 

HCFCs amounted to nearly 190 ppt, or almost 7% of al l 

chlorine carried by long-I ived, purely anthropogenic 

halocarbons. Total chlorine from the HCFCs increased at 

between 8 and 9 ppl yr·

1 over this period . Despite rapid 

110 

180 

160 

140 

120 

ii 100 

c.. 80 

60 

40 

20 . 

0 

HCFC-22 

.. .. 

1986 1988 1990 1992 1994 1996 1998 2000 2002 

18 

16 

14 

12 

ii 10 c.. 8 

6 

4 

2 

HCFC-141b 

0 ~ ...... 

1986 

16 

14 

12 

10 

-

c.. 8 c.. 6 

4 

2 

0 

1986 

25 

20 

15 

ii 

c.. 10 

5 

0 

1988 1990 

HCFC-142b 

1988 1990 

HFC-134a 

1992 1994 1996 1998 2000 2002 

1992 1994 1996 1998 2000 2002 

1986 1988 1990 1992 1994 1996 1998 2000 2002 

Year 

Fig. 5. 10. Atmospheric dry mole fractions (ppt) of selected HCFCs and 

HFC- 134a measured by GC-MSD in the CMDL nask program. Each 

point represents monthly means at one of eight or nine stations: ALT, 

BRW, NWR, red; KUM, MLO, green; SMO, CGO, PSA, SPO, blue. 

Also plotted are results from analysis of archived air samples (open red 

circles) filled at NWR and in past cruises from both hemispheres. 

relative growth observed for HFC- l 34a during the midI 990s, a fairly constant rate of increase o f 3.2 ppt yr" 1 has 

been obse rved since 1998 (Table 5.4). 

Atmospheric methyl chloroform. Atmospheric mixing 

ratios of meth yl chloroform (I , I, I-tri chloroe thane, 

C H3CCl3) continue to dec line exponentially (Figure 5.1 1 ). 
( ,. .,, 

1 

TABLE 5.4. Global Burden (Mixing Ratio) and Rate of 

Change of HCFCs and HFC- I 34a 

Mean 2000 Mean 200 I Growth Rate 

Compound (ppt) (ppl) (ppl yr"') 

HCFC-22 141.6 146.3 5.0 (1992-2001) 

HCFC-141b 12.7 14.0 1.7 ( 1998-2001 )* 

HCFC- 142b 11.7 12.5 1.0 ( 1998-200 I)* 

l-IFC-134a 13.8 17.2 3.2 (1998-2001) 

Quan1i1ies arc cs1ima1ed from la1i1udinally weighted measurements al 

seven remote s1a1ions: SPO, CGO, SMO, MLO, NWR, BRW, and ALT. 

•Slower growth is indicated in 2000-200 I (0.1-0.2 ppl yr·' less 1han 

shown). 

During 2000 through mid-200 I, the growth rate of C H3CCl3 

declined at about 18% yr" 1

• The exponenti al decay time 

constant has been consistent at 5.5 ± 0.1 yr since the 

beginning of 1998, and continues to provide an upper limit 

to the global li fetime of C ll 3CC13 in the atmosphere 

[Montzka et al., 2000]. If it is presumed those emissions of 

C ll 3CC13 have not changed substantially from that estimated 

for 1998-1999 [ Montzka et al., 2000; Prinn et al., 200 I], 

then these results continue to suggest a global lifetime for 

C l-1 3CCl3 of 5.2 years (for the years 1998-200 I). In contrast 

to estimates of Cl-13CCl3 li fetime for the years before 1995, 

this lifetime estimate is very insensitive to calibration 

uncertainties. It is still sensitive, however, to the magnitude 

of present-day emissions. 

Slightly shorter estimates of methyl chloroform lifetime 

have been reported by Prinn et al. [200 I] for the period 

1978-2000. They suggest, however, that the methyl 

chloroform lifetime has changed over time. They also 

estimate a lifetime longer than 5.0 years in the later 1990s, 

which is reasonably consistent with 5.2 years in 1998-2001. 

The outstanding question with regard to this issue is 

understanding this apparent change in lifetime. Docs it 

stem from inaccurate estimates of emissions, decreases in 

011 in recent years, or a change in the true lifetime of 

methyl chloroform that is unrelated to 0 1-1 ? 

The hemispheric di ffcrcnce has not changed substantially 

since 1998; for the years 1998-200 I, the hemispheric 

difference is estimated to be 2.8 (±0.4)%. This difference is 

similar at all sampling stations at comparable latitudes in 

the two hemispheres: 2-3% in the tropics deduced from 

SMO, MLO, and KUM data; 2-3% in midlatitudes deduced 

from CGO, NWR, and LEF data; and 2-4% in polar region s 

deduced from PSA, SPO, BRW, and ALT data (see Table 

5.1 for station definitions and locations). The constancy in 

both the decay time constant and the hemispheri c difference 

suggests that the influence of emissions on estimates of 

global lifetime and hemispheric lifetimes has either been 

s mall or relatively constant since 1998. 

Overall trends in ozone-depleting gases. Ground-based 

measurements provide an indication of the burden and trend 

of individual ozone-depleting gases. The sum of chlorine 

and bromine atoms in long-lived trace gases provides an 

estimate of equivalent tropospheric chlorine (ETCI) after 

111 

160 - .. .f'~ (a) 

140 ..,. ~ NH 'l> 

ii 120 

.9: 

0 100 

~ Cl 80 + c 

·x 

~ 60 

40 + 

20 

1992 1994 1996 1998 2000 2002 

Year 

25% -

(b) 

Cl> 20% .D " J. 0 

a •• x 15% - . .,~ 

--'*' 10% + 

•• . x 

I 5% :- , z • • :' • v , ~ 0% .: \., • 

.. -5% +- --~~ _...,. .. •--r~ ... -t- _.. ~--i 

1992 1994 1996 1998 2000 2002 

10 ..,. 

.s 1 (c) 

<l> 9 + E 

+:: 

>- «I 

0 

8 ..,. 

<l> 

-0 

-0 7 

:§ 

Qi 6 .;. 

-0 

<l> 

~ 5 + <l> 

(/) 

.0 

0 4 

1992 1994 1996 1998 2000 2002 

Fig. 5.11. (a) Atmospheric dry mole fractions (ppl) of CH3CCl 1 

measured by GC-MSD in the CMDL nask program. Each point 

represents a monthly hemispheric surface mean as de1em1ined by a 

latitudinal weighting of rcsuhs from individual sampling stations 

(northern hemisphere = triangles. southern hemisphere= circles). (b) The 

hemispheric mixing ratio difference for CH3CC'3 at the Earth's surface 

in recenl years. The difference was inferred from weighted, monthly 

mean mixing ratios at three to six sampling stations in each hemisphere. 

Monthly differences (solid circles) are connected with a thin line: 1he 

hea' y curve represents a 12-mo mnning mean difference. (c) TI1c 

observed e-fold decay time for monthly hemispheric surface means of 

Cl 13CC'3 shown in (a). A fairly constant exponential decay in surface 

mixing ratios of CH3CCI; has been observed since lhe beginning of 

1998; the exponential time constant for this decay is 5.5 years. 
the enhanced effi ciency of bromine to destroy ozone 

compared with chlorine is included (a factor of SO is used 

he re; Solomon et al. [ 1995]). ETCI provides an indication 

of the upper limit to ozone-depleting chlorine and bromine 

in the future stratosphere. Better approximat ions of trends 

in inorganic halogen in the lower stratosphere can be 

derived fro m ETCI after accounting for the diffe rent rates at 

which halocarbons photo-oxidize in the stratosphere. These 

rates have been estimated empirica lly or with mode ls and 

are applied as weighting factors to mixing ratios of 

indi vidual gases in the calculation of effective equivalent 

chlorine (EECI) and effective equivalent stratospheric 

c hlorine (EESC) [Daniel et al., 1995; Montzka et al., 1996]. 

The only difference between EECI and EESC is that EESC 

explicitl y includes a 3-yr time lag (dat es associated with 

EECI corres pond to the time when the surface measurement 

was made). 

The net sum of ozone-depleting halogen from purely 

anthropogenic gases continued to decrease during 2000-

200 I (Figure S.12). The rates of dec line for EECI and ETCI 

in 200 I were about I% yr" 1 a nd 0.5% yr1

, respectively. 

Amounts of EECI during mid-2001 were about S.5% below 

the peak observed near the beginning o f 1994. The rate of 

decline in both EECI and ETCI has slowed by about onethird compared with peak va lues as the in nuence of meth yl 

chloroform has diminis hed. 

The two scenarios for EECI and ETCI shown in Figure 

S.12 provide some insight into causes of past changes and 

the future evolution of net halogen in the atmosphere. The 

measured trends in EECI and ETCI since 1998 have 

remained fairly c lose to scenario A, in which constan t 

emissions were presumed [Mont.:ka et al., I 999J. Although 

substantial reductions in emissions were reali zed during the 

1990s, these results suggest that these emission reductions 

have slowed in rece nt years, perhaps owing to enhanced 

CFC production in developing countries. 

The updated projections for scenario B ( Figure S.12 , solid 

lines) are somewhat diffe rent from the ones made 

previously (see refe rences noted in Figure S. 12). The main 

difference arises from consideration of halons in the future. 

In the present calculation it has been assumed halon 

emissions wi ll dec rease in future yea rs in reasonabl e accord 

with reported halon production [Fraser et al. , 1999] and a 

small a llotment for additional future production. 

Shorter-lived gases- Measurements o f other chlorinated 

and brominated trace gases were continued during 2000-

200 I (Figure S.1 3). The results suggest further decre ases in 

mixing ratios of C H2Cl2 and C2Cl4• lnterannual variability 

is observed for the methyl halides and will be discussed in 

future publications. 

No11-stai11less-steel flasks circulated to sampling stations. 

Although most samples arc routinel y collected in stainl essstccl flasks in the HATS program, glass flasks have also 

been used recently. Glass flasks are particularly useful 

when known artifacts affect sampling in steel flasks. Glass 

flasks sampled during the South Pole 2000 winter allowed 

for additional measurements of compounds that unde rgo 

substantial degradation in stainless-steel flasks durin g the 

long period betwee n sampling and analysis (Figure S. 14). 

Glass nasks are a lso useful to determine if results for more 

reacti ve gases are independent of flask type. Preliminary 

11 2 

3.2 

3.1 -f 

3.0 

~ 

~2 9 

u 

w 2.8 

w 

2.7 

· .. ....... ..... 

·· .. .......... ....: 

···---- .. . B 

2.6 

2.5 

1990 1995 2000 2005 2010 2015 

4.6 

4.5 

4.4 

~4 3 

a .e: 4.2 

u 4.1 Iw 4.0 

• :..::... ..:. -_: :_::_ __ A 

·· .. -..... _ ··.. --...... 

·.. -..... 

······ ... ....., 

B 

3.9 

3.8 

3.7 

1990 1995 2000 2005 2010 2015 

Year 

Fig. 5. 12. The measured and potential future burden of ozone-depleting 

halogen in 1he lower atmosphere. Ozone-depleting halogen is estimated 

from tropospheric measurements of anthropogenic halocarbons by 

appropriate weighting factors to calculate effective equivalent chlorine 

(EECI) for midlatitudes (top) and equi\ a lcnt tropospheric chlorine 

(ETCI) as an upper limit for polar latitudes (bottom) [Daniel et al., 1995; 

i\/0111zka et al .. 1996, 1999]. A constant offset was added to account for 

Cll 1CI and CH1Br. Projections are based on two limiting scenarios: A. 

emissions of all long-lived halogenated gases (CFCs, HCFCs, Cl 11CCb, 

CCI,, and halons) remain constant at 200 1 levels, and B, scenario A with 

the exception that emissions of CFCs, Cl 13CC'3, halons, and CCI, 

continue decreasing at 5 to 8% yr--'. Future scenarios have been 

fomrnlated in previous CMDL S1111111101J' Reports and other publications 

with ambient air measurements through 1997 (short-dashed lines 

[Mo11t=ka et al., 1999]) and through 1999 (long-dashed lines [/fall et al., 

200 I]). Updates to current emission rates and their rates of change based 

on measurements through 200 I were used to update projections for both 

scenarios (solid lines). 

results of glass flasks filled at CGO and SPO show good 

consistency for HCFC-22, HCFC-142b, and 1-1FC-I 34a. 

Glass flasks are not without problems for some compounds, 

however. Poor consistency is observed for HCFC- 141 b and 

C2Cl4 in glass flasks; this contamination probably is 

associated with the Teflon seals in these flasks and does not 

suggest trouble in results reported from stainl ess-steel 

n asks for these gases. 

Carbonyl sulflde. Measureme nts of carbony l sulfide 

(COS) were begun from flasks during 2000-200 1. COS is 
800 

700 

600 

- 500 0. 400 0. 300 

200 

100 

0 

1992 

20 

15 

ii 10 0. 

5 

0 

1992 

50 

40 

- 30 0. 

0. 20 

10 

0 

1992 

25 

20 

ii 15 

0. 10 

5 

0 

1992 

14 

12 C2Cl4 

10 

ii 8 0. 6 

4 

2 

0 

1992 

1994 1996 1998 2000 2002 

. . ; .i ' o.'i _.,I,• .. ·~ · . " -

1994 1996 1998 2000 2002 

1994 1996 1998 2000 2002 

1994 1996 1998 2000 2002 

·"' 

1994 1996 1998 2000 2002 

Year 

Fig. 5. 13. Atmospheric dry-air mole fractions (ppt) determined for 

selected chlorinated trace gases and Cl-'3Br by GC-M SD in the CMDL 

fla sk program. Each point represents the mean of two simultaneously 

ti lied flasks from one of eight or nine stations (symbols the same as in 

Figure 5. 10). Results shown for all compounds except C2CI, arc from 

2.4-L stainless-steel flasks only. 

an abundan t sulfur-conta ining gas that is believed to 

contribute sign ificantly to the sulfur found in the 

stratosphere. More recent mode l calculations, ho we\ e r, 

have suggested a lesser role for COS in maintaining the 

stratospheric aerosol than was previously thought 

[Kjells1r6111 , 1998]. 

The results from nasks show a sma ll he mispheric 

differe nce biased sli ghtly toward higher levels in the 

11 3 

12 ' 

a. 

a. 6 

4 

2 

0 0 0 00 

0 0 

0 0 

0 

0 

0 

00 

00 

0 

0 

0 ~~~~~~~~~~~~~~~~~~~~ 

1995 1996 

a. 

a. 60 0 0 

40 

20 ° 0 

0 

1997 

0 0 

o~ 

0 

0 

0 

1998 

0 0 

0 0 0 

0 

1999 

0 

0 0 

0 0 0 

2000 2001 

0 .., 

0 

0 

0 

0 '--<,_.,>-- ..,_<>-~O--~~-o.oo---c0-< ----c~~-

1995 1996 1997 1998 

Year 

1999 2000 2001 

Fig. 5. 14. Mixing ratios determined from difTercnt sites and different 

types of flasks. Results for CH3Br and CCI, from Cape Grim, Tasmania 

(40°5). from stainless-steel fla sks (red pluses) are compa1ed with data 

obtained from South Pole from stainless-steel flasks (open blue 

diamonds) and glass flasks (solid black circles). 

southern hemisphere, strong seasona l variat ions at all sites 

except SMO . and seasona lity in the two hemispheres that is 

not 180 days out o f phase (Figure 5. 15). These fea tures are 

a lso evident in data from Chroma tograph for Atmospheric 

Trace Spec ies (CATS) GC-ECD instrumentation located at 

selected sites. Many con ni cting reports regard ing hemispheric distributions and seasonali ty can be fo und in the 

current literature for COS. These observations will add 

substantially to the understanding o f the g lo ba l budget o f 

this gas. 

5.2.2. I N SITU GAS C HROi\I ATOGRAPH 

MEASU REMENTS 

Radiatively /111porta11t Trace Species 

The Radi ati vely Important Trace Species (RITS) project 

has ended. Table 5.5 outlines, for each station and data 

c ha nnel, the shutoff dates for the RITS equipment. Channe l 

A measured N20. CFC- 12 (CC l2F 2) , and C FC- I I (CCl3F): 

c hannel B mea sured CFC- I I, C l 13CCl3, and CCl4; and 

c ha nne l C measured N20. The RITS instrume nts continued 

to collect data until data from the replacement CA TS 

in strume nts showed similar trend s and equal or bett er 

precision. The precision fo r a particular chemical was 
600 

500 

400 

a. 

Cl. 

• 

300 -

200 

100 

0 - ~ 

1998 1999 2000 2001 2002 

Year 

Fig. 5.1 5. Mixing ratios for COS detennined from sampling and analysis 

of stainless-steel flasks at BR W (red), KUM (green), and CGO (blue). 

Also shown arc momhly means at BR W from the on-site CA TS GCECD (purple diamonds). For clarity, SMO data are not shown. 

determined as the standard deviation of the ratio of the 

responses of two calibration gases over a~ extended period 

o f time (usually more than I month). Calibration gases are 

normally very stable for the species of interest. 

Instruments associated with the CA TS project, developed 

to replace the aging RITS instruments and add new 

measurement capabil iti es, continue to operate at the CM D_L 

field sites. A CATS system was installed at N WR m 

O ctober 2000. Table 5 .6 shows the install ation dates for the 

CATS instrume nts and the duration of the RI TS-CA TS 

comparisons. 

A two-channel Hewlett-Packard 5890 GC-ECD used in the 

RITS project was refurbished for installation at Ushuaia, 

Tierra del Fuego, Argentina (TDF), as part of a cooperative 

venture with the Servic io Meteorologico Nacional de 

Argentina, sponsored by WMO. The TDF site is part of the 

WMO GAW program. This GC measures N20 a nd SF6 on 

the first channel and CFC-1 2, CFC- I I, CFC- 11 3, CH3CCl3, 

and CCl4 on the second c hannel. A significant difference 

between this system and the previous RITS system is that 

nitrogen carrier gas with a C0 2 dopant is used on the N10-

SF6 channel as opposed to 5% CH4 in argon (P-5). The use 

o f COrdoped N2 should (a) e liminate any C02 interfe rence 

TABLE 5.5. RITS Project Shutdown Schedule 

Station Channel* Date and Time (GMT) 

BR\V A, B,C Feb. 17, 1999 (2100) 

NWR A, B, C Aug. 7, 200 1 (1900) 

MLO A,C April I 0, 2000 (2130) 

B Dec. 18, 2000 (2030) 

SMO A,B April 22, 2000 (0530) 

c Sept. 30. 2000 (0000) 

SPO A, B Nov. 30, 2000 (0200) 

• See text for channel definitions. 

Station 

BRW 

NWR 

MLO 

SMO 

SPO 

TABLE 5.6. CATS Project Startup and Overlap 

Schedule with RITS 

Installation Date 

June 16, 1998 

Oct. 13, 2000 

Sept. 29, I 998 

Dec. 4, 1998 

Jan. 30, 1998 

Overlap with 

RITS (months) 

8 

IO 

18 [26]* 

17 [22]* 

34 

*Months in brackets are for the one channel that cominued to be 

operated after the others were turned ofT. 

on the N20 signal and (b) improve carrier gas quality (highqua lity P-5 is diffi cult to obtain, particularly at remote sites). 

The TDF GC system was installed on October 26, 200 I 

providing the first in situ CFC measureme nts in South 

America. Scientists from Argentina are interested in 

measuring CFCs because stratosphe ri c chlorine fro m CFCs 

contributes to the formation of the Antarc tic ozone ho le. 

Duri ng vortex breakup, low-ozone events can occur over 

southern South America. Furthermore, whil e the tota l 

atmospheric chlorine burden is dropping [Montzka et al., 

1999; Elkins, 2000], CFC-12 is slowly increasing. Under 

the Montreal Protocol on Substances that Deplete the 

Ozone Layer [ UNEP, 1987] and its amendments, developing 

countries can produce CFCs until 20 I 0. 

Mixing Ratio Calc11/atio11 Methods 

O ver the past 3 years the RITS three-chan ne l GC 

instruments at the CM DL baseline observatories have been 

replaced by four-channe l GC instruments (CATS). In 

addition to the five trace gases measured by RITS 

instruments (N20 , CFC- I I, CFC-1 2, C H3CCl3, and CCl4), 

CAT S instrume nts measure SF6, CFC- 11 3, C HCl3, COS, 

halon- 130 I, ha lon- 12 11 , C H3CI, CH3Br, HCFC- I 42b, and 

HCFC-22. 

11 4 

Both RITS and CA TS instruments are calibrated using 

two calibration tanks that are sa mpled alternate ly along with 

ambie nt air. One calibration sta ndard (C I) consists of a 

mixture o f 90% ambient air and I 0% syntheti c ultrapure air. 

The other standard (C2) is 100% ambi ent air. The seq ue nce 

of sample inj ections is C I, A I, C2, A2, w he re A I and A2 

are ambient air samples obtained at two different he ights on 

the sampling tower. Each sample c hromatograph is 30 

minutes in length ; thus the full sequence takes 2 hours. 

Both RITS and CATS in situ measureme nt programs have 

utili zed several different methods to compute the trace gas 

concentrat ions in air samples bracketed by two calibration 

sampl es. This section focuses on the difficulties involved 

in these calcul a tions. A new a lgorithm, designed to 

minimize problems associated with calibration tank changes 

and uncertainties in the assignment of calibration tank 

mixi ng ratios (see section 5.2 .3), is presented here. 

One-point method. The simplest method of calculating 

mixing ratios is to use onl y one calibration tank as a 

reference measureme nt: 
R 

x., =-;r--x, c 

(I) 

\\here R., is the ECO response of the air sample. R, is the 

ECO response of the calibration sample. X is the known 

mixing ratio of the calibration samp le. and z, is the mixing 

ratio of the air sample. The one-point method can be 

plagued b) nonlinearities in chromatography and detector 

response (Fi gure 5. 16). Compounding problems occur 

"hen the calibration tank is replaced " ith a nC\\ tank with 

di ffcrent assigned concentrations. Because the one-point 

method approximates the actual ECD response with a 

straight line \\ ith a zero intercept. a change in the mixing 

ratio of the cal ibrat ion tank().'.', and R, ) results in a different 

slope used to appro\irnate the ECO response (Figure 5.16a). 

This can lead to discontinuities in the atmospheric record 

\\ hen the true ECO response is nonlinear. Small errors can 

occur e\en when two cal ibration tanks are used (i.e .. mixing 

ratio is determined as the mean of two one-point 

calculations). 

Two-point method. The results of both ca libration tanks 

together can be used to calculate mi.\ing ratios b) 

approximation of the ECO response \\ ith a straight line'' ith 

a nonzero intercept (Figure 5. 17): 

Ra - Rt1 (Xc1 Xe.:>) 

1.a = + 1.d (2) 

\\here R., is the ECD response of the air sample. R,.1 is the 

ECD response of Cl. I< ! IS the l:.CD response orc2. X.1 is 

the known mi\ing ratio of CI. and Xe-' is the known mixing 

ratio of C2. Im pro' ements in accuracy. compared with the 

one-point method, can sometimes be obscured b) precision 

problems associated with the two-point method. Random 

noise in both measured quantities R.-1 and R,! can affect the 

slope and intercept. Averaging ca libration tank respon ses 

over short time periods can improve precision. Changing 

calibration tanks can also lead to discontin uit ies in the 

atmospheric record when the two-point method is used. 

because different segments of the non linear response cune 

arc encountered as calibration tanks with different mixing 

ratios are used. This is particularly true for trace gases\\ ith 

strong tropospheric trends (such as Cll 1CCI i). 

In addition to difficul ti es associated \\ ith nonlinear ECO 

response. the accuracies of both the one-point and two-point 

methods arc dependent on the accuracies of the mixing 

ratios assigned to the calibration gases ().'.', 1 and X,!)· To 

address these issues. a new method that utilizes the 

thousands of routine measurements made of each cal ibration 

tank during normal operation was de\ eloped. The method 

can be used to adjust assigned calibration tank 

concentrations (\\ ithin specifi ed uncertainties) to provide a 

se lf-consistent set of calibration standard s and minimize 

discontinuities in th e atmospheric time series. 

Statistical ratio method. Th e CATS GCs make 

continuous measurements of each calibration tank every 

day. about 12 injections per da). O'er the lifetime of the 

calibration tank (usuall) 9 to 12 months) nearly 4000 

separate measurements of each calibration tank can be 

11 5 

Q) l. 0 {/) a i:: C1 1 0 

p, 

{/) 0 .8 Q) 

0:: 

,.,.. 

0 0.6 C1 2 JJ 

u 

Q) 

JJ 

Q) 

Cl 0.4 

'O 

Q) 

N 

·rl 

...... 0 . 2 <ll 

E 

,.,.. 

0 

z 

0.0 

0 100 200 300 

Mixing Ratio 

Q) / / {/) 

i:: b / 0 0 . 9 

p, 

{/) 

Q) 

0:: 

,.,.. 

0 0.8 JJ 

u 

Q) 

JJ 

Q) C1 2 Cl 

'O 0 . 7 Q) 

N 

..... 

...... / <ll / C1 1 

x E 0 .6 a ,.,.. x1 x2 0 

z 

160 180 200 220 240 260 

Mixing Ratio 

rig. 5.16. Estima1es of mixing ratio b) the one-poim me1hod. Plot (a) is 

full scale and (b) is expanded. Both plots demonstrate 1he potential 

problems that can occur" ith onl~ a single calibration measurement. The 

nonlinear response cur.c (solid) is the nonnaliLed response to a knmrn 

quantit) of a panicular molecule (in arbitrnT) uni1s). The one-point 

method ll>C> a single measun:rrn:nt of an assigned mi,ing ratio (CI ) and 

as>umcs a linear response (dotted lines). For an ECO "ith a nonlinear 

response. a calibration error \\ill occur if the air sample and calibra1ion 

gas ha\'e significantly differem responses. The solid 'enical lines (X1• 

X: ) com:spond 10 1he mi.\ing ra1ios calculated for a response of0.8 using 

'''o diflerent calibra1ion standards (C I and C I: ). The middle \Cnical 

line (X,) is 1he actual mi\ing ratio if the response cur.e is knO\\n. 

made. Se\eral comparisons of one calibra tion tank to 

another (Figure 5.18) can be used to adjust the assigned 

mix ing ratios such that the effects of calibration tank 

changes arc minimi zed. 

A two-step procedure is used to establish a sci f-consistent 

set of calibration tank mixing ratios. The tirst step takes 

adrnntage of the fact that the mean response ratio of 

calibration tanks is functionally related to the assigned 

calibration tank' alues: 
Qi 

Ul 

i:: 

0 

Cl. 

Ul 

Qi 

~ 

H 

0 

JJ 

u 

Qi 

JJ 

Qi 

Cl 

'O 

Qi 

N 

·.-i 

.-i 

cu 

E 

H 

0 

z 

0 . 8 

0 . 6 

0 .4 

0 . 2 

.. .... ····· 

0 

Cl 

........................ 

C2 

100 200 300 

Mixing Ratio 

Fig. 5.17. E>t1111ates of mi"ng ratio b) the t\\ o-point method. This 

method utili1es t\\O cahbrauon tank measurements (C 1 and C:!) to 

appro.,imate the response cunc (solid) with a straight line (dashed). 

59981 52762 65142 65178 64466 64461 67?14 66000 '-, \ I 

"' ., 

"' 11 c: 

0 

Q, 

"' ., 

Q: 09 

;;; 

u 

0 07 

.!2 

;;; 

Q: 

05 

1998 1999 2000 2001 2002 

Date 

lig. 5.18. Response ratio (Cl C'.!) for ClLCCl, at S:'\10 for different 

pairs of calibration tandard ~>. Calibration tank changes are sho" 11 a ... 

\enical lines identified b) cylinder number along the top of the figure. 

,,= l(x .x ,:J"' 111(~''.'l +h. x,_., 

(3) 

"here 8 11 is the response ratio of the ;•h CI tank to the /h C'.2 

ta nk. Xc1, is the assigned concentration for the ;•h C I tank, 

and X. c:, is the assigned concentration for the /h C'.2 tank. 

The ratio 8 11 can 'ary between 0.5 and I. I depending on the 

gro\\ th rate of the compound anal)led and \\hen the 

cal ibration tanks \\'ere prepared. Plotting the measured 

mean calibration tank ratios (8 11 ) versus assigned 

concentration ratios creates an effecti\e ECO response 

cun e (Figure 5. I 9a) that can be fitted \\'ith a least-squares 

regression line. The line repre sents a long-term a\'erage 

ECD response for a part icular molecule. If the 

116 

1.1 

0 

+.: 

"' 0::: 0.9 

ci. 

"' 41 

0::: 0.7 

l1l 

() 

0.5 

ui 0.1 0 

~ 0.00 

~ -0.10 

1.1 

0 

+.: 

l1l 0.9 0::: 

ci. 

"' 41 0.7 0::: 

l1l 

() 

0.5 

a 

0.5 

b 

0.5 

... :: :::::::. ·::::: .. :r:•:::::::: ............... . .. ; ........ _ .. "-"""l ·-!.::·····-· ··-·· 

- ······· i -r -----· ······ 

·················· ·i· 

0.7 0.9 1.1 

Assigned Cal. Ratio 

·····-··-·-···-·I·-·-····-···-··- -------·-··-··?-- ·-·-··· 

0.7 0.9 1.1 

Assigned Cal. Ratio 

Fig. 5.19. (a) :'\lean response ratio for C H,CCh at S\10 plotted against 

the ratio of assigned Cll ,CCI; concen tration for each calibration tank 

pair. A linear least-square;, fit through the calibration tank ratio> (solid 

line) is used to compute an a,·eragc cffccti\'e response cune. Residual 

differcnccs are plottcd at the top of the graph and demonwmc the 

magnitude of errors assoc iated "ith a calibration tank change. (b) \lean 

response ratio as in (a) e:-.cept that calibration tan I.. concentrations IHI\ c 

been adjusted to minimi1e the residuals. 

chromatography is stable O\cr the period of all B,, 

measurements, the linear fit can be used to calculate air 

concentrations and estimate errors. The functional 

relationship is nearly linear for all compounds measured by 

the CA I S instru ments. Problems arise in the linear 

representation "hen there are chromatographi c problems. 

such as co-eluting compounds and ECO res ponse cun es 

that s ho" rclati\ el) large nonLero intercepts. For current 

tropospheric mixing ratios or all species measured b) CATS 

instruments. equation (3) seems to pro' ide a good estimate 

for the effectiYc response cunc. 

Once the slope and intercept of the effecti\e response 

cur\c are kno\\ n. uncertainti es in the assigned calibration 

tank mixing ratios ca n be incorporated: 
B _ ( Xc1,;+<lc1,;) + b ij - Ill 

X c2.j + <J c!.j 

(4) 

where <Jc1.; is the possib le uncertainty assoc iated with the i

1

h 

CI and <Jc!.J is the possible uncerta inty associated with the 

/h C2. A nume ri ca l algorithm is used to iterati vely adjust 

a ll <Jc1.; and <Jc!.J to minimi ze the residual difference (Figure 

5. I 9b). The adjustme nts to the calibrati on tank va lues are 

constrained by the estimated uncertainties on the a ssigned 

values (section 5.2.3). For most compounds the 

adjustme nts are less than 0.5% of the ambient mixing ratio. 

Equation (4) c an be rewritten in te rms of Xa to yield two 

equations to compute atmospheric mi xing ratio usi ng the 

optima l values o f <Jci.; and <JcZ,/ 

(5) 

Xa=<xc2.1+acz.)_!_ ( RRa -b) · 111 c2.j 

(6) 

If both calibrat ion tanks are in operation, the average of 

equations (5) and (6) is used . Atmospheric mi xing ratios 

calculated with the statisti ca l ratio method tend to be more 

precise than with the two-point method and are more 

accurate than the one-point method. The gain in precision 

comes from use of the average response curve rather than 

estimation of a response curve from each sequence of 

measurements, as in the case o f the two-poi nt method. 

Figures 5.20 and 5.2 1 illu strate the diffe rences between 

results from the two-point method and fro m the statistical 

ratio method. Figure 5.20a shows discontinuities in the 

mixing ratio for C H3CCl3 at SMO calculated with the twopoint method . T hese discontinuit ies are the result of rapidly 

changing atmosphe ric CH3CCl3 mtxmg ratios, and 

calibration tanks that have widely varyi ng C H3CCl3 re lati ve 

to the atmosphere. The CH3CCl3 data shown in Figure 

5.20b were calculated with the statistical ratio method. 

These data clearly represent a continuous time series. The 

missing data seen prior to the 64461 calibration tank change 

correspond to a period in which the C2 tank (65178) was 

emptied before the arrival of its repl aceme nt. Even though 

the ratio of calibration tanks cannot be used for this period , 

the statistical re lationship used to deri ve equa tions (5) and 

(6) is still val id. In th is case the atmospheric mixing ratio 

can be calcul ated with equation (5) withou t having to rely 

on the one-point calcu lation method. The CFC- I I data 

from BR W shown in Figure 5.2 1 do not show large 

discontinuities associated with calibration tank changes. 

However, application of the statistical ratio method reveals 

a possible downward trend in CFC- I I concentration 

(Figure 5.2 1 b) that is not apparent in data computed with 

the two-point method (Figure 5.2 1 a). 

The application of the statistica l ratio method is new to 

the HAT S in situ program and may undergo further 

enhancements. For example, the two-point method may be 

preferred during periods when chromatography is 

11 7 

52762 59981 65142 65178 64466 64461 67714 66000 "/ I I I I 

60 

a 

50 

40 

a. 30 .e: 

_,, 

0 

0 60 £ 

0 b 

50 

40 

30 

a 

J~ c ~ 

I 

.e: 

~~ ., 

- I l u .... ' c 

e 

., 

:i: 

i5 I I I I 

1998 1999 2000 2001 2002 

Fig. 5.20. CH3CCI; data from SMO computed with two difTere111 

methods: (a) the two·poi111 method and (b) the statistical ratio method. 

The difTerence between methods (a) and (b) is shown in (c). Note that 

many of the discontinuities in (a) are absent in (b). Calibration tank 

changes are shown as vertical lines identified by cylinder number along 

the top of (a). 

66834 38422 651 58 65994 64612• 

275 

265 

a 255 

.e: 

~ 

u 

u. 275 0 

265 

255 

a 

11 

.e: 

" u 

c 

e 

., 

:i: 

i5 

111198 

b 

c 

-*- Flasks GC-ECO 

_._ Flasks GC MSD ==="'="= ==""=~ 

+ CATS 

CA TS Monthly 

Barrow, Alaska 

1/1/99 1/1/00 

Date 

111101 111/02 

Fig. 5.2 1. CFC- I I data from BR W. as in Figure 5.20. Also included are 

data from nasks analyzed on GC-ECD (red) and GC-MSD (green) 

instruments. and monthly mean values from the CA TS instrument 

(yellow). Although disco111inuities are not apparent in (a). the statistical 

ratio method (b) dramatically improves precision. 
noticeably di ffcrcnt from the statistics upon \\'h i ch the 

method is based. 1-lo\\'e\ er. \\'ith each additional working 

standard. the entire data record could change signifi cantly 

when the statistical ratio method is applied. A future 

improvement might be to use equation (2) in conjunct ion 

with the est imated a, 1 , and a ,!.J for these periods. 

5.2.3. GRA\' L\I ETRIC STA:'\DARDS 

Calibration Scales 

Numerous standards were prepared in 2000-2001. In 

total. 62 gravimetri c standards were prepared and 89 

working standards were filled at N\VR during this period. 

The calibration scales of N20. SF6• CFC-12. CFC-I I. 

CH3CCl3• CCI~, and halon-121 I were examined \\'ith the 

aim of incorporating all HATS measurements. as well as 

CCGG N20 and SF6 fl ask measurements, on common 

scales. This ir1\ol\ed analysis of numerous working 

standard s used by the flask programs. airborne programs, 

and in situ programs. This work will continue into the near 

future and will include additional molecules. 

A key element o f this work involved the preparation o f 

additional gravimetric standards for N~O and SF6 (Fi gures 

5.22 and 5.23). Previous scales for these molecules had 

been defined by a limited number (four to six) of gravimetric 

1.2 a (j) 1.0 <J) 

c 

0 

0.. 

<J) 

~ 0.8 Q) 

> 

~ 0.6 

Qi 

a: 

0.4 

0.2 

2 b • 

ti. .0 

0.. 

0.. 

ro 0 ::::> 

0 t;ti.O ti. 

ti. A 

ti. 

"O 

"ii) 

Q) 

a: -1 

• 

0 0 

ti. ti.. 

• -2 

100 200 300 

Prepared Mixing Ratio (ppb) 

Fig. 5.22. (a) Second-order calibration cune and (b) residual. resulting 

from analysis of gra\'imetric standards that define the :moo N,O scale. 

Standards prepared from similar primary standards are sho\\"n as similar 

S)mbols. 

11 8 

a 

1.5 Q) 

<J) 

c 

0 

0.. 

<J) 1.0 ~ 

Q) 

> 

~ 

Ui 0.5 a: 

0.0 

0 2 4 6 8 

0.2 ____.. b Nol included in 2000 scale 

0.. 0.1 ti. 0 0.. 

co 0.0 0 ::::> ti. ~ti.ti.~ 0 "O QI ·u; 

Q) ti. 

a: 

0 -0.1 

-0.2 

0 2 4 6 8 

Prepared Mixing Ratio (ppt) 

Fig. 5.23. (a) Second-order calibration cun·e and (b) residual. resulting 

from anal)sis of gra\'imetric standards that define the 2000 SF6 scale. 

Standards prepared from similar primary standards are shown as similar 

symbols. 

standards. While these standards were useful for defining a 

scale O\'Cr a wide concentration range. the lack of mu ltiple 

standards with near-ambient concentrations presented 

difficulties in establishing the long-term stability of these 

scales. New primary standards were prepared from the same 

reagents used to establish the original scales. Secondary/ 

tert iary standards were prepared from the new primary 

standards as well as from exist ing primary standards. The 

2000 N20 scale is about I ppb lower than the 1993 scale. and 

it is 0.5 ppb higher than that predicted using 300 and 330 ppb 

National Institute of Standards and Technology (N IST) 

Standard Reference Materials (SRMs). The 2000 SF6 scale 

differs from the 1994 scale [Geller et al .. 1997) by less than 

0.1 ppt, \\'hich is \\'ithin the uncertainty assoc iated with the 

199~ scale. 

A scale based on a large number of standards makes it 

easier to identify outliers (standards that. for \\·hatever reason. do 

not agree with the majority) (Figure 5.23). These new N~O-SF6 

standards ha\·e also helped to improve the long-term stability of 

the N20 and SF6 scales (e.g .. the loss or drill ofa single standard 

does not affect the scale as much as it would if the scale were 

defi ned by onl y a few standard s). More information on 

gravimetric standards used to define HATS scales. 
including a list or the standards used 10 define the ne\\· :moo N~O and 2000 SF6 scales. is available on the Cf\IDL llATS 

website (l111p:/ \\" \\'.cmdl.noaa.go\ hats standard 1scales.h1m). 

A second element of this work ill\ohed the anal)sis of 

reagent-grade materials used 10 prepare primar) standard s. 

The reagents used 10 prepare primar) Cll ,CCI,. CCl4 • and 

CFC-12 standards \\ere sent 10 l\ IST (Gaithersburg. 

f\laryland) for purity analysis. No significant ,·ola1ile 

impun11es were found in CFC-12 or CCl 4 reagents. 

I I owe\ er. 1he Cl l)CCl3 reagent used 10 establish the 1996 

Cll 3CCl 3 scale [sec Hall et al .. 200 I] \\as found 10 contain 

impurities amounting to approximately 6.4°0 (by mole). 

New high-purit) reagent-grade Cl 11CCl3 11as purchased 

from a different 1cndor (Sigma-Aldrich. SI. Louis. 

f\lissouri .). The puril) of this ne\\ reage111 is approximate!) 

99.8% based on the l\ IST analysis (99.9% according to the 

manufacturer's assay). New primar) standards \1ere 

prepared from this reagent. These ne" standards sho\\ a 

molar response that is roughly 5% higher than those 

prepared from th e old reagent, which is consistent with the 

results of the reagent ana lysis. Dc1 elopment of a new 

Cl 13CCl 3 scale 1s under \\'ay. 11 is e.\peeted that this ne" 

scale will be about 5°0 lo\\'er than the 1996 scale used in the 

publications of l/11r.11 e t al. [ 1997]. Volk et al. [ 1997]. 

Butler et al. [ 1999) . . \font=ka et al. [ 1999. 2000]. and 

Ro111ashki11 et al. [ 1999]. 

Gra\'imctric standards for carbon) I sulfide (COS) were 

prepared from ne\1 ly purchased COS reagent. Se\ era! pptle1 el standards were prepared in 29-L Aculi fe-treated 

aluminum C) linders. The stability or these standards is 

being e1aluatcd. Two of fi\e ppt-le1el standards an: 

already sho" 1ng signs or COS loss. Although many of the 

working standards used in the in situ program do not sho\\ 

COS loss. the 1 iabilit) of aluminum C) lind ers for COS at 

the ppt le, el is sti ll being e\aluated. 

Ne11 gra\ imetric standards for CO 1\cre prepared in 

1999-2000. These ne\\' standards helped 10 con firm that 

secondary standards prepared in 1989 had drifted and that a 

scale update \\as needed [Tans e t a l .. 2001 ]. The scale \I ill 

be maintained by preparation of ne\1 gra\ imetric standards 

e\·ery 2 years and by comparison of ppb-lc\ e l standards lo 

ppm-le,el l\IST SR\1s. 

Calibration of Working Standards 

Working standards continue 10 be caltbra1ed using a fourchannel gas chromatograph similar to those used for in situ 

measurements (CATS). The initial cal ibration of this 

instrument \\'as established in 1999 by comparison of a 

\\Orking standard (natural air at ambient conecntration) to 

gra1·imetric standards. as well as to pre\ ious working 

standards. Routine calibration is maintained b) comparison 

of the working standard to fi,e additional '' orking 

standards (mixtures of natural and ultrapurc air at 

concentrations ranging from -t0°o to I00°·o of ambient). 

These comparisons are performed C\ er) 1-2 months or after 

a significant change in GC operating parameters. Frequent 

analysis of these working standards enables detection of 

small changes in GC performance or response 

characteristics '' ithou1 depletion of gra' imc1ric standard s. 

Each set of gra\ imctric standards used to define a particular 

sca le is anal) Led yea rl y. 

The routine ana lysis of the working standards also 

pro\ ides information on the da)-lo-da) \ariability of the 

GC. This information can be used to pro' iclc an estimate of 

the uncertainties associated \\ ith the calibration of \\ Orking 

standards using this instrument. KnO\\ ledge of the day-toda) \ ariabilil) is crucial if small changes (drift) are to be 

detected. Table 5.7 sho\\ S the precision O\er a single da) 

and uncertainties O\er multiday periods. associated \\ ith the 

calibration of a working standard. The information in Table 

5.7 is related onl) to the performance of the CATS 

instrument and does not describe the accuracy or the 

calibration scales. It is useful lo assess ho\1 well t1\0 

identical standards can be ca librated. or the degree to which 

two calibrations of the same standard. performed months or 

years apart. can be expected to agree (assuming that the 

standard is stable 0\ er this period). Instrument precision on 

a gi\cn day (Table 5.7) is often \cry good. 0.-t ppb for N~ O. 

for example. HO\\e\ er. differences in the mean 

concentration determined on different days can occur 

because of the imprecise nature of the calibration method 

and small changes in response characteristics associated 

'' ith changes in carrier gas purity. column condition. etc. 

For these reasons. standard s are typicall) analy1cd on 2-3 

different days. Uncertainties associated '' ith multiday 

ca librations are larga than the dail) precision and decrease 

'' ith additional analysis. as expected. Although it is 

impractical 10 ana ly1e working standards O\ er I 0 days. 

these data pro\'idc an estimate of the best o\·erall 

uncertainty achiernble '' ith 1hc CATS calibration system. 

119 

Sell' Higll-Pre!.!.11re Cylinders 

Aluminum cylinders arc not ideal for the long-term storage 

of methyl halides. Air stored in Aculife-treated aluminum 

C) linders. particular!) those purchased since 1998. tend 10 

sho\1 decreases of Cll1Br and increases in Cll 1CI O\er time. 

The rate or change of these compounds is high!) \ariablc and 

C)linder specific. A small number of these C)lindcrs seem to 

be relatively stable. but an altcmati\e is clearly needed. 

TABLE 5.7. Precision and Unccnainties Associated'' ith 

the Calibration of Working Standards 

Uncena11ll) l.Jncenamt} 

Precision* (3 da)>l·;· ( 10 da)>)i· 

l\.Q (ppb ) 0.-1 0.8 0.5 

CTC-12 (ppt) 0.8 1.3 0.8 

crC-11 (pptl 0.6 1.0 0.6 

Cl C-113 CpptJ 0.2 0.5 0.3 

( II CCh!pptl 0.2 0.6 cu 

CCIJ (pptJ 0.2 0.7 0.-1 

sr <rr•I O.D3 (l.0~ 0.02 

llalon-12 11 (pptJ 0.0~ 0.03 0.02 

*Typical dail) precision (e\prcsscd as 2cr"N'"J associated \\ith 8- 10 

co111parisons of an unkno\\ n to a rd'erence standard at a111bicnt conce111ra1ion. These data are si1111lar to those of I /all <!I al. [200 I]. 

·;·uncenaintics associated \\ith a muhida) calibrauon (95 . confidence k1 cl). The uncenaintics associated "ith the 3-da) calibration 

arc typical for the calibrauon of 11orking standard'> used 111 the fla sk and 

in situ programs. 
In an allcmpl to obtain gas cylinders that 11 ill be superior 

to aluminum cylinders for the long-term storage of methy I 

halides. se' eral clectropolishcd. sta inl ess-steel cylinders were 

purchased. These cylinders arc appro' ed by the Department 

of Transportation for transport at pressures of 6200 kPa (900 

psi). Pre limina ry stability tes1ing inrnh·ed filling cylinders 

with moist ultrapure air and moist natural air. No sig nificant 

changes were observed in the ultrapure air samples (i.e .. 

outgassing of compo unds normally detected with CATS 

instruments was not obser,ed). 

5.3. AIRBOR~E PROJECTS 

The Airborne Chromatograph for Atmospheric Trace 

Species (ACATS-IV) [Romaslikin e1 al .. 2001 ) and 

Lightweig ht Airborne Chromatograph Experiment (LACE) 

(.\foore el al., 2002] arc GC instruments designed to measure 

CFCs, N~O. SF6• and other trace gases aboard aircraft 

(ACATS-IV and LACE) and balloo n (LACE) platforms. 

Measurements of these trace gases in the lowe r stratosphere 

can pro' ide insight into the chemistry and transpo rt o f that 

region . This section desc ribes some of the science results 

deduced from measurements made during the Stratospheric 

Aerosol and Gas Experiment Ill (SAGE Ill) O.wne Loss and 

Validation Experiment (SOLVE) (11ith ACATS-IV and 

LACE ) and the Atmospheric Chemistry and Combustion 

Effects Near the Tropopause 11 (ACCENT-I I) campaign (with 

LAC E). 

SOLVE was an in, estigation of 11 intertime stratospheric 

ozone losses in the Arctic 'ortex usi ng in situ and remotely 

sensed measurements made from aircraft and balloon 

platforms. The primary goal of SO L VE was to increase 

knowledge of the processes that influence northern polar 

ozone from lat e autumn throug h lat e winter. A second 

object he. ,·al idat ion of SAGE 111 o7one measurements. was 

no t achie,ed because the sa tellite was not deployed prior to 

the campaign. SOL VE was conducted simultaneously with 

the Third European Stratospheric E\periment o n 0 7one :moo 

(TllESl:.O 2000). which inc luded independent measurements 

from aircra ft and balloons. 

AC A TS-I V 11as part o f the NASA hig h-altitude ER-2 

aircraft payload during the 2000 SOL VE campaign. The ER2 aircraft flew 11 science fli gh ts from Kiruna. S11eden 

(67.9° 1• 2 1.1 °E). and 5 transit fli ght segments between 

Kiruna and NASA Dryden. Edwa rds. Californ ia. between 

Ja nuary 9 and i\larch 18. 2000. Science flig hts included deep 

,·orte:-. penetratio ns to 90°N. \'Ortex edge and extra-\ortcx 

sur,eys. and multiplc-le\el fli ghts for \ert ical profiling. 

ACATS-IV produced science-quality data for each of these 

flig hts. As discussed by Romashkin et al. (2001]. ACATS-IV 

was modifi ed for SOLVE by decreasi ng the interval between 

measurements of N~O. Sf 1,. CFC- 12. and halon-12 1 I to 70 

seconds. while CFC- I I. CFC-1 13. CHCl_i. C ll,CCl1• CCl 4• 

. and Cl 14 11 ere measured e\'er) 140 seconds. Rommhkin 

et al. [200 1) also pro,idcd detailed information about the 

operation and cali bration of AC A TS-IV. the processing of 

data. and the precision and e rrors of measurements. 

LACE was flo11n on 1110 NASA-spo nsored !lights of the 

Obsenatio ns of the l\liddle Stratosphere (Oi\IS) balloon. The 

fi rst flight. No\ ember 19. 1999. occurred just afte r the 'ortex 

edge had formed. The second fli ght. March 5. 2000. occurred 

just prior to 'orte.\ breakup. 

120 

Several significant alterations were made to the ER-2 

payload fo r SOL VE. One important c hange was the 

replacement of the 1 ASA Airborne Tunable Laser 

Absorption Spectrometer (ATLAS). a long-standing source of 

high-quality. 1-117 N~O data. 11 ith a ne11. compact. 

lightwe ight mnable diode laser spectrome ter (Argus) 

designed to pro' ide high-quality. 1-117 N~O data as 11 e ll as 

high-precision measurements of Cl 14 every 3 seconds. A 

comparison of coincident N20 data from ACATS-IV. 

ATLAS. and the NASA Jet Propulsion Laboratory (JPL) 

Aircraft Laser Infrared Absorption Spectrometer (ALIAS) 

during t\\'O pre\ ious ER-2 campaig ns [Hur / el al., 2000) 

showed ty pica I agreement o f I.9°·o between AC ATS-IV and 

ATLAS. 2.7°·o between ACATS-IV and ALIAS. and 2.8°0 

between ALIAS and ATLAS. A similar comparison of 

SOL VE O data re\'caled typi ca l agreement of 3.8°0 

between ACATS-IV and Argus. 2.6°0 between ACATS-IV 

and ALIAS. and 4.0°0 between ALIAS and Argus [/lurst el 

al .. 2002). The poorer agreement between N20 instruments 

during SOLVE spa\\'ncd the idea to construc t a selfconsistent. high-resolution N~O data set from the data o f the 

three in situ N~O instruments. An objecti\' e statisti cal 

method 11 as de\ eloped to reduce biases between the 

instruments. then combine their meas ureme nts into a 

"unified" N20 data set 11 ith 3-s temporal resolution (/!ttr.11 el 

al., 2002). The qualit y o r unified N~O data 11as evaluated by 

integration or the data O\'er the canister-filling periods of the 

National Center for Atmospheric Research (NCA R) \\hole 

Air Sampler (\VAS) during SOLVE F:R-2 fli ghts. The N~O 

data from the canisters agree" ith the integrated unified o 

data 11 ithin about 1. 5° o. 11 hi ch is belier than the agreement 

between any pair of'N~ O instruments. 

Record ozone losses for the Arctic stratosphere ha'e been 

reported for 11 inter 1999 2000 [Richard et al.. 200 I: 

Sa/all'itch el al .. 2002). These losses arc predominantly 

auributed to chemical 0 1 destruction dri' en by 1he most 

11 idespread presence of po lar stratospheric c louds (PSCs) in 

the Arctic since the 1970s [Rex el al .. 2002) and near-peak 

le\Cls of tota l halogen (Cl + Br) in the lo11 e r stratosphere 

[£/kins. 2000]. Measurements of chlorinated and brominated 

source ga ses in the lower stratosphere. combined with CMDL 

surface measurements of these gases. auest to the high 

a'ailability of ino rganic halogen in the older air masses o f the 

Arcti c 1 ortex. Figure 5.24 ii lustrat es that o rgani c chlorine 

(CCI, ) a nd organic bromine (CBr,) are more 1han 50°0 

col1\ertcd to inorgani c chlorine (Cl,'i and inorganic bromine 

(Br) in air masses with mean ages. greater than 4.5 and 3.0 

years. respecti' ely. In addition. sc\ ere denitri fication [Popp 

et al .. 2001] (Figure 5.25) grea t!) inhibited chlorine and 

bromine deacti\'ation reactions that moderate 0 3 destruction 

rates [Cao el al .. 200 I]. Fahey e1 al. (200 11 describ1.:d the 

first in si tu measurements o f the large llNOrcont aining 

partic les \\'hose gra' itational sedimentation resulted in the 

obsen ·ed seYere denitrifi cation. In contrast. signili cantl y 

dehydrated air masses (>I 0°o 11 0 loss) were rare!) 

encountered bet11een 17 and 2 1 km. indicating that 

temperatures in this altitude range were often belo11 the 

temperatu re at 11 hich nitric acid trihydrate (NAT) forms. but 

seldom below the ice frost point. Ho11·e\ er. Herman et al. 

[2002) reported a sl ig ht decrease in to tal hydrogen 11 ith 

altitude that resulted from the "idcspread sediment ation of 

PSC pan ides during the 11 inter. 
Cumulati ve 0 3 loss and 0 3 loss rates in the Arctic vortex 

during SOL VE have been calculated from measurements 

made by instruments aboard the ER-2 aircraft and balloons. 

Richard el al. (200 I] ana lyzed in situ data lo determine a 

cumulative 0 3 loss of 58 ± 4% al 19-km altitude bet\\·een 

February 3 and March 12, 2000. Their calculations are 

based on the wintertime evolution of the vortex 0 3:N20 

relationship (Figure 5.26a). Ozone loss rates at 19 km were 

as high as 51 = 3 ppb d. 1 during late winter (Figure 5.26b) 

(Richard et al., 2001]. Rex et al. (2002] examined data 

from 770 0 3 sondes launched from 29 northern stations to 

sample distinct air masses twice over several day intervals 

as they circumnavigated the pole and reported 70% 

cumul ative 0 3 loss near 18-km alti tude and a cumul ative 

~ 3.5 

ITota,'cq., 

0 0.. 

s 3.0 "Tl 0 Q3 >. Co n. 0 2.5 Oo ' i5" -0 ... .. 0 :::J 

c .. rw.· (n g_ <U 2.0 >. [§] (") 

0 1.5 0 0 

() 

.~'1." . ~ -< - 1.0 v 

() .i/1 '~?' .. : 0 0 Iii 0.5 .'.~ @§] i\J -< 0 ,,:\.' CCly 

f- .. ::lilt .. . . 20 

a. 0 s "Tl 

2'.' Q3 15 0 Q. co CX> 6' -0 :::J c 

ell ~ 0 

10 (J) - i- 0 

co 0 OJ 

() ~ -< ..: 5 v co 0 OJ Iii i\J -< 0 ... f- ....... 0 0 .. 0 

0 2 3 4 5 6 7 

Mean Age (yr) 

Fig. 5.2-l. Top: Total chlorine (solid cur\'e). organic chlorine (CCI,. gray 

squares). and inorganic chlorine (Cl,. black circles) as a function of mean 

age for air masses sampled by AC A TS-IV during SOLVE. The fraction of 

organic chlorine com'ened to inorganic chlorine resenoirs was approximated by the black circles using the right axis scale. Bollom: Same as the 

top graph. but for bromine. CCI, and CBr, are the sums of chlorinated and 

brominatcd source gases measured in the lower stratosphere by AC A TS 

and the NCAR \\hole air sampler. Tomi chlorine and total bromine were 

dctennined from C~I DL global surface trends of source gases with 

appropriate age spectral weightings. CI, and Br, were calculated as the 

difference bem·een total Cl (Br) and CCI. (CBr,). ean ages were 

calculated from ACATS measurements of SF6 in the lower stratosphere 

and the SF6 global surface trend [Geller et al.. 1997]. 

12 1 

15 

~ 

0.. 10 s 

>-

0 

z 

5 

0 

0 50 100 150 200 250 300 

Fig. 5.25. Coincident in situ measurements of NO, with the NOAA 

Aeronomy Laboratory total reactive nitrogen instmn;ent [Fahe1· et al .. 

1989) and NiO with ACATS-IV on board the ER-2 aircraft during 

SOL VE (black circles). These data document severe and extensi\c 

denitrification in the Arctic vortex. The reference cun'e, a quadratic fit 

to NO, and N10 measured by the balloonbome klV interferometer on 

December 3, 1999 (open diamonds), represents the early-vortex 

N0,:1 10 relationship before the onset of denitrification. Points belm1 

the reference cun e indicate that air masses between 17 and 21 km 

altitude were denitrified by up to 75%. Nitrification at lower altitudes 

(14- 16 km) is shown by points above the reference curve. (Figure 

adapted from Popp et al. [200 I].) 

column reduction of 11 7 :r 14 Dobson uni ts (DUs) by late 

March 2000. Salall'itch et al. [2002] studi ed the evo lution 

of 0 3 :N10 relationshi ps to concl ude that chemical 0 3 loss 

between 14 and 22 km caused a 6 1-DU reduction of column 

0 3 between late November 1999 and March 5. 2000. The 

ozone loss and loss rates deduced in these three studies are 

in good agreement. 

Grooss et al. (2002] used data from ACATS-IV and other 

instruments to initialize a stratospheric chemistry and transport 

model. the Chemical Lagrangian Model of the Stratosphere 

(CLaMS), that simulated Arctic ozone loss during SOLVE. 

Model simulations agreed well with the observed ozone loss at 

450 K (about 19-km altitude) but tended to underestimate 0 3 

losses at higher altitudes, probably because of the limited 

amount of data used to initialize the model at higher altitudes 

and the absence of diabatic descent in the model. 

Accurate differentiation between wintertime changes in 

vortex 0 3 caused by chemistry and those caused by 

transport relies strongly on determinations of how much 

extra-vortex air mixes into the vortex. The vortex edge is a 

barrier to the exchange of midlatitude and vortex air. 

Previous work implied that differences between vortex and 

extra-vortex tracer-tracer relationships were due to largescale, homogeneous descent in the vortex and significant inmixing of extra-vortex air [Pl11111 b el al .. 2000]. Descent 

can be roughly estimated by tracking the motion of air 

parcels with an inert tracer, as shown for N10 in Figure 

5.27. Most of the molecules measured by ACATS-IV and 

LACE are inert in the vortex. lacking local sources and 
3000 

2500 

:g: 2000 

s 

0 1500 

1000 

500 

-10 

-20 

-30 

-40 

-50 

- 20000226 -e- 20000305 

- 20000307 - 20000312 

B 

. .. · ; 

.,. 

-60L-~~......_~~-'-~~~~~--''--~___, 

50 100 150 200 250 300 

N20 (ppb) 

Fig. 5.26. (a) Coincident in situ measurements of 0 1 with the NOAA 

Aeronomy Laboratory dual-beam ultraviolet photometer [Proffill and 

/llcla11ghli11, 1983) and N20 with ACATS-IV on board the ER-2 aircraft 

during SOLVE. These data show the wintertime losses of 0 1 in the 

Arctic vortex. ll1e gray reference curve. a quadratic fit to 0 3 and N20 

measured during four ER-2 and balloon nights between December 3, 

1999. and February 3, 2000, represents the early-vortex 0 3:N20 

relationship prior to ozone losses. Data from subsequent ER-2 flights 

demonstrate cumulative 0 3 losses of up to 60% from early February to 

mid-Ma rch 2000. (b) Ozone loss rates calculated from differences 

between 0 3:N20 relationships in the early vortex and for the four ER-2 

flights shown in (a). (Figure adapted from Richard el al. (2001).) 

800 "' ., LACE SOLVE N20 32 'O 

'O ... ... "' 700 '\J 11/19/99 0 u 30 >< "' 0 03/05/00 .... ... 

., 3 28 .. a. 600 SJ\OOth E it to data ,... e "' ., Mixed 11/19/99 26 f.< 

..... "' 24 ..... 500 ,... 

"' 22 .... .... ,... ,, 20 c:: c 18 ., a. 400 "' ,, 

0 16 

"" ;;;:: 

300 ~ 

0 50 100 150 200 250 300 

N 20 (ppb) 

Fig. 5.27. Profiles of N20 as a function of potential temperature (K) 

from LACE for the two OMS balloon flights during the SOL VE mission. 

Solid curves through the data arc fits used in the calculation of descent in 

the vortex between the nights. Also included is a representation of a 

well-mixed early-vortex profile (dashed curve) from the differential 

descent mixing calculation. 

sinks on the time scales of transport. Because these 

mo lecules have different verti cal mixing ratio p rofi les, each 

mo lecul e a llows fo r an independent measureme nt o f descent 

a nd other tra nsport characteristics. This calc ulation of 

descent is only valid if mixing between air parcels of 

differing tracer concentra tion does not occur on similar time 

scales. In the absence of chemistry, this type of mixing can 

be seen as a shift in the curved tracer-tracer correlation 

plots (Figure 5.28). 

122 

Ray et al. [2002] were unable to produce the vortex 

trace r-tracer relat ionsh ips observed by LACE and ACATSIV during SOLVE by mode ling homogeneous descent and 

in-mixing of extra-vortex air. They showed, instead, that 

differential descent and isentropic mixing within the vortex 

could prod uce the observed vortex re lationships. These 

processes were folded into the descent calculations (do tted 

line in Fi gure 5.27) to give the final descent rates s hown in 

Figure 5.29a. Note the good agreement across all tracers. 

The differenti al descent needed to reproduce the changes in 

tracer-tracer correlations is shown in Figure 5.29b. The 

lack of significant in-mix ing of extra- vo rtex air during 

winter 1999/2000 is an important findin g because it 

identifies chemistry, not transport, as the predominant cause 

of the large ozone losses observed during SOLVE. Analyses 

:::- 150 a. 

a. 

::- 100 

u 

u.. 50 (.) 

a 3.0 .s 

(;; 2.0 

c 

.Q 1.0 .. .c 0.0 

::;-120 

a. 

a. 

::- 80 

~ 40 (.) 

0 

300 

:0 ,9; 200 

~ 100 

x t 1119199 

• 03/05100 I 

50 100 150 200 250 

N,O (ppb) 

, • 

l • 

,,/ 

150 200 250 300 

N,O (ppb) 

"' 

\ • x• 

-· 

,_•xx 

600 800 1000 1200 1400 

CH4 (ppb) 

3.0 3.5 4.0 4.5 

SF6 (ppt) 

:::-150 a. 

a. 

::-100 

u 

u.. 50 (.) 

15: 4 a. 

::- 3 

;::, 

c 

2 

.Q 

.. .c 

0 

300 

:0 ,9; 200 

0 

:i' 100 

0 

_250 

~200 

:: 150 

u 100 u.. 

(.) 50 

0 

0 

-

100 200 300 400 

CFC-12 (ppt) 

• x • 

°;(.~ 

.. 1000 1200 1400 1600 1800 

CH, (ppb) 

JI.. 

..,. 

"" 

500 1000 1500 

CH4 (ppb) 

_.J'-;IJ. 

; 

• x 

2.5 3.0 3.5 4.0 4.5 

SF6 (ppt) 

Fig. 5.28. Tracer-tracer correlation curves from the two LACE SOLVE 

flights. Data from the second night are significantly shifted from the 

first flight toward the conca\ e side of the curves, which suggests mixing 

of some type occurred. 
30 

(j) 

(j) 

--(j) 

..--

--..--

..-- 25 c 

0 

......... 

E 

,..__.. 

~ 

Q) 20 "O 

::J 

-:;:; 

<( 

15 

0 

SF6 

• CH4 

0 N20 

0 CFC-12 

0 CFC-11 

0 halon 1211 

-- Weighted 

Mean 

2 4 6 8 

Integrated Descent (km) 

(11/19/99 to 3/5/00) 

b. 

30 

25 --ljl-::;:: -SV- SF 6 I N 2 0 

-:;;*'==t:l,_.:::..__ -e- SF 6 I CF C-11 

-R- SF6 I halon 1211 

-e- CH4 I CFC-12 

--+-- CH4 / CFC-11 

-A- CH4 I halon 1211 

-e- N20 I CFC-11 

-SV- N2 0 I halon1 211 

15b:_~~:::r~ =--- ~C:F~C~-1~2~/~C~FC~-~1~1_TI 

0 2 4 6 

Residual Differential Descent (km) 

(mixed out by 03/05/00) 

8 

Fig. 5.29. (a) Integrated and (b) differential descent deduced from measurements associated with two LACE nights within the core of the Arctic vortex 

during SOLVE. Error bars represent the calculated statistical uncertainty. 

by Greenblatt et al. [2002] and Morgenstern et al. [2002] 

using unifi ed N20 and ACATS-IV tracer data also conclude 

that the 1999/2000 Arcti c vortex was strong ly iso lated and 

experi enced little in-mixing. 

The importance o f accurate determinatio ns o f mean age 

distributions in the stratosphere has been stressed by 

Andrews et al. [2001 ]. Compared w ith mean ages 

calculated from in situ measurements o f age tracers like SF6 

and C0 2, mean ages from many stratospheri c. transpo rt 

models are unde restimated by as much as a facto r of 2. If 

general c irculation rates in the mode ls a re dec reased to 

inc rease mean ages, mode l tracer distributions fail to match 

o bserved distribut ions. Hence, mode l eva luatio ns of 

important enviro nme ntal issues related to trace gases, suc h 

as the impacts o f exhaust from a proposed flee t of 

stratospheric aircra ft and o zone layer recovery time scales, 

ma y be of limited accuracy until these discrepanc ies 

between mode ls a nd observatio ns are red uced. Using lo nglived trace r data fro m ACATS, LACE, a nd o the r 

instrume nts, Andrews et al. [2002] have constructed 

accurate distributions o f mean age in the stratosphere that 

w ill he lp improve the transport in mode ls. 

SF6 is a strong greenho use gas w ith a lo ng life time. 

Estimating its atmospheri c li fetime is impo rtant in terms of 

its contributio n to the Earth's rad iative budget as we ll a s its 

use as a tracer of atmospheri c motio n. The stratospheri c 

lifetime of SF6 is dominated by loss that occurs in the 

mesosphe re. Evidence o f this loss is measurable in 

mesospheric a ir that descends into the po lar vorti ces. 

Moo re et a l. [Measured SF6 loss and its influence on age -ofair c a lcul ations, in preparat ion, 2002] ca lcul ated the 

stratospheric life time o f SF6 from OMS data assuming that 

123 

(a) the age o f a ir calculated w ith C0 2 dat a [Andrews et al., 

2002] is correct, and differences between C02 and S l76 ageo f-air estimates from vortex data (Figure S .30) are due to 

S F6 loss, and (b) the loss of SF6 occurs o ver 6 months, a nd 

the mesosphe ri c air descends o nly into the no rt he rn vortex 

(6 months later the process repeats into the southern 

35 

30 

"E 

6 

Ql 25 "O 

~ <( 

20 

0 2 4 6 

t C02 SOLVE I Vortex 

_._ SF6 SOLVE I Vortex 

+ C02 POLARIS I Vortex Filaments 

-e- SF6 POLARIS I Vortex Filaments 

8 10 12 14 

Mean Age (years) 

Fig. 5.30. Age-of-air estimates from both C02 and SF6 data, assuming all 

stratospheric sources or sinks are taken into account. The difference 

between these two age estimates, seen both in the vortex filaments and the 

vortex core data, is then assumed to be due to SF6 loss in the mesosphere. 
'onex). The net loss withi n the northern 'ortex \\as 

multiplied b) two to estimate the yearl) loss rate. Their 

new estimate for the stratospheric li fetime of SF6 is 600 

( +200, - I 00) years. "hi ch is better constrained than the 

pre' io usly reported range of 600-3200 years [.\forris et al .. 

1995]. The upper bound in the ne\\ estimate is less certain 

than the lower bound because of an uncertainty in SF6 loss 

aboYe 32 km within the \'Ortex. 

S ignifi cant global 0 3 destruction will continue we ll into 

the 2 1" century because of the hi g h halogen burden of the 

stra tosphere [Pri1111 el al., 1999]. Accurate predictions o f 

future 0 1 le' els require accurate determinations of halogen 

budgets and the ir trends. Stratospheric chl orine 

[Woodbridge el al .. 1995] and bromine [Wamsley el al .. 

1998] budgets are periodically calcul ated from ACAT S, 

LACE, and \VAS measurements of halogenated source 

gases, allO\\ ing the determinatio n of tre nds. The calcu latio n 

methods ha'e been re' ised over time to reflect sig ni fica nt 

c ha nges in the tropospheric trends of some halocarbons. An 

important, recent refinement in these calculations is the 

weighting of tropospheric trends with age spectra (Hall and 

Plumb, 199-1; A11drell's el al .. 200 I] instead of mean age, to 

det ermine trends in total chlorine (Cl,01 ) and total bromine 

(13r",.) ente rin g the stratosphe re [Elkins. 2000]. These 

re\ is ions impro\e calculations of total inorganic chlorine 

(Cl>) and total inorganic bromine (Br>) as the difference 

between to tal chlorine (b romine) and the sum o f chlorinated 

(brominated) source gases CCI, (CBr, ). 

Scha u[/ler et al. [2002] · have · recently revised the 

stratospheric chlorine budget based on WAS and /\CATS-IV 

measurements made during SOL YE. A comparison of 

AC/\ TS-IV and \VAS CCI, for SOLVE reveals differences of 

0.015-0.190 ppb (Figure ·5.3 1), with \VAS \alues a lways 

larger because the ACATS-IV method does not account for 

c hlorine from CFC- I 14, C FC-I 14a, CFC-11 5, lf ~C ~. C~C , 

I IC FC- l-12b, and HCFC-14 1 b. These omissions account for 

0.023-0.130 ppb of the CCI> differences. The rest of the 

discrepmlC) results from ca libration-scal e differences and 

disparity in the llCFC-22 and C H3CI mixing ratios ca lcul ated 

by AC ATS-IV but measured by \VAS. The two independent 

data sets are complementary in that AC ATS reports CCI, 

more frequentl y (e,er) 140 seconds) than WAS, but thc \VAS 

CCI, data are inhere ntly more accurate. 

Ti·e nds in Cl, determined from ACATS and LACE 

measurements near 19-, 20.5-, and 2 7 .5-km altitude 0\ er the 

pe riod 1992-2000 impl y that Cl, eithe r peaked o r le,eled o ff 

by th e year 2000 (Figure 5.32a). The s um of ch lo rinated 

source gases (CCI>, or ETCI) measured at the surface by 

CMDL ( Figure 5.32a) illustrates the decreasing trend in 

Cl,01 [Mont:ka et al., 1999], large ly because o f the rapid 

decline in CH ,CCl3. These s urface CCI, data represent an 

upper limit for C l, and are closely matched by I lalogen 

Occultation Experin1ent ( HALOE) Cl> (llCI) data at 55-km 

alt itude. where near-complete con, ersion of CCI, 10 Cl, ha s 

occurred (Fig ure 5.32a). Upward trends in Br" ·appare.nt at 

all three a ltitudes (Figure 5.32b). are dri,en predominant!) 

by continued emissions of halons. The increasing sum of 

brominated source gases (CBr) measured at the surface b) 

C MDL pro, ides an upper limit for Br, . 

Of piYotal importance to stratos.pheric O/one are the 

combined influences of ch lorine and bromine trends. The 

124 

:0 

a. 0.15 

s 

Q) 

u 

c 

Q) 

Q.; 0.10 :::: 

15 

>-

0 

0 0.05 

o.oo ...._ ___ ...._ __ __..__ __ ..... ___ __. ___ ....... _ _, 

50 100 150 200 250 300 

N20 (ppb) 

Fig. 5.31. Differences between \\AS and \ CATS-IV detcm1inations of 

CC ~ as a function of N~O (solid cur\c). Values range from 0.015 to 

0.190 ppb. Panial differences in CCI, that result from the J\Ci\TS 

omission ofCFC-11..J. CFC-1 1..Ja. CFC-115. Cll:Cb. C~C . HCFC- 142b. 

and HCFC-1..J I b (dashed cun c) range from 0.023 to 0.130 ppb. The 

remaining diOercnces bemeen \\AS and AC ATS-IV CCI, result from 

calibration scale differences and the fact that Cll ,Cl and l.ICFC-22 are 

ca lculated by AC ATS- IV and measured b) WAS. (Figure adapted from 

Sclwuf}/er et al. [2002].) 

we ig hted sum of ino rganic chlo rine and bromine. namely 

equi valent inorgani c chlorine (ECll C l) + 45 x Br), 

re fleets the fact that Br, is o n a' erage 45 Ii mes mo re 

effic ie nt than Cl, at the .destruc11 on or 0 3 L1Ja11iel e1 al., 

1999]. Trends iii ECI, (Figure 5.32c) mimi c the decline or 

le,eling off of Cl, (Figure 5 .32a), because Cl, is 100-150 

times more abundant than Br, and the upward Br, trend 

docs littl e to offse t the decreasing trend in Cl,. ·Future 

trends in ECI), and hence 0 3, are strongly dependent on this 

interpla) between increasing bromine and decreasing 

chlorine abundance. Continued halon accumulation in the 

atmosphere may e,·entually o,·ershado" reduced chlorine 

burdens, especially as the rate o r Cl 13CCl 3 decl ine 

approaches zero. 

Up to this point. HATS a irborne GCs were specificall) 

designed to make measurements in the upper troposphere 

and lower stratosphere. Tropospheric issues such as a ir 

qual ity and the accumu lation o f greenhouse gases are 

expected 10 take a higher pri o rit y in this century. Funding 

was pro' ided by the NASA Instrument Incu bator Program 

to develop the PAN and other Trace ll ydrohalocarbons 

Experime nt (PANTll ER) next-generation a irborne GC. A 

ma ss se lecti\e detector" ill be combi ned "ith two o r more 

ECD c hannels to focus on more reactiYe and sho rter-lived 

species. The first test flight of PANTllER is schedule d for 

spring 2002 on the ASA l:.R-2 aircraft. Key molecules 

measured o n this test fl ight \\ill include pcro.\yacctyl nitrate 

(PAN), acetone (Cll 3C(0)Cll1). and llCFCs. PAN 

comprises the largest fraction of oxides of nitrogen (NO,) 

under natural conditions in the troposphere and is ·a 

precursor of 0 3. Acetone is a precursor of PAN and an 

important source of hydroxyl radical in the upper 

troposphere. 
73 

0. 

g 

u 

u 

c 

"' e 

0 

E 

c;; 

~ 

4.0 

3.5 

3.0 

2.5 

2.0 

1.5 

1.0 

73 

0. 5 

g 

u 

u 

c 4 .. 

e 

0 

E 3 

c 

., 

;;; 

> 

5 2 C' 

w 

;;; 

;§ 

NOANCMDL Ground based CCly a 

--- HALOE data @ 55 km 

~--·-·-·-·- -·- · ... . - • - • A;rborne GCs @ 27.5 km 

............................ -· ....... ···---------· Airborne GCs 0 19 km Airborne GCs @ 20.5 km _ _.,#w __________ _ 

NOAA.CMDL Ground based CBry 

~---'-------~------

b 

Airborne GCs 0 27.5 k'.!! • _ • - • - ·-·-· -·- ~·-·-· 

~-~---·················~················· Airborne GCs @ 20.5 km 

----~---------

Airborne GCs @ 19 km 

NOANCMDL Ground based c 

Airborne GCs @ 27.5 km 

,_.-·-·-·-·-·-·- -·-·- Airborne GCs @ 20.5 km 

............... .1 ..................................... . 

Airborne GCs @ 19 km 

----~---·--·--

1990 1992 1994 1996 1998 2000 

Year 

Fig. 5.32. Estimates or total inorganic halogen from airbom..: GCs 

(includ ing ACATS and LACE): (a) total inorganic chlorine (ppb). (b) 

total inorganic bromine (ppt). and (c) total equivalent inorganic chlorine 

(ppb). at equivalent altitudes of 19. 20.5. and 27.5 km. 11/\LOE 

inorgamc chlorine data at 55 km arc ploucd in (a) (updated b) .-l11deno11 

et 11/. [2000)l. C\IDL ground-based data ar..: ploucd in (a)-(c). 

5.4. OCEAN PROJECTS 

5.4. 1. DATA A:\A LYSlS 

Na tural halocarbons are important contributors to the 

destruction of stratospheri c ozone. For examp le, methyl 

bromide (Cl 13Br) and methyl chloride (Cl 13CI) together are 

the source or about one-quarter of the equi\·alent chlorine in 

the troposphere [Butler. 2000], \\here equivalent chlorine is 

one \1ay to evaluate the ozone-depicting capacit) of the 

aunosphcrc [Da11iel et al.. 1995). Other brominated 

compounds, such as dibromome thanc (C ~Br~) and 

bromoform (CllBr3), also might be significant sources of 

bromine to the upper atmosphere [e.g., Sclu11~f{ler et al .. 

1999: Sturges et al., 2000). An understanding or the 

sources and sinks of these compounds would enable the 

pn:diction or changes in the cycl ing of these compounds 

associated with climate change. Because the oceans are 

both a source and a sink of most natural halocarbons. 

oceanic measurements have constituted o ne component of 

the II/\ TS group research effort. 

Data obtained from previous field missions were 

analyLed during 2000-2001. The \ ariabil ity in sea surface 

temperature (SST ) has been shO\\ n to account for one-half 

10 t\\O-thirds of the variability in methyl bromide oceanic 

saturations. according to King et al. (2000). In that stud y, 

data from six cruises were fitted 1\ ith two quadratic 

equations. While global extrapolations with this relationship appear reasonable. this relationship does not 

accuratel y reproduce observations on a regional basis. 

llo\1eye r, reexamination of the data. along w ith inclusion of 

data from a 1999 expedi tion lo the Paci fie Ocean, has 

significantl y impro\ed the abili t) to reproduce field 

obsen at ions. 

Data from SC\ en research cruises (five conducted by 

CMDL and two by Dalhousie Uni\ersi1y) were di\ ided 

seasonally into two data sets: spring-summer and fa ll-

\\ inter. These data include measurements from the At lantic 

[Lobert et al., 1996: Gros::ko a11cl .\foore, 1998; King et al .. 

2000], the Pacific [Lobe/'/ et al., 1995: Gros::ko and Moore. 

1998: King et al., 2000; unpublished CMDL data], and the 

Southern Ocean [Lober/ et al., 1997). Measurements made 

bet ween March 20 and September 21 were considered 

spring-summer if north of the equator and fa ll-\\ inter if 

south of the equator. Data collected during the remainder 

of the year \\ere assigned to fall-1\ inter if north of the 

equator and spring-summer if south of the equator. Each 

seasonal data set was fitted with t1\0 quadratic equations, 

describing data abO\ e and below I 6°C (Figure 5.33 ). 

125 

The new equations repre sent a significant improvement O\ er the existin g equations. particularly in iemperule 

regions. For example, the previous equations cou ld account 

for only about 15% of the seasonal difference (summertime 

supersaturations and fall undcrsaturations) in Cl 13Br 

sa turation anomaly observed in the North Atlantic 

temperate waters (Ki11g et al., 2000). f-10\1 e\ er, the ne'' 

equal ions can reasonably reproduce the obscn cd seasonal 

difference for C ll1Br in these waters. The seasona l SST 

re lationships also impro\'C the abil it) to estimate the mean 

saturation anomaly for a gi\en data set. For the two most 

recent c ruises, Gas Exchange Experiment (Gas Ex 98) 

[King et al .. 2000] and Bromine Air-sea Cruise Pacific 

( BJ\CPAC 99) [Seline/I et al .. 200 I], the mean C H3Br 

saturation anomalies estimated \\1th the ne\\ equations arc 

about 90°0 of the measured \aluc!>. In contrast, the mean 

sa turation anoma lies as determined \\ ith the old equat ions 

[Ki11g et al., 2000] arc only about 60% of the measured 

\ alues. 

\!ethyl bromide saturation anomaly maps ha\ c been 

generated \\ ith the seasonal SST relationships and a global 

map ofSSTs (Figure 5.34). The SST data set consists of 1° 

x I monthly means from the National Oceanographic Data 

Center (NODC) [Lel'illls. I 982). Each g rid point represents 

a 3-mo a\·cragc \aluc. In this model C l 13Br undersalUrations are predicted in both the tropics and polar 

regions throughout the year. The temperate waters. 

howe\ er. show a strong seasonal cycle in both hemispheres. 

With the data used to c reat e these maps, the global. 

annually averaged Cll 1Br saturation anomaly is calculated 
150 

-

";!. 100 

-

< 50 "' .... 

m 0 M 

:I: -50 

(.) 

-100 

150 

";!. - 100 

-

< 50 "' '° o M 

:I: -50 

(.) 

-100 

-5 

-5 

Spring/Summer 

R2 = 0.66 + 

R2 = 0.51 

~ 

0 5 10 15 20 25 30 35 

Sea Surface Temperature (C) 

Fall/Winter 

R2 = 0.55 R2 = 0.15 

0 5 10 15 20 25 30 35 

Sea Surface Temperature (C) 

fig. 5.33. Methyl bromide saturation anomaly data lrom li ve CMDL 

cruises and two Dalhousie University cruises between 1994 and 1999. 

plotted as a function of sea surface temperature. The data are divided 

seasonally, with local spring and summer data in the upper plot and local 

fall and winter data in the lower plot. Quadratic fits are used to describe 

data above and below I 6°C for each seasonal data set. 

to be - 15.5%. The calcu lated global, annua lly averaged 

CH3Br flux is - 19.9 Gg yr' 1

. Both of these val ues agree 

with othe r publis hed estimates [ e.g., Lober/ et al. , 1997; 

King el al., 2000]. 

5.4.2. 2001 OCEAN C RUISE 

During fa ll 200 I the HA TS group participated on a 

research cru ise in the Southern Ocean. The Australian s hip 

Aurora Australis departed Hobart, Tasman ia, on October 29 

and returned to Hobart on December 13. The vessel headed 

south towa rd the Antarctic coast before returning to 

Australia, retracing a previous Climate Variability a nd 

Pred ictabil ity (CLIVA R) cru ise track (Figure 5.35). The 

HA TS group measured over 20 halogenated compounds in 

the surface seawater and overlying atmosphere. The results 

will be coordinated with those obtained by research groups 

from NOAA Atlantic Oceanographic and Meteorological 

Laboratory (AOM L) (halocarbon depth profi les) and the 

University of California at Irv ine (methyl bromide and 

meth yl chloride degradation rates). 

126 

15' 

o· 

1) 

o· 

January- February -March 

-120' -eo· o· 60' 120' 180' 

1eo· ·120' -60. o· 60' 120' u~r 

Ju~ - August- September 

o· 60' 120· 1eo· 

180' -120· -GO' o· eo· 120· 1eo· 

15' 

o· 

SA 

39.0 

31.5 

2•.o 

18.!i 

9.0 

1.5 

-6.0 

-13.5 

·21.0 

·28.5 

-00.0 

SA 

(%) 

39.0 

31.5 

24.0 

~· 165 

15' 9.0 

o· 1.5 

-6.0 

·13.5 

·2t.O 

·28.5 

o 

Fig. 5.34. Methyl bromide saturation anomalies plotted as 3-mo 

averages on I 0 by I 0 grid size. These maps were generated with 

relationships between sa1ura1ion anomaly and sea surface temperature 

(shown in Figure 5.33). White spaces represent regions with insufficient 

sea surface temperature da1a to calculate a value for the Cl 13Br sa1uration 

anomaly. 

Fig. 5.35. The cmise track for the fall 2001 cmise on which the HATS 

group participated. The Aurora Australis departed Hobart, Tasmania, 

and returned to Hobart after approaching the Antarctic coast. 
S.S. SPECIA L PROJECTS 

s.s.t. i\IETllYL H A LIDE El\11 ss10Ns rno:-.1 T ol\tATO 

PLA:\"TS 

Fieldwork 

The atmospheric budgets of most natural halocarbons arc 

poorly de fined . For both meth) l bromide (Cl l1Br) and 

methyl chloride (Cl 11CI). best estimates of the known sinks 

outweigh best estimates of the known sources b) 30-50°0 

[K111:1·lo et al., 1999). Although plant production or natural 

halocarbons has not been studied extensi\ e ly. there is 

considerable ne'' e\ idence that plants are ill\ ol ved in the 

cycling of these compounds. Pre\ ious studies ha\ e 

primari l) i11\olved the use of a flux chamber. which docs 

not isolate the plant from the soil and potentially stresses 

the plant [e. g. , Gan et al .. 1998: Redeker et al .. 2000: Rhew 

et al .. 2000, 200 I). Soi ls are potentia lly problematic 

because they have been observed to remove Cl 13Br from the 

atmosphere [e.g .. Jlnmer et al .. 1999). 

The llATS group conducted an experiment in a 

hydroponi c greenhouse in orthern California 

(McKin ley\illc) over a 2-wk period in July 2001. The 

greenhouse was coYered with doublc-l<1)ered polye thykne 

and housed about -100 tomato plants (lycopersico11 

esc11le11t11111). The plants \\ere gro'' n in bags of inert 

support materia l (Pearlite) '' ithout so il and were flu shed 

with an aqueous nutrient mixture at frequent inten als 

througho ut the day. During each experiment, the 

greenhouse was sealed . and halocarbon concentrations were 

mca~u1ed in the g reenhouse atmosphere with a GC-M S [) 

located at the site. Sampling lines were placed in the center 

and at one end of the greenhouse. Fans were used to keep 

the greenhouse atmosphere 11ell mixed. o concentration 

differences were obsened between the two sampling 

locations. Experiments were started 111 the late 

afternoon/early evening and were run until the air 

temperature in the greenhouse exceeded about 35°C. usuall) 

about noon the following da y. Eight experiments were run 

in total . and each experiment lasted 16-20 hours. The 

standard nutrient mixture was used first for two control 

experiments (C- 1 and C-2). This nutrient mixture conta ined 

no significant halide concentrations. A solution containing 

about 5 ppm Br". Cl", and r was added in line with the 

nutrient mixture during the third. fourth. and fifth 

experiments (H5- I. 11 5-2. and 11 5-3). During the final three 

experiments (1120- 1, H20-2, and 1120-3). a solution of about 

20 ppm Br", er. and r was added in line II ith the nutrient 

mixture. These halide solutions were added continuously 

over the course of several days. not just during the 

experiments themselves. 

Results a11d Discussion 

During C. I and C-2, no production of CH3Br (Figure 

5.36a) o r Cll1Cl was observed. but methyl iodide (Cll_;I) 

(Figure 5.36b) increased by a factor of about 5 by the end of 

the experiments. Production was also obsen ·ed for sci era I 

other halogenated compounds. including bromochloromcthane 

(Cl 11BrCI). dibromomethane (Cl-l1Br1). dibromochloromethane 

(CHBr1Cl). and bromoform (Cl-! Br3) (Figure 5.36c). In 

general. anthropogenic compounds. such as CFC- I I (Figure 

127 

Loca l Time 

18:40 21:40 0:40 3:40 6:40 9:40 12:40 15:40 

0 

(.) 

3.5 

3 

2.5 

2 

~--­

IC H3Brl 

(} 1.5 

1 ... 0.5 

0 

45 

40 

ICH3l I 35 

30 0 25 (.) 

(} 20 

15 

10 

5 

~ 

45 

4 II C HBr3 j 3.5 

3 

u 2.5 

(} 2 

1.5 

1 

0.5 

o L 

1.4 

1.2 

• 1 .+" 

u 08 

(} 0.6 

0.4 

0.2 1 I CFC11 j 

0 

. .. 

•• 

•• • 

[!] I 

_j 

... ~ 

• 

... .. 

0 2 4 6 8 10 12 14 16 18 20 

Elapsed Time (hr) 

Fig. 5.36. Concentration changes of(a) CH.Br. (b) Cl U. (c) Cl I Br,. and 

(d) CFC- I I. during a greenhouse experiment. plotted a~ a fu nction of 

time. All concentrations \\ere non11ali1ed to the corresponding initial 

concentration (C C0 ). During this experiment. no halide ions \\ere added 

to the nutrient mixture. 

5.36d). CFC- 113. and halon-1211. remained relative!) 

constant on:r the course o f the st udy, suggest ing that largescale contamination from materials in the greenhouse or 

from the greenhouse it sci r was uni ikcly. 

The addition of the halide so lution affected the 

production rates of only CH3Br and CH3 1 (Figure 5.37a.b). 
19:09 22 :09 

3.5 

3 

2.5 

u 2 

u 1.5 

1 

0.5 

0 

45 

40 

35 

30 

u 25 

u 20 

15 

10 

5 

0 

4.5 

4 

3.5 

3 

u 2.5 

u 2 

r 

J. 1.5 I 

O.; r 

0 

1.4 

1.2 

o0.8 

(.) 

uo.6 

• • 

• 

•• • 

Local Time 

1 :09 4:09 7:09 10:09 13:09 

•• ... 

• 

• • --...... ~~· 

•• 

0.4 

0.2 

0 

lcFc11 I 

0 2 4 6 8 10 12 14 16 18 

Elapsed Time (hr) 

Fig. 5.3 7. Concemration changes of (a) CH3Br. (b) CH11. (c) Cl !Br,. and 

(d) CFC- I I. during a greenhouse experiment. ploncd as a function of 

time. All concentrations \\Crc non11alized to the corresponding initial 

concentration (C/Co). During this e:--pcriment. a solution containing 

about 20 ppm Br-. Cr. and r flushed the plants wi th the nutriem mixture. 

During experiments f-1 20-1. f-120 -2. and 1120-3. C H3Br 

increased by nea rl y a factor of 3. Production of Cl 13 1 

increased by a factor of about 35 during these experiments, 

almost an order of magnitude more than with the standard 

nutri ent mixture alone. Production for other halogenat ed 

compo unds, suc h as CllBr3 (Figure 5.37c) and C HBr2CI, 

128 

did no t change noticeably between experiments run with 

and without th e ha lide solution. 

Similar results were observed for the HS experiments. 

Only CH3Br and Cl 131 production d iffered fro m the other 

experiments. The productio n for those two compounds 

increa sed with each experiment. Production during f-1 5-3 

approached the values that were observed during the f-12 0 

experiments. This suggests that production of Cl 13Br and 

Cf-13 1 by tomato plants is a function of halide concentration. 

More studies are necessa ry to determine if these 

obser\'ations are reproducible for these and other plants. 

Although tomato plants were chosen for lilt le o ther 

reason than opportunity, this stud y suggests that man y 

plants could emit significant amounts of organi c halogens to 

the atmosphere. It also supports propositions from other 

investigators that there is a relationship between halide 

concentration in the soi l and organic halogen production by 

plants [e.g .. Redeker et al., 2000; Rhell' et al. , 2000]. This 

preliminary study ha s raised many questions. One question 

concerns the production of polybrominated compounds 

when no halides were added, whereas CH3Br concen trations 

remained constant. It is also unknown why the production 

ofCll 3Br and CH3 1 increased wi th the addition of the halide 

solution while that o f other halocarbons d id not. The 

po tential variability o f production rates as a function o f 

plant growth stage was a lso not addressed in this study. 

Further studies of these and other plants will be necessary 

before these questions can be adequately addressed. 

5.5.2. TRANS-SIBERIAN OBSERVATIONS I~TO THE 

CllEi\llSTRY OF T HE ATi\IOSPHERE (TROICA) 

From June 27 to Ju ly I 0. 200 I, about I 1,000 in situ 

mea surements of CFC-12, halon-1 2 11. N20, and SF6 , and 

nearl y 5000 mea surements o f C FC- I I. CFC- I 13, C HCl3• 

C l 13CCl3• CCl 4, C H4, and f-1 2 were made a long 17 ,000 km of 

the full y e lectrified tran s-Siberian railway be tween Moscow 

and Khabarovsk, Russia (Figure 5.38), with the ACATS-IV 

gas chromatograph (GC). These measurements were part of 

the seventh Trans-Siberian Observations into the Chemistry 

of the Atmosphere (TROICA-7) scient ific ex pedition, a 

collaboration between CMDL. the Coooperati\'e Institut e 

for Researc h in Environmental Sciences (CIR ES), NASA, 

the Max Planck Institute for Chemistry (Mainz, Germany). 

and the Ru ssi an Institute of Atmospheric Physics 

( Moscow). TROICA expeditions we re inaug urated by 

German and Russian sc ientists in 1995 and have taken place 

annua lly during differe nt seasons [ Crnt=en et al., 1998: 

Oberlander et al.. 2002]. The primary CMDL objecti ve for 

TROICA-7 was to make freq uent (every 70 or 140 seconds) 

measurements of halocarbon and g reenhouse gases along 

the trans-S ibe rian railway. creating a database to which 

future TROICA measurements of the se gases can be 

compared. CM DL participation in TROICA-7 produced the 

first extensi\'c set of halocarbon measurements in Russia by 

American scicntisis. 

As during past TROICA expeditions, German and 

Russian sc ientists operated in situ analyzers for C O. C02• 

0 3 • C H4• NO,, 222Rn, H20. aerosols, solar radiation. 

temperature, pressure. and rclati\'c humidity [Crut=en e l al. , 

1998]. A g lobal positioning system recei\'er tracked 
MONQOLIA 

r - .; 

CHINA 

\ .. ., 

( 

.· ·' 

..... 'l 1' 

Fig. 5.38. Route of the TROICA-7 science expedition along the transSiberian raih,ay. Each of the transects, l\loscow-Khabaro\Sk and 

Khabaro,sk-Moscow, was approximately 8500 km in length and took 

6.25 days. Major cities along the railway are indicated by filled circles. 

movements of the train, and visual observations along the 

route were recorded in detail. A microwave temperature 

profiler was also part of the payload. All instrume nts were 

housed in a special rail car (Research Institute of Railroad 

Transport of Russia) situated immediately behind the 

1000 

~ 

900 

15. 

s 800 " . · .. N .... , 0 700 . , .. u. .. (.) • :. .. 600 

7.0 

6.5 

1i 

s 6.0 

c;; 5.5 

c. 

0 

<ii 

~ 5.0 

4.5 

0 1000 2000 3000 

electric locomotive. Air intakes for instruments were 

attached to a frame structure on top of the science car. 

ACATS-IY sampled air at approximately 4 L min- 1 through 

5 m of 6.4-mm-outside-diameter Dekabon tubing with a 

Teflon diaphragm pump (model UN05, KNF Neuberger 

Inc., Princeton, New Jersey). A 2-mm-pore glass fiber filter 

was used to keep large particles out of the intake tubing. 

The sample stream was dried with Mg(Cl04)i. 

The train traveled at a mean and maximum speed of 57 

and 129 km h1

• Numerous stops were made during the 6.25 

days required to travel each direction. There were 216 

scheduled stops at stat ions wi th durations of 2-90 minutes. 

Track maintenance and stop signals accounted for 43 

unscheduled, non-stat ion stops with durations of 1-69 

minutes. In general, population density decreased with 

distance from Moscow, though large, industrialized cities 

were encountered a lmost daily a long the length of the 

railway. East of the Ural Mountain s, the population density 

is greatest in southern Siberia, near the railway. Rural areas 

were typically birch and larch forest (taiga) or rolling 

grasslands with some large lowland areas. The MoscowKhabarovsk segment of the railway spans lat itudes of 48.6° 

to 58.6°N and altitudes of 0 to 998 m above sea level. 

Temperature ranged from 3° to 33°C, with three daytime 

highs >30°C and three nighttime lows < I 0°C. Rain, heavy 

at times, was encountered on 12 of the 14 trave l days. 

Large fluctuations in the mixing ratios of some gases 

were observed during the expedition, as illustrated by the 

time series for the refrigerant CFC- 12 and fire extinguishing 

agent halon-1211 (Figure 5.39). The variability ( I standard 

I 

·, 

I • '· . 

4000 5000 6000 

• Eastbound 

• Westbound 

. :~ ., 

-: '· .. 

I• 

• • I 

7000 

.. 

.. 

i •• 

8000 

km from Moscow 

Fig. 5.39. Time series of CFC-12 (top) and halon-1211 (bottom) mixing ratios during TROICA-7 as a function of distance from Moscow. For CFC-12. 

1here were 34 and 83 measurements > I 000 ppt during the eastbound and westbound transects. respectively, that are off-scale in this figure. There were 

2 eastbound and 4 1 westbound halon-1211 measurements > 7 ppt that are off-scale. Of interest for these two gases are their high variability along the 

railway and their generally higher mixing ratios during the westbound transect 

129 
dc,·iation) of e' Cl') gas measured along the rail\\'ay "as at 

least 50°0 greater than lls measurement precision (Table 

5.8). Variabilit) rclati\e 10 the mean mi:-.ing ratio wa\ n~r) 

high (>70°0) for CHCl1 and CO: 11-32% for CFC-12. 

halon- I:! I I. . and CO, ; 6-9% for CFC- I 13 and C114 : and 

<3°o for N,O. SF6 • CFC- II , Cll 3CCl1. and CCl4 . 

Fluclllations in mixing ratio obsened along the raih,ay 

were also much greater than at Point 13arro". Alaska 

(BR\\'). during June-Jul y 2001 (Table 5.8) except for 

CH3CCl 3, "hich showed about the same lo\\ 'ariabilit) at 

both locations. Ratios orTROICA-7 to BR\V \ari abilit) for 

gases other than Cl I ,CCl3 ranged from I. 7 for SF 6 10 59 for 

CFC-I:!. 

For gases that exhibited conct:ntrations higher than the 

northern hemispheric background. a major concern is the 

possibilit) of air sample contamination due to train-based 

sources fornard and or aft of the sampling inlets. No 

kno\\ n sources of the measured gases \\'ere located forn ard 

of the sample inlets. but > 100 mart there were small coalfired "ater heaters in passenger carriages and a working air 

conditioner in the restaurant car. There \\·as also an 

inoperative air cond itioning unit in the science carriage with 

no discernible pressure of CFC-12. lntuiti\cly. a forward 

source \\ ould frequentl y contaminate the air stream sampled 

by instruments, espec ial!) at high train speeds. An aft 

source cou ld ha' e contaminated samples" hen the train was 

moving slow!) or stopped. 

To e:-.plore the possibilit) of contamination by trainbased sources, data for four highl y 'ariable gases (CFC-12. 

halon- I:! 11. CO. and CO~) were separated b) train speed: 

high. IO\\. and stopped. For\\'ard con1amina11011 of samples 

was im estigated by comparison of data at high train speeds 

with CM DL data al remote, h igh-latitudc northern 

hemisphere sitt:s during June-Jul) 200 I. For these gases. 

30-60% of the data taken at high train speeds were 

represcntati,·c of we ll-mixed. background air masses. 

indicating that samples \\Cre not consistently contaminated 

b) forward sources. This is supported b) the fact that 

de' ated mi:-.ing ratios (>80'h percentile) were detected lt:ss 

frequent I) at high train speeds than \\hen the train was 

stopped. ll owc,er. this t:\idencc. along \\ith significantly 

lo\\ er fractions of background CFC- I:! and CO mi\ing 

ratios at stops compared \\ ith high train spi:eds. suggests 

that aft sources on the train man) ha\'c contaminated 

samples \\hen the train \\aS stopped. Of course. these 

biases may simpl) reflect the fact that the train stopped 

primaril) at stations in populated areas where sources were 

present. To explore train contamination from aft sources 

during stops. CFC- I:!. halon-121 I. CO. and CO: 

measurements made at scheduled station stops were 

st:parated from those made at unschcduh:d. non-station 

stops. For these four gases. fractions of background data at 

non-station stops (57-80°/o) were I A lo 2.3 times greater 

than at station stops (24-4 71\o). Fractions of elcrnted 

mixing ratios at station stops were also factors of 1.3 to 3.5 

higher than at non-station stops. Though these statistics for 

station and non-station stops do not preclude the possibility 

or sample contamination by the train during stops. the) 

strongly imply that sources proximate to train stations in 

populated areas "ere responsible for the ele,·atcd mi\ing 

ratios measured during stops. 

CFC- 12 and halon-1211 concentrations \\ere quite 

'ariablc during both the eastbound and westbound transects 

of TROICA-7 (Figure 5.39). but were general!) higher 

throughout the \\CSlbound return to Mosco\\ because or 

lame. sustained concentration increases obsened on some 

nigl11s. These increases. abo seen in C01• 11' Rn. and Cl ICl1 

data (Figures ).40 and 5.4 1 ). occurred beneath noctu111al 

temperature in ' crsions that were much stron ger and 

prolonged during the westbound transect (Figures 5.40a and 

5.4 1a). Increases in ~!! Rn and CO: beneath the night1ime 

inversions \\ere generall y broad and \\ell-corrt:lated because 

TABLE 5.8. Summary Statistics of Gas Measurements During TROICA-7 and at Barro\\. Alaska 

TROICA-7 

75rn - 25.n 95•h - 5•h BR\\' 

Gas N \lean \tedian Precision• \'ariahilit) -<· Percentile Percentile Variahilityt 

1',0 (ppl) 10815 316.7 316.4 0.6 1.9 I. I 3.7 0.8 

sr. (pp1l 11 086 5.00 4.99 0.05 0.15 0.07 0.19 0.09 

CFC-12 {pptl 11132 573 551 4 118 36 123 2 

llalon-1211 {pp!) 11125 H6 4.55 0.0.J 0.52 0.25 0.94 0.04 

CFC-I I {ppt) 4629 263.0 262.0 0.5 5.3 1.3 6.3 1.2 

CFC- I 13 (ppl) 4573 82.3 81.9 0.3 7.2 0.9 2.3 0.7 

CHCI, (ppt) 4929 16.3 14.1 0.2 12.6 .J.2 15.3 1.7 

CH,CCJ, (ppt) 4700 38.9 38.8 0.5 0.8 I. I 2.1 0.8 

CCI, (ppt) 4690 102.7 l02.5 0.4 2.5 0.6 2.3 0.4 

H, (ppb) 463.J 549 507 14 177 66 350 15 

CO{ppb) 82.JI 146 126 10 102 59 218 5 

CH, (pph) 4459 1882 1852 16 109 83 212 2l 

CO, (ppm) 10706 379.3 365.3 .j 1.8 2.J.9 127.8 1.4 

*Precision is e-...pressed as the standard de' iation of residuals of AC A TS-I\' calibration measun:mcnts made during the e'pedition. "here residuals 

are de' iations of ra\\ calibration data from >lllOOthed. drift-corrected calibra11011 data. 

tTROIC A-7 'ariability is e\pressed as l standard de\ iation. 

t BR\V ' ariabilit} is expressed as the standard de\iation of residuals of houri) a'erages of in situ obscrrntions made at Pomt Barro\\. Alaska 

{ T2° :-; ). during June-Jul} 200 I. Re,iduab are de\ iatiom, from smooth cun e lits to the data that account for seasonal cycles and longer-term trends. 

130 
km from Moscow (Eastbound) 

0 1000 2000 3000 4000 5000 6000 7000 8000 

Fig. 5.40. Solar flux, temperature difference, and mixing ratios for C02, 222Rn, CFC-12, halon-1211. and CHCl3 during the eastbound transect ofTROlCA-7. 

The mixing ratios of these gases increased broadly beneath relatively weak temperature inversions during several nights of the transect. CFC- 12, halon1211, and CHC13 mixing ratios also sharply increased near several cities. Data for these gases are the 20th percentiles in 1-h windows. Solar fluxes identify 

daytime and nighttime periods . .6.T is the difference in temperature at 0 and 600 m above the science car roof such that .6.T < 0 indicates a temperature 

inversion. Major cities along the railway are listed along the bottom axis. 

km from Moscow (Westbound) 

0 1000 2000 3000 4000 5000 6000 7000 8000 ~-; 800 ~~~~-+~~~.,....;t-r~~~+-~~~-+-o~~~-+-~~~ ....... ~~~~,_,~~~+-~~ 

~ 

~ 400 

u:: 

(i; 

0 

(/) 

E 460 a. 

-9' 

ON 400 

u 

(3 '"' 

I 

u 

10 

5 

0 

-5 

-10 

Fig. 5.4 1. Same as Figure 5.40, except for the westbound transect ofTROICA-7. Time series should be viewed from right to left (east to west) as the train 

retumed to Moscow. Several strong nighttime temperature inversions caused large. broad increases in gas concentrations. Note the greatly expanded 

concentration ranges compared with those in Figure 5.40. the result of stronger temperature inversions and perhaps greater emissions from upwind sources. 

13 1 
both gases a re wide ly emitted by soils. Simil ar nighttime 

incre ases in 222Rn , C02, a nd other gases have been observed 

during previous TRO ICA expeditions [Bergamaschi et al., 

1998; Crutzen et al., 1998; Oberlander et al., 2002]. 

C HCl3, CFC- 12, a nd ha lon- 12 11 mixi ng ratios increased 

broadly be neath several nighttime inversions and sharp ly 

near some c ities. Nighttime increases in these ha locarbons 

were typic all y coincident with inc reased 222Rn and CO, but 

their magnitudes were not genera lly consiste nt with ihRn 

and C0 2 increases, possibly because o f geographi cal 

variations in the strengths of halocarbon sources. 

Ana lyses o f the TROICA-7 data continue in an e ffort to 

characteri ze the source emissions, transport, a nd boundary 

laye r dynamics responsible for the observed trace gas 

variability. Under the Montreal Protocol on Substances 

that Deplete the Ozone layer [ UNEP, 1987], non-Article 5 

(developed) countri es like Russia a nd the United States 

were required to cease production of ha lons a nd CFCs by 

Ja nuary 1994 and 1996, respecti vely. Economi c diffi culties 

prevented Russia from mee ting these targe t dates. Only 

with substanti a l financial incentives did Russia fina lly cease 

C FC and halon production in December 2000. Inspectors 

have since verified that Russia is no longe r produc ing C FCs 

and ha Ions. It is o f great interest now to determine whether 

the detected emissions of CFC- 12 and ha lon- 12 1 I a long the 

tra ns-Siberian railway a re re lated to stockpil e leaks, discharges from in-use structures a nd equipme nt, or seepage 

from abandoned structures a nd disca rded equipment. 

CMDL sc ientists inte nd to be part of the next TROICA 

expedition proposed for winter 2002/2003. 

5.5.3. FIRN AIR SAl\IPLING, 2001 

In Janua ry 200 I, CM DL scie ntists joined investigators 

from Bowdoin Universi ty, Pri nceton Uni versity, and the 

University of Wisconsin to collect an archive of 2o•h 

century a ir from the firn (snowpack) at South Pole (Figure 

5.42). Sampl es were coll ected into separate pa irs of 3-L 

glass fl asks for measurements o f Oi/N2 (by Bowdoin a nd 

Princeton) and carbon cycle gases (by CM DL/CCGG); 

ind ividual 3-L stai nless-steel and glass flasks for 

measurements o f halocarbons, N 20 , SF6, and COS; large 

(33-L) sta inless-stee l canisters to mai nta in an arch ive of air 

for futu re analyses; and a few can isters each for 

measurement of 14CH4 (by NIWA and CS IRO) and very 

low-level ana lyses of SF6 (by Scri pps Institution of 

Oceonograpy, SIO) (Table 5.9). A ll sampl es were ana lyzed 

d uring 2001 , incl uding ini tia l ana lyses of the archive 

caniste rs. Although it was hoped to obtain air dat ing back 

to the turn of the century, the ana lyses suggest that the 

earl iest date was 192 1 for C02 and just after 1900 for gases 

that diffuse more slowly, such as methyl bromide and 

meth yl chloride. 

CM DL scientists have been participating in the collection 

a nd a na lysis of fi rn air from Antarct ica and G reenl and since 

1995 . Samples have been analyzed from Vostok, Taylor 

Dome, South Po le, and Siple Dome in Antarct ica and from 

Tunu in Greenland. The data have been used to estimate the 

atmospheric histories of these gases where real-time 

measurements were not ava ilable [Bal/le et al., 1996; Butler 

e t al .. I 999], extending the earl iest records of many trace 

132 

Fig. 5.42. Bladder being sent down into one of the two holes at South 

Pole for subsequent sampling of fim air. The 10-m-long bladder was 

pressurized 10 inhibit airflow from above while fim air was sampled 

through a 15-cm-high, stainless-steel-lined open chamber situated 

between the bottom of the bladder and the bollom of the hole. Each of 

two holes, extending ultimately 10 the snow-ice transition at 122-m 

depth, was drilled and sampled at 2- to 10-m increments. The drill lies 

on the snow 10 the left. 

gases from the late 1970s back to the end of the 19•h 

century. They also have been used to evaluate seasonal 

biasing of the mean gas mixing ratios [Severinghaus et al., 

2001]. The 200 1 samp ling at South Po le was the second 

deep sampling conducted at that site; the first was in 1995. 

Samples from this most recent collection provide a uniq ue 

opportunity to examine the diffusion of trace gases in the 

fi rn (Figures 5.43 and 5.44), which should reduce error in 

the estimation of the age of the firn air. A lso, the oldest 

firn air ever collected comes from South Pole, whic h makes 

the archived samples particularly val uable for fu ture 

a nalyses o f gases not yet reported. 

Pre liminary evaluation o f the data from the 200 1 

campaign shows that diffusion rates of gases in the firn are 

very c lose to molecul ar rates, calculated by extrapo lat ion of 

measurements made at very high tempera tures to the 

temperature of the firn , - -50 °C. Although often used in 

models of firn a ir movement, such extrapolated va lues are 

always suspect. Determination of the actua l d iffusion rates 

in the fi rn will remove this uncerta inty and allow for the 

direct calcul ation o f gas diffusion at these temperatures and, 

subsequentl y, the mean age of the air at each depth. 

TABLE 5.9. Gases Measured in South Pole Fim Air, 2001 

Institution 

CM DL or Univ. of 

Colorado 

Princeton Univ. 

orSIO 

NIWA or CSIRO 

Gas 

CO,, CO, CH,, N20, H2, SF6, CFCs, 1-ICFCs, 

HFC-134a, CH3Br, CH3CI, Cl-131, COS, 

halons, tJco, •sN,O, N,'so, isN,, iso,. 110 ,, t•co,. 

Ar, Kr, Xe. Ne, Ar/Ni. 0 1/Ni, SF6 14CH, 
~ 

0 

0 

-20 

-40 

-60 

.s 

.c 

a. 

~ -80 

-100 

Dry Mole Fraction (ppt) 

50 100 150 200 250 300 

···············~·············· +········· ···+·· ··········· ! ....... • ~ .......... . . ; ~ l l ~ 

i j j !• : .............. i ........ ..... L ........... .l ..........•. ! . ... ~ .... : .............. . . : : :a : : : 

·························' .,: .. ·············! - : • :. l l : . : : : ...... j .............. ,. ~··· ·· ·· -~. . . ···············i······ ·········i················ 

i.· ~ • l . I ··········· ·· r-·· ··· · i········ ······~····· ······· .. : .............. . 

• 1995, Both Holes, Glass Only 

• 2001, Hole 1. Glass 

-120 A 2001, Hole 1, Steel 

• 2001, Hole 2, Glass 

A 2001, Hole 2, Steel 

-140 L--..i....--=========::...1 

Fig. 5.43. CFC- I I in South Pole fim air in 1995 and 2001. Samples in 

1995 were collected from two separate hole~, but only imo glass flasks. 

Samples in 200 I also were collected from two separate holes, but both 

glass and electropolished stainless-steel flasks were used. ote the lower 

\alue at the surface in 200 I, reflecting the decreased atmospheric burden 

between 1995 and 2001. Also note the 20-m penetration at mid-depth, 

where the gradient is steepest and venical restriction still low. 

Data are being analyzed and evaluated with the obj ectives 

to (I) improve estimates of trace gas diffusion at low 

temperatures and the corresponding effect on mean-age 

estimates for lirn air samples and (2) report 20'h century 

histories of gases, such as COS, previously not ana lyzed 

throughout the century. Other laboratories are currently 

analyzing the archive of air in 33-L canisters in an attempt 

to obtai n reliabl e records of additional gases. It is 

anticipated that sufficient air will be available for analysis 

of even more gases a nd isotopes as new ana lytica l 

techniques become available. 

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Dry Mole Fraction (ppt) 

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0"T"""~~~,....-!!I~~,....~~~,....~ --. 

-120 

• 

e 1995, Both Holes, Glass Only 

e 2001 . Hole 1, Glass 

A 2001, Hole 1, Steel 

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Romashkin. P.A.. D.F. llurst. J.\\'. I lkins. G.S. Duuon. D.\\. Fahe). 

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loss of ozone dunng the \retie \\inter of 1999-::>000: ,\n analysis 

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Geopl1y.1. Re.1 .. Ill./.::> 1.513-21.535. 1999. 

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preS>. ::>002. 

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D. S1e. OLOne depiction potentials. global wanning potentials. and 

future chlorine bromine loading. in Sci<!llli/ic .l\1<•1.1111e111 11/ O=om· 

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Sturges. \V.T.. D.E. Oram. L.J. Carpenter. S.A. Pcnkctt. and A. Engel. 

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135 

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1995. 
6. Cooperative Programs 

UV Spectroradiometer Monitoring Program: Calculation of Total Column Ozone 

from Spectra of Global Irradiance Measured at South Pole and Barrow and 

Comparison with CMDL/Dobson and NASA/TOMS Ozone Data 

G. B1:R:-:11.\RD. C.R. Boo rn. \:-.D J.C. EHRA\tJIA:-< 

Bio.1pherical /11111w11e1111 Inc .. 53./0 Riley St .. San Diego. Cal[{omia 92110-!6! I 

{;'l;TRODUCTI0:-.1 

The U.S. National Science Foundation ·s Office of Polar 

Programs (NSF/OPP) Ultra \ iolct Spcctroradiometer 

Monitoring Network was established in 1988 lo collect data 

on the consequences of ozone depletion. The net\\ Ork 

currently consists of several sites with automated. highresolution spcctroradiometcrs (Table I). Three are in 

Anta rctica. including the CMDL site al South Pole Station. 

Another instrument is deployed at the CMDL faci lit) in 

Barrow, Alaska. Now in its fourteenth year of operation, 

the network continues to make measurements of ultra\ iolct 

(UV) spectral irradiancc and pro' ides a \ariety of data 

products to quantify biologically relevant UV exposures. 

Biosphcrical Instruments Inc. is responsible for operation 

and maintenance o f the network, and distribution of data to 

the scienti fi e community. 

The network is equipped with Biospherical Instruments 

Inc. model SUV- 100 ~μec t1oradiomc ers. Each in strument 

contains a double monochromator with holographic gratings 

and a photomultipl ier tube detector. Spectra are sampled 

automatically every 15 min between 280 and 600 nm with a 

spectral bandwidth of 1.0 nm full width at half maximum 

( F\VHM ). Tungsten-halogen and mercury 'apor calibration 

lamps arc used for daily automatic internal calibrations of 

bot h responsi' ity and wa\clength registration. All 

instrument functi ons. calibration acti' itics. and solar data 

acquisition are computer controlled. Further details on the 

spcclroradiometers are descri bed by Booth et al. [ 199-l. 

2000]. Data from the net\\ ork. network operations reports. 

and an extensive list of references can be accessed 'ia the 

website WI\" .biospherical.com. 

UV RADIATI0:-.1 CLlt\IATE AT SPO A:-.10 BRW 

This report focuses on data from the South Pole 

Observatory (SPO) and the Barrow Observatory (BR \\I) 

CM DL facilities. The SPO site is a unique place for 

atmospheric stud ies because of the stable meteorological 

conditions. negligible aerosol innuence. frequent cloudless 

days, constant and we ll-defined high surface albedo, and 

'irtuall) constant solar 7cnith angle (SZA) during one day. 

The conditions at BR\V are quite different from SPO. 

Cloud cover is highly \ariablc. and significant changes in 

surface albedo occur due to the springtime sno\\ melt and 

changes in sea ice co' erage. Also. Barro" undergoes 

significant changes in incident irradiance due to Arcti c 

storms. 

Figures I and 2 contrast the radiation patterns of both 

sites. Time seri es of integrated spectral irradiance at local 

solar noon are depicted for two "a\ elength bands covering 

the period 1991-200 I. One spectrnl hand (Figure I) 

represents spectral irradiance in the visible, integrated 

between 400 and 600 nm. From Figure I it is e' iden t that 

\isiblc rad iation at SPO shows little \ariation from one da) 

to the next. or between consecutiYe years. In contrast, 

irradiances in the 400-600 nm band at BRW arc highly 

rnriabl e during fall due to day-to-day changes in c loud 

cover. Because o r the di !Terence in latitude, rad iation levels 

in the' isible are usually lower at SPO than at BR \V. 

Figure 2 sho\\ s deo:-.yribonucleic acid (DNA)-weighted 

irradiance, which has been calculated from measured solar 

spectra and the action spectrum for DNA damage suggested 

by Setlo11· (197-l]. DNA-weighted irradiance has a high 

contribution from \\'avclengths in the UV B and is therefore 

TABLE I. Installation Sites of the Ultra\ iolet Spectroradiometer Monitoring Net\\ork - -~- - -- - -- - - -- -- --- --

Site Latitude Longitude Established Location ----- --- -- --- -- --- South Pole 90"00'S Fcbnml") 1988 

Mc1\1urdo Station n°s1·s 166"40'E March 1988 

Palmer Station 64"46'S 64"03'\V i\la) 1988 

U~huaia. Argentina 5-l"49'S 68°19'\V '\m·embcr 1988 

ffarro\1 . A la ska 71°18'i\ 156°47'\V December 1990 

San Diego. Califomia 3~ 45'i\ 11 7"1 l'\V October 1991 - - -- *ARO. Atmospheric Research Obscnato1y S)>tem relocated to this ne\\. joint :-.:SF-C\1DL facilit~ in January 1997. 

1· CADIC. Centro Austral de hl\cstigaciones Cicntificas, Argentina. 

! UIC-'\ARL. Ukpeag1 ik lnupiat Corporation-"la,al Arctic Research Laborator). 

136 

ARO* 

Arri\ al heights 

T-5 building 

CADICt 

lJIC-i\ARL; 

Biospherical Instruments Inc. 
"e 35000 

~ 30000 

2: 

fl 25000 c 

.!l! 

-0 20000 

~ 

'E 15000 

u 

Cl> 

a. 10000 rn 

5000 

0 

~ - South Pole I 

Barrow I 

' ! 

I ~ 

WU I 

I I 

' \ J I 

01 -Jan-91 01 -Jan-93 01 -Jan-95 01 -Jan-97 01-Jan-99 01 -Jan-01 

Date 

Fig. I. Visible spectral irradiance (-l00-600 nm integral) at local solar 

noon al South Pole and Barro\\ for the period 1991-200 I. 

NE 

~ 2: 

Cl> 

u 

c 

., 

:0 

-~ -0 

~ .s;: 

."' 4i 

3: 

<( 

z 

c 

0.2 

0.18 

0.16 

0.14 

0.12 

j-South Pole1 

Barrow 

I 

I I 

I 

0.1 

0.08 

0.06 

0.04 

0.02 

0 

.. I n ft 1 ' I\ I ~ \ ~ v .V ~ I v ~ .V 

01-Jan-91 01-Jan-93 01-Jan-95 01 -Jan-97 01-Jan-99 01-Jan-01 

Date 

Fig. 2. DNA-weighted irradiance at local solar noon at South Pole and 

Barro\\ for the period 1991 -200 1. 

very sensitiYe to changes in atmospheric ozone 

concentrat ions. In contrast to visible radiati on. D Awe ighted irradiancc at SPO shows high day-to-day 

fluctuations because of the ozone influence. For example, 

the peak in DNA-weighted irradiance observed at SPO in 

late November 1998 is due to extraordinari ly low total 

column ozone va lues and the comparat ively high solar 

elevat ions prevailing during this part of the year. UV levels 

in the austra l spring of 2000 were a ffected by the unusual 

behavior of the ozone hole of that year. whi ch was 

except ionally large until early October 2000 before it 

exhi bited an unprecedented rate of decrease in size and 

depth. Between mid-October and mid-December 2000. 

levels of DNA-weighted irradi ancc at SPO were low 

compared with typical va lues from ot her years. 

137 

CALCULATION OF TOTAL COLU1\ IN 0ZOl\E FRO;\! 

SPECTRA OF GLOBAL IRRADIANCE 

A new method was developed in 200 I to retrieve total 

column ozone from measurements of spectral global 

irradi ance of the SUV- I 00 network instruments. In brief, 

the met hod is based on the comparison o f measured spectra 

with results of the rad iative tran sfer model 

UVSPEC/libRadtran. ava ilable at www.libradtran.org. For 

every measured spectrum. several model run s with different 

val ues of the model input parameter --ozone column·· are 

performed. The ozone value retrieved by the method is the 

model ozo ne value tha t gives the best agreement between 

measurement and model. More details on the algori thm are 

given by Bemhard et al. [2002]. 

The assessment of the method revealed that its accuracy 

is affected by the atmosphe ri c ozone profile when SZAs are 

larger than 75°. This fac t is particularly important for SPO 

and BR W. where la rge SZAs are prevailing. Ozone va lues 

were therefore retrieved both with standard profil es and 

profi les measured by CMDL with balloon ozonesondes 

[Bernhard et al., 2002]. 

COi\IPARISON OF OZONE VALUES 

Values of tota l column ozone retri eved from the SUV - I 00 

measurements with the algorithm introduced above were 

compa red with Dobson ozone measurements performed by 

CM DL at SPO and BR\V. and with satell ite ozone 

observations by the National Aeronautics and Space 

Administration (NASA) Ea rth Probe Total Ozone Mapping 

Spectrometer (TOMS). Figu re 3 shows the ratios of ozone 

va lues from the SUV- 100 and TOMS to the Dobson va lues 

at SPO for the period October-December 2000 . referenced 

to the CM D L Dobson measurements. SUV - I 00 ozone 

values were dete rmined with CMDL balloonsonde ozone 

and temperature pro fil es in the retrieval algorithm. Figure 3 

shows that SUV - I 00 and Dobson measurements agree to 

within ± 1 .5% for SZAs as high as 80°. TOMS observations 

are generally 5- I 0% higher than Dobson ozone 

c 

g 

.0 

0 

c 1.1 

~ 

-g 

u 

c 

e 

~ a: 

.2 

ii 

a: SZA>80° 

0.9 

Oct-00 

SZA < 75° 

Nov-00 Dec--00 Jan-01 

Date 

Fig. 3. Comparison ofSUV-100 and TOMS total column ozone measurements at South Pole with CM DL Dobson ozone observations during 

austral spring 2000. 
measuremenb. This de\ iation of TOi\I S and ground-based 

oLone obsen at ions m high latitudes o f the southern 

hemisphere lrns been noticed before f e.g .. Piace11ti11i e1 al .. 

'.WOO]. Becm1se SUV- I 00 measurements represent an 

independent darn set. the) can be used 10 \ alidate ozone 

measurements from other instruments. elucidming the 

obsen ed discrepancies. 

SL.,V-100 01one \alues at BR\\' \\ere calculated for 

i\larch-April 2001 during the period of the Total Ozone 

i\leasurcments b) Sa tellites. Sondes. and Spectrometers at 

Fairbanks (TOMS1F) campa ign. Pre liminary res ults show 

that Dobson obsen at ions during April 200 I \\ere on 

a\ernge 20.0 lower than SUV- 100 measurements: TOi\IS and 

SUV- I 00 darn agreed 10 within :!:0.5° o. Despite the good 

agreement. uncerrninties in the SUV- 100 data a re larger at 

BR\\' tlrnn at SPO. because no o7one and temperature 

pro Ii le obscn at ions are a,·ailable from Barro\\. Profiles 

"ere therefore taken from Ci\I DL balloonsonde nights at 

Fairbanks. Because Barro\\ and Fairbanks are separated by 

more than 6° latit ude. the definition of the prolile is less 

accurate than it is for South Po le. J\s of this "riting, the 

data arc still under e\ al uation. One further objecti\ e is to 

quantif) the recent!) obsened drift of ror-.1s ozone data 

due lo deterioration of the instrument's scan mirror. b) 

comparing different \ersions of TOi\IS data \\ith SUV-100 

ozone retrie\ a ls. 

Ack11ow/edge111e111.1. 1 he l\SF OPP UV i\lonitoring Net\\ork i> 

operated and maintained b) l> iospherical In strumen ts Inc. under a 

contract from the \J<;F OPP ( P. Penhak) \ia Ra)theon Polar Sen ices 

(RPS). The L'kpcag' ii-. lnupim Corporation of Barro" pro' irled 

assistance in 1hc original 111qalla11on at BR\\'. Par11cular thanks are 

c\lended to the current Barn)\\ operators. D. Endres. \I. Gaylord. 

and G. :'\lcC011'ille from C\IDL. Operaiors a1 Sou1h Pok "ere 

affiliated \\ith An1arc11c Suppon \ssociates (ASA) and RPS. 

Rl:FEHE\CES 

Bernhard. G .. C.R. Booth. and J.C. Ehramjian. Comparison of 

measu red and modeled spectral ultra' iolc1 1rrad1ance at 

Antarctic stations used to determine biases in total 01one daia 

from 'arious sources. 111 f..,/1ral'iolet Gro1111d- 1111d Space-Blll ed 

\fe{/\11reme11t.1 .. \lodel.1. 11111/ £.f/eet1. edited b) J.R. S lus>er. J.R. 

Hermon. and \\'. Gao. !'roe SP/£, ././8!. in pres" :!002. 

Booth. C.R .. T.13. Luca-.. J.H. /'.lorro". C.S. \\eder. and P.A. 

l'cnhale. The L'1111cd Staie., '\a11onal Science Foundauon's polar 

nel\\ork for monllonng ultra\ iolet radia11on. 1n /..,/tra»iolet 

R11diatio11 i11 A111arctic11 \lea111reme111 1111d Biological E//eet.1. 

ed11cd b) C.S. \\ eiler and P.A. Penha le. A11tan1. Re.1. Scr .. 6!. 

pp. 17-37. Am. Geophys. lnion. \\ashington. DC. 1994. 

Booth. C.R .. G. 13ernhard. J.C. EhramJian. L.\\. Cabasug. \'.\'. 

138 

Quang. and S.i\. L)nch. NSF Polar Programs U\' 

Spcctroradiomcter '\et,1ork 1999-2000 Operations Report. 

B1o>phcncal ln~,irumcnt> Inc .. San Diego. CA. :!OCH>. 

1'1act=ntin1. R.D .. [, . Crino. f. S1rur. and \I. Gin1burg. Intercomparison bel\\ecn TO\IS EP and Sou1hern Cone 

01onc Projec1 (SC03P) \\ \10 ground based 01onc data. 

po>ter prescmed at the 2nd SPARC General Assembl). /'.tar dcl 

Plata. Argentina. (\\" 11 .• 1ero.Jussieu.fr - spare SP \RC:!OOO ne\\ 

index:!.html). Nm. 6-10. :!000 

Sctlo11. R. B .. The "a' cleng1h in sun ligh1 cffecti\ c in produc ing 

skill cancer: ,\ theoretical analysis. Proc. \at/ ..lead Sci. 

l .S. I..-,. 3363-3366. 19 74. 
Size-Resolved Trace Elemental and Organic Aerosols at 

Mauna Loa Observatory, Spring 2000 

THO\I \SA. C.\lllLL. STE\T' s. Cl IH. l\l lCHAEL Ji\ll ,1/-CRLL. 

S.\R \It G. RIDDLE. Prn.R B. Kr.u '. "o Kt\ 1' D. PERR' 

DELn Group. L111n:n111· o/Ca/ifomia. Om·" 95616 

The siLe dis1ribu1ion of aerosols is of kc) importance in 

their climaiic impact. To belier establish this parameter. 

and in an1icipation of the large i\.::rosol Characterization 

Experiment (i\Cf)-Asia project of spri ng 1001. our ne" 8-

stage sloucd Da' is Ro tating-drum Unit for l\lonitoring 

(ORI.JM) sampler "as deployed al l\launa Loa Obsen al Or) 

(:\ILO ) to collect aerosols during the Asian transport period 

each spring. While \le had earlier \\Orkcd \\ith data from 

simple fine filters (< 1.5-pm diameter. 1989-prcscnt) and a 

3-stage sampler (spring 1996). the present sampler was 

designed to map the optically important region below I pm 

\\ith fi,e submicron siLe classifications: 1.15 to 0.75. 0.75 

to 0.56. 0.56 to 0.3-1. 0.3-1 to 0.13. and 0.13 lo 0.07 pm 

30 

NE 

.!:! 

., .,, 

- 20 E c 

. r? . , 

8' 1! 

Ic 

.. Sulfur z 10 

aerod) namic diameter. Regret full). the samples were 

integ rated O\er 6 \leeks because of a failure of the drum 

rotation system. a problem that was corrected for the studi es 

at l\ ILO in spring and summer 2001. The samples \\ere 

scanned for elemental content. sodium through uranium. b) 

the nc\\ S) nchrotron-\-ra) fluorescence ( S-X RF) aerosol 

and climate mi crop robe at the Ad\ anced Light Source. 

La\\ rence Berkele) National Laborator). and for o rganic 

matter "ith the Laser Desorption Ionization Time-of-Flight 

I\ lass Spectrometer ( LDI TOFl\IS) at Da\ is. 

The data for aerosol clements in Figure I sho\\ that 

chlorine (and sodium. not shown) as a tracer of sea salt 

aerosols is essenti all) absent belo" I ~lm. "hi le iron (a 

.Q Sulfur 

+ Chlorine 

.. PoUnlum 

..., Iron 

O 23 to O 07 05610034 11510075 5 Oto 2 5 

O 3c to O 23 O 75 to O 56 2 5 to I 15 

Diameter in microns (at 3.4 km) 

~N~o-te-S~u""°~ur as-s-•"'if1-te_ro_ug_hl'"'"t_O_S 1c rogra 5/_m~3 

6 "M!'ek sample Mafch - A.pm 2000 

2000 

NE 1500 

.!:! 

E "' 

.. 

Ci 

0 

c 

1000 

.. 

z 500 ' .. ··~·~·-- ······· · ... ····· 

•·········· ~ .... ~-, 

o 23 to O 07 o 56 too 3< I 15 to 0 75 

,' 

5 o to 2 5 

OJ< to023 075to056 25to115 

Diameter in microns (at 3.4 km) 

>5 

.. 

>5 

~ Vanadium x 20 

... Zinc 

...._ Copper 

Fig. I. Six-\\ eek compo;,ite sample ofs1zc-rcsohcd aerosols measured at 1'-1auna Loa Obsenator). :>.larch-April 2000. 

139 
Impactor - Negativ e Ion Mass Spe c tra 1200 

1100 C N 

Pa rt1cle size 

1000 > 1 μm diameter 

900 

800 

::;. 

·u; 700 

c 600 2 

E 500 N02 

400 

300 " Cl C NIO I c, 

31CI 

c , c, 

200 

100 I 

0 

650 N02 Particle size 

0 07 to 0 34 μm diameter 

600 

CNO 550 

::;. 500 ·u; HSO," CH,CH 2CO, 

c 

2 450 E 

400 

350 

300 

250 

0 10 20 30 40 50 60 70 80 90 100 

M ass/C h arge 

fig. 2. Sample mass spectra of organic mailer at Mauna Loa Observatory. March-April 2000. 

soil tracer) has two separate peaks, o ne submicron (0.66 ± 

0.3 } and one supcrmic ron (approximate ly 4 μm , with the 

uncertainty associat ed w ith the inl et capture). All the soil , 

which inc ludes fine soil o n upslo pe winds. appears 

consistent w ith Asian sources. Except for a small amo unt 

o f sulfur assoc iated with the sea sa lt, sulfur was fin e. 

peaking at 0.45 ± 0.3 μm. The very fine/ultrafine sulfur is 

no t the tail of the large r peak. but represents a third mode 

that we hypo thesize is primarily industrial, based o n recent 

data in the United States and Asia. This assoc iati on is 

stre ng thened by the trace eleme nt data, w hi ch have a 

complex size profile indicative of di verse sources and 

processes and an important ultrafine compo nent. The 

resolution o f these hypotheses must await the a vail ability o f 

time-resol ved data. 

The samples were also analyzed by LDI TOFMS for 

organi c speciation. Some of the results are shown in Figure 

140 

2 and exhibit d ramati c diffe rences as a functio n of size. The 

HS0 4 - peak is not seen in the supermi cron frac tion, but is 

prominent in the ultrafine aerosols. Normally, this is 

associated with a sulfuri c acid aerosol. Again, much work 

needs to be done to understand these complex results. 

In summary, a g reat deal was learned during these tests, 

both about sampling and anal ysis in the ve ry c lean conditions 

at MLO and in the complex suite o f compositional techniques 

that can now be employed o n such samples. The soils arc 

even finer than estimated in our earli er work. and thus mo re 

important per unit mass in terms o f o ptical impact. The 

organi cs possess complicated patte rns in size and bear little 

resemb lance to existing source profiles such as biomass 

burning. and diesel and automoti ve smoke. 

Ack1101rledg111e11 r. T he excell ent support of th e Director and 

sta ff at Mauna Loa Observato ry is gratefu ll y acknowledged. 
Migration Rates and Flight Behavior of Migrating Eiders Near Towers at 

Barrow, Alaska 

RORI: RT H. DAY AND JOllN R. ROSE 

.IBR. /11c .. £11l'iro11111e111al Re1·earc'1 a11d Sen·ices. P.O. Box 80410. Fairba11k1. Alaska 99708-n.J 10 

BRIA'\/ A. COOP!:R A:\D RIC II \RD J. BLAll.\ 

ABR. /11c .. E11riro11111e111al Research a11d Sen'ice.1. P.O. Box !49. Fore.\/ Grm·e. Orego11 9-116-0!49 

During spring and fall migrat ion, Common (Somateria 

11101/issima) and King (S. spectabilis) eiders pass Point 

BarrO\\. Alaska, in large numbers [Thompson mu/ Person. 

1963: Timson. 1975: Day et al .. 1998: Suydam et al .. 1997, 

2000]. Spectacled (S. fischeri) and Steller's (Polysticta 

stelleri) ciders also pass Point Barrow, although in small 

numbers. Common and King cider populations are decl ining 

dramatically, and populations of Ihese two species arc so low 

that they are protected under the Endangered Species Act. 

Because populations of all four species are in trouble, 

conscn at ion of c:-.isting populations becomes increasingly 

important. 

\Ve studied mo\'emcnls and beha' ior of eiders migrating 

past the Atmospheric Radiation Measurement (ARM) tower 

at the CM DL Barrow Obsen atory (BR \V) and the 

GEOCORONA IO\\er at the U.S. Air Force Point Barro\\ 

Long Range Radar Site near Barro'' . Alaska. under \ arious 

levels of visibility in August September 2000. The 

objectives of this study were to (I) determine flight tracklines 

of ciders migrating in the vicinity of the ARM tower (primary 

interest) and the GEOCORONA tu\\eJ (secondar) interest): 

(2) measure 1110\emcnt rates. bclia\ ior, and fli ght altitudes of 

migrating eiders in this area: (3) determine \\ hcthcr any of 

these allributcs varied by \'isibili ty category, especially near 

these towers: and (4) assess the probability of collision of 

migrating eiders\\ ith these towers. Both ornithological radar 

and 'isual methods were used for sampling. 

During radar sampling. 13.-13-1 eiders were recorded in I 33 

identified radar echoes. Another 4-12 "ciderlike" radar targets 

that were unidentified to species, possibly representing an 

additional -45,000 ciders, based on mean flock siLe. were 

recorded. During 'isual sampling, 19,023 eiders ( 6.090 of 

them not detected by radar) were recorded in 187 flocks ( 56 

of them not detected by radar). ll cnce, data were collected 

on at least 19,524 eiders (not coun ting possibly 45.000 

eiders represented by uniden tified cidcrlike radar targets) 

over the 21 days of sampling. 

Mean daily mo\cmenI rates of "ciders" (i.e., unidentified 

ciders + unidentified ducks -r unidentified \\atcrfo,, I + 

unidentified targets that were ciderlike in fli ght 

characteristi cs) on radar ranged between 0 and 12.8 radar 

targets per hour. "Eiders" were recorded migra1 ing on all 

days except one, indicating pulsed, but fairly continuous. 

migration during this period. 

l\kan mo,·emcnt rates of "eiders" ''ere significantly higher 

during the night than during the day, during nights '' ithout 

precipitation . and during nights '' ith good \ isibility. 

Frequent tailwinds at night may ha\e increased nocwrnal 

1-11 

movement rates: however, all of 1hc increase could not be 

explained by ''ind direction, suggesti ng that movement rates 

ac tually are higher al night. 

"Eiders" passed the ARl\t tower at a significantly greater 

distance from the tower during the day than at night and at a 

greater distance during daytime without precipitation than 

du ring all other light conditions. Visibility did not affect the 

distance at which they passed the lO\\ er. 

"Eiders" exhibited lit1lc variation in nightlines by time of 

day. light condition, or session \isibility. Essentially all 

mo\ cment was to the north of the site. around or O\ er Brant 

Point, and, eventually, over Duck Camp and/or North Salt 

Lagoon. Only 14 (2.4%) of 590 "cider" radar targets passed 

south of the ARM tower. and only 9 ( 1.5°0) passed ::>500 m 

from this to\\'cr. indicating that a 'cry lo'' percentage of all 

birds crossed inland near this tower. 

Straight-line flight was. by far. the dominant flight 

behavior, occurring >99% of the time on radar and >95°,o of 

the time during 1 isual sampling. Frequencies of straightline tlighl and non-straight-line flight did not differ 

sign ificantly by time of day. lighl condition. or session 

\ isibility. "Eider" echoes occurring ::>500 m from the tower 

exhibited on ly stra ight-li ne flight, regardless of 'isibility 

category. 

During visual sampling, "eiders" exhibited substantial 

\ariation in minimal flight altitude, ranging from 0 m above 

ground level (agl: i.e., landing) to 70 m agl. with the overall 

mean flight altirnde being - 12 m agl. "Eiders" obscncd on 

radar and visua lly c.\hibited no discernible response to the 

tO\\Cr as they passed the ARM tower, regardless of 

visibility category and distance from this tower. The 

O\ era II distance from this tO\\'er ai '' hich birds passed ''as 

large. howe\er. in 1ha1 onl) 5 (2.7°0) of 186 flocks seen 

\ isually passed ::>500 m from the tO\\ er. 

"Eider" movements discussed here \\ere simi lar to those 

seen previously near Barro\\, although the amount of 

nocturnal migration was not previously kno\\'n to be this 

large. Se\ era I obsen ed aspects of the flight behavior of 

"eiders" suggest that. although these birds arc extremely 

'ulnerable to collisions \\ ith human-made objects, the 

preferred route of movement by migrating "eiders" in this 

area is over the base of Barro\\' Spil, near Duck Camp. \\'ith 

fc" flying inland near the towers. That "ciders" fle\\' 

significantly farther from the to1\er during the daytime than 

they did at night. mostly passing around Brant Point. 

suggests that these birds are strongly relying on visual cues 

to orient themseh cs and fly around Brant Poinl. rather than 

that they are a' oiding the ARM tower. 
We conclude that the p robability of collision of migrating 

"eiders" \\'ith the existing structures at Barrow is lo''. 

Ho\\'ever. it is recommend that ( 1) no ne\\' tall structures 

(such as towers) be built closer to the coast than these 

existing structu res already are, and (2) any tall structures 

(such as tO\\'ers) that are built in this area should be visible to 

"eiders" at a distance to gi\'e them a greater distance in whi ch 

to react and a' oid collisions. 

REFERE:\CES 

Da). R.11 .. J.R. Rose. and B.A. Cooper. E,·aluation of ornithological 

radar for monitoring eider migration at Point Barro\\. Alaska. 

unpublished report prepared for U.S. Fish and Wildlife 

142 

Sen ice. Fairbanks. AK. and North Slope Borough. Barro\\. AK. -12 

pp .. J\BR. Inc .. Fairbanks. AK. and Forest Gro\C. OR. 1998. 

Suydam. R .. L. Quakenbush. i\1. Johnson. J.C. George. and J. 

Young. l\ligration of King and Common ciders past Point 

Barrow. Alaska. in spring 1987. spring 199-l. and fall 199-l. in 

King and Co111111on Eiders of 1/ie We.I/em Canadian Arc1ic. 

edited by D.L. Dickson. Occasional Paper Xo. 9./. pp. 21-28. 

Canadian \\'ildlife Sen·ice. Onawa. 1997. 

Suydam. R.S .. D.L. Dickson. J.B. Fadely. and L.T. Quakenbush. 

Population dec lines of King and Common eiders of the Beaufort 

Sea. Condor. IO:!. 219-222. 2000. 

Thompson. D.Q .. and R.A. Person. The cider pass at Point Barro\\. 

Alaska. J Wildlife Manage .. :!-. 3-18-356. 1963. 

T imson. R.S. Late summer migration at Barro\\. Alaska. 

unpublished report. 25 pp .. U.S. Fish and \Vi ldli re Sen ice. 

Anchorage. AK. 1975. 
Occurrence Probability of Pel Micro Pulsations Observed at Barrow 

During the Solar Quiet Period 

KA\JI H A YASlll 

Depamne/I/ of Earth and Planetary Science. The U11il"ersi11· o(Tokyo. 811nkyo. Tokyo. Japan 133-0033 

Observation of short-period magnetic pulsations at the CMDL 

Barrow Observatory (BR\V) continued uninterrupted since 1995 

using an induction magnelOmeter with a digital data logger. All 

the acquired daily data produced at a 5.2-mb rate at Barrow has 

been compiled into an archive of the Solar-Terrestrial Energy 

Program (STEP) Polar Net\\Ork. Quick-look plots of Fourier 

d ynamic spectra including 9 days on a page ha\ c been produced 

and are publicly accessible at http://hpcp3.cps.s.u-tokyo.ac.jp. 

\Ve show in the data set synoptic characteristics of Pc I-type 

magnetic pulsations deduced from features of the dynamic 

spectra during the solar quiet period of 1995-1997. 

Pc I-type spectra were searched o n every spectral chart. and 

their occurrence was examined in bins of 0.1-0.5 llz. 0.5- 1.0 ll z 

and above 1.0 I lz for every 2 hours of universal time (UT). 

Table I shows occurrence probabilities of Pc I pulsations 

involved in the .b ins of the three frequency bands for e\'ery 2 

hours. Statistics were developed on four ensembles: the whole 

period. the equinox seasons. the summer seasons, and the winter 

seasons. Occurrence probability in the IO\\·-frcquency band is 

found to be high around local Barrow noon (UT - 12 hours. 

approximately) to afternoon and is highest in the summer season. 

Small enhancements of Pc I occurrence in high and middle 

frequency bands arc found from midnight to early morning both 

in winter and equinox seasons. but are suppressed in summer 

seasons. Taking imo account the geomagnetic latitude (69.9°) of 

Barrow and past reports of similar observations. the above 

results can be considered reasonable. It wi ll be interesting to see 

how the previously noted tendencies will be modified by the 

recent solar active period. These effects will be determined as 

the final data become available. These results will also be 

derived from simultaneous data from identical instruments 

operated at more than 20 locations at various latitudes. Toward 

this end. a special algorithm to pick up Pc I events automaticall y 

is being developed because such an algorithm is essential to the 

efficient processing of such a large amount of data and to 

produce frequency statistics eniciently. 

TABLE I. Time Dependency of Occurrence Probabilities of Pc I Micro Pulsations During the Solar 

Quiet Period. 1995-1 997, Observed at Barrow, Alaska. 

- - - -- Tim~ Occum:m:c Probability 

(UT) 0.1-0.5 Hz 0.5-1.0 Hz 1.0-2.0 Hz 0.1 -0.5 Hz 0.5-1.0 Hz 1.0-2.0 117 

Whole period (809 da_1·s) Equinox seasons (358 days) 

0-2 4 1.53 25.59 1.61 48.32 3 1.01 1.40 

2-4 35.97 10.51 1.24 39.66 13.1 3 1. 12 

4-6 9.02 2.22 0.49 10.89 3.07 0.56 

6-8 1.48 1.73 0.37 2.23 2.51 0.56 

8- 10 0.25 1.85 0.62 0.28 2.51 0.56 

10-1 2 0.12 2.72 0.87 0.28 3.35 1.68 

12-14 0.00 4.45 1.36 0.00 4.75 J.96 

14-16 0.74 6.67 2.10 0.56 6.98 3.07 

16-18 3.09 7.29 1.98 3.35 7.54 2.5 1 

18-20 5.32 6.92 1.61 4.75 6.70 1.68 

20-22 11.99 7.91 1.36 11.73 10.34 1.68 

22-24 21.14 14.71 0.87 22.07 16.48 1.68 

S11111111er seasons (197 day s) Wimer seasons (25./ dars) 

0-2 56.85 22.34 2.03 22.83 22.05 1.57 

2-4 59.90 7.61 0.51 14.96 9.45 1.97 

4-6 19.80 2.03 1.02 1.1 8 1. 18 0.00 

6-8 3.05 2.03 0.51 0.00 0.39 0.00 

8-10 0.51 3.05 1.52 0.00 0.00 0.00 

10-1 2 0.00 3.55 0.51 0.00 1. 18 0.00 

12-14 0.00 2.54 0.51 0.00 5.5 1 1. 18 

14- 16 1.52 2.54 1.52 0.39 9.45 1. 18 

16-1 8 4.57 2.03 1.02 1.57 11.02 1.97 

18-20 7.11 3.55 0.51 5.12 10.24 2.36 

20-22 16.75 6.60 1.02 9.45 5.9 1 1.18 

22-24 29.44 13.20 1.02 14.1 7 13.78 0.39 

143 
NIWA 's NDSC UV /Visible Measurements at the 

Mauna Loa Observatory 

P. V. JoHNsroN 

Nmio11al lllstit11te of Water and Atmospheric Research. Lauder, Xe\\" Zealand 9182 

The National Institut e of Water and Atmospheric 

Research (NIWA) start ed Network for the Detection of 

Stratospheric Change (NDSC)-certified ultraviolet (UV)/ 

visi bl e spectroscopic measurements of stra tospheric 

ni trogen diox ide (N0 2) in July 1996 at the CM DL Mauna 

Loa Observatory (M LO). In December 1999 a new 

UV/ visible spectrometer was installed to measure 

stratospheric bromine monoxide (BrO), an important 

species, in current attempts to model future nonpolar ozone 

trends. In addition to this instrument. a second N02-

mcasuring spectrometer was installed in the NDSC 

bui !ding. The BrO instrument makes w hat is expected to be 

defined as NDSC standard measurements: however, full 

certifi cation canno t be completed until a community BrO 

instrument intercomparison is undertaken. This is planned 

for March 2003 . 

Measurements of N02 and BrO have been successfully made 

o n most days over the reported period. Althoug h one of the 

l ·H 

two N02 instruments failed in December 2000 

and could not be repaired until August 2001, the backup N02 

spectrometer maintained data continuity. The data were 

presented at the 200 I NDSC Symposium [Kreher e t al., 200 I). 

N02 data measured at MLO in the N DSC database have 

been archived to the end of2000. 

Ack11011"/edg111e111. Thanks arc extended to the l\I LO staff for 

their continued support or the instrumentation. 

REFERENCE 

Kreher. K .. P. V. Johnston. G.E. Bodeker. J.A. Burrowes. J.B. 

Liley. and 1'1.P. Chipperfield. Time series or N01 data at lo\\. 

middle and high latitudes: Observations and comparison with 

model results, paper presented at Network for the Detection or 

Stratospheric Change (NDSC) 200 I Symposium "Celebrating I 0 

Years of Atmospheric Research," NDSC. Palais des Congres 

"Le Palatiurn." Arcachon. France. September 24-27, 2001. 
Quasi-Biennial Oscillation Signatures in Ozone and Temperature Profiles 

Measured by the JPL Lidar at Mauna Loa 

T. LEBLA'\C AND l. S. 1\IC0LR1'11D 

Tahle \fo1111tai11 Facility. Jet Prop11l1io11 laborato1J". Califomia !11s1i111te o/Tec/1110/ogy. Wrigluwootl. Cal(fomia 9:?397 

l :\'.TRODUCTIO:'i 

The stratospheric quasi-biennial oscillation (QBO) is most 

casil) identified as an alternation of descending westerly and 

easterl) ''ind regimes 111 the equatorial Im\ er stratosphere 

[e.g .. Reed et al .. 1961) with a period ,·arying from 22 10 3-1 

months. To allempt to elucidate the exact mechanisms of the 

equatorial and e: tratropical QI30. and because the QBO has a 

major impact on the intcrannual \ariability of the stratosphere 

and in turn on major issues such as o7one depiction and 

climate change. it is critical 10 maintain lo\\-. mid-. and highlatitude continuous long-term measurements of the key 

atmospheric parameters. As pan of the Net\\ ork for the 

Detection of Stratospheric Change (NDSC). a Jet Propulsion 

Laboratory (JPL) lidar has been taking long-term 

measurements of middle atmospheric temperature and o7one 

at 1\launa Loa Obscn ato!). Ha\\aii (1\ILO. I 9.5"N. 155.5°\V). 

since 1993 [,\fcDemticl er al., 1995). The first simultaneous 

obsen a11ons of the 1 ertical structure (20-50 km) of the 

temperature and ozone QBO at a subtropical station are 

presented here. 

LIDAR DATA SET 

The data presented here extend from June I, 1994. to 

September 30. 2000. The corresponding -800 indi\ idual 

OLone and temperature profiles were computed into monthly 

means bet\\ een June 199-1 and September 2000. Then the 

climatological means were calculated for the period October 

1994-Septcmber 2000 for each month of the year. thus 

emcnng three full QBO C)Cles. These climatological 

month I) means were subtracted from the indi' idual monthly 

means to obtain what is hcreaner called the "deseasonali1cd" 

ozone and temperature profiles. The seasonal (mainly annual 

and semiannual) components were remm ed. lea' ing the 

possible signatures of the QBO. solar cycle. long-term trend. 

and any other interannual rnriations. Because of the 

rela111 Cl) short measurement period. no allempt was made 10 

isolate each of these interannual components. 

QBO W l:\'.DS 

A comparison of the NOAA 1 1ational Weather Sen ice 

("l\\'S)-1 lilo momhl) mean wnal "inds near 30-km altitude 

"ith the near-equatorial monthly mean tonal winds at I 0 hPa 

(-30-31 km) shows a clear in-phase correlation. indicating 

that 1 lawaii i> under the innuence of the equatorial QBO 

"inds. The 20 time-height section of the 7onal "inds at Iii lo 

is sho\\n in Figure I (bollom panel). In this panel the altitude 

range e\lends from 15 10 35 km. but the scale of the 1 ertical 

axis has been chosen to match that of the OLonc and 

temperature plots displayed abm c it. The contours range 

1-15 

from - 10 (\·iolct) 10 + 10 111 s·' (red) with a I 111 s·' intenal. 

The QBO structure is \\Cll identified and is therefore used as 

the QBO \\'ind reference 10 ill\ cstigate the phases of the 

temperature and ozone QBO signatures in the ne\t sections. 

QBO S tG:-.'ATURES I;\ T H E TD! l'ER.\T!JRE PROFI LES 

The 20 time-height section of the deseasonali7ed 

stratospheric temperatures is shown in Figure I (top panel). 

o QBO signature was identified abm e 60 km. The contours 

range from - 3 (' iolet) to + 3°0 (red)" ith a 0.5° o intcnal. The 

most striking feature obsen ed here is a clear seasonal I) 

synchronized QBO anomaly near 35-36 km in "inter" ith an 

amplitude exceeding 3% (6-7 K). The warm phase coincides 

with the maximum westerlies at 30 km, i.e .. \\'ith an expected 

easterly shear above 30 km. The cold phase coincides "nh 

the maximum easterlies at 30 km. i.e., with an expected 

\\ esterly shear abol'e 30 km. 

QBO StG:-.'ATUllES !:-.' Tl!E 0ZO'[ PROFILES 

The center panel of Figure I shows the 20 time-height 

section of the dcseasonalized ozone profiles. rl1c plot is 

divided into two parts. The lower part (between 20 and 30 

km) shO\\S the deseasonalized OLOne number density (in °o). 

"ith contours ranging from - 12 (1 iolet) to .,-12•,. (red)" ith a 

2°·o interval. The upper part (abo1e 30 km) shows the 

deseasonalized ozone mixing ratio. "ith contours ranging 

from - 0.5 (\ iolet) 10 +0.5 -ppn11 (red) "ith a 0.1 ppm~ 

interval. Although the lidar measures OLone number density. 

the mi\ing ratio is preferred for displa) abm c 30 km to amid 

excess ii e percemage 'alues in the upper regions where the 

OLone number density is 1ery lo\\. No 01one number density 

contour is displayed be lo\\' 20 km because of the large re lathe 

variability in the lower stratosphen; (::t: I 001\o). 1 ote that since 

relati\e quantities are considered. the contours of the 01onc 

mixing ratios and number densities abmc and bclO\\' 30 km 

should. and do, exhibit \Cl)' consistent structures. As "as the 

case for temperature. a strong seasonally synchronized QBO 

signature can be obsened in" inter-spring with an amplttude 

exceeding 0.5 ppm' (I 0° o) near 31 km. 

D ISCl:SSIO:\" 

This first im estigation of simultaneous temperature and 

o?One QBO signatures at \launa Loa. lla\\aii. has re1ealed a 

remarkably consistelll pattern. typical of the expected 

cxtratropical as) mmetrical effect of the stratospheric QBO. 

Although less organi7cd and weaker (I 0- 15 111 s1 ). the 

obsen eel QBO \\'inds from NOAA 'N\VS in Hilo. I lawaii. are 

in phase with the equatorial QBO winds. The temperature and 

ozone results obtained b) the JPL ozone lidar sho\\ a clear 
50 

.......... 

E 

6 40 

w 

0 

:J 

f-

~ 30 

<( 

20 

50 

.......... 

E 

6 40 

w 

0 

:J 

f-

~ <( 

20 

.......... 

~ 30 

w 

0 

:J 

f- 20 ~ <( 

DESEASONALIZED TEMPERATURE VARIATIONS 

--- --

-----

DESEASONALIZED OZONE VARIATIONS 

EQUATORIAL WINDS 

1994 1995 1996 1997 1998 1999 2000 

Fig. I. Two-dimensiona l time-height sections of the deseasonalized temperature (top), ozone (center), and winds (bottom). Top: The 

temperature contours range from - 3 (violet) to + 3% (red) with a 0.5% interval. Center: For ozone, the lower part (between 20 and 30 km) shows 

the ozone number density (in %). with contours ranging from - 12 (violet) to + 12% (red) with a 2% interval; the upper part (above 30 km) shows 

the ozone mixing ratio with contours ranging from -0.5 (violet) to +0.5 ppmv (red) with a 0. 1 ppmv interval. Bottom: For the monthly mean 

winds at Hilo, Hawaii, contours range from - 10 (violet) to + IO ms·' (red) with a I ms·' interval. 

146 
QBO signature at several altitudes and times of year. 

highl y consistent with previous observations [e.g .. Randel 

and 11'11, 1996) and with the mechanisms suggested by 

modelers. 

Both the prevalent temperature and ozone QBO anomalies 

arc seasonally synchronized (northern hemisphere \\'inter) and 

out of phase with the expected equatorial anomalies. 

indicating that Hawaii is located in the subtropical branch of 

the asymmetrical QBO-induced meridional circulation. The 

QBO-rclated temperature perturbations observed at Hawaii 

are clearly out of phase with those expected from thermalwind balance at the equator, i.e .. positive (hot) at 47 and 24 

km, and negative (cold) at 35 km for easterly winds 

maximizing at 30 km. The QBO-related ozone perturbations 

appear to match remarkabl y well with those observed. for 

example, by the Stratospheric Aerosol and Gas Experiment 

(SAGE II) [Randel and Cobb, 1994; Randel and IV11, 1996), 

and simulated by Jones et al. [ 1998): positive slightly above 

and below the altitude of easterlies (31 and 23 km, 

respectively, for easterlies maximizing just below 30 km) and 

a negative perturbation well above (>45 km). A weak signal 

has also been observed at 24 km in summer that appears to 

match the model results of Jones et al. [ 1998), but this signal 

is not consistent enough from year to year to be certain of its 

actual existence. 

These results suggest that the mechanisms for production 

of the ozone QBO are more complex than that for temperature. Above the ozone concentration peak, the ozone QBO is 

both chemically and dynamicall y produced through the 

combined e ffect of the QBO nonlinear horizontal and vertical 

advection of NO" and the horizontal advection of ozone. 

Below the ozone concentration peak, the ozone QBO is 

dynamically produced by nonlinear advection of ozone out of 

and into the neighboring latintdes. For temperature. the 

thermal wind balance causes the QBO signature in the 

subtropics to be out of phase with that at the equator. The 

warm phase in Hawaii coincides with the maximum easterl y 

shear at the equator. The cold phase in Hawaii coincides with 

the maximum westerly shear at the equator. 

A strong El N ino event in 1997-1 998 considerably 

disturbed the QBO signature in both ozone and temperature. 

Its main effect was to reduce the lower stratospheric ozone 

amount, and to cool down the lower stratosphere up to 25-27 

km. Both El Ni no/Southern Oscillation (ENSO) signatures in 

ozone and temperature arc consistent with previous 

observations [ Shiotani, 1992: Randel and Cobb, 1994; Randel 

et al .. 2000). Despite this disruptive event. and even though 

the ozone/temperature lidar data set covers only three foll 

QBO cycles, the results presented here have shown several 

significant QBO signatures and remain promising for a more 

detailed investigation of the temperature and ozone 

intcrannual variability at this latitude. 

Ack11owledg111e11ts. The work described in this paper was carried 

out at the Jct Propulsion Laboratory. California lnstirute of 

Technology. under an agreement with the National Aeronautics and 

Space Administration. We would like to acknm' ledge those 

members of the J PL Lidar Team. T. Arakelian. G. Beyerle. R. P. 

Cageao. the late M. Schmoe. and T. D. Walsh. "ho assisted in the 

collection of the data used here. We would also like to thank John 

Barnes of NOAA/i\ILO and OAAIN\VS at llilo for prm iding the 

Hilo "ind data. and J. K. Angell of OAA/Occanic and Atmospheric 

Research for providing the equatorial wind data. 

REFERENCES 

Jones. D.B.A., 1-1.R. Schneider. and M.B. McElroy. Effects of the 

quasi-biennial oscillation on the zonal!) averaged transpon of 

tracers. J. Geoph1•s. Res .. 103. I l.235-11.2-l9. 1998. 

i\lcDennid, l.S .. T.D. Walsh. A. Deslis. and M. White. Optical 

systems design for a stratospheric lidar system, Appl. Opt .. 34, 

620 1-6210, 1995. 

Randel. W.J .. and J.B. Cobb. Coherent variations of monthly mean 

total ozone and lower stratosphere temperatures. J. Geophys. Res .. 

99, 5-03-5474. 199-l. 

147 

Randel. \V.J .. and F. Wu, Isolation of the ozone QBO in SAGE II 

data by singular-value decomposition, J. Armas. Sci., 53. 2546-

2559. 1996. 

Randel, \\'.J .. F. Wu, and D.J. GafTen. lnterannual variability of the 

tropical tropopausc derived from radiosonde data and NCEP 

reanalyses. J. Geophys. Res .. 105. 15.509-15.523. 2000. 

Reed. R.J.. \V.J. Campbell. L.A. Rasmussen. and R.G. Rogers. 

Evidence of a downward propagating annual wind reversal in the 

equatorial stratosphere. J. Geophys. Res .. 66. 813-8 18, 1961. 

Shiotani. M., Annual. quasi-biennial. and El Niflo-Southem 

Oscillation (ENSO) time-scale variations in equatorial total ozone, 

J. Geophys. Res., 97. 7625-7633. 1992. 
Investigation of Chemical Transfer Processes between 

Atmosphere and Snow at South Pole 

JosEr11 R. t-. tcCoNO\ELL 

Dil'ision o.fl/i'drologic Sciences. Deserl Research l11S1i1111e. Reno . .\'ernda 8951:! 

ROGER C. BALFS 

Dept11·1111e111 o.f I ll'drology and Wa1er Resources. U11i1·ersi1y o.f Ari 01w, Tucson 85-:! I 

Oxidation by 011 is the pri mary atmospheri c si n k for 

many en\ ironmentally impo rtant gases. including me thane 

(CH4 ). carbon monoxide (CO), and halogenated 

hydrocarbons. Because of its very sho rt lifetime. OH is not 

presened in sno\\' and ice. Hydrogen peroxide (H20 2) is a 

si nk for O H. and, because it is preserved in sno\\' and ice. 

concentrations of H20 2 preserved in ice sheets offer the 

potent ial to reconstruc t past atmospheric concentrations o f 

H20 2 and . hence. 0 11. However. to ma ke use of the 

chemica l archi,·e, a quantitati 1·e understanding of the 

processes that control atmosp here-to-snow tra nsfer and 

presen·ation of 11 10 2 in polar ell\ ironments is requi red . 

Through a cooperati\ e agreem ent with CM DL at South 

Pole. l\' C have been making year-round measurements of 

11 20 2 concentration in the surface and near-surface snow 

since No1 ember 1994. These yea r-round measurements in 

the surface snow com plement more intensive. summertime 

me asu rements in the atmos phere and in snow pits and 

shallo,,· cores. The summer sam pling a nd all s amp le 

a nal yses at Sou th Po le are conducted u nder NSF-funded 

gran ts. 

Results o f the nearl y continuou s, year-round surfacesnow sampling (No\'ember 1994 throug h January 200 I) are 

shown in Figure I. Replicate sampl es are co ll ected at each 

sam pling period and error bars s how the vari ability ( I cr) of 

the H20 2 concentration between replicates. There is a 

dist inct annual cycle in 11 20 2 concentration in the su rface 

25 I I I 

tl I I 

20 I I 

I I II n1 I I I 

15 

!~ : I I I 

== 

:IJ I I I ::i. o'' I I I 

':r." 10 : I.:: 

I ' 'I~ i 

5 !\,: I ~ i Jl~ . I t· 

I I i 

0 • 

1995 1997 1999 2001 

Year 

Fig. I. Hydrogen peroxide in surface snow at South Pole. Error 

bars sho\\ 1 standard de\ iation in replicate measurements. 

snO\\' that results from a combination of' ery strong c hanges 

in atmospheric concentration of H20 2 throughout the year 

[Ste1rnr1 and .\fcC01111ell, 1999]. a strong annual 

temperature cycle at South Pole. and a hi ghl y nonlinear 

partitioning of the 11 20 2 between air and snow as a func tion 

o f temperatu re [Co11kli11 et al .. 1993; ilfcC01111elf et al., 

1997]. Because deposition of 11 20 2 is rc\'e rsiblc. 

preservation is strongly dependent on deposit ion al 

parameters such as temperature and sno\\ accumu lat ion rate 

and timing [.\fcC01111ell. 1997: .\fcC01111ell et al.. 1998. 

l/11:1erli el al .. 2001). By reversible \\e mean that some 

frac tion of t he de posited mass cycles between the snow and 

air until the snow is cut off from the atmosphere by buri al. 

The net result is that \\ hil e \\'e ha\'e measured a strong 

dec rease in H10 2 concentration in firn cores fro m South 

Pole representing sno11 deposit ed O\ er the past - 30 yea rs, 

much o f the o bsen ·ed d ecrease is likely the result o f a slow 

release of f-1 20 2 from supersaturated layers near the surface. 

The decrease w it h depth is pronounced at South Pole 

because the relat i,·e ly cold temperaltlres slow diffusioncon troll ed release of H20 2 from the snow pack a nd because 

the low sno11· accumulation rates allow exchan ge with the 

at mosphere for many years aft er the sno" is deposited. 

1-18 

Formaldeh yde ( HCHO ) concentratio ns also pro\'ide 

information o n the atmospheric oxidation capacity. and 

HCHO studi es in the air and snow at South Po le arc int egral 

to our oYcrall research e ffort. Results of rece nt sno\\ pit 

and shallow core studi es at South Pol e, in agreement with 

similar studies in G reenl and and other Antarctic locatio ns. 

show that HCI 10 deposition is a lso reversible and that 

exchange with the atmosphere is much greater tha n for 

H10 1 (to.I. Hutt erli et al.. HCI 10 in Antarc ti c snow: 

Preservation in ice cores and air-snow exchange, submitted 

to Geophl'Sical Research Lellers. 2002). HCHO 

concentrations in snow sampl es are time-sensiti ve. thereby 

precluding year-round su rface snow sampling by onsitc 

CMD L personne l. 

Year-round surface snow studi es at Sou th Pol e have 

recentl y been expanded to include sampling for 

tri nuoroacetate (TF A). TF A is the primary atmospheric 

d egradation product of the CFC replacement HFC- 13-la. and 

there is concern about the enY iro nmental consequences of a 

build up of this stro ngly hydrophil ic compound in natural 

,,·aters. South Po le is a particularly ap prop riate location to 

carry o ut such sampling because atmospheric measurements 

o f the primary precu rsor, H FC- I 34a. and other related 

compounds ha\'e been made b y CMD L sin ce - 199-1 

[,\10111.:ka et al .. 1996]. Moreover, measurements of HFCl 34a in the firn air at South Po le have recently been 

reported [8111/er e l al .. 1999]. As with the H20 2 studi es. the 
yea r-round sampling by onsit e CMDL personnel 

compl ements mo re intensi,·e summer sno,,· pi t sampling 

conducted unde r NSF fund ing. The TFA project has o nl y 

sta rted recently: there fore . no results are a\·ailable at this 

time . 

The year-round South Pole data, made possible th rough the 

cooperati\·e agreement \\"ith CMDL. are also importan t for the 

inte rp retatio n o f simil ar H20 2, HCHO . and TFA data from 

snow pits and shallow cores coll ected in summertime in \Vest 

Anta rc tica as pan o f the International Tra ns-Antarctic 

Scientific Expeditio n (ITASE) [Fre.1· et al .. 200 1]. 

REfERE:\'CES 

Butler. J.11.. 1''1. Battle. M.L. Ben der. S.A. l\lon tzka. A.O. C larke. 

E.S. Sa lt zman. C.i\I. Sucher. J.P. Se\'eringhaus. and J.\V. Elkins. 

A record o f aunospheric ha locarbons during the twentieth 

cent ury from polar fi rn ai r. ,\la111re. 399. 749-755. 1999. 

Conklin. l\l.H .. A. Sigg. A. Neftel. and R.C. Bales. Atmospheresnow transfer function for 11 ,0,: l\I icrophysical considerations. 

J. Geop/n•s. Res .. 98. 18.367-18.376. 1993. 

Frey. l\1. , J. McConnell, R. Ba les, and M. Hutterli. Peroxid es and 

formald ehyde in West Antarctica: Atmospheric and sno" 

chemistry measu rements a long the ITASE tra\erse. Eo; Tra11s. 

AGU. 8:!. S234. 2001. 

Hutterli. l\1.A .. J.R. l\1cConncll. R.\\'. Stewart. H.- \V. Jacobi. and 

R.C. Ba les. l111pact of temperature-driven cycling of hyd rogen 

pcro:-.ide (H,O,) between air and snow on the planetary 

boundary layer. J. Geophys. Res .. 106. 15.395-15 .404. 200 I. 

l\lcConnell. J. R .. Investigation o f the a unosphcre-sno\\ transfer 

process for hydrogen peroxide. Ph.D. d issertation. Departmen t 

of Hydrology and Water Resources. Un i\crsity o f Arizona. 

1997. 

l\lcConncll. J.R .. J.R. Winterle. R.C. Ba les. A.l\1. Thompson. and R. \V. 

Stewart. Physical I) based ill\ ersion of surface snow concentrations 

of hydrogen peroxide 10 a1111ospheric concen trations at South Pole. 

Geophys. Res. Lm .. :n 44 1-444. 1997. 

McConnell. J.R .. R.C. Bales. R.\V. Ste\\ art. A.M. Thompson. l\1.R. 

Albert. and R. Ramos. Physically based modeli n g of 

at111osphere-to-sn o\\ -to-firn transfer of hydrogen peroxide at 

South Pole. J. Geophys. Res .. 103. 10.561-10.570. 1998. 

i\Jontzka . S.A .. J.11. Butler. R.C. i\lyers. T .l\1. T hompson . T.H. 

s,,anson. A.D. Clarke. L.T. Lock. and J.\V. Elkins. Dec li ne in 

the troposp heric abundance of halogen from haloca rbons: 

Imp lications for stratospheric OLone dep iction. Science. :!7:!. 

1318-1322. 1996 . 

Stewart. R.. and J. l\lcConnell. Antarc tic photochemistry: 

Uncertainty analysis. Eos Tra11s. AGU. 80. F197-F l98. 1999. 

149 
Microwave Measurements of Middle Atmospheric Water Vapor From 

Manna Loa, 1996-2001 

GERALD E. NEDOLUHA, RIC HARD M. BEVILACQUA, R. MICHAEL GOMEZ, AND BRIAN C. HICKS 

Naval Research laborato1J1, Code 7227, Washington, D.C. 203 75-5320 

JAMES M. RUSSELL Ill 

Hampton University, Hampton, Virginia 23668 

INTRODUCTION 

The Naval Research Laboratory Water Vapor 

Millimeter-wave Spectrometer (WVMS) system has been 

making nearl y continuous middle-atmospheric water vapor 

profile measurements at Mauna Loa, Hawaii {l 9.5°N , 

204.4° E), si nce March 1996. The measurements are made 

at 22 GHz, an emission line that is s ufficiently optically 

thin to allow ground-based measurements of the middle 

atmosphere through the troposphere. The Mauna Loa site 

is ideal for these measurements both because of its high 

altitude, which minimi zes the tropospheri c signal, and 

because of its relatively low latitude, which minimizes the 

seasonal variations in the middle atmosphere and thus 

simplifies the monitoring of long-term changes in middl eatmospheric water vapor. 

Measurements of water vapor provide important 

information on several processes in the middle atmosphere. 

Water vapor is an ideal transport tracer and has been used 

in numerous studi es o f atmospheric transport in the middle 

atmosphere [e.g. , Bevilacqua el al., 1990; Nedoluha el al., 

1996; Summers el al., 1997]. Water vapor is also the 

reservoir of odd hydrogen in the middle atmosphere, and, 

although the studi es of s hort-term variatio ns in Halogen 

Occultation Experiment ( HALOE) data (D.E. S iskind et 

al. , A search for an anticorrelation between H20 and 0 3 in 

the lower mesosphe re, submitted to Journal of Geophysical 

Research , 2002) suggest that the effect of water vapor on 

ozone is not yet well described by standard photochemical 

mode ls, it is important to ozone chemistry. Changes in 

middle-atmospheric water vapor may also impact 

stratospheric temperatures and thus indirectly affect ozone 

depletion [Kirk-Davidoff el al. , I 999]. 

WYMS MEASUREMENTS 

The \VVMS3 instrument at Mauna Loa is the third such 

instrument to be deployed. It is essentially identical to the 

WVMS2 instrument that operated at the Network for the 

Detection of Stratospheric Change (NDSC) sit e at Table 

Mountain, California (34.4°N , 242.3° E), from A ugust 1993 

to Novembe r 1997. These instrume nts are both very 

similar to the WVMS I instrument that is taking 

measurements at the NDSC site at Lauder, New Zealand 

(45.0°S, 169. 7°E). 

The retrieval of a vertical water vapor profile w ith 

ground- based microwave measurements relies upon the 

change in pressure as a function of a ltitude . The line 

w idth of the spectrum decreases monotonically wi th 

altitude due to the dependence on pressure broadening. 

Thus the re sul tant signal, which is the s um of the emission 

from all altitudes, can be deconvolved to retrieve a vertical 

profile. Details of the measurement technique and instrumentation are given by Nedoluha el al. [ 1995, 1996]. 

The mixing ratios retrieved from 40 to 80 km using 500 

scan (- 1 wk) integrations are shown in Figure 1. There is 

a summer peak in the upper mesospheric mixing ratio 

consistent w ith the upward motion of the atmosphere in the 

summer hemis phere. The large positive trend in water 

vapor that was observed by the WVMS instruments at 

Table Mountain and Lauder and by HALOE in the early 

1990s [Nedoluha el al., 1998] is not apparent in the data 

from Mauna Loa since 1996. Nevertheless, interesting 

variations are captured by both HALOE and the groundbased instruments. 

A comparison of WYMS and HALOE data at several 

altitudes is s hown in Figure 2. There is an offset between 

the average va lues of the HALOE and WVMS 

measurements at 50 km and 60 km, but the annual and 

interannual vari ations at Mauna Loa are very similar. Note 

in particular the interannual variation in the December/ 

January minima at and above 60 km. Similar variations 

from WVMS measure ments at Table Mountain and from 

Fig. I. Water vapor mixing ratios retrieved from WVMS3 

measurements at Mauna Loa , Hawaii (I 9.5°N, 204.4°E). The 

data are smoothed using a Gaussian filter with a {l ie) width of25 

days. 

150 
~! ·~rr \ 1 111ou lo 1 

"71},..(I \I )U .,) I) 

<:. [ ' r .! [ 

sf 

(:if; ~ JI 

.~o .. ,., .... '·' JL L > 

. rc 

l. 

1 ~ -....._. \ .....-.... ../\...__ --- ~ "'-' .r-.- _ , ~ ~ -= ~~ 

~ 

.Z~J1 

).---

e~ ~ ( . l 

e -"' "'--~ . . i --

-

............... _ /""--.--,, ~ ~ 

'"~ "----~ --- -- ----- ~-~j 1 •.• ~ 20 1 

Fig. 2. Lines: WVMS (red) and llALOE (blue) data at several 

altitudes smoothed as in the contour plots. Measurement gaps of >50 

days arc left blank. Points: WYMS retrievals from approximately 

weekly averaged integrations. The 1 IALOE data are all taken from 

within ±5° latitude of the WVMS measurements, and have been 

convolved with the WYM S averaging kernels to present data with 

similar sensitivity and resolution. 

earl ier HALO E data suggest that these variations may be 

related to the quasi-biennial oscillation (Q BO) [Nedo/uha 

et al., 2000). Preliminary comparisons with inte rannual 

variations in High Reso lution Doppler lmager ( HRD I) 

zona l winds and wi th interannual vari a tions in 1 IA LOE 

tempe ratures suggest that there may be a correlation 

between strong zonal w ind gradients, high tempera tures, 

and low water vapor mixing ratios 1n the upper 

mesosphere. 

Ack11011'fedgme111s. We wish to tha nk S. McDermid, R. 

Cageao, and D. Walsh for their tec hn ical assistance with the 

Mauna Loa radiometer. This project is funded by NASA under 

the Upper Atmospheric Resea rc h Program. 

REFERE CES 

Bevilacqua, R.M., D.F. Strobel, M. E. Summers, J.J. Olivero, and 

M. Alle n. The seasona l variation of water vapor and ozone in the 

uppe r mesosphere: Implications for vertica l transport and ozone 

photochemistry, J. Geophys. Res .. 95, 883-893, 1990 . 

Kirk-Davidoff. D.B., E.J. Hinsta, J.G. Anderson, a nd D.W. Keith , 

The e ffect of c li mate change on ozone depletion through changes 

in stratospheric water vapour. Na111re. 402. 399-40 I. 1999. 

Nedoluha, G.E., R.M. Bevilacqua, R.M. Gomez, D.L. Thacker, 

W.B. Waltman , and T.A. Pauls, Ground-based measuremen ts of 

water vapor in the midd le atmosphere. J. Geophys. Res .. 100. 

2927-2939, 1995. 

Nedoluha, G.E. , R.M. Bevilacqua, R.M. Gomez, W.B. Waltman, 

B.C. !lic ks, D.L. Thacker, and W.A. Matthews, Measurements of 

water vapor in the middle atmosphere a nd implications for 

mesospheric transport, J. Geophys. Res.. JO I, 21. 183-21. 193. 

1996. 

Nedoluha, G. E., R.M. Bevi lacqua, R.M . Gomez, D.E. Siskind, B.C. 

I-licks, J.M. Russell Ill, and B.J. Connor, Increases in middle 

atmospheric water vapor as observed by the Halogen Occultation 

Experiment and the ground-based Water Vapor Millimeter-wave 

Spectrometer from 199 1 to 1997, J. Geophys. Res .. 103, 353 1-

3543. 1998. 

Nedoluha. G.E .. R.M. Bevilacqua, R.M. Gomez, B.C. llicks, J.1\1. 

Russell Ill, and B.J. Connor, Ground-based microwave 

observations of middle atmospheric water vapor in the 1990s, in 

Almospheric Science Ac ross !he S1ra1opa11se, edited by D.E. 

Siskind, S.D. Eckerman , and M.E. Summers. Geophysical 

Monograph. I 23, pp. 257-270, Am. Geophys. Union, 

Washington, DC, 2000. 

Summers, M.E., D.E. Siskind. J.T. Bacmeister, R.R. Conway, S.E. 

151 

Zasadil, a nd D.F. Strobel, Seasonal variations of mi ddle 

atmospheric ll ~ and H20 with a new chemical-dynamical 

model, J. Geophys. Res .. I 02, 3503-3526, 1997. 
Aerosol Chemical Species and Volatile Organic Compounds at Barrow 

S \CllJO 011 r \. NAOTO ML R \0. A::-:D T \.I SL YA Fl K \SA\\ A 

Graduate School o(E11gi11eeri11g. Hokkaido L'nil'enity. Sapporo 060-86:!8. Japan 

l:'\TRODUCTIO:'\ 

In '' i111er and spring, a dense haze occurs in the Arctic. 

This "Arctic haze" contains large amounts of particulate 

pol lu tants, such as soot, s ulfat e. organics. and hca' y metals, 

and gaseous pollutants. such as sulfur dioxide. nitric acid. 

and \Olatilc organic compounds (VOCs) [S/urn. 1995] . The 

soot particles strongly absorb solar radiation. " hi ch changes 

the therma l structure of the Arctic atmosphere. Deposited 

soot reduces sno\\ surface albedo, "hich perturbs the 

radiation budget in the Arctic [Bla11c/ie1. 1989: ..loki er al .. 

1998]. In addition. hea') metals, such as lead. rnnad ium. 

and a rsenic, and VOCs, such as benzene. trichloroethylene. 

and tetrachloroethylenc, in the ha7e attract concern w ith 

respect to their possible human health impacts because the) 

are known carcinogenic compounds. 

In th is stud ) results arc reported from the measurement of 

the concentrations of chemical species in fine particles 

(aerosols less than 2 ~tm in diameter) and voes collected at 

the CM DL Barro\\ Obserrntor) in 1999-200 I. The 

measurement results sen e as basic data "ith "hi ch to 

ernluatc possible effects of pollutants on climate. human 

health . and ecosystems in the Alaskan Arc ti c. 

l\lATERIALS A:'\D \I ETllODS 

Atmospheric fine particles "ere coll ected on Tenon 

filters (Sumitomo Electri c Industry Inc .. FP-1000. -17 mm) 

and quam fiber filters (Pallnex 2500 QAT-UP. -17 mm) 

simultaneously by dra\\ 111g outdoor air through a cyclone 

separator with a 50°0 cut point of 2-pm diameter at a no" 

rate of20 L min·'. Each sample \\<lS integrated O\er a 2-wk 

period from August 1999 through June 200 I. Ionic 

components of aerosols collected on the Teflon filter \\ere 

extracted ultrasonicall) "ith distilled-deioni7cd "ater and 

analyLed with an ion chromatograph (IC. Yokoga\\ a 

Anal) ti cal Systems) for anions (model IC 7000. column 

E.\cclpack ICSO-A23) and for callom (model ICS-C25). 

i\ktal components of aerosols on the Tenon fi lter \\ere 

extracted "ith a mixed solution of nitric acid and 

h)dronuoric acid and ana l)7ed \\ith an inducti\el) coupled 

plasma mass spectrometer (ICP-i\IS. Yokoga"a Analytical 

Systems. 11 P -1500). The carbonaceous components of 

aerosols (e lemental and organic carbon) on the quartz fiber 

filters were determined by sample combust ion in a 

condensation nuclei (C'l) coder at 850°( coup led "ith a 

flame ioni1at ion detector (FID) \\ilh a nickel catalyst 

methanizcr [Oltra and Okira. 198-1]. 

voes \\e re sampled o nce a month from March 2000 

through August 2001. Air ''as dra\\n into a collcc1ion tube 

(Carbotrap 317. SUPELCO) at a !lo\\ rate of 100 ml min·' 

for 2 hours. The collected \'OCs \\Cre thermall) desorbed 

and injected into a mass spectrometer using a Thermal 

Deposition Cold Trap (TCT) inj ector. 

152 

R ES L TS A:'\ D DISCUSS IO:'\ 

T\\ o-week a\ crage concentrations of chemical species in 

fine particles in the atmosphere collected at Ci\ID L. 

Barro\\, from Aug ust I 999 through June 2001 are presented 

in Figure I. The conce111rations of species ranged as 

follows: elemental carbon (EC). 0.001-0.32 μg C m·

3

: 

organic carbon (OC). 0.20-0.69 pg C 111·

1

: su lfat e (S04•

1 ). 

0.09-1.7 11g m·

3

: nitrate ( 0 3.), 0.00-0. 15 ~1 g m· 3: chloride 

(Cl"). 0.001-1.8 1 11g m·3: ammonium (N l1 4 ). 0 .00-0.14 μg 

m· 1

: scasah cations (S.S.C.), 0.007-1.8 ~1g rn·3 : and soil 

particles (Soil). 0.003-0.25 1tg m·'. The concen1ra1ions of 

S.S.C. and Soi l \\ere calcu lated respecti\ cl) as folio\\ s: 

(S.S.C.] = 1.19-1 x [Na ] and [Soil] = 12.35 x [Al] . 

The tota l amount of the chemi cal species increased 111 

\\'inter and spring (No,·cmbcr-Apri l) and decreased 111 

s ummer and autumn (Ma) -Oc tober). In particu Jar. 

concentrations or EC and so4•

1 increased in "inter and 

spring. in concert '' ilh the occurrence of Arctic ha1c [Sltc111·. 

I 995). 

In preparation for th e QC measurements, the quartL fiber 

filters ''ere pretreated by heating at 850°C in air for I hour 

to rcmo\e organic contaminants 8111 . rt11e 10 the heating. 

the clean surfaces of the quart7 fiber filters easi ly absorbed 

gaseous organi cs in the sampling a ir. Thus the OC 

concentration reported herein may be O\ crcst imaled. 

Figure 2 shows 2-wk a\erage concentrations of metal 

components of fine particles 111 the atmosphere at Barrow. 

The eonccntrations (ng m·

1

) of species ranged as follo\\s: 

'anadium (V), 0.02-0.82: manganese (Mn). 0.00-1. 73: 

copper (Cu). 0.00-0.83: zinc (7n). 0.00-6.-18: arsenic (As). 

0.00-1.97: and lead (Pb). 0.06-6.68. These concentrat ions 

increased in "inter and spri ng (No' ember-Apri l) and 

decreased in sumnH:r and autumn (May-October). simil a r to 

concentratio ns of EC and so4·

1 . again due 10 Arct ic haze. 

Concentrations of Zn and Pb. increased in January and 

Februar) 2000 and January to f\ lay 200 I. Zn and Pb are 

emi11cd mainly from so lid waste incineration and 

automobile exha usts. respect i1cly. 

Table I shows atmospheric concentrations of VOCs from 

~larch 2000 through August 200 I at Barro\\. The concentrations (ppb') ranged as follows: chloroform (0.005-

0.0 1-1 ); I, 2-dich loroethanc (0.00-0.0 12): carbon tetra -

chloride (0.00-0. I I): eth yl benLene (0.008-0. I I): m. pxylenc (0.01-0.15): styrene (0.006-0.092): o-xylenc (0.007-

0.096): 1-cthyl-3-methyl-ben7ene (0.002-0.0-1 ): I. 3. 5-

trimeth) I benzene (0.002-0. I I): I. 2. -l-1rime1hylhcnzcne 

(0.008-0.50): and I. -1-dichlorobenzcne (0.001-0.057). 

E.\ccpt for chloroform. I. 2-dich loroethane. and carbon 

tetrachloride . concentrations of the other compounds had 

seasonal Yariations "ith spring maxima. Data from fiyc of 

the compounds listed in Table I arc plotted in Figure 3. 
6 

s 

.., 

~ 

E 4 

0, 

::J.. 

c 

0 

:;:: 3 ~ 

c 

Q) 

() 

c 

0 2 

0 

1 

. 

0 ,..,. 

:I 

O'I ~ 

< 8l I 

g: 

Fig. I. 

8 

7 

6 

.., 

~ 

E 

0, s c 

c 

0 

:;:: 4 ~ 

c 

Q) 

() 3 c 

0 

0 

2 

1 

0 .-'I 

g' 

< 

I 

g: 

er 

.-'I 

Fig. 2. 

D Soil 

• SSC 

ONH4+ 

o n- rn N03-

D S042-

l!ll oc 

•EC 

~ = ~ 

~ ; ~ ,..,. '.d "" ru ru ~ rn ~ ,..,. ru rn ru ..... ,..,. > u L >. :I ...., u L L >. 

~ 2: QI 51- i¥. -:> QI u QI 11) 

~ a. 11) 

u.. VJ 0 A -:> < :c 

Two-week average concentrations of chemical species in fine particles in the atmosphere al Barrow. 

ru ...... u :I QI 

A ~ 

"" u 

~ ~ 

I 

,..,. 

0 

@ 

........_ v 

---Mn 

--fr- Cu 

-+--Zn 

As 

-&- Pb 

Two-week average concentrations o f metal components of fine particles in the atmosphere at Barrow. 

153 

; 

...... 

:I 

~ 
TABLE I. Concentratio ns o f Volatile Organic Com pounds (VOCs) in the Atmosphere at Barrow 

Compound 

Chlorofonn 

Ethane. 1.2-dichloro 

Carbon tetrachloride 

Ethylbcnzene 

m,p-Xylene 

Styrene 

o-Xylene 

Benzene, 1-cthyl-3-methylBenzene, 1,3.5-trimethylBenzene, 1,2.4-trimethylBenzene, 1.4-dichloroChlorofom1 

Ethane, 1,2-dichloroCarbon tetrachloride 

Ethylbenzene 

m.p-Xylcne 

Styrene 

o-Xylene 

Benzene. 1-ethyl-3-mcthylBenzene, 1,3,5-trimethylBenzene, 1.2.4-trimethylBenzene. 1.4-dichloro0.20 

0. 18 

0.16 

> 0. 14 .D 

a. 

.Q, 0.12 c 

0 

~ ..... 0.10 c 

Q,) 

() 

c 0.08 0 

() 

0.06 

0.04 

O.Q2 

0.00 0 

0 

... 

'" 

0 

0 

~ 2 < 

2000 

March 9 

0.0 12 

0.007 

0.060 

0.06.J 

0. 120 

0.044 

0.090 

0.018 

0.023 

0.098 

0.002 

Jan. 18 

0.01 1 

0.0 12 

0. 106 

0.067 

0.093 

0.068 

0.066 

0.0.JO 

0.111 

0.498 

0,038 

-<>- Ethy lbenzene 

~ m , p-Xyle ne 

......_ Styrene 

March 30 

0.012 

0.007 

0.06.J 

0.068 

0. 126 

0.075 

0.096 

0.021 

0.026 

0.11 0 

0.007 

Feb. 26 

0.0 13 

0.0 12 

0.101 

0.1 11 

0.148 

0.092 

0.089 

0.023 

0.034 

0. 127 

0.057 

*-Be n zene, 1,4 -dic hloro-

-tt- Chloroform 

0 0 0 0 0 0 0 9 0 0 >. c ~ 0.. "' :::l :::l '-' 2 :::l < C/l 

April 27 

0.013 

0.009 

0.083 

0.049 

0.084 

0.08 1 

0.054 

0.010 

0.015 

0.058 

0.035 

March 30 

0.011 

0.011 

0. 103 

0.082 

0.093 

0.05.J 

0.057 

0.0 10 

0.0 15 

0.058 

0.006 

0 0 

9 9 

> u 0 

0 z 

2001 

Concentration (ppb') 

March-December 2000 

May26 J1111e26 J11~1' 26 

0.011 0.0 13 0.013 

0.006 0.00.J 0.006 

0.075 0.05 1 0.088 

0.052 0.008 0.009 

0.094 0.012 0.01 1 

0.073 0.006 0.009 

0.059 0.009 0.007 

0.0 10 0.002 0.003 

0.015 0.002 0.003 

0.060 0.008 0.011 

0.01 1 0.001 0.008 

Ja111ia1)•-Augus1 2001 

April 25 May 18 J1111e 15 

0.008 0.008 0.005 

0.008 0.005 

0.100 0.099 

0.083 0.049 0.013 

0.103 0.060 0.0 14 

O.O.J9 0.039 0.013 

0.077 0.038 0.011 

0.022 0.010 0.00.J 

0.0.J6 0.015 0.006 

0.2 10 0.058 0.025 

0.007 0.007 0.008 

0 - 0 c 0 0 

u 9 Jo ... ... '-' c: " '° 0. 

0 "' ~ l!.. 2 < 

Fig. 3. Concentrations of VOCs in the atmosphere at Barro". 

154 

Ocr. 26 Nov. 15 

0.0 11 0.01 .J 

0.005 0.005 

0.073 0.065 

0.027 0.024 

O.O.J3 0.036 

0.029 0.028 

0.026 0.021 

0.005 0.003 

0.007 0.00.J 

0.027 0.017 

0.005 0.002 

July 18 Aug. 25 

0.008 0.008 

0.084 0.099 

0.053 0.049 

0.048 0.060 

0.019 0.039 

0.028 0.038 

0.005 0.010 

0.006 0.015 

0.023 0.058 

0.0 11 0.007 

0 9 9 >. 

"' <::: ~ 

2 :::l 

Dec. 21 

0.010 

0.007 

0.092 

0.062 

0.091 

0.048 

0.064 

0.012 

0.016 

0.06 1 

0.023 

) 

0 

~ :::l 

< 
Et h ylbenzene is used as a sol\'ent. and xylene. styrene. and 

other benzenes a re emitred from automobi le exhaust, 

reinforcing that these gases ha,·e been transp orted at least 

6.000 miles from Eurasia. Since the voes \\'ere sampled 

o n ly for 2 hours each sample da y . the measured voe 

concentrations inevitably depend on \\'Cather conditions and 

transport history. Thus ,,·ind direction. w ind sp eed . and 

a tmosphe ric stability must be checked on the days the 

voes were sampled. as well as t he back trajectories for the 

sampling times. in order to betrcr interpret the data. 

155 

REF E RE:\CES 

Aoki. T .. T. Aoki. i\I. Fukabori. and Y. Zaizen. Spectral albedo 

obsen at ion on the sno\\ field at Barro". Alaska. Climate .\lo11irori11g 

a11d Diag11os1ics Labormory S11111111ar1· Repon .Vo. !4 1996-1997. 

edited by D.J. Hofmann. J.T. Peterson. and R.i'vl. Rosson. pp. 122-123. 

NOAA Em iron. Res. Labs .. Boulder. CO. 1998. 

Blanchet. J.-P .. Toward estimation of climatic effects due to Arctic 

aerosols. A1111os. E11dro11., !3. 1609-2625. 1989. 

Ohta. S .. and T. Oki ta. i\leasurements of paniculate carbon in urban and 

marine air in Japanese areas. Almos. Em·iro11., 11. 2439-24-15. 198-l. 

Shaw. G.E .. The Arctic haze phenomenon. Bull. Am. Me1eorol. Soc., 76. 

2-103-2-113. 1995. 
Advanced Global Atmospheric Gases Experiment (AGACE) 

R.G. PRJ'\'\ 

.\lassac/1mel/\ /1111i1111e C)/Tecl11w/og1. Cambridge . .\/assac/1me11;, Ill 139 

R.F. \\'uss 

Scripps lnsti1111io11 ofOcecmogmphy. l,1111·<T.1ity <>.! Cal(fomia. La Jolla. Ca/ifi1111ia 9:!1193 

D.1\1. CL \J:\OLD 

Georgia /1111i1111e o/Tec/1110/ogy. Atfallla. Georgia 3033:! 

P.J. FR.·\SER 

CS/RO. Dil'i1i1111 o/A11110.1pheric Rfiearch. J"ictoria. Australia 3195 

P.G. SIXJ\IOi\DS 

1.:11i1·erw1· of Bri1111!. School()/ C/w111istr1·. Briwol. C11itecl Ki11gc/0111 BSN I TS 

i:"TROOCCTIO:'\ 

The Ach anced Global Atmospheric Gases Experimem 

(,\GAGE) and its predecessors pro' ide continuous highfrequenc) gas chromatographic measureme nts of biogenic 

and anthropogenic gases that arc carried out at glo ba l I) 

distribut ed sites in order to quantitati,el) determine the 

source and sink strengths and circulation ofa large numba of 

chemica ll y and radiatively important long-Ji, ed gases. The 

prog ram that start ed in 1978 is con,·enientl) di\ ided into 

three pans associated with three changes in in strumentatio n: 

the Atmospheric Lifetime Experime nt (ALE). the Global 

Atmospheric Gases Ex periment (GAGE), and AGAGC. 

l:leginning in 1978. these three successi,·e automated. highfrequ ency. in situ experiments lrnYe documented the longterm behavio r of the measured concentrations of the se 

important gases o\·er the past 23 years and sho\\ both the 

e'olution of latitudinal gradients and the high-frequency 

\ari ab ility due to sources and c irculation. 

AGAG E began O\ er the 1993-1996 time period and 

continues to the present. It has two instrument components. 

First. a highly impro,ed gas chromatographi c system 

measures fi, e biogenic ·anthropogenic gases (Cll4, 20, 

C l ICl1. CO. and H2 ) and fi,e anthropogenic gases (CCl 1L 

CCl 2F2, C ll 3CCl3• CCl2FCCIF2. and CCl4). Each species is 

measured 36 times per day "ith an e lectron capture detec tor 

(ECO). Ila me ionila t ion detector (Fl D ). and mercuric ox ide 

reduction detecto r (MRD; this detector is for CO and 11 2 and 

is currently present at o nly two of the stations. Mace I lead . 

Ireland, and Cape Grim, Tasmani a). Second, a gas 

chromatograph-mass spec trometer (GC-MS) system measures 

a "ide range of hydrochloro fluorocarbons and 

hydrofluorocarbo ns: Cll 2FCF1 (HFC-134a). CJl ,CCJ,F 

(llCFC-14 1b). ll CC IF ~ (HCFC-142b). etc. These are 1101\ 

sc rnng as interim or permanent alternati\ es to the 

chlorofluorocarbons and other long-Ji, eel halocarbons 

regulated b) the Montreal Protocol [ ll.\'EP. 1996). Also 

measured "ith the GC-\IS system are the rneth) I halides 

(Cll 3CI. C H1Br. and C H31) and the halons (C8rF1 and 

CBrC F~). AGAGE also inc ludes de,·elopment and use of 

ne\\, much mo re accurate absolute calibrations for most of 

the measured gases. 

156 

The ALE. GAGE. and AGAGl: stations ha\ e been located 

in fi,e globally distributed localities: (I) Ireland. first at 

Adrigole. 52°N. I 0° \\' ( 1978-1983 ). then at Mace llead. 

53°N. IOV\V (1987 -presem): (2) U.S. \\est Coast. fi rst at 

Cape t\leares. Oregon. 45°N. 124 \\ ( 1979-1989). then al 

Trinidad Head. Cali fornia. 41 N. 124 \V (1995-pn:sent): (3) 

Ragged Po int. Barbados. 13 N. 59 \\' ( 1978-prcscnt): (4) 

Cape Matatula. American Samoa, I 4°S. 171 ° \V ( 1978-

present): (5) Cape Grim. Tasmania. 4 1 S, 145°E ( 1978-

prcsent ). 

Of special significance is the AG AGE o peratio n at Samoa. 

It enables a direct intercomparison with similar real-time 

measurements (and also w ith flask measurements) by the 

C M DL group. This intercomparison has already aided us in 

determining the net effec t of calibration and instrument 

differences on the measurements b) each group so that the 

data from both the A GAGE and Ct\I DL nel\\ orks can be 

utilized in combination b) theoreticians to inn:stigate 

c hemi cal and meteorological phenomena. 

RECE'liT PROGRESS 

The instrumentatio n and calibrations used in the ALE. 

GAGE. and AGAGE experiments and a histor) o r the majority 

of the anthropogenic ozone-depleting and climate-forcing gases 

in air based on these e.\periments ha\ e been described in detail 

[Pri1111 et al .. 2000]. \Ve pro' ide estimates of th e long-term 

trends in total chlorine contained in long-lived halocarbons 

imolYed in ozone depletion. \Ve summarile interpretations of 

these measurements using im erse methods to determine trace 

gas lifetimes and emissio ns. Finall). \IC pro,·ide a combined 

obsenational and modeled reconstruction of the e\'olution of 

chlorocarbons by latitude in the atmosphere O\er the past 60 

years. which can be used as boundar) conditions for 

interpreting trapped air in g laciers and oceanic measurements 

of chlorocarbon tracers of the deep oceanic circulation [Prinn 

et al .. 2000: see also Walker et al .. 2000). 

A recent analysis of the entire 1978-2000 ALl:.-GAGEAGAGE CH3CCl3 data set indicates that O il Je,·els in the 

southern hemisphere are higher than in the northern 

hemisphere and that OH Je,els rose between 1978 and 1988. 
and then subsequently decreased in 2000 to le\ els belO\\ 

1978 \ alues [Prinn et al .. 200 I]. The I 99..t-1998 AGAGE 

Cl ICIJ measurements ha\ e been analyzed. showing that this 

gas has a pronounced seasonal cycle (driYen largely by 011). 

a global a\·erage baseline mole fraction of 8.9 ppt 11 ith no 

signilicanl lrend. and a global lifetime of6.J months. lll\erse 

methods indicate emissions are predominantly in the J0°N900N region [ O'Doliert.1• et al.. 200 I). ,\filler [ 1998 J 

established the abundance and trends of Cl ICIF2 and CH3Br. 

Huang [ 1999] produced ne\\ estimates of 011 using Cll 3CCI3• 

Cl ICIF 2• Cl 12FCF 3• Cl IJCCl2 F. and Cl 13CCI F2, simultaneously. An analysis of the GAGE-AGAGE measurements 

of Cll 4 for 1985-1999 indicates a decreasing trend. in 

agreement \\ ith pre\ ious independe111 analyses. and has 

yielded estimates of Cl 14 emissions in each semi-hemisphere 

[C111111old et al., 2002]. l\leasurements of Cll.1Br from 

AGAGE and other il1\estigators ha\e been modeled \\ith the 

JD l\lodel of Atmospheric Transport and Chemistry 

(MATCH) [Jensen, 1999]. A comprehensi\'e discussion of 

the use of Kalman filters in trace gas inYerse problems has 

been published [Prinn. 2000]. A critical analysis of 

polynomial-based approaches to the CH3CCI3 inverse 

problem has also been published [Pri1111 and l/11a11g. 200 I]. 

AGAGE GC-MRD measurements of hydrogen at Cape 

Grim ha\·e been reported and i111erpre1ed [Si111111011cl.\ el al .. 

2000]. GAGE//\GAGE measurements of CCl1F indicate its 

global concentrations reached a ma.\imum in 1993 and 

decayed slightly after that. while CCl 2F2 le\els continued to 

increase. but only slO\\ ly since 1993 [ C111111old et al .. 1997: 

Pri1111 et al .. 2000]. Se\ era I AG/\GE scientists \\ere lead 

authors or co-authors in the 1998 ozone assessment (/\111:1·/o 

el al.. 1999: Pri1111 et al.. 1999). Analysis of regional 

pollution e\en ls in Ireland suggest that industry estimates of 

the rate of decline in European emissions are 100 small 

[Derwent et al .. I 998a]. i\leasurements of CCl4 from July 

1978 to June 1995 show a maximum in its global 

concentration in 1990. followed by a small decreas..: since 

then I Si111111011ds el al., I 998a]. GC-:-.1S measurements of 

C11 2FCF). CH,CCI 2F. and CH3CCIF2 at i\ lace Head indicate 

rapid increases in the le\ els of these CFC replaceme111s. and 

that industr) estimates of llCFC-1..tlb and particularl) 

HCFC- I ..t2b emissions appear far 100 smal l 10 e.\plain the 

obserrntions [S1111111011cl.1 el al., I 998b ]. Measurements of 

ll CIF~ (HCFC-22) in the Cape Grim archi1·e and al La Jolla 

ha\C been used to estimate OH concentrations. and this yields 

Yalues larger than those determined from CH1CCl1 (but 

because of the larger uncertainty in the llCFC-22-based 

estimate. the difference is not s1a1is1icall1 significant) [.\filler 

el al .. 1998]. 

A Lagrangian dispersion model has been used to analyLe 

1996 Mace II cad obsen at ions sholl'ing that North American 

sources occasionally produce pollution events at this station. 

\\ hich are about I 0°0 of those due 10 the European sources 

[Ryal/ et al .. 1998]. Mace I lead data for Cl 14 , N~O. and C02 

ha\ e been analyzed 10 elucidate European and northcrnhemispheric sources [Dern·ent el al .. 1998b). Wamsley el al. 

[ 1998] reported measurements of the halon C BrCI F 2. Fraser 

et al. [ 1999) discussed halon trends and emissions 0\ er the 

past 20 years. Frmer and Prather [ 1999] re\ iewed the 

current prognosis for reco\ery of the ozone layer. D.S. 

Cohan, ct al. (Meth) I iodide ob sen at ions at Cape Grim. 

Tasmania. using the AGAGE GC-MS instrument. submitted 

157 

to Journal ci/ . I tmospheric Che111i.rn:1·. 2002) reported 

AGAGE CH11 measurements at Cape Grim and interpreted 

them using trajectory analysis. D1111se et al. [200 I) reponed 

the results of modeling studies of Cape Grim pollution 

episodes recorded in AGAGE measurements. 

The ALEGAGE/\GAGE data are a\ailable th rough the 

Department of l:nergy-Carbon Di oxide 

Center (DOE-CDIAC) World Data 

cpd 'a ornl.go\. Dataset No. DB- I 00 I). 

Information Analysis 

Center (e-mail lo 

Ack11oll'/edg111e1111. In its initial years. the global net\\ork (/\LE) 

\\as supported first by grants from the Chemical i\1anufocturers 

Association and latt:r also by the upper Atmospheric Research 

Program of the ;-.;a1ional Aeronau11cs and Space Administration 

(NASA). GAGI· 1rns subsequently supported by multiple grants 

from NASA. In ns latest phase (AGAGE) support came (and comes) 

primari I~ from 'ASA (grants :-:AG\\' -732. 1'.AG 1-1805. AG5-

397.J to the ~1assachuseus lnstitme of Technology: grants NAG\V203.J. l\AG5-.JOD to Scripps Institution of Oceanography). with 

important contributions also from the United Kingdom Department 

of l-1111ronment (no11 Department of Em ironment. Transport. and 

the Regions) (contracts Pl:CD 7 10 15.J and EPG I I r and I I 82 

to lnscon). Common11eal1h Scientific and Industrial R..:search 

Organintion (Australia). Bureau of 1\kteorology (Australia). and the 

\lterna1i1 e Fluorocarbons 1:11\ iron mental Acceptabilit) Stud). 

Support for the Barbados Station during GAGL AG,\GE has been 

shared apprO\imatcly equally hc111een 1'.J\SA and NOAA. \Ve also 

thank '.OAA for its infrastructure support at the Samoa station by 

Cooperall\ e Agreement. 

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Cunnold. D .\I.. R.I. Weiss. R.G. Prinn. D.E. Hartle). P.G. !:>11nmonds. 

P.J. Fraser. B.R. i'.liller. F.N. Alyea. and L. Port..:r. GAGl: 1\GAGL: 

measurements mdicating reductions in global emissions of CCIS 

and CCl~F~ in 1992-199.J. J. Geoph.n Rei .. /II]. 1259-1269. 1997. 

Cunnold. D.\I.. et al.. GAGI ,\GAGI measurem..:nts of methane at 

fi1e sites from 1985-1999 and source inlcn:nccs there from. J. 

Geoph_n. Re.1 .. 111 press. 2002. 

Derncnt. R .. P.G. Simmonds. S. O'Dohert). and D. Ryall. The impact 

of the \ 1ontreal Protocol on halocarbon concentrations in non hem 

hemisphere baseline and European air masses at i'.lace llead. 

Ireland. from 1987-1996. ltmm. Endrnn .. J]. 3689-3702. 1998a. 

Derwent. R .. P.G. Simmonds. S. O'Doherty. P. Cia1s. and D. Ryal!. 

European source strength:. and 'orthcm I k1111spherc baseline 

conc..:ntrations of radia1i1cly acti1e 1race gasc'> at ~lac..: llead. 

Ireland. A111101. E111'iro11. 3!. 3 703-3 715. I 998b. 

Dunsc. B.L.. LP. Steele. P.J. Fraser. and 'i.R. \\'ilson. An anal) -,is or 

~lclbourne pollution episodes obsencd at Cape Grim from 1995-

1998. in Bmeli11e 9--98. pp. 34--12. CSIRO-DAR and Bureau 

~lctcorolog). \spcndalc. Australia. 2001. 

Fra-;er. P.J .. and \1.J. Prather. \n uncertain road: The science of 

atmospheric rcco1ery . . \a111re. 39S. 663-66.J. 1999. 

Fraser. P.J .. D. Oran. C. Rce1e:.. S. Penkett. and A. 1\lcCulloch. 

Southern hemispheric halon trends ( 1978-1998) and global halon 

em1ss1ons.J Geoplin. Rei. /IJ./.15.985-15.999.1999. 

Huang. J.. Optimal determination of global tropospheric 011 

concentrations using multiple trace gases. Ph.D. disscrtallon. 163 

pp .. \lass. ln:.t. ofTeclmol.. Cambridge. 1999. 

Jensen. C.. Terrc,1rial sources and sinks of atmospheric methy I 

bromide: Three-dimensional mod..:hng of tropospheric abundance 

and sensiti1 i1ic ... i'.l.S. diss..:rtaiion. \/IT Ce11tl!r/or Global Change 

Scie11cl! Report fi! . .JI pp .. \lass. In st. of -, cchnol.. Cambridge. 

1999. 

Kury lo. \1.J.. ct al.. Shon-hied O/One-related compounds. in Scie111!fi£ 

..l11e1.1111e111 o( O:o11e Deplf'tio11. 1998. Global O:mu: Re.1. am/ \lo11i1. 

Prof Rep.././. pp. 2.1 -2.56. \\orld ~leteorol. Org .. Gene1a. 1999. 
\tiller. B.R.. Abundances and trends of atmospheric chlorodilluoromethane and bromomethanc. Ph.D. dissenation. I .J9 pp .. 

Uni\. ofCaliL San Diego. 1998. 

:<.lillcr. B.R .. J. Huang. R.F. \\ ciss. R.G. Prinn. and P.J. Fraser. 

.-\tmospheric m:nd and lili:timc of chlorodilluoromcthane (llCFC22) and the global tropospheric 011 concentration. J. Geophn. Res .. 

/03. 13.:!37-13.:!-18. 1998. 

O'Dohert). S .. ct al.. In suu chloroform measurements at AG.-\GE 

atmospheric resea rch stations from I 99-l-1998. J. Geophy.1. Re\ .. 

106. 20.-1:!9-20.-1-1.J. :!00 I. 

Prinn. R.G .. 1\leasurcmcnt equation for trace chem1cab in fluids and 

solu11on of its irn erse. in flll"erse \/etl10ds i11 Global Biogeochemical Cycle1. edited b) P. Kasibhatla cl al.. pp. 3-18. 

Geophy11cal .\lanograph. \o. 11./. .-\111. Gcophys. Lnion. 

Washington. DC. :!000. 

Prinn. R.G .. and J. I luang. Co111111e111 on "Global 011 trend in li:rred 

from methylchloroform measurements" b) 1\1. Krol ct al.. J. 

Ceoph.n. Res., 1116. :!3.151-23.158. 200 I. 

Prinn. R.G .. R. Zander. D.1\1. Cunnold. J. \\'. Elkins. A. Engel. P.J. 

Fraser. 1\1.R. Gunson. 1\1.K.\\'. Ko. E. :-.tahicu. P.1\1. 1\lidgle). J.1\1. 

Russell Ill. C.1\1. Volk. and R.F. Weiss. Long-Ji,ed oLonc-related 

compounds. in Sciem!{ic AHe.;.;111e111 of O=o11e Depletion. 1998. 

Global O=o11e Re.1. and .ll<mit Proj. Rep . ././. pp. 1.1-1.5-I. \\ orld 

1\letcorol. Org .. Gcnc\a. 1999. 

Prinn. R.G .. R.F. Weiss. P.J. Fraser. P.G. Simmonds. D.1\1. Cunnold. 

F.:'\. Al)ea. S. O'Dohcrl). P. Salameh. B.R. i\liller. J. Huang. R.H.J. 

\\'ang. D.E. Hanley. C. Hanh. L.P. Steele. G. Sturrock. P.:-.1. 

i\lidglc). and A. l\lcCulloch. A hrstor) of chcrnicall) and 

radiati,ely imponant gases in air deduced from 

ALE: GAGE AGAGE. J. Geoph.n. Re.1 .. 115. 17.75 1-1 7.792. 2000. 

Prinn. R.G .. J. Huang. R. \Verss. D. Cunnold. P. Fraser. P. Simmonds. 

A. l\lcCulloch. P. Salameh. S. O'Dohert). R. \\'ang. C. llanh. L. 

Porter. and B. l\liller. E\idence for significant \ariatiom, in 

158 

atmospheric hydro.\yl radicals o,·er the last mo decades. Science, 

!93. 10-18-105-1. 2001. 

Ryall. D .. R. \lar)on. R. Dement. and P.G. Simmonds. \lodeling 

long-range transport of CFCs to :<.lace Head. lrdand. Q. J. R. 

.\feteoro/. Soc .. I!./. -117-4-16. 1998. 

Simmoncb. P.G .. D.\I. Cunnold. R.F. \\ ciss. R.G. Prinn. P.J. frascr. 

and A. :-.tcCulloch. Global trends and emission estimates of 

carbon tetrachloride (CCI,) from in situ background obsen at ions 

from Jul) 1978 to June 1995. J. Geophys. Re.1 .. 103. 16.017-

16.0:!7. I 998a. 

Simmond-,. P.G .. J. Huang. R. Prinn. S. O'Doherty. R. Dement. D. 

Ryall. G. Nickless. and D. Cunnold. Calculated trends and 

atmospheric abundance of 1.1, 1.2-tetralluoroethanc. 1.1-dichloro-llluorocthanc. and l-chloro-1.1-lluoroethanc using automated in situ 

gas chro111atograph}-111ass spectro111ctr) measurc111cnts recorded at 

!\lace Head. Ireland. from October 199-1 to /\larch 1997. J. Geophys. 

Res .. 1113. 16.029- 16.037. 1998b. 

Sim111onds. P.G .. R.G . Dernent. S. O'Dohcrty. D.B. Ryal!. L.P. 

Steele. R.J. Langcnfelds. P. Salameh. H.J. Wang. C.11. Di111mcr. 

and L.E. Hudson. Continuous high frequenc) obsenations of 

hydrogen at the !\lace I lead baseline atmosphaic monitoring 

station O\Cr the 199-1-1998 period. J. Geopl1ys. Rt•\ .. 105. 12.105-

12.121. 2000. 

UNEP (Lnitcd l\'ations En' iron111ental Progra111mc). Handbook for the 

lntemmio11al Treaties for the Protection of the O:one layer, 4th 

ed.. airobi. Kenya. 1996. 

\\alker. S.J .. R.F. \\'crss. and P.K. Salameh. Reconstruc ted histories of 

the annual mean atmospheric 111ole fractions for the halocarbons 

CFC-I I. CFC-12. CFC-113. and carbon tetrachloride. J. Geophys. 

Res., /05. 1-1.285-1-1.296. 2000. 

\\'amsle). P .. c1 al.. Distribution ofhalon-1211 (CBrClf: ) in the upper 

troposphere and lo\\ er stratosphere and the 199-1 bromine budget. J. 

Ceophys. Res .. /03. 1513-1526. 1998. 
USDA UVB Monitoring and Research Network Langley 

Calibrations at Mauna Loa Observatory 

J.\\IES SUJSSER 

l;SDA UIB .\lo11itori11g and Research .\"et11·ork. .\'atural Resource Ecology Labora/01T. 

Colorado State U11i1·ersi1y. Fon Colli111 805:!3-l./99 

l:\TROD UCTIO:\ 

The U.S. Department of Agriculture (USDA) ultraviolet 

B (UV B) l\lonitoring and Research Network [Bigeloll' et al .. 

1998) set up a climatological site as \\'ell as an experimental 

research sit e al Mauna Loa Observatory. 1 lawaii (l\I LO). in 

November 1997 in o rder to in\·est igate its ne\\' 

instru mentation 's performance and ability to self- cali brate 

using the Sun as a source. The US DA Network makes 

measu rements at 28 U.S. and 2 Canadian si tes \\·ith the 

Yankee Environmental Systems (Turners Falls, MA) UV 

multi-filter rotating shadowband rad iometer (UV-MFRSR). 

The measurements are made every 20 seconds and 

combined to 3-min averages. The UV-MF RSR [Bigeloll' et 

al.. 1998) is a se\'en-channel ultra\ iolet version of the 

\ isible multi-filter rotating shadowband radiometer 

described by Harrison et al. [199~). This UV instrument 

contains separate solid-state d etectors. each with nominal 2-

nm full-\\'idth half-maximum ( F\VHM ) ion-assisteddeposition interfe rence filters at 300-. 305-. 31 I-. 318-. 

325-. 332-. and 368-nm nominal-center wa\ clcngths. The 

368-nm wa\'ele ngth is a standard \\IMO wa\elength. and the 

others. except 300 nm. are c lose to Dobson wavelength s. 

The 300-nm channel was chosen as the shortest waveleng th 

\\·here suffi cient signal-to-noise ratio was achic\'ablc. Each 

detector shares a co mmon d iffuser, thereb y allowing tota l 

horizontal (no blocking) and diffuse horizontal (d irect beam 

blocked by the shadowband) irradiancc to be measured 

simultaneously at each passband. Direct normal irradiancc 

is deri\ed in nea r-real time by fi rmware included\\ ith in the 

data-logging componen t of the instrument. 

LA:\GLEY CA LIBRATIO:\S 

The Langley method o f calibrating the UV-M FRSR was 

explored by Slusser et al. [2000) under the exceptionally 

clear skies at M LO. The objecti\'e of the study \\as to 

compare Langley calibration factors with those from 

standard lamps. Th is method has SC\ era I adva ntages O\ er 

the tradition al standard lamp cal ibrations: the Sun is a free. 

universally a\·ai lable. a nd very constant source. and nearly 

continual automated field calibrations can be made. 

Although 20 or so La ng ley en:nts are required for an 

accurate calibration. the radiometer remains in the field 

during calibrati on. Difficulties arise as a result of changing 

ozone opti cal depth during the Langley event and the 

breakdo\\n of the Beer-Lambert law over the fin ite filter 

bandpass. since optical depth changes rapidly \\ ith 

wa\'clength. The Langley cali bration of the radiometers 

depends critically upon the spectral characterization of each 

channel and on the wa\'elength and absol ute calibration of 

159 

the extraterrestrial spectrum used. Resu lts of Langley 

calibrations for two UV-l\IFRSRs at Mauna Loa were 

compared \\'ith calibrations using two National Institute of 

Standards and Technol ogy (N IST) traceable lamps. The 

two radiometers were run simultaneously: one on a Suntracker using a coll imating tube and the other in the 

conventional shadO\\·band configurati on. Both radiometers 

were calibrated wit h two secondary 1000-\\1 lamps. and 

later the spectral response functions of the channels were 

measu red. 

T he range o f air ma ss fac tors at a given wavelength 

su itable for Langley plots is governed by the s um of the 

products of the optical depths and the ind iYidual air mass 

factors. E:--tinction of the d irect beam is much larger in the 

UV than i n the visible region of the spectrum. This is the 

result of both the strong absorption due to ozone and the 

molecular Rayleigh scatteri ng. which increases approximately as /,·•, resultin g in a combined optical depth 

exceeding 3.0 at 300 nm. Current state-o f-the-art sol idstate d etectors are limited to not more than four decades of 

dynamic range. Therefore the range o f air masses 

appropriate for UV Langley plots is more restri cted than for 

the visible. where at -115 nm the total optical depth is 

typically less tha n 0.5. After a number of ranges were tried. 

an air mass range of 1.2 to 2.2 [solar zenith angle (SZA) 

33.6° to 63.0° ) was determined to be suit abl e for the UV. 

instead of the range of 2 to 6 (SZA 60.0° to 80.4° ) 

commonl y used in the visible part of the spectrum 

[ Harriso11 and Micha/sky. 199~) . 

Extrapolations to zero air mass \'Oltage in the UV. central 

to the Langley calibrations. are more \ ariable th an those in 

the \'isible region as a consequence of the diurnal variat ions 

in the ozone and lo a small er extent aeroso l optica l depth. 

Large changes in ozone optical depth in the HartlcyHuggins band below 320 nm O\ er th e finite 2.0 -nm 

passband of the UV-MFRSR result in the failure of the 

Beer-Lambert law, addi ng to the uncertainty of the LangleyderiYed calibrations [ ll'ilso11 and Forgan. 1995). Since the 

shorter \\ a\•elength s are attenuated more strongly than the 

longer as the SZA or column ozone increases. the effccti\'e 

center \\·aye length of the passband sh ifts to the red. Further 

comp licat ions result from the large r fraction of diffuse light 

in the field o f \ iew around the Sun's disc d ue to molecular 

scatterin g at these shorter UV wavelengths [Tiig and 

Bauman. 1994: ,\/cKen::ie and Joh11sto11. 1995). Corrections 

for these problems \\ere performed as discussed in Slusser 

e1 al. ['.WOO]. 

The rat io of Langley to lamp calibration factors for the 

two radiometers after 213 days in 1998 for the se\'en 

channels from 300 nm to 368 nm. using the shadowband 

configuration. ranged from 0.988 to 1.070. The estimated 

uncertainty in accuracy of the Langley calibrations ranged 
from ±3.8% at 300 nm to ±2. 1 % at 368 nm. For all 

channe ls calibrated with Central UV Calibratio n Facility 

(CUCF) lamps the estimated uncertainty \\'as :r2.5%. The 

Langley and lamp calibration factors from t\\'o lamps agreed 

to \\'ithin their combined uncertainties for all c hannels of 

the first radiometer and for all but o ne channel of the 

second radiometer. These are the tirst successful Langley 

cali-brations o f filter radiometers at 300 nm and 305 nm. 

The Langley ca libration factors w ith the radiometer in the 

shadowband mode for all the channels agreed with those 

derived from lamps. from 0% difference to at \\'Orst 7°0 

hig her at 300 nm. The uncerta int y due to the radiometer 

sig nal-to-noise ratio is smal lcr using the Langley method 

than du ring lamp calibrations. which constitutes a major 

advantage of UV Langley calibrations fo r these radiometers. 

There were no significant differences 111 Langley 

ca libration factors when th e radiometer was in the s hado\\'-

band config ura tio n compared with when it was on the Suntracker. Th is s uggests that in the UV the shadowband is 

equally as capable as the Sun-tracker in iso latin g the direct 

beam. This study shows that using Langley-method 

shadow-band UV radiometers at a high-altitude site is an 

e ffective method to obtain cal ibrations that approach the 

accuracy o f those from lamps. Adrnntages over lamp 

calibratio ns include superior signal-to-noise ratio. 

auto mat ed opera tion. no loss of instrument o peration, and 

reference to an absolut e, nearly unchanging standard that is 

universal ly avai lable. Used together with lamp calibrations. 

the Langley me thod provides continual checks of 

radiometer and lamp stability. The ad vantage of a s hadowband over a Sun-tracker radio-meter is that in addition to 

the direct beam the shadowband radiometer retrie\ es globa l 

and diffuse irradiances. 

Ack11oll"ledg111e111s. The ou1stand ing togis1ical su ppon of the 

i\ l auna Loa Obser\"atory operated by Ci\IDL. and especially the 

help of its Director J. Barnes. arc greatly appreciated. 

REFERE:-iCES 

Bigelo\\. D.S .. J.R. Slusser. A.F. Beaubien. and J.11. Gibson. The 

USDA Ultra\ iotc1 Radiation i\tonitoring Program. Bull. Am. 

,\ feteorol. Soc .. 79. 601-6 15. 1998. 

ll arrison. L .. and J. f\l ichalsky. Objccti\e algorithms for the rctric,al 

o f optical depths from ground-based measurements, Appl. Opt .. 33. 

5126-5132. 1994. 

Harrison. L.. J. Michalsky. and J. Berndt. Automated multi-filler 

rotating shado" band radiometer: An instrument for optical depth 

and radiation measurements. Appl. Opt., 33. 51 18-5 125. 1994. 

160 

'.\le Kenzie. R.L.. and P. V. Johnston. Comment on ··Problems of UV-B 

radiation measurements in biological research: Critical remarks on 

current techn iques and suggestions for impro' emcnts"' by 11. Tiig 

and f\l.E.f\1. Baumann. Geophys. Res. Lett .. 12. 1157-1158. 1995. 

Slusser. J.R .. J.H. Gibson. D. Kolinski. P. Disterhoft. K. Lantz. and 

A.F. Beaubien. Langley method of calibrating UV filter 

radiometers. J. Geophys. Res .. 105. -18-11--18-19. 2000. 

Tlig. II .. and f\ 1. Baumann. Problems ofUV-13 radiation measurements in 

biological research: Critical remarks on currents techniques and 

suggestions for imprmements. Geophys. Res. I.ell., ]/. 689-692. 

1994. 

\Vi Ison. S.R .. and B. \V. Forgan. In sirn calibration technique for 

UV spectral radiome1ers. Appl. Opt .. 34. 54 75-54 84. 1995. 
Long-Term Trends of Trace Gases over Mauna Loa 

R. VA' ALLEl\. F.J. MlJRCRAY. T.M. SHPllL'. Al\D R.D. BLATHER\\l(K 

Depart111e11111f l'h_l'lics and .·I 11ro110111y. l..,11i1·ersi1y o.f De111·er. Dem·er. Colorado 80108-0101 

h'TRODUCTIO:\' 

Since Non:mber 1991. the University of Dcn,·cr (DU} has 

operated a \Cry high resolution (- 0.0035 cm. 1

) Fourier 

transform spectrometer (FTS) from the Network for the 

Detection of Stratospheric Change (NDSC) site at Mauna Loa 

Obsen·ator) to obtain atmospheric transmission spectra in the 

infrared region of the solar electromagnetic spectrum. 

Initially, a Bomem D/\3.002 FTS was employed. This 

instrument required considerab le operator attent ion and was 

consequently only operated routinely once a week at sunrise. 

and more frequent!) when DU personnel were on site for 

maintenance or for special campaigns. The spectral regions 

routine ly co\crcd were 750-1250 cnf 1 and 2400-3050 c111· 1

• 

and 'ertical column densities of N20. 0 3• HNO.i. I !Cl. and 

CllCI F2 were retrie,ed from the data. In August 1995. this 

system was replaced '' ith a Bruker 12011 R S)Stem. The ne'' 

system includes a weather station and control software 

designed and fabricated at DU. It is almost completely 

automated. requiring an operator only to till the detector 

de,,ars "ith liquid nitrogen. and runs t\\ ice daily when 

''cat her permits. With the installation of this instrument. 

addit ional spectral intervals ''crc added. permitting the 

retrieval of column densities for additional molecules. In this 

<;lll<ly the trend<; for 1 :1 molecules are presented. and 0 3 

'alucs measured '' ith the FTS arc compared '' ith Dobson 

measurements for the I 0-yr period of 1991-2000. 

1E+19 1 

9E+18 

c 

5 7E+18 

~ c 

E 

:> 

0 

o 6E+18 ... 

0 • 

RESULTS A~D DISCUSS O~ 

Sho,,n here are the cumulatiYe results of the 

observations: a I 0-yr record for 0 3 • l INO~. N20, I !Cl. and 

CllCIF2 (llCFC-22). and a 6-yr record for Cll 4, C211r,. llCN. 

NO. N02• HF. and CO. 

The analysis ''as performed using the computer code 

SFIT [Rim/and et al., 1984). wh ich minimized the root 

mean square residual between a simulated spectrum and the 

obsen eel spectrum by multiplying an assumed Yertical 

volume mixing ratio pro!ile by a scaling factor. The present 

analysis employed the HITRAN 96 spectral-line-parameter 

data base [Rothman el al.. 1998] and the pressuretcmperature pro!ilcs from the daily National Weather 

Sen ice radiosondes launched from Ii i lo. Ila'' aii. 

A comparison was conducted between 0 3 measured with 

a Dobson [Dobson a11d Harrison, 1926; Dobson, 1957] and 

FTS measurements (Figure I ) ( R. Van Allen et al .. 

unpublished manuscript. 2002). For this comparison points 

that were as close in time as possible ''ere chosen. but 

always within 24 hours. For the 1991-199-t data, measured 

with a Bomem spectrometer. a systematic offset between 

FTS measurements and the Dobson was found. The Dobson 

data \\ere taken from the World Ozone and Ultra' iolct Data 

Centre (\VOUDC}. The ratio a\eragc (Dobson rTS) for 

1991-1992 is 1.03, \\ith a standard de,iation (SD) of 0.04. 

and for 1993-1994 the average ratio is 1.03. with a SD of 

0 

6 

5 

• 

3E+18+---1:>-~~~ ~~~~~~~~~~ ~~~.-~ ~~~-,..~~ ~~-+ 0 

01.Jun-91 30-Nov-92 01-Jun-94 01-Dec-95 01.Jun-97 01-Dec-98 01.Jun--OO 

Fig. I. Comparison bct\\CCn 0 3 retric,cd \\ith a Dobson (\\hitc circles) and \\ith a FTS (hlack circles). at MLO. The ratio Dobson FTS 

(open square) is also >h0\111. 

161 
0.05. This comparison of the 199 1-1992 data agrees "cl I 

with pre\ ious studies [Dal"id et al.. 1993). The ~ma ll 

difference in the systemati c offset between the current and 

the pre\ ious analysis is due to the fact that points "ere 

matched in the current comparison. wh il e the previou s stud y 

used a\ erages. The agreement between Dobson and FTS 

c 

& 

E 

<( 

9.00E+18 

7.50E+18 

c 6.00E+18 § 

8 

.., 

0 

4.50E+18 

0 

\'alues is much impro\ ed for the Bruker data. The a\ erage 

ratio for 1995 -2000 is 1.00. ''ith a SD of0.025 . 

The seasonal cycles of03 and II 0 1 are sho,,n in Figure 

2. Otone amounts shO\\ ed no obvious trend from 1991 10 

2000. The reco\'ery of IINO-' from Pinatubo-induced high 

le\'cls is appa rent from 1991 to 1996. wit h an O\erall 

• 

i .. ·t_,i1w ! ~ ,, • ,, :if" 

2.70E+16 

2.08E+16 

-c 

s 

~ c 

1.45E+16 § 

8 

.., 

~ % 

8 25E+15 

3.00E+18 +-----~-- -----.--------- --- - ---,-.------<- 2.00E+15 

1-Jun-91 30-Nov-92 1-Deo-95 1-Jun-97 1-Qeo.98 1-Jun-00 

... 

c 

g 

~ 

3.00E+15 

2 25E+15 

E 1.50E+15 

0 " 

0 

0 

::c 

7.50E+14 

Fig. 2. Total column amounts ofO, (black circles) and ll NO;. (white circles). at t'.ILO. 

• 

• 

• 

• I • .. ... . .: 

., f:"'· ~ :.~6·.~~=~ .. .. . v· . 1.50E+15 E 

7.50E+14 

0 

----~ O.OOE+OO 

30-Nov-92 01-Dec-95 01-Jun-97 01-Dec-98 01-Jun-OO 

Fig. 3. Total column amounts ofllCI (black circles) and llF (\\hite circles). at t'.ILO. 

162 

0 " 

0 

LL 

::c 
dec rease o f about 30% . During 1997-200 I there is no 

apparent trend in I IN03. 

The quasi-seasonal trend in HCI and I IF is shown in Figure 

3. The increase in II F is approximate ly 12% from 1995 to 

200 I. The increase in HCI for the same time period is about 

6% . 

2.00E+18 

1.50E+18 

c 

::J 

0 

E 

<( 

c 

,, 

E 1.00E+18 • I 

0 

::J , u 

0 

u 

5.00E+17 

Figure 4 shows the high variability of CO, and the overall 

increase in HCFC-22 of about 50% between 199 1 and 1998. 

where the tre nd levels off. 

Figure 5 shows C2H6 and HC 1. The high va lues of C2H6• 

HCN, and CO at the encl of 1997 and in 1998 correlate with 

---------- 6.00E+15 

• • • 

• • ., • 

• • 4.75E+15 

. ~- . E 

•• ::J 

0 

I ,; v:• ·f~~ ~ e 

< 

c 

3.50E+15 ~ :~. 0 

u 

0 

~ :c 

u 

2.25E+15 

O.OOE+OO 1--__J'-'--------~------ - -----+ 1.00E+15 

01-Jun-91 30-Nov-92 01-Jun-94 01-Dec-95 01 -Jun-97 01-Dec-98 01-Jun-00 

Fig. 4. Total column amounts of llC FC-22 ( wh ite c ircles) and CO (black circ les). at MLO. The polynomial fit (second order) shows that 

HCFC-22 amounts level off in 1998. 

c 

::J 

0 

E 

< 

c 

E 

::J 

0 

u 

ID 

:c 

N 

u 

1.40E+16 

1.05E+16 

7.00E+15 

3.50E+15 

0.00E+OO -i---- ---------

1-Jun-91 30-Nov-92 1-Jun-94 

0 

4e 

• ~::: c 

::J 

0 

E 

< 

c 9.00E+15 E 

::J 

4.50E+15 

0 

0 

z 

u 

:z: 

----- - ---- -----.-------+ 0.00E+OO 

1-Dec-95 1-Jun-97 1-Dec-98 1-Jun-00 

Fig. 5. Total column amounts ofC 6 (black c irc les) and ll CN (white circles). at MLO. 

163 
Asian tropical fires [Rinsland et al .. 1999). Figure 6 shows NO 

and N02. Photochemistry is e' idem in AM-PM di fferem:cs. 

Ad110111etlg111e11/\. This research was partial!) supported b) the 

National Aeronautic, and Space 1\dministration under grant N,\G 

2-1391. The collcc11on of the data was done "ith the support of 

Ci\tDL. We arc espec ial!) grateful to R. Uchida for maintaining 

the e\perimcnt O\Cr the years. 

Figure 7 shows Cll 4 and t ~O. No significant trends are 

obsen ed. and the rctrie' al or these molecules can be used 

to study the achievable precision. 

8.00E+15 

6.00E+15 k ~ ~. •J :~ :• i~:o c 

g o dP~o Voo ~ & 0 0 

c 4.00E+15 0 

~ 0 

'"''\'I'"'' u 

i 

2.00E+15 

IP!~ ~111~ a O.OOE+OO 

1-Jun-91 30-Nov-92 1-Jun-94 1-Dec-95 1-Jun-97 1-Dec-98 

- · 8.00E+15 

l:" 6.00E+15 

~~ c 

"' 0 

0 6 E 

"" c 4.00E+15 ~ 

0 

(J 

... 

-

0 

z 

2.00E+15 

O.OOE+OO 

1-Jun-00 

Fig. 6. Total column amoun ts of NO-sunscr (h lack circles). NO-sunrise (\\ hite circles). NO~-sunsct (black squares). and l\O -sunrrsc 

(\\hitc squares), at M LO. 

c 

g 

~ c 

E 

::i 

0 

u 

., 

::c 

u 

3.00E+19 7.00E+18 

2.60E+19 

~ flll(_,I;~ • 6.00E+18 

it c 

g 

~ c 

2.20E+19 • • • 5.00E+16 E 

• ::i 

0 

u 

~e"~~~-i fa 

~oL~~~~ -

z 

1 4.00E+18 .60E+19 o ~o 

1.40E+19 

01-Jun-91 

--------~- --~----- - -----------t- 3.00E+18 

30-Nov-92 01-Jun-94 01-0ec-95 01 -Jun-.97 01-Dec-98 01-Jun--OO 

Fig. 7. Total column amounts ofCll, (black circles) and O (\\hite circles), at tvtLO. 

164 
REFERENCES 

Da\ id. S.J .. S .. \. Bcaion. \l.H. Anderberg. and F.J. \1urcra). 

De1crmina1ion of ioial oLonc mer /\1auna Loa using 'er) high 

rcsoluiion infrared solar spectra, Geophys. Re.1. Leu .. 10. 2055-

2058. 1993. 

Dobson. G.;\l.B .. Obscncr·s handbook for !he ozone spectropho1ome1er. tl1111. /111. Geophrs. l'ear. 5. 90. 1957. 

Doh,on. G.M.B .. and D.N. I larri ~on. 1\1casuremcn1' of 1hc amount or 

ozone in the Fanh 's almospherc and iis relaiion 10 oiher 

geophysical condi1ions. Proc. Roy Soc .. A 110, 660-693. 1926. 

Rinsland. C.P .. R.E. Boughner. J.C. Larsen. G.~1. Stokes, and J.\V. 

165 

Broull. Diurnal 'aria1ions of atmospheric niiric o:-.idc: Ground 

hased infrared speciroscopic rncasurcrncnls and !heir 

interprc1a1ion "iih 1imc-dependen1 pho1ochemical model 

calculalions . ./ Geophy.1 . Res.. 89. 9613-9622. 198-l. 

Rinsland. C.P .. cl a l.. Infrared speciroscopic rncasuremcnis of free 

1ropospheric CO. ll , .. and llCN abo\C auna Loa. Hawaii: 

Seasonal 'ariaiions and e\ idenccs for enhanced emissions from 

!he Sou1heas1 Asian lropical fires of 1997-1998 . ./. Geoph_n 

Rei .. 104. 18.667-18.680. 1999. 

Roihman. L.S.. c1 al.. The 11 ITRAN molecular spectroscopic daiabasc 

and llA \\'KS (I llTRAN Almospheric \\ ork S1a1ion): 1996 cdiiion, 

./. Q11a111. Speurosc Radial. Tram/er. 60. 665-710. 1998. 
Geomagnetic Field Monitoring at Barrow, Alaska 

E.W. \VORflll'\GTOJ\ 

U.S. Geological S11n·e.1', College ilf11g11e1ic Obsell'<llOI)'. Fairba11A.1. Alaska 9977j 

J.J. LO\I 

U.S. Geologirnl S11n·c.1'. Box !50./6 .llS 966. Dem·e1', Colorado 80115 

Temporal variations in the Earth's magnetic field occur 

over an astonishingly '' ide spectrum. with periods ranging 

over 20 orders of magnitude: sub-milliseconds to tens of 

mil lions of years [Parkinson, 1983: Courtiflot and Le.\/ouel. 

1988). These 'ariations have a variety of causes and 

effects. some or which are understood and ot hers of which 

remain rather more mysterious. Magnetic field \ariations 

with periods less than a fc\\ decades can be monitored and 

studied with magnetic obscr\'atories. such as that operated 

by the U.S. Geological Survey (USGS) in Barrow, Alaska. 

The most rapid geomagnetic licld 'ariations arc of 

external ongrn. coming from the ionosphere and 

magnetosphere. The magnetic field is particularly time 

dependent during so-called "magnetic storms," "hi ch, at the 

surface of the Earth, are prominent manifestations of the 

\ariablc conditions in the near-Earth space en\ ironment, or 

"space-weather." The most energetic magnetic storms occur 

during peaks in solar acti\ ity and "hen the interplanetary 

magnetic field ( ll\1F) becomes intimately connected with 

that or the Earth (Figure I) [Russell, 1991: Co11::ales et al .. 

1994: Coll'/e_1'. 1995: Burch. 2001]. 

Data from ground-based magnetic obserrntories pla) an 

important role in the diagnosis or space "eat her conditions. 

which in nuence the performance and reliability of 

...... ~~~---··· 

Fig. I. Soutlmard orienrntion of the interplanetal) magnetic field. being 

swept lO\\ard the Eanh by the solar" ind. rcsults in sC\cre geomagnetic 

stom1s. Al the front of the magnetosphere. this geometl) is unstahk and 

field reconnection occurs "ith the geomagnetic field. A> the 

interplanctal)' magnetic field i> blo" n past the Eanh. the geomagnetic 

field is peeled back. causing acceleration of charged particles in the 

magnetosphere. A related etTect occurs in the tail of the magneto~phcre. 

\\here neighboring hut oppositely directed field lines can reconnect." ith 

a resulting recoil and acceleration of charged particles. The timedependent panicle accelerations amount to induced electric currents that 

sustain their O\\ 11 magnetic fields and contribute to the magnetic 

'ariations detectable at the Earth's surface. 

technological systems that are criti cal to modern ci\'ili7ation 

[Dooli11g, 1995; Seo//. 1997: Nordll'all. 1999]. During 

stormy cond itions both high- and low-frequency radio 

technological systems that are criti cal to modern civiliLation 

communi cation can be difficult if not impossible, Global 

Position ing Systems (GPSs) can be degraded. satellite 

electroni cs can be damaged. satellite drag can be enhanced. 

and astronaut and high-altitude pilots can be subjected to 

enhanced levels or radiation [Alaynard, 1995: Shea and 

S111a/'/. 1998: Feynman a11d Gabriel. 2000). 

To\\ard the other end of the temporal scale, geomagnetic 

variations with periods longer than a few decades, including 

the occasional reversal of the magnetic field, arc of internal 

origin, caused by nuid motion in the Earth's liquid iron 

outer core [Busse. 1983: Bloxham and Gubbins, 1989: Lo1·c. 

1999). It is well known that the compass docs not usually 

point toward true north. In fact. the deviat ion from north, 

or dee I ination. differs depending on the obsen er· s 

geographic location. Fu rthermore, O\er historical times, 

declination and the entire magnetic vec tor change 

noticcabl) with time. These complexities. "hi le 

scientificall y interesting. have long been a nuisance for 

navigators [Jackson et al., 1997) and helped to motivate 

some or the ori gina l research in geomagnetism. 

T HE GEO~IA GNETIC OBSERVATORY 

166 

The Barrow Geomagnetic Obscn·atory is the northernmost of 1-1 USGS digi tal magnetic obscn atorics. 

Established in 1949 by what was then the U.S. Coast and 

Geodetic Survey. responsibility for obscn atory operation 

"as passed on to NOAA in 1970 and then ultimately to the 

US GS in 1973. Its location puts it near the boundary of the 

auroral zone and polar cap. two distinctly different regions 

of the Earth's magnetic fie ld. As such it is an important site 

in the global nel\\ ork of geomagnetic observatories. \\ hich. 

in combination, allows for global monitoring o f 

geomagnetic field variations. Ground-based stati ons, such 

as the Barrow Geomagnet ic Obscn atory. sen e as controls 

for internal and external field modeling, as reference 

stations for satellite measurements made within or above 

the ionosphere. and as absolute calibration locations for 

field sun eys. 

O\er its lifetime Barro\\ Obsenator) (Figure 2) has been 

extensively upgraded, wi th new bu ildings. magnetometers. 

and data transmission equipment installed 10 meet modern 

demands for precision and timeliness [To1rnshend. 200 I). 

Build ing insulation and heaters provide a thermally stable 

environment for the magnetometers eYcn though the outside 

temperature can reach - 50°C. All buildings and exterior 

structures must be capable of handling "ind speeds in 

excess of 113 km (70 mi) per hour. 
Fig. 2. Top: TI1e variation building that houses the lluxgaie magnetometer. 

Bonom: TI1e main building that contains data collection electronics. 

Magneti c measurements at Barrow are made consistent 

with standards set by Intermagnet, an international 

consortium that oversees the operation of about 80 magnetic 

observatories throughout the world. Being a vector, the 

Earth's magnetic field has both direction and intensity; fi e ld 

components are defined in Figure 3. To measure the various 

parts of the magnetic vector, the observatory is equipped 

with a tri-axial nuxgate magnetometer and a tota l field 

proton magnetometer, both of whi ch are controlled by a 

digital data acquisition system. The fluxgate, shown in 

Figure 4, continuously records variat ions in the Earth's 

magnetic field, specifically, the horizontal field (H), the 

deviat ion from geographic north, or dec linat ion (0), and the 

vertical field component (Z). To account for a slow drift in 

calibration, the intensity (F) is m~a ured absolutely by the 

proton magnetometer, and direction is measured absolutely 

by hand with a declination-inclination magnetometer, 

consisting of a single-axis flu xga te magnetometer mounted 

to a theodolite (Figure 5). 

Piers within the site buildings (Figure 6) provide stable 

plat forms to make the vectorial magnetic measurements, but 

the active permafrost layer makes pier construction 

difficult . At most observatories large non-magnetic 

concrete piers are set straight into the ground. However, at 

167 

Down 

Geographical 

North 

I Magnetic 

Meridian 

East 

Fig. 3. The magnetic field components. The Cartesian components (X, 

Y. Z) define north. east. down; the spherical components (F, I, D) define 

intensity, inclination, declination; H is the horizontal component of 

intensity. 

Barrow a pier can shift because concrete acts as a heat 

cond uctor, warming the permafrost, and thereby causi ng a 

seasona l freezing and thawing. To avoid this, a hole is 

Fig. 4. A tri-axial flux gate sensor of the type used to measure magnetic 

field 'ariations at Barrow. 
ll 

Fig. 5. A declination-inclination magnetometer of the type used to 

measure the absolute magnetic field direction. 

drilled to a depth below the active permafrost layer, and a 

long wooden post is then frozen into place during the 

wintertime. The post is packed a'round with insulating 

Styrofoam. The top part of the post is encased in a concrete 

jacket, which uses Styrofoam pellets and vermiculite as the 

aggregate. This concrete is a thermal insulator but retains 

enough stre ngth to achi eve stability. The surface aro und the 

pier is covered with rigid foam insulation to insulate the 

ground from the building. 

1e'-0 ~1-1------' 

L~ 

CONCRETE 

ALUMN.H JACKET 

FIBERGLASS INSlAJ<TION BETWEEN 

PIER AND 4" PLATFORM TO BOTTOM 

OF SILL 

STYROFOAM PELLETS ENCASED IN 

A FIBERGLASS OR ~ JACKET 

INSIA.ATEO FLOOR JOISTS Y fr14• GRAVEL ON STYROFOAM AND 

~/ EXTENDS ~FROM PIER JACKET 

l" AIR SPACE 

. . . , ... 

4" STYROFOAM ON GROUND AND 

AROUND PIER JACKET TO BOTTOM 

OF FLOOR JOISTS AND EXTENDS 

4' FROM PIER JACl<ET 

' FROZEN MIXTURE OF GRAVEL. SAt«>, 

AND WATER 

12" l«lOO POST 

Fig. 6. The design of the absolute pier used at Barrow. 

MAGNETIC DATA: EXAMPLES AND USES 

Data from Barrow are transmitted via a combination of 

satellite a nd ground links to the USGS Geomagnetism 

Group, which is part of the Central Region Geologic 

Hazards Team headquartered in Golden, Colorado. Nearreal-time data from Barrow, together with similar data from 

the group's other observatories, are forwarded by the USGS 

to the NOAA Space Environment Center (SEC) and to the 

U.S. Air Force for use to forecast space-weather 

phenomena. Final processed data from Barrow, and the 

other 13 USGS observatories, are sent to NOAA to be 

archived, and they are a lso distributed on lntermagnet CDs. 

During magnetic storms, data recorded at Barrow display 

a high level of activity compared with data from 

observatories at lower latitudes. As an examp le, data 

recorded during the so-called "great" magnetic storm of 

March 1989 are shown in Figure 7. This storm induced 

currents in power grids, thereby causing system-wide power 

blackouts in Quebec, power equipment problems in the 

northeastern United States, radio communication blackouts, 

and increased satellite drag that actually altered the orbits 

of a number of satellites [Joselyn, 1989]. The sharp, sudden 

onset of magnetic field variation in the beginn ing of March 

13 is the result of a large mass ejected 2 days earlier from 

the surface of the Sun (Figure 7). 

The higher level of activity seen at Barrow is caused by 

magnetic fields sustained by the auroral electrojet (AE). As 

illustrated in Figure 1, with an enhancement of the solar 

wind caused by ejection of charged partic les from the Sun's 

surface and a coupling of the solar and geomagnetic fields, 

energy stored in the magnetosphere is released as an e lectric 

current. This current nows into the ionosphere near the 

geomagnetic poles and drives the auroral electrojet, a 

symptom of which are the bright auroras seen during 

magnetic storms. Barrow is one of 12 high-latitude 

magnetic observatories that provide magnetic data to 

compute the AE index, a simple measure of the auroral 

electrojet intensity [Parkinson , 1983; McPherro11, 1995]. 

Near-real-time and historical values of AE can be obtained 

from the World Data Center at Kyushu University, Japan. 

168 

Long-term averages of the magnetic data can be used to 

stud y the dynamic processes operating in the Earth's liquid 

iron outer core, which is the site of the dynamo that sustain s 

the main part of the geomagnetic field. With annual means 

of magnetic data it is possible to observe the slow drift in 

the field that results from nuid motion in the core. Figure 8 

shows the change in the declination, inclination, and 

intensity at Barrow since the observatory was opened in 

1949. Ultimatel y, the data from Barrow and other 

observatories are used to generate maps and models of the 

Earth's magnetic field , such as the International 

Geomagnetic Reference Field [Macmillan and Quinn, 

2000]. 

CONCLUSION 

The USGS Geomagnetism Group is working to upgrade the 

faci lities at Barrow so that measurements are made with 

better prec ision and finer temporal resolution. Data 

transmission capabilities are being upgraded so that the data 

can be distributed in real time with improved reliability. All 
AE Index March 1989 Magnetic Storm 4000 

3000 

';: 2000 

1000 

0 

Horizontal Component 

2000 

1000 Bam:ffl, AK 

Ic 0 

-1000 

-2000 

Horizontal Component 

2000 

1000 College, AK 

Ic 0 

- 1000 

- 2000 

Horizontal Component 

2000 

1000 Sitka, AK 

Ic 0 

-1000 

-2000 

Horizontal Component 

2000 

1000 NeWJX>rt, WA 

Ic 0 

- 1000 

-2000 

Honzontal Component 

2000 I I I I 

1000 Tucson, AZ -

Ic 0 -- - 1000 

- 2000 I I 

March 12 Mardl13 March 14 March15 Marcil 16 

Fig. 7. i\lcasurcmcnts made during the "great storm" o f\larch 1989. The top panel is the AE index. which measures auroral electroj et current: belm' 

are the horizontal magnetic fi elds as measured at li\C different USGS magnetic obsen atories. 

169 
(a) 

30 

28 

;;; 

SJ 26 

.,; 

Q) 

~ 

g> 24 0 

22 

20 

(b) 

82 

81 

</) 

Q) 

a, 80 Q) 

0 

79 

(c) 

57500 

57400 

57300 

i=" 

c 

i:L 

57200 

57100 

57000~~~~~~~~~~~~~~~~~~~--'-~~~ 

1940 1950 1960 1970 1980 1990 2000 2010 

Fig. 8. Field components at Barrow from 1949 to present: (a) declination 

angle. (b) inclination angle. and (c) intensity as measured in nanoTeslas 

(nT). Reduction in the scaner seen in the field intensity after 1962 

rellects an instrument upgrade. 

these efforts will enhance the scientific and societal rele,ance 

of the USGS Barrow Geomagnetic Obsen atory. 

Ack11owledg111e1111. \\'e thank '.'\OAA and. in particular. D. Endrc> 

for >upport operating the Barro\\ Geomagnetic Obsen atory. We 

thank the USGS Geomagnetism Group staff for their considerable 

efforts and the Central Regi on Geologic Hazards Team for their 

suppon. T. lyemori of the WDC-2 in K"oto. Japan. 1no,idcd the AE 

data. 

REFERE:\CES 

Blo:-.ham. J .. and D. Gubbins. The C\o)ution of the Earth"s 

magnetic lield. Sci. Am .. :!60. 68-75. 1989. 

Burch. J.L.. The fur y of space storms. Sci. Am . . :!8./. 86-9-l. 2001. 

Busse. F.H .. l\lagnetoh)drodynamics of the Earth" s core. A1111. Rei·. 

Eanh Planet. Sci .. 11. 2-1 1-268. 1983. 

Courti llot. \I .. and J.L. Lel\louel. Time Yariations of the Earth"s 

magnetic field: From daily to secular. A1111. Rei·. Earth Planet. 

Sci .. 16. 389--1 76. 1988. 

Co\\ ky. T.G .. The Earth ·s magnetosphere: A brief beginner's 

guide, Eos. Tra11.1. AGl.I. 76. 525-529. 1995. 

Dooling. D .. Stormy \\Cather in space. IEEE Spec1ru111. 3:!. 6-1-72. 

1995. 

Feynman. J .. and S.B. Gabriel. On space weather consequences 

and predictions. J. Geophys. Res .. 105. I 0.5-13-10.56-l. 2000. 

GonLales. \V.D .. J.A. Joselyn. Y. Kamide. H.\V. Kroehl. G. 

Rostokcr. B.T. Tsurutani. and V.M. Vas)li unas. \\'hat is a 

geomagnetic storm". J. Geophn. Re;.. 99. 5771-5792. 199-l. 

Jackson . A .. A.R.T. Jonkers. and A. l\lurray. Past anractions. 

As1ro11. Geophys .. 38. 10- 16. 1997. 

Joselyn. J .. Case stud) of the great geomagnetic storm of 13 I\ larch 

170 

1989. paper AAS 89--1 18 presented at AAS AIAA 

Astrod)namics Specialist Conf .. Sto\\e. VT. August 1989. 

Lo' c . J.J .. Reve rsals and excursions of the gcodynarno. As1ro11. 

Geophys .. ./0. 6.1-1-6.19. 1999. 

l\lacmi llan. S .. and J.M . Quinn. The 2000 re' ision o f the joint 

UK US geomagnetic licld models and an IG RF 2000 candidate 

model. Earth Planets Space. 52. 11 49- 1162. 2000. 

aynard. N.C.. Space weather prediction. Rei'. Geoplffs .. Part I 

Suppl. 33. 5-1 7-557. 1995. 

~lc herron. R. L.. l\lagnctospheric dynamics. in ll11rod11ctio11 10 

Space Ph.1·sics. edited by 1\1.G. Ki,elson and C.T. Russe ll. pp. 

-100--158. Cambridge Uni' ersity Press. Cambrid ge. UK. 1995 . 

Nordwa ll. 13.D .. Natural hazards threaten milsats. A1·ia1. Week 

Space Tech11ol .. 150. 59-60. 1999. 

Parkinson. W.D .. l111rod11c1io11 10 G£'0111ag11e1ism. -1 33 pp .. Scottish 

Academic Press. Edinburgh. 1983. 

Russell. C.T .. The mag netosphere. A1111. Rei·. Earth Pla11e1. Sci .. 

19. 169-182. 1991. 

Scott. \V. B .. Operators place h igh va lue on space weather 

forecast ing. A 1·ia1. Week Space Tec/1110/ .. 14 7. 5-1-55. 1997. 

Shea. M.A .. and D.F. Smart. Space \leather: The effects on 

operations in space. Adi-. Space Res .. 2:!. 19-38. 1998. 

To\\nshend. J.B .. Fifty years of monitoring. geophysical data at 

Barro\\ . Alaska . in Fifty .\lore !'ears Belo11· Zero. edited by 

D. \V. ~orton . pp. 61-6-l. Uni\. of Alaska. Fairbanks. 2001. 
UAF-Frontier Snowfall/Blowing Snow Observations at CMDL, Barrow: 

Preliminary Result for 2001 

D.-\QtNG YANG 

JJ'wer and E111·iro11111e111al Re1eorc/1 Ce111er. L"11il'ersin· of Alaska. Fairbo11k1· 997-5 

KONOSCKE SUGtl'RA 

Fro111ier Oh.1e1Tolio11al Research S_n1e111for Global Clio11ge. Tok_rn 105-0013. Japan 

TETSUO 011ATA 

/1111i1111e of /.011 Te111pero111re Science. Hokkaido L"11i1·ersi1y. Sapporo. Japan 

BACKGROU:\"D 

Systematic errors caused by 11 ind-induced undercatch. 

11 etting, and C\ aporation losses in precipitation measurement ha\e long been recognized as affect ing all types of 

prec1pilation gauges. The need lo correct these biases, 

especially for solid precipitation measurement. has nO\\ 

been more widely acknowledged. as the magnitude of the 

errors and their \ ariation among gauges ha\e become 

kno\1 n and their potential effects on regional. national. and 

global climatological. hydrological. and climate change 

studies haYe been recogniLed. 

To assess the national methods of measuring so lid 

precipitation. the World i\lctcorological Organization 

(\Vi\10) initiated the Solid Precipitation i\leasuremenl 

lntercomparison Project in 1985. Thirteen countries 

participated in this project. and the experiments \I ere 

conducted al 10 selected sites in these countries from 1986 

to 1993. Methods of bias correction ha\ e been de\ eloped 

for many national precipitation gauges commonl y used in 

the northern hemisphere [Yang er al., 1995. I 998a. 1999. 

1000: Goodiso11 er al .. 1998]. Test implementations of the 

\VMO correction procedures ha \'e been made 10 the 

archi\ eel precipitation data in some regions/countries 

(.\lelcal(e and Goodison. 1993: For/and el al .. 1996: Yang 

el al .. I 998b]. The bias corrections ha \'e increased the 

\\'inter and annual precipitation amounts by up lo 50-100°o 

in the high-latitude regions. Th ese results clearly show 1ha1 

precipitat ion amounts in these regions are much higher than 

pre\ iously reported. This points lo a need 10 rcvic11 our 

understanding of freshwater balance and the assessment of 

atmospheric model performance in th e Arctic regions. 

The Arctic cl imate is characteriLed b) 1011 temperature. 

generally IO\\ precipitation. and high winds. Arctic 

prec1p11ation C\ ents generall y produce small amounts. but 

the) occur frequently and often \l'ith blo1\ ing snow. 

Because or the special conditions in the Arctic. the 

S)Slematic errors of gauge-measured precipitati on and 

factors such as \\'ind-induced undcrcalch, ernporation. and 

\l'etting losses. underestimates caused b) not accounting for 

trace amounts of precipitation and O\ er under measurement 

because of blowing sno\\' arc enhanced and need special 

attention. This issue has been a consideration in World 

Climate Research Program (\VCRP) projects. For instance_ 

the \VCRP/Arctic Climate System Study (ACSYS) program 

concludes that correction of gauge prec1p1tation 

obscr\'ations is a major issue with respect 10 solid 

17 1 

precipitation in the polar regions and that this issue is 

particularl y rele\'ant to studies of the fresh\\'atcr cycle in the 

Arctic region being undertaken in ACS YS and Global 

Energy and \Valer Cycle Experiment (GE\VEX) projects. 

such as the GE\VEX Asian Monsoon E.xperimenl (GAME)-

S iberia [Yang and Ohata. 200 I] and the Mackenzie Basin 

GE\VEX Study (i\IAGS). 

The review of the \Vi\10 lntercomparison results by the 

\VCRP/ACSYS project concluded that although the results of 

the \VMO Solid Precipitation Measurement lntercomparison 

ha\e not been f"ully tested in Arctic conditions. the general 

principles and the results from the 'v\IMO project can serve as 

a guide for de1·cloping correction procedures for Arctic 

precipitation data. II is recommended that an intercomparison experiment be conducted to runher test the 

national precipitation gauges commonly used in Arctic 

regions and to C\ aluatc the existing bias correction 

procedures. 

Recognizing the importance of the precipitation data qualit) 

to cold-region hydrological and climatic i11\'cstigations. the 

Japan Frontier Research System fo r Global Change and the 

\Yater and Em ironmental Research Center (\VERC). 

University of Alaska_ Fairbanks (UAF), have collaborali \·ely 

undertaken a gauge intcrcomparison experiment and 

blowing/drifting sno\\' observation study al the Barrow. Alaska. 

CMDL research laboratory. The goals of this research are 10 

(I) revie\\' the existing bias-correction procedures that ha\ e 

been de\eloped in gauge intercomparison experiments and that 

may be suitable for high latitude regions: and (2) test and 

evaluate the applicability of the \Vi\ 10 bias-correction methods 

in polar regions of high 1\ inds 1\ ith blm\ ing/drifling snm1 

conditions. 

S ITE A:\D ) \'STRU;\IE'iTATIO:\ 

This study \\'as carried out at the CM DL Barro\\' site. In 

February and September 100 I. several precipitation gauges 

\\'ere installed for intcrcomparison. These include reference 

gauges and \'arious national standard gauges commonly used in 

the Arctic regions: 

• Double fence inlcrcomparison reference (DFIR) at 1.5 m: 

\Vl\10 reference (Figure I). 

• Wyoming sno\\' fence system at 1.5 m: U.S. reference 

gauge for sno\1·fall observations (Figure 1). 

• NOAA-ETI gauge at I m. 

• Hellmann gauge at 1 m; standard gauge for Greenland. 

Denmark, and Germany. 
Fig. I. WMO double fence imercomparison reference (DFIR). 

Fi.g. 2. U.S. Wyoming snow fence. 

172 
• Russian Tretyako,· gauge at 2 m: Russian standard gauge. 

also used in Mongolia and other countries. 

• U.S. National Weather Ser\'ice (N\VS) 8-in (20-cm) 

nonrecording gauge at 2 m: U.S. standard gauge, widely 

used in othe r countries. 

An au tomatic \\'Cather station for b lo\\'i n g drifting sno\\ 

obserrntions in \\'inter months \\'as set up to in \'est iga te 

b lowing snoll' mass nuxes as functions of \\'ind speed. air 

temperature . and h e ig ht, and to evalu a te their impact on 

ga uge sno" fal I obsen·a tions. 

DATA A:\A LYS IS A:\D PRELDll:\ARY RESULTS 

Da ta analysis fol lo\\'S the guidelines established in the 

\\IMO Solid Precipi tation Measurement lntercomparison 

Project. with a focus on defining mea n catch ratio o f gauges 

and the relation of gauge catch as a function o r ll'ind speed 

and a ir temperature. 

Up to December 2001. 31 precipitation events. i.e .. 3 rainfall 

cases and 28 sno\\'fall cases, ha ,.e been coll ected. The event 

total precipitation amounts measured range from trace (\\'hen 

the gauges registered Lero amount or precipitation) up to 40 

mm. These event data sometimes were the total accumulation 

of several precipitation e\'ents. because the gauges were 

emptied irregula rl y. The data also include a few cases or 

blowing-sno\\ C\ ents during high wind conditions. 

Prelim ina ry analysis of collected d ata sholl's that the 

mean catche s of the g auges re lative to the DFIR for 

s no \\'fall observa ti on s were ab out 90% for the Wyoming 

s no\\ fence, 59°·0 for the TretyakO\ gauge, 24% for th e U.S. 

8-in gauge. and 27% for the llcllmann gauge (Fi gure 3 ). 

These mean catches a re close to the results for si milar 

test in g environmen ts of the WMO gauge intercomparison 

ex peri ments. For instance. the catch ratios of the Wyoming 

fence to the D FI R were 89°0 and 87% at Regi na and Yaldai, 

respectiYely. The mean catch o f s nowfa ll for the U.S. 8-in 

gauge at Yaldai was 44% [l'a11g e l al .. I 998a]. For the 

Tretyakov and Hell mann gauges. the mean catch of s no\\'fall 

was reported to be 63-65% and 43-50%, respectiYely. at the 

northe rn test sites o f the \VMO experiment [Yang el al .. 1995. 

1999). 

FUTURE WORK 

Contin ued intercomparison data need to b e collected at 

Barro\\' in the n ext fc\\' winter seasons. A comprchcnsiYe 

dat a set w ill enable us to carry o ut (I) compatibl e analysis 

\\'it h the \\IMO in tercomparison d ata sets. (2) analysis of the 

catch ratio 'ersus wind s peed /tempe rature. and ( 3) 

assessment of th e applicability of the \\IMO methods and 

resul ts in the Arctic regions. In add ition , the impact of 

blowing/dri fli ng snow on gauge catch is anoth er issue that 

needs research attenti o n. We \\'ill de velop procedures to 

quantify the nux of b lo w in g snow into a snow gauge and 

evaluate the impact of blo\\ing.drifting snow to bi as 

correction or gauge-measured sno\\ fall data in the polar 

r egions. This work wi 11 also generate bias-corrected 

precipitatio n dat a sets and c limatology for Barrow and 

northern A las ka. including seasonal annual regiona l 

precipitation maps. 

17 3 

100 

90 

80 

70 

~ 

~ 60 .2 

~ ..... 50 .r; 

u 

.... 40 

u '° 

30 

20 

10 

0 I I ~ng gauge Russian gauge US 8" gauge Hellmann gauge 

fig. 3. :\!.:an catch ratio of fou r gauges \ersus the DFIR. Barro\\. 

.-lck11011-/edg111e11ts. This project "as fonded by the International 

,\retie Research Center and the Japan Frontier Obsen ational 

Research S)stem for Global Change. This is also a co-op project 

\\ ith Cl\1DL. \\'e appreciate the help and support from the Barro\\ 

Arctic Science Consortium (BASC) and th.: Cl\tDL staff (D. 

Endres and others) at Barro\\. 

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Yang. D.. and T. Ohata. A bias corrected Siberian regional 

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1995. 

Yang. D .. B.E. Goodison. C.S. Benson. and S. Ishida. Adjustment of 

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Yang. D .. B.E. Good ison. J.R. :\lctcalfc. V.S. Golubc\. R. I3atcs. T. 

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Yang. D .. E. Elomaa. T. Gunther. \/. Golube'. B.E. Goodison. B. 

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The ANSTO-CMDL Radon Program at MLO 

\V. L.\llORO\\SKI "ll s. Cll.\\llJLRS 

A1111r11/ia11 S11clcar Science and Tech110/ogy Orga111w11011. \frm11. \"SW :!:!3.J . .ltt<tralia 

P \l I FL KL\IL R \-S \\\\I>.\ 

\ 011 \/11111111 l.ua O/><e1Tator1 llilo. Hc111w1 96-:!() 

The abil il) to predict the impact or rapid de\t:lopmcnt 

in the Asian Pacilic region on climate is dependent upon 

an impro1 eel scientilic understanding or the radiati1c 

forcing of at:rosols and trace gases. as "ell as the 

e ffic ient implementation of these processes in regional 

and globa l climate models. Finding suitabh: tools to 

e1aluate the performance of transport. mi,ing. and 

chemical processes "ithin such models is challenging. 

The "ell-delincd sourcc and sink patlrn ays of radon-

'.!'.!'.! make it an ideal tracer of atmospheric d) namics. Its 

ori gin s are almost c:1.elusi1 ely terrestrial. and because it is 

a noble gas that docs not react chemicall) "ith other 

species. its predominant sink is by radioac1i1c decay. The 

half~li fe of radon (3.81 da} s) is comparable with the 

lifetimes of short-Iii eel atmospheric pollutants (e.g .. :'\O_. 

SO~. CO. and 0;) and residence times of "ater and 

aerosols. This time scale is also comparable "nh man) 

important aspech of atmospheric d) namics. making radon 

a useful tracer at local. regional. or global scales. This 

predictable bcha1 ior means measuremems of rado n 

concentration arc surlicienl to indicate 11 hethcr an air 

mass has been in contact 11 ith land in the past st:1 era I 

weeks. Consequent I}. the simulation of radon transport is 

currently one of the best e1·aluation tool ~ for 1rnn~por1 

schemes in regional and global circulation models. 

Subgrid i~ing processes also cause sign i ticant changes 

in radon conccmrations. Thus comparisons het\\ccn 

obserwd and modeled radon concentrations can be used 

to impro1·e local mi:-.ing schemes. Changes in radon 

concentration can be measured 11 ith high precision and 

temporal resolution at permanent stations and on board 

ships with au tomated dt::tectors. 

The last ckcadc "itnessed the first serious allempts to 

model radon concentrations on global and regional scales 

and to compare the modt:led results 11 ith obscn at ions. 

The purpose of radon simulations 1ancd: some \\ere 

aimed at the dc1clopment or 1alidation or subgrid mi,ing 

schemes and indication or regions associated "11h largest 

uncertainties [e.g .. Jacob and Prather. 1990: Stockwell et 

al .. 1998]. others at the intercomparison of models [e.g .. 

Ge111/1011 and :lr111e11ga11cl. 1995] or the comparison of 

di ffcrent meteorological input data sets [e.g .. \/altownld 

et al .. 1997]. In general. a belier understanding of the 

kc) atmospheri c fcawres that comrol transport. mi\ing. 

and distribution or radon has been sought b} detailed 

comparisons of modeled radon time series and 1 ertical 

profiles "ith th.: best radon data sets a1 ail able [e.g .. 

. \la/101rnld el al .. 1997: S1ock11·ell el al .. 1998: De111e11er 

el al., 1999]. De111e11er e1 al. [ 1999] contrasted the 

modeled data for f\I LO with those from other surface 

baseline stations including Cape Grim. Tasmania. and 

Kcrguclen. CrO/Cl. and Amsterdam Islands. all in the 

Indian Ocean . 

A first comprchcnsi\C c1aluation and intcrcomparison 

of global atmospheric transport models us111g radon time 

series was published in 199- [Jacob el al .. 1997]. The 

174 

intercomparison. sponsored h) the \\'oriel Climate 

Re search Program (\\'CR P ). e1 aluatcd and compared 

con1ccti1c and synoptic processes in '.!O models. Results 

11 ere compared with the: obscn eel mean radon 

concentrations. 

Con,c4uentl). at '.\I LO the focus remains on '''° uses for 

radon data: (I) as one of the .,c1cc11on criteria of baseline 

air samples. because it pro1 ides a quantitati1 e. continuous 

measure or the influence of the Asian continem on air 

samples at \I LO. and (2) as a trac.:r tn test the accuracy of 

global-scale atmospheric transport models. 

The present detection systt::m "as lirst launched in 

1994 and has been imprO\ ed in reccrn years. The 

fundamental characteristics or the instrumelllation arc 

included in S11111111m:1· Repon \'o. !J [Ho/111m111 et al .. 

J 996). ,\ thorough discussion or the principk of 

op.:ra11on of the radon detector can be found in 

Whi1111!11011e and Z11/10ro1nki [ 1998]. It is pertinent to 

note that the lower limit of detection for the radon 

detec tor cum:nll) deplo)ed at \ !LO ('.!0 mBq m '> 

matches the ltl\1 est radon concentration reported for 

oceanic air. 

The only instrument problem for this period ( 1989-

prc~cn ) i<; an apparent reduction 111 air sampling rate from 

late October '.!000 until April 200 I. E1 idcnce from other 

equipment indicates that this was simpl) due to a fault) 

tlo\\ meter. The problem \\as subsequently rectified b) 

instaJ Jat1on of a nC\\ 110\\ meter. 

\lost recentl) the MLO data recorded during the li rst 

Asian Pacific Regional Aerosol Characterintion 

Experimrnt (ACE-Asia) lmensi'c Operation Period (IOP) 

(J\pri I f\la) '.!00 I ) 11erc combined "ith corresponding 

time- scric~ data from obscn at ions at l\\O ACE-Asia 

surface stations: Kosan (Cheju Island. South Korea) and 

Hok Twi (I long Kong). The combined set is imendcd lO 

be tl',cd 111 a model 111tercompanson c\crcise of two global 

chemical transport models in support of the !OP. 

Data for the reported pt:riod ma} be obtained b) 

contacting \Vlodck ZahOrtl\\ ski (\\ lodek.zahoro\\ ski 

'a ansto.go1 .au). 

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Al3 L 

AC ATS 

ACCENT 

ACD 

ACE 

ACE-Asia 

A CSYS 

AE 

A ERON ET 

AES 

AGAGE 

AIR KIT 

AIRS 

ALE 

ALIAS 

ALT 

ANS TO 

!\OD 

AOivIL 

ARL 

ARM 

ARO 

ARO 

ASA 

ASL 

ATLAS 

ATMOS 

AVHRR 

BACPAC 

BAO 

BASC 

BC 

BIF 

BN D 

BR\V 

BSI 

BSRN 

CA DIC 

CAF 

CALTECH 

CART 

CAS 

CASA 

CATS 

CCGG 

CCN 

CCRL 

CD I AC 

CERES 

CFC 

CGO 

CI RES 

CLaMS 

CLI VAR 

CM DL 

CN 

CNC 

CRN 

8. Specialized Abbreviations and Acronyms 

atmospheric boundary layer 

Airborne Chromatograph for Atmospheric Trace Species 

Atmospheric Chemistry and Combustion Effects Near the Tropopause 

Atmospheric Chemistry Division (NCAR) 

Aerosol Characterization Experimelll 

Asian Pacific Regional Aerosol Characterization Experiment 

Arct ic Climate System Study 

aurora l electrojet 

Aerosol Robotics Network (NASA) 

Atmospheric En\'ironmcnt Sen ·ice (Canada) 

Ad\'anced Global Atmospheric Gases Experiment 

Air Kitzis sampler 

Atmospheric Infrared Sounder 

Atmospheric Litctime Experimelll 

Aircra ft Laser Infrared Absorption Spectrometer 

Alert, Canada. sampling site 

Australian Nuclear Science and Technology Organ ization 

aerosol optical depth 

Atlantic Oceanographic and Meteorological Laboratory (NOAA) 

Air Resources Laboratory (NOAA) 

Atmospheric Radiation Mcasuremelll (DOE) 

Arctic Research Ortice (NOAA) 

Atmospheric Research Observatory (South Pole. Antarctica) 

Antarcti c Support Associates 

above sea lc,·cl 

Airborne Tunable Laser Absorption Spectrometer 

Atmospheric Trace Molecule Spectroscopy 

Adrnnced Very High Resolution Radiometer 

Bromine Air-sea Cru ise Paci fi c 

Boulder Atmospheric Observatory 

Barrow Arctic Science Consortium 

black carbon 

Balloon lnnation Facility 

Bondville, Il linois 

Barrow Observatory. Barrow. Alaska (CMDL) 

Biospherical Instruments Inc., San Diego. Cali fornia 

Baseline Surface Radiation Network 

Centro Austral de ln\'estigaciones Cientilicas. Argentina 

Clean Air Facility (South Pole. Antarctica) 

California Institute of Technology 

Cloud and Radiation Testbed 

Clean Air Sector 

Carnegie-Ames-Stanford Approach 

Chromatograph for Atmospheric Trace Species 

Carbon Cycle Greenhouse Gases group (CMDL) 

cloud condensation nuclei 

Carbon Cycle Research Laboratory 

Carbon Dioxide Information Analysis Center 

Clouds and Earth's Radiant Energy System 

chloronuorocarbon 

Cape Grim Observatory. Tasmania. Australia 

Cooperati\'e Institute for Research in En\'ironmemal Sciences (Uni\'crsity of Colorado) 

Chemical Lagrangian Model of the Stratosphere 

Climate Variability and Predictability Programme 

Climate Monitoring and Diagnostics Laboratory (NOAA) 

condensation nuclei 

condensation nuclei counter 

Climate Reference Network (NOAA) 

180 
CSIRO 

CUCF 

DE\\' 

DFIR 

Dt\IS 

DNA 

DOE 

DOY 

DRUM 

DSRC 

DU 

DU 

EC 

ECC 

ECO 

ECI 

EOIWF 

EECI 

l:ESC 

H IL 

ENSO 

EOS 

EPA 

ETCI 

FID 

FSU 

FSU 

FT 

FTIR 

FTP 

FTS 

F\Vlll'\I 

F\\INI P 

GAGE 

GAME 

GA\\' 

GC 

GC 

GCM 

GC-1\IS 

GEOSECS 

GE\\IEX 

UFDL 

mice 

GPS 

llALOE 

llAO 

HATS 

llC 

llCFC 

HFC 

llP 

llPA 

llRDI 

llST 

llVO 

IAC 

IAEA 

IC 

ICP 

ICP 

IFP 

Common\\eahh Sciemilic and Industrial Research Organization (Australia) 

Central UV Calibration Facilit) 

Distant Early \\'aming 

double fence intercomparison reference 

dimethyl sulfide 

deoxyribonucleic acid 

U.S. Depanment of Energy 

day of year 

Da\'is Rotating-drum Unit for l'\ lonitoring 

Da\'id Skaggs Research Center (Boulder. Colorado) 

Dobson unit 

Unhersity of Denver 

elemental carbon 

electrochemical concentration cell 

electron capture detector 

equi\ alent chlorine 

European Centre for l'\lcdium-Range \\leather Forecasts 

effecti\'e equivalent chlorine 

effecti,·e equivalent stratospheric chlorine 

Em ironmemal l'\leasurements Laboratory (DOE) 

El Ni1lo Southern Oscillation 

Eanh Obsen ing Sysiem 

Em ironmental Protection Agency 

equi\'alent tropospheric chlorine 

flame ionization detector 

Florida State Unh ersity 

Fonner So\'iet Union 

free troposphere 

Fourier transform infrared (spectrometer) 

File Transfer Protocol 

Fourier transform spectrometer 

full width at half maximum 

filter wheel no1111a l incidence py rheliometer 

Global Atmospheric Gases Experiment 

GE\\IEX Asian t\lonsoon Experiment 

Global Atmospheric \Vatch 

gas chromatograph 

graphitic carbon 

global circulation model 

gas chromatograph-mass spectrometer 

Geochemical Ocean Sections 

Global Energy and \\later Cycle Experiment 

Geophysical Fluid Dynamics Laboratory (NOAA) 

Geophysical Monitoring for Climatic Change (no11 CMDL) (NOAA) 

Global Positioning System 

1 lalogen Occultation Experiment 

High Ahitude Observatory 

I lalocarbons and other Atmospheric Trace Species group (CM DL) 

hydrocarbon 

hydrochlorofluorocarbon 

hydrofluorocarbon 

1 lewlett-Packard 

Hawaii Preparatory Academy 

High Resolution Doppler lmagcr 

Hawaii Standard Time 

I lawaii Volcano Obsenatory 

Institute of Atmospheric Chemistry (China) 

International Atomic Energy Agency 

ion chromatograph 

inductively coupled plasma 

intercomparison 

lntensi1·e Field Phase 

18 1 
IFT 

IMF 

INDOEX 

INSTAAR 

IPASRC-1 

IPC 

IPCC 

IR 

!SCAT 

ITCZ 

ITN 

JMA 

JOSIE 

JPL 

KCO 

KUM 

LACE 

LAN 

LOI TOFMS 

LEAPS 

MAGI CC 

MAKS 

MATCH 

MBL 

MFRSR 

MHD 

MLN 

MLO 

MOP ITI 

MRD 

MRI 

MRI 

MSC 

MSD 

NARL 

I ASA 

NAT 

NAVSWC 

NCAR 

NCDC 

NCEP 

I DIR 

NDSC 

ERL 

NH 

NILU 

NIP 

IST 

NIWA 

NOAA 

NODC 

NPC 

NRC 

NREL 

NRL 

NSF 

NSFA 

NSRB 

WR 

NWS 

OAR 

oc 

Institute for Tropospheric Research 

interplanetary magnetic field 

Indian Ocean Experiment 

Institute for Arctic and Alpine Research (University of Colorado) 

International Pyrgeometer and Absolute Sky-scanning Radiometer Comparison 

International Pyrheliomctcr Comparison 

Intergovernmental Panel on Climate Change 

infrared 

Investigation of Sulfur Chemistry in the Antarctic Troposphere 

lntertropical Convergence Zone 

Grifton, North Carolina, sampling site 

Japan Meteorological Agency 

Jiilich Ozonesonde lntercomparison Experiment 

Jet Propulsion Laboratory 

Kaashidhoo Climate Observatory 

Cape Kumukahi, Hawaii, sampling site 

Lightweight Airborne Chromatograph Experiment 

Local Area Network 

Laser Desorption Ionization Time-of-Flight Mass Spectrometer 

Low Electron Attachment Potential Species 

Measurements of Atmospheric Gases Influencing Climate Change 

Martin and Kitzis Sampler 

Model of Atmospheric Transport and Chemistry 

marine boundary layer 

multi-filter rotating shadowband radiometer 

Mace Head, Ireland, sampling site 

Mauna Loa New 

Mauna Loa Observatory, Hawai i (CM DL) 

Measurement of Pol lution in the Troposphere 

mercuric oxide reduction detector 

Meteorological Research Institute, Japan 

Meteorology Research, Inc. 

Meteorological Service of Canada 

mass selective detector 

Naval Arctic Research Laboratory 

National Aeronautics and Space Administration 

nitric acid trihydrate 

Naval Surface Weapons Center 

National Center for Atmospheric Research 

National Climatic Data Center 

National Centers for Environmental Prediction (NOAA) 

non-dispersive infrared analyzer 

Network for the Detection of Stratospheric Change 

National Exposure Research Laboratory 

northern hemisphere 

Norwegian Institute for Air Research 

normal incidence pyrhcl iometer 

National Institute of Standards and Technology (U.S. Dept. of Commerce) 

National Institute of Water and Atmospheric Research (Ne\\' Zealand) 

National Oceanic and Atmospheric Administration (U.S. Dept. of Commerce) 

National Oceanographic Data Center 

NREL Pyrheliometer Comparison 

National Research Council 

National Renewable Energy Laboratory 

Naval Research Laboratory 

National Science Foundation 

Naval Support Force Antarctica 

net surface radiation budget 

Niwot Ridge. Colorado. sampling site 

National Weather Service (NOAA) 

Oceanic and Atmospheric Research (NOAA) 

organic carbon 

182 
OD 

OMS 

OPP 

OTTO 

PAN 

PANTllER 

PAR 

PBL 

PEM Tropics 

PFC 

PFR 

PMEL 

PMOD 

POES 

POLARIS 

POP 

ppb 

ppt 

PSA 

PSAP 

PSC 

PSP 

PV 

QBO 

RAF 

RCF 

R!TS 

RPS 

SAFARI 

SAGE 

SASP 

SBUV 

SC 

SCAR 

SD 

SEAR EX 

SEASPAN 

SEC 

SGP 

SH 

SHA DOZ 

SHEBA 

SIL 

S!O 

SMO 

SOLVE 

SOWER 

SPO 

SRF 

SRM 

SRRB 

SST 

STAR 

STEP 

SUNY 

S-XRF 

SZA 

TCT 

TDF 

TEI 

TEO 

TEXAQS 

outside diameter 

Observations of the Middle Stratosphere 

Office of Polar Programs ( SF) 

automated flask GC-ECD instrnment (not an acronym) 

peroxyacetyl nitrate 

PAN and other Trace Hydrohalocarbons Experiment 

photosynthetically acti\'e radiation 

planetary boundary layer 

Pacific Exploratory Mission in the Tropics 

per fluorocarbon 

precision filter radiometer 

Pacific Marine Environment Laboratory (NOAA) 

Physikalisch-Meteorologisches Observatorium Davos (World Radiation Center) 

Polar Operational Environmental Satellite 

Photochemistry of Ozone Loss in the Arctic Region in Summer 

persistent organic pollutant 

parts per bi II ion 

parts per trillion 

Palmer Station, Antarctica. sampling site 

particle soot absorption photometer 

polar stratospheric cloud 

precision spectral pyranometer 

photovoltaic 

quasi-biennial oscillation 

radiative amplification factor 

Radiometer Calibration Facility 

Radiatively Important Trace Species 

Raytheon Polar Services 

Southern A!Tican Fire-Atmosphere Research Initiative 

Stratospheric Aerosol and Gas Experiment 

Surface Air Sampling Program 

solar backscatter ultraviolet 

sky cover 

Scientific Committee in Antarctic Research 

standard deviation 

Sea-Air Exchange Experiment 

SEAR.EX South Pacific Aerosol Network 

Space Environment Center (NOAA) 

Southern Great Plains (Lamont, Oklahoma) 

southern hemisphere 

Southern Hemisphere Additional Ozonesondes 

Study of the Heat Budget in the Arctic 

Stable Isotope Laboratory (INST AAR) 

Scripps Institution of Oceanography (University of California. San Diego) 

Samoa Observatory, American Samoa (CM DL) 

SAGE 111 Ozone Loss and Validation Experiment 

Soundings of Ozone and Water in the Equatorial Region 

South Pole ObserYatory. Antarctica (CM DL) 

Solar Radiation Facility (CM DL) 

Standard Reference Material 

Surface Radiation Research Branch (NOAA) 

sea surface temperature 

Solar and Thermal Atmospheric Radiation group (Ci\IDL) 

Solar-Terrestria l Energy Program 

State Uni,·ersity of New York 

synchrotron-x-ray fluorescence 

solar zenith angle 

thermal deposition cold trap 

Ushuaia Observatory (near Tierra del Fuego. Argentina), sampling site 

Thermo Environmemal Instruments 

Territorial Energy Office 

Texas Air Quality Study 

183 
THD 

THESEO 

TMJ 

TOil.IS 

T011.IS 1F 

TOR 

TRACE-P 

TROIC\ 

TSI 

UAF 

UCI 

UCSD 

UIC 

UNEP 

UPS 

USAP 

USDA 

USGS 

UTC 

UV 

UVB 

voe 

VOGNET 

WAS 

WCRP 

\VEPC 

WERC 

WMO 

WOCE 

\VOUDC 

\\/RC 

\VRR 

\VSA 

\VSG 

\\/VMS 

YES 

Trinidad I lead. California. sampling site 

Third European Stratospheric E:-.pcrim.:nt on 0Lonc 

Tracer :VI ode I J 

Total 0Lone !\lapping Sp.:ctrometer 

Total 0Lonc l\lcasurements by Satellites. Sondes. and Spectrophotometers at Fairbanks 

thermal optical rellectancc 

Transport and Chemical Ernlution 0\ er the Pacific 

Trans-Siberian Obscn at ions Into the Chemistry of the 1\tmosphere 

Thermo Systems Incorporated 

Uni\crsity of Alaska. Fairbanks 

Uni\ ersity of California. In ine 

Uni,ersity of California. San Diego 

Ukpeag\ ik lnupiat Corporation (Alaska) 

United Nations Ell\ ironmcntal Programme 

uninterruptible po\\'er suppl} 

U.S. Antarctic Program 

United States Department of Agriculture 

United States Geological Sun·ey 

Uni\ ersal Time Coordinated 

ultra' iolet 

ultra\ iolct B band 

volatile organic compound 

Volcano Gas obscnatory Network 

Whole Air Sampler 

World Climate Research Program 

\\'ater equi,·alent precipitation 

Water and En\'ironmental Research Center 

World Meteorological Organization. Gcnern. s,1 itzerland 

World Ocean Circulation Experiment 

World O?One and Ultra\'iolet Data Centre (Canada) 

World Radiometric Cemer 

World Radiation Relerence 

Sable Island. Canada 

World Standard Group 

Water Vapor Millimeter-wave Spectrometer 

Yankee Environmental Systems 

18-1