NASA/TM-1999-209486

SIMBIOS Project 1999 Annual Report

Charles R. McClain, Goddard Space Flight Center, Greenbelt, Maryland

Giulietta S. Fargion, SAIC General Sciences Corporation, Beltsville, Maryland

National Aeronautics and

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771
SIMBIOS Project Annual Report

ii

Preface

The purpose of this technical report is to provide current documentation of the the Sensor Intercomparison and Merger

for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, NASA Research Announcement

(NRA) research status, satellite data processing, data product validation, and field calibration. This documentation is

necessary to ensure that critical information is related to the scientific community and NASA management. This critical

information includes the technical difficulties and challenges of combining ocean color data from an array of

independent satellite systems to form consistent and accurate global bio-optical time series products. This technical

report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the

multitude of technical reports issued by an operational project.

The SIMBIOS Science Team Principal Investigators (PIs) original contributions to this report are in chapters four and

above. The purpose of these contributions is to describe the current research status of the SIMBIOS-NRA-96 funded

research. The contributions are published as submitted, with the exception of minor edits to correct obvious

grammatical or clerical errors.
SIMBIOS Project Annual Report

iii

Table of Contents

1. AN OVERVIEW OF SIMBIOS PROJECT ACTIVITIES AND ACCOMPLISHMENTS DURING FY99.................1

2. SIMBIOS: NRA CONTRACTS ......................................................................................................................................7

3. SIMBIOS PROJECT DATA PROCESSING AND ANALYSIS RESULTS ................................................................12

4. VALIDATION OF SURFACE BIO-OPTICAL PROPERTIES IN THE GULF OF MAINE AS A MEANS FOR

IMPROVING SATELLITE PRIMARY PRODUCTION ESTIMATES.......................................................................30

5. OCTS AND SEAWIFS BIO-OPTICAL ALGORITHM AND PRODUCT VALIDATION AND

INTERCOMPARISON IN U.S. COASTAL WATERS ................................................................................................36

6. VALIDATION OF OCEAN COLOR SATELLITE DATA PRODUCTS IN UNDER SAMPLED MARINE AREAS

............................................................................................................................................41

7. STRAY LIGHT AND ATMOSPHERIC ADJACENCY EFFECTS FOR LARGE-FOV, OCEAN

VIEWING SPACE SENSORS.......................................................................................................................................45

8. BIO-OPTICAL MEASUREMENTS AT OCEAN BOUNDARIES IN SUPPORT OF SIMBIOS...............................50

9. REMOTE SENSING OF OCEAN COLOR IN THE ARCTIC: ALGORITHM DEVELOPMENT

AND COMPARATIVE VALIDATION........................................................................................................................55

10. HIGH FREQUENCY, LONG TIME SERIES MEASUREMENTS FROM THE BERMUDA TESTBED

MOORING IN SUPPORT OF SIMBIOS......................................................................................................................58

11. SATELLITE OCEAN COLOR VALIDATION USING MERCHANT SHIPS............................................................65

12. HIGH ALTITUDE MEASUREMENTS OF RADIANCE AT HIGH SPECTRAL AND SPATIAL RESOLUTION

FOR SIMBIOS SENSOR CALIBRATION,VALIDATION, AND INTERCOMPARISONS......................................70

13. MERGING OCEAN COLOR DATA FROM MULTIPLE MISSIONS........................................................................74

14. VALIDATION OF BIO-OPTICAL PROPERTIES IN COASTAL WATERS: A JOINT NASA-NAVY PROJECT .78

15. BIO-OPTICAL MEASUREMENT AND MODELING OF THE CALIFORNIA CURRENT AND POLAR

OCEANS........................................................................................................................................................................80

16. SIMBIOS NORMALIZED WATER-LEAVING RADIANCE CALIBRATION AND VALIDATION: SENSOR

RESPONSE, ATMOSPHERIC CORRECTIONS, STRAY LIGHT AND SUN GLINT..............................................85

17. VALIDATION OF CARBON FLUX AND RELATED PRODUCTS FOR SIMBIOS: THE CARIACO

CONTINENTAL MARGIN TIME SERIES AND THE ORINOCO RIVER PLUME.................................................88

18. THE BERMUDA BIO-OPTICS PROGRAM (BBOP)..................................................................................................93

19. SPECTRAL DATA ASSIMILATION FOR MERGING SATELLITE OCEAN COLOR IMAGERY........................99

20. SIMBIOS DATA PRODUCT AND ALGORITHM VALIDATION WITH EMPHASIS ON THE

BIOGEOCHEMICAL AND INHERENT OPTICAL PROPERTIES .........................................................................101
SIMBIOS Project Annual Report

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21. ATMOSPHERIC CORRECTION ALGORITHMS FOR OCEAN COLOR REMOTE SENSING ...........................105

22. VALIDATION OF THE SEAWIFS ATMOSPHERIC CORRECTION SCHEME USING MEASUREMENTS OF

AEROSOL OPTICAL PROPERTIES .........................................................................................................................110

23. MEASUREMENTS OF AEROSOL, OCEAN AND SKY PROPERTIES AT THE HOT SITE IN THE CENTRAL

PACIFIC. .....................................................................................................................................................................115

24. ASSESSMENT OF THE CONTRIBUTION OF THE ATMOSPHERE TO UNCERTAINTIES IN NORMALIZED

WATER-LEAVING RADIANCE: A COMBINED MODELING AND DATA ANALYSIS APPROACH. ............118

25. VALIDATION OF THE WATER-LEAVING RADIANCE DATA PRODUCT .......................................................121

26. INTENSIVE AND EXTENSIVE FIELD PROGRAMS FROR DATA PRODUCT VALIDATION OF 

OCTS/ADEOS AND GLI/ADEOS II............................................................................................127

GLOSSARY.................................................................................................................................131
SIMBIOS Project Annual Report

1

Chapter 1

An Overview of SIMBIOS Project Activities and

Accomplishments During FY99

Charles R. McClain

NASA Goddard Space Flight Center, Greenbelt, Maryland

The purpose of this annual report is to review and

document the activities and accomplishments of the Sensor

Intercomparison and Merger for Biological and

Interdisciplinary Oceanic Studies (SIMBIOS) Program

including those of the Project Office at the National

Aeronautics and Space Administration (NASA) Goddard

Space Flight Center (GSFC) and the SIMBIOS Science Team.

The accomplishments of the Project’s first year are

documented in McClain and Fargion (1999), and this report

provides an annual update. In the past year, the Project Office

completed many tasks and established stronger working

relationships with a number of international projects and

investigators. This chapter will review the SIMBIOS Project

Office activities and the second chapter will summarize the

accomplishments and status of the SIMBIOS Science Team.

In 1999, the ROCSAT Ocean Color Imager (OCI)

Taiwan, the IRS/P-4 Ocean Color Monitor (OCM) India, and

the KOMPSAT Ocean Scanning Multispectral Imager (OSMI)

from South Korea were launched. The SIMBIOS Project will

assist these projects as opportunities for collaboration develop

either through direct communication or through the

International Ocean Color Coordinating Group (IOCCG). The

Project Office is also prepared to assist the Moderate

Resolution Imaging Spectroradiometer (MODIS) Oceans

Team in its validation efforts once the Terra platform is

launched. The Project was recently selected by Japan’s

National Space Development Agency (NASDA) to be a

member of the Advanced Earth Observing Satellite-II

(ADEOS-II) Global Line Imager (GLI) Calibration and

Validation Team and by the Centre National d’Etudes

Spatiales (CNES) for ADEOS-II Polarization Detecting

Environmental Radiometer (POLDER) Team membership.

ADEOS-II is scheduled for launch in November 2000.

SIMBIOS Project Office Status

The SIMBIOS Project Office is co-located with the Seaviewing Wide Field-of-view Sensor (SeaWiFS) Project and

shares the same management infrastructure. In FY99, the

Project Office completed its staffing program, i.e., all

positions were filled to a level commensurate with the

Project’s budget. Many positions are shared or co-funded by

SeaWiFS because the nature of some tasks are common to

both projects, yet do not require a full time person for each,

e.g., the educational outreach and science support coordinator.

Figure 1 and Table 1 illustrates the present project

organization and staffing plan. The data processing systems,

as originally scoped, have been procured and are operational.

These systems are incrementally upgraded to ensure the

greatest computational capability and efficiency possible

within the Project’s budget.

 In order to better communicate with the ocean color

community, the Project greatly expanded its web site

(http://simbios.gsfc.nasa.gov) to include, among other things,

monthly reports of the Science Team investigators. The

SIMBIOS web site is organized to serve as the main

information resource to access the Project activities, Project

Office and Science Team. The web site is organized under five

main topics: News and Information, Support Services and

Schedule, Project Status, Instrument Pool, and Contacts. All

sections are updated as needed. The Project Office, in an effort

to educate and promote the concept of an organized program

of sensor cross-calibration and validation, send representatives

to several international conferences (Table 3). In several

cases, the SeaWiFS-SIMBIOS booth was manned as well.

SIMBIOS Science Team Administration

The Project Office drafted the SIMBIOS NASA Research

Announcement (NRA) which went through three iterations

with NASA Headquaters (HQ), the final being submitted in

August. The NRA had an expected release date of November

from NASA HQ. NASA HQ manages the process of team

selection, but the SIMBIOS Project Office handles the team

contracts and final budget negotiations. The Science Team

meeting was held in Annapolis, Maryland on September 13-

15, 1999. Nearly all Science Team members were in

attendance or were represented by one of their staff (in only

one case was a team member not able to attend). Also, the

IOCCG was invited, and most attended or sent representatives.

The Project provided travel support for most of the IOCCG

participants. Finally, the Project held formal reviews of each

Science Team investigation. For those under contract, the

reviews were provided to the GSFC Procurement Office under

a new regulation to conduct annual evaluations for the record.
SIMBIOS Project Annual Report

2

All contracts, with the exception of one, were renewed for the

third (and final) year.

SIMBIOS Calibration Round-Robin

The main parts of the round-robin over the past year have

been (1) the completion of the SeaWiFS Transfer RadiometerII (SXR-II) including operating and data logging software, and

(2) evaluation of the Airborne Visible and Infrared Imaging

Spectrometer (AVIRIS) laboratory calibration using the SXRII. High altitude AVIRIS underflights of SeaWiFS can

provide top-of-the-atmosphere radiances for direct comparison

with SeaWiFS, especially for the 765 and 865 nm bands where

vicarious calibrations using the Marine Optical Buoy (MOBY)

are not possible. However, the AVIRIS calibrations must be

accurate at the ± 2% level to be useful. An initial calibration

experiment at the Jet Propulsion Laboratory was conducted,

but problems with the SXR-II were identified after the

experiment which rendered the evaluation suspect. A second

experiment is being scheduled for early 2000.

Another activity related to the calibration round-robin is

the commercialization of the SeaWiFS Quality Monitor

(SQM; Johnson et al. 1998). Early in the SIMBIOS program,

seed funds were provided to Satlantic, Inc. and Yankee

Environmental Systems, Inc. to develop commercial versions

of the SQM. Both companies have done so and, during 1999,

the SIMBIOS Project provided a detailed evaluation of the

Yankee Environmental prototype.

Ocean Color Satellite Data Processing

During FY99, the Project conducted extensive studies of

the calibrations and derived products from the Ocean Color

and Temperature Scanner (OCTS) the POLDER instrument,

and the Modular Optoelectronic Scanner (MOS). The work

with the OCTS and MOS were completed and the evaluations

of POLDER are ongoing. In all cases, the work was in

collaboration with instrument team members associated with

the respective missions. More specifically, the work on OCTS

included the following:

• Evaluation of the postlaunch postlaunch calibration of the

visible bands was completed using coincident waterleaving radiance data from the MOBY (D. Clark, PI).

• Comparisons of SIMBIOS Project derived level-2

products, level-2 products from NASDA, and in situ

observations were completed and posted on the SIMBIOS

web site.

• Completion of level-0 and -2 processing of all OCTS data

collected at the Wallops Flight Facility (WFF). The data

were processed using code developed within the

SIMBIOS Project Office which was made available to the

ocean color user community via the SeaWiFS Data

Analysis System (SeaDAS). The data products can be

displayed using a browser and were left online for the

user community to download for nearly eight months.

Work with MOS included the following:

• Completion of an evaluation of the MOS on-orbit

calibration and level-2 processing code (Wang and Franz,

1999). A MOS processing module has been incorporated

into SeaDAS.

• Purchase and installation of a ground station subsystem

for MOS at WFF. The subsystem was purchased from an

Indian firm, Antrix, Corporation Ltd., which delivered,

installed, and tested the subsystem hardware and

software.

• Commencement of routine MOS data reception and

archiving at the SIMBIOS Project. All MOS data

collected at WFF can be browsed and ordered from the

SIMBIOS Project.

Work with POLDER consists of both satellite data

analysis and evaluation of in situ data from SIMBAD.

SIMBAD is an instrument designed to collect above-water

reflectance data and is the primary field instrument used by

the POLDER science team for validation. POLDER activities

include the following:

• Evaluations of the Rayleigh radiance tables used for

operational POLDER processing and the POLDER

science team’s methods for vicarious calibration.

• Comparison of level-2 products generated by the

SIMBIOS Project and by CNES with in situ data. As

with OCTS, MOBY was used for vicarious calibration of

the visible bands.

• Purchase of two different SIMBAD instruments (8 and 11

band models) and field data collection (8 band

instrument) for comparison with in-water measurements

of reflectance.

Support for Field Operations

During the first two years of SeaWiFS operations, the

SIMBIOS Project provided support for 125 cruises. Support

can include orbit analyses for cruise track planning, as well as

real-time image data sent directly to the vessel.

 During 1999, the SIMBIOS Project also initiated an

effort to participate on at least one field deployment with each

SIMBIOS Science Team member during the three-year period

of performance. In FY99, members of the SIMBIOS staff

participated in six field experiments with different PIs. The

Project also continued coordination of the instrument pool and

initiated upgrades of the micropulse lidar and one of the
SIMBIOS Project Annual Report

3

PREDE sun photometers. The PREDE upgrade consisted of

the addition of a stabilizer for deployment on ships. The

Project has a second PREDE is integrated with a stabilizer

which was deployed during the Indian Ocean Experiment

(INDOEX) on the RV Thompson.

 Aerosol Robotic Network (AERONET)

In FY99, the re-engineering of the original 12 CIMEL sun

photometers purchased by the Project was completed. The reengineering included a number of modifications to “harden”

the instruments for deployments in marine environments.

SIMBIOS sun photometers were installed at coastal sites in

Lanai (Hawaii), Bahrain, South Korea, Ascension Island,

WFF, Tahiti, and Turkey (Black Sea). Negotiations for

installations in the Azores and Australia are near completion.

Finally, equipment developed at the University of Lille

(France) for the calibration of polarized channels in the sun

photometers was purchased and installed at the GSFC

calibration laboratory used by the AERONET group.

Plans for FY2000

Several specific tasks and activities have been identified for

the coming year.

• POLDER evaluations: The work described above will be

completed.

• SeaWiFS evaluations: Participation in the ongoing

improvements to the SeaWiFS calibration and data

processing algorithms will continue. The SeaWiFS

Project anticipates complete reprocessings on an annual

basis so as to incorporate the latest algorithm and product

revisions.

• NRA recompetition and contract negotiations: Once the

NRA is released, members of the Project will be involved

in the proposal evaluations, selection panel, and contract

negotiations.

• Chlorophyll-a Round-robin: This activity has been

designed to evaluate the differences in fluorometric and

high performance liquid chromatography (HPLC)

pigment analyses between several U.S. laboratories

presently providing data to the Project.

• AVIRIS evaluation: The calibration experiment described

above will be completed.

• SeaWiFS Bio-optical Archive and Storage System

(SeaBASS) redesign: A complete redesign of SeaBASS

will be undertaken to make the data in the database more

accessible and to increase its flexibility.

• SeaWiFS Bio-optical Algorithm Mini-workshop:

(SeaBAM) data set reconstruction. A second SeaBAM

activity will be initiated to update the original SeaBAM

data set and the algorithm evaluations (O’Reilly et al.

1998).

• New mission support: The Project will work with the

OCI, OCM, OSMI, and MODIS programs to provide

validation data and whatever assistance possible.

Preparations for evaluating GLI products will begin.

• Data merger: In order to prepare for the eventual merger

of different ocean color data sets, the Project will consider

the OCTS-POLDER and SeaWiFS-MODIS combinations

for merger algorithm evaluation purposes.

REFERENCES

Johnson, B. C., P-S. Shaw, S. B. Hooker, and D. Lynch, 1998:

Radiometric and engineering performance of the

SeaWiFS Quality Monitor (SQM): a portable light source

for field radiometers, J. Atmos. Oceanic Technol., 15,

1,008-1,022.

McClain, C.R,. and G.S. Fargion, 1999: SIMBIOS Project

1998 Annual Report, NASA Tech. Memo. 1999-208645,

NASA Goddard Space Flight Center, Greenbelt,

Maryland, 105 pp.

O’Reilly, J. E., S. Maritorena, B. G. Mitchell, D. A. Siegel, K.

L. Carder, S. A. Garver, M. Kahru, and C. McClain,

1998: Ocean color chlorophyll algorithms for SeaWiFS,

J. Geophys. Res., 103(C11), 24,937-24,953.

Wang, M., and B. Franz, 1999: Comparing the ocean color

measurements between MOS and SeaWiFS: A vicarious

intercalibration approach for MOS, IEEE Trans. Geosci.

Remote Sens., (accepted).
SIMBIOS Project Annual Report

4

* The SIMBIOS Project is co-located with the SeaWiFS Project and many of the SIMBIOS Staff are shared.

G. Fargion

Assistant Project Manager

F. Patt*

Contract Staff Supervisor

M. HeO. KopelevichG. KorotaevH. LiS. Saitoh 

F. ChavezB. ChenG. CotaT. DickeyP. Flateau

R. FrouinR. GreenW. GreggM. MillerR. Miller

US SIMBIOS PI’s

A. SubramaniamK. StamnesR. Zaneveld

International SIMBIOS PIs

W. BalchJ. BrockC. BrownD. CaponeK. Carder

G. MitchellJ. MuellerF. Muller-KargerJ. PorterD. Siegel

SIMBIOS Science Team NRA-96

G. Feldman

Satellite Data Processing

Satellite Data ProcessingSatellite Data AnalysisData Set ManagementI. Durham*B. Franz*J. GalesProcessing System SupportS. Lee *L. Smith *P. Smith *B. Woodford *

C. McClain*

Data Product Validation

Merged Data Set AssemblyAlgorithm DevelopmentAlgorithm ValidationA. IsaacmanM. WangSeaBASS InterfaceJ. Werdell*Cruise ScheduleSatellite Overflight SupportS. Bailey *Match-up Data AnalysisS. Bailey *J. Werdell 

T. Riley

Sensor Engineering 

& Calibration 

SIRREX ProgramAERONET InterfaceT. RileyC. PietrasSatellite Sensor Characterization andData CalibrationR. Barnes*Field Instrument PoolS. Bailey*

Procurement SupportP. Clow *L. Hoppel*C. Tiger*Technical SupportI. Antonenko*System SupportAdministration SupportResources SupportI. Robinson *J. Stubblefield*T. Tucker*SIMBIOS ScienceTeam SupportG. Fargion

SIMBIOS Project Office

C. McClain*

Project Scientist & Manager

..

Figure 1. SIMBIOS Project organization chart
SIMBIOS Project Annual Report

5

Table 2. SIMBIOS Project

SIMBIOS Project Address

NASA/Goddard Space Flight Center (GSFC)

SIMBIOS Project

Code 970.2, Building 28

Greenbelt, MD 20771

Telephone: (301) 286-6800

FAX: (301) 286-0268

E-mail: project@simbios.gsfc.nasa.gov

SIMBIOS Project Personnel

Irene Antonenko*

Sean Bailey*

Robert Barnes *

Patty Clow *

Giulietta Fargion

Gene Feldman *

Ian Durham *

Bryan Franz *

Joel Gales

Lynne Hoppel *

Alice Isaacman

Sung Lee *

Charles McClain *

Fred Patt *

Christophe Pietras

Tom Riley *

India Robinson *

Linwood Smith *

Paul Smith *

Judy Stubblefield*

Camille Tiger *

Tamara Tucker *

Menghua Wang

Jeremy Werdell*

Bill Woodford*

SAIC General Sciences Corporation

FutureTech Corporation

SAIC General Sciences Corporation

NASA

SAIC General Sciences Corporation

NASA

SAIC General Sciences Corporation

SAIC General Sciences Corporation

FutureTech Corporation

NASA

SAIC General Sciences Corporation

SAIC General Sciences Corporation

NASA

SAIC General Sciences Corporation

SAIC General Sciences Corporation

NASA

NASA

FutureTech Corporation

SAIC General Sciences Corporation

SAIC General Sciences Corporation

NASA

SAIC General Sciences Corporation

Univ. of Maryland Baltimore

SSAI Corporation

FutureTech Corporation

Note: total civil servant staff ~ 2.5 man year

* shared with SeaWiFS Project
SIMBIOS Project Annual Report

6

Table 3. Conferences at which the SIMBIOS Project staff either presented papers or manned the

 SeaWiFS-SIMBIOS booth.

Conference name, date and location Booth Presentations

5th Environmental Conference on Remote Sensing of Marine &

Coastal Environments, October 5-7, 1998, San Diego, California. ! !

IOCCG Meeting , November 5-7, 1998, Hawaii. ! !

Ocean Optics XIV, November 10-13, 1998, Hawaii. ! !

Japan-U.S. Workshop on Ocean Color, November 15-16, 1998,

Hawaii.

! !

Ocean Community Conference ‘98, November 16-19, 1998,

Baltimore, Maryland. !

American Geophysical Union Fall Mtg., December 6-10, 1998,

San Francisco, California.

! !

ALPS99 Mtg. (CNES), January 18-22, 1999, Méribel, France. !

1999 American Society of Limnology and Oceanography Aquatic

Science Mtg., February 1-5,1999, Santa Fe, New Mexico.

!

SeaWiFS Postlaunch Algorithm Workshop #1, March 18-19,

1999, Greenbelt, Maryland.

!

ADEOS-II Workshop (NASDA), March 29-April 2, 1999, Tokyo,

Japan. (Material provided to Dr. J. Dodge, NASA HQ)

!

3rd Annual MOS Investigators Mtg., April 21-23,1999, Berlin,

Germany.

!

1999 Oceanography Society Scientific Mtg., April 27-30,1999

Reno, Nevada.

!

Mini-Workshop on Case-2 Algorithms, May 18, 1999, MBARI,

Moss Landing, Californa.

!

SeaWiFS Post-launch Algorithm Workshop #2, July 28-29, 1999,

Greenbelt, Maryland.

!

Oceans ‘99 (Marine Technology Society, Institute of Electrical

and Electronic Engineers), September 13-16, 1999, Seattle,

Washington.

!

Europto Conference (Society of Photo-Optical Instrumentation

Engineers), September 20-24, 1999, Florence, Italy.

!

ADEOS-II Workshop (NASDA), December 6-10, 1999, Kyoto,

Japan.

!

International Symposium on Ocean Color Remote Sensing and

Cabon Flux and the Japan US Working Group on Ocean Color

(JUWOC), December 13-15, 1999, Chiba, Japan.

!
SIMBIOS Project Annual Report

7

Chapter 2

SIMBIOS: NRA Contracts

Giulietta S. Fargion

SAIC General Sciences Corporation, Beltsville, Maryland

2.1 CONTRACT OVERVIEW

The second-year SIMBIOS NRA contracts ended

in the July-September 1999 time frame. The SIMBIOS

Project scheduled a telephone conference (telecon), of

about 30-45 minutes, with each PI and other

appropriate staff during the month of June. Prior to the

telecon, the SIMBIOS Project reviewed each contract,

the statement of work, and the agreed to deliveries. The

Project Office followed the same procedure used in

1998 and coordinated an inside panel with key contract

and project personnel to perform an across-the-board

evaluation of all funded contracts (Table 1).

The four categories to be evaluated are suggested

in the “Evaluation of Performance” from the Federal

Acquisition Regulation (FAR) 42.15 and NASA FAR

Supplement (NSF) 1842.15 or NASA form 1680 used

by GSFC. Under the “quality” category the following

are considered:

• data quality and completeness;

• ancillary information provided on the data

(metadata);

• the data's usefulness in relation to SIMBIOS goals,

i.e., calibration, validation, and algorithm

development; and

• quality of technical reports.

The “time” category is a mixed bag, but is viewed

with respect to data and documentation (monthly and

year-end reports, and special topic publications) and

delivery times. Under the “other” category is

considered:

• scientific publications and scientific achievements;

• science team collaboration and involvement; and

• other significant events occurring during the

contract period evaluated.

As a result of the formal evaluation and telecon

with the SIMBIOS PIs, all but two investigators were

evaluated as good or very good. The GSFC

Procurement Office implemented and executed 20

third-year options, closed one contract, and gave an 8-

month no cost extension to one contract.

Table 1. Contract evaluation key personnel

Contracting Officer: Lynne Hoppel

Contracting Assistant: Camille Tiger

Resource/Financial Officer: Patty Clow

Assistant Project Manager: Giulietta Fargion

Project Manager: Charles McClain

Presently, the Project has in place 19 contracts and

two interagency agreements. Further details are given

in Table 2. The SIMBIOS Program has established a

worldwide ongoing data collection program via the

SIMBIOS Science Team and AERONET. Data

provided to the SIMBIOS and SeaWiFS Projects are

summarized in Figures 1 and 2. From 1997 to July

1999 the SIMBIOS Program sponsored and supported

over 130 oceanographic cruises. Some cruises, such as

INDOEX, on which SIMBIOS PIs participated, lasted

several months. Table 3 shows partial data submitted to

SeaBASS by the funded PIs.

2.2 SCIENCE TEAM

NASA SIMBIOS Science Team PIs were

composed of those selected under the NRA-96. Some

members of the MODIS Ocean Teams, and certain

members the SeaWiFS Project, are considered informal

members of the Science Team. There are many more

U.S. and international co-investigators and

collaborators actively participating in the international

SIMBIOS program. This year, three PIs moved to

different institutions, and two PIs resubmitted

proposals for continuation of awarded research. The

SIMBIOS Science Team meeting is held each year, and

information and documentation produced in the

previous three meetings (1997, 1998, and 1999) are

posted on the SIMBIOS web-site. During the last

Science Team meeting (September 13-15,1999,

Annapolis, Maryland), the SIMBIOS Project suggested

the following areas for improvement to the Team

members:

• Matchup effort: water-atmosphere-satellite;

• Complete cruise information along with the data

submission;

• Improved information across the Team;
SIMBIOS Project Annual Report

8

• Timely submission and enhanced quality of

monthly web reports and TM contributions;

• Faster notification to the Project of PI

publications; and

• Standardized publication acknowledgements, such

as “this research was supported under the

SIMBIOS NASA contract # ”,

 Chapters 4 to 26 contain the individual PI’s

contributions to SIMBIOS and describe the funded

research topics, field studies activities, and ongoing

research results.

Table 2. SIMBIOS contracts and Government Interagency Agreements *.

Principal Investigator

Contract

Number

Begin Date End Date

Monthly Report

End-year TM

Cruise Report

Metadata

Special Topic TM

Field Data Within

3 or 6 Months

Algorithm

Development

Science Team

Meeting

William Balch 97268 9/97 9/2000 √√ √ √ √

J. Brock / C. Brown * 7/97 7/2000 √√ √ √ √

D. Capone / E. Carpenter 97131 9/97 9/99 √√ √ √ √

D. Capone / A. Subraniam 99232 9/99 9/2000 √√ √ √ √

Ken Carder 97137 9/97 9/2000 √√ √ √ √

Francisco Chavez 97134 9/97 9/2000 √√ √ √ √

Glenn Cota 97132 9/97 9/2000 √√ √ √ √

Tom Dickey 97127 7/97 7/2000 √√ √ √ √

Dave Eslinger 97133 9/97 5/99 √√ √ √ √

Robert Frouin 97135 9/97 9/2000 √√ √ √ √

Robert Green * 8/97 8/2000 √√ √ √ √

Watson Gregg * 2/97 2/2000 √√ √ √ √

Rick Miller * 12/97 12/2000 √√ √ √ √

Greg Mitchell 97130 8/97 8/2000 √√ √ √ √ √

Jim Mueller 97126 8/97 8/2000 √√ √ √ √

Frank Müller-Karger 97128 8/97 8/2000 √√ √ √ √

Dave Siegel 99083 2/99 11/2000 √√ √ √ √

Dave Siegel 97125 7/97 7/2000 √√ √ √ √ √

Ron Zaneveld 97129 8/97 8/2000 √√ √ √ √ √

Piotr Flatau 97139 9/97 5/2000 √√ √ √ √ √

Mark Miller * 9/97 9/2000 √√ √ √ √ √

John Porter 97136 9/97 9/2000 √√ √ √ √

Knut Stamnes 97138 9/97 9/99 √√ √ √ √ √ √

Knut Stamnes 92238 9/99 9/2000 √√ √ √ √ √ √
SIMBIOS Project Annual Report

9

Table 3. SIMBIOS supported data submitted to SeaBASS from 1997 to 07/99

Principle

Investigator

University

or Laboratory

Optics

Data

Pigment

Data (Chl)

AOP

data

AD or

other

William Balch Bigelow Labs 7 AT 261

J. Brock / C. Brown USGS / NOAA 115 140 1 AT

Capone/Subraniam U. of Southern Ca 88 34 210 AD

Ken Carder U. South Florida 25 25

Francisco Chavez Mont. Bay ARI 116 +

2 Moor

334+

2 Moor.

Glenn Cota ODU 412 92 1 AT

Tom Dickey UC SantaBarbara 7 Moor.

Dave Eslinger NOAA/CSC 403 90

Piotr Flatau Scripps, UCSD 22

Robert Frouin UCSD / Scripps 304+AT 304+AT

Robert Green JPL other

Watson Gregg GSFC

Mark Miller BNL 14 99

Rick Miller Stennis Space Ctr. 197 172 2 AT

Greg Mitchell Scripps, UCSD 240 344 1 AT

Jim Mueller San Diego St. U. 161 70 AD

Frank Müller-Karger U. South Florida 162 82

John Porter U. Hawaii

Dave Siegel UC Santa Barbara AD

Dave Siegel UC Santa Barbara 2701 93 13 AT

Knut Stamnes Stevens Inst. Tech. AD

Ron Zaneveld OSU 59

TOTAL

1997 data sets 48

1998 data sets 70

07/1999 data sets 23

5009 +

8 AT +

9 Moor.

1676 +

2 Moor.

705+

19 AT

AT = along track; Moor. = moorings; AOT = aerosol optical thickness;

AD = algorithm development; other = AVIRIS
SIMBIOS Project Annual Report

10

Figure 1. Bio-optical data submitted to SeaBASS from 1997 to July 1999.
SIMBIOS Project Annual Report

11

Figure 2. Atmospheric data submitted to SeaBASS from 1997 to July 1999; CIMEL stations are

numbered: Ascension Island (1), Bahrain (2), Lanai (3), Honolulu (4), WFF Virginia (5),

 Tahiti (6), South Corea (7), San Nicolas (8), Bermuda (9), Dry Tortugas * (10) and Kaashidhoo (11). * MODIS Oceans Team supported.
SIMBIOS Project Annual Report

12

Chapter 3

SIMBIOS Project Data Processing and Analysis Results

Menghua Wang

University of Maryland Baltimore County

at Goddard Space Flight Center, Greenbelt, Maryland

Bryan Franz, Alice Isaacman, Christophe Pietras and Paul Smith

SAIC General Sciences Corporation, Beltsville, Maryland

Tom Riley and Gene Feldman

NASA Goddard Space Flight Center, Greenbelt Maryland

Sean Bailey

FutureTech Corporation, Greenbelt, Maryland

Jeremy Werdell

Science Systems and Applications Inc., Greenbelt, Maryland

3.1 INTRODUCTION

During the year, SIMBIOS Project Office has fostered

several international collaborations (Table 1) between the

various space agencies and science working groups. The

Office has done this to assist in solving common technical and

scientific problems, as well as to leverage limited individual

project resources as much as possible. Specifically, some of

the common scientific problems are (1) to quantify the relative

accuracies of the products from international ocean color

missions, (2) to improve the level of confidence and

compatibility among the products, and (3) to generate merged,

improved Level-3 products. For each sensor, the SIMBIOS

Project reviews the sensor design and processing algorithms

being used by the particular ocean color project, compares the

algorithms with alternative methods when possible, and

provides the results to the appropriate project office, e.g.,

CNES and NASDA. The SIMBIOS Project Office

accomplishments during 1999 year are summarized under (a)

satellite data processing, (b) data product validation, and (c)

sensor engineering and calibration activities and are described

below.

3.2 SATELLITE DATA PROCESSING

One of the primary goals of the SIMBIOS Project is to

develop methods for meaningful comparison and possible

merging of data products from multiple ocean color missions.

 Direct comparison of such products is complicated by

differences in sensor characteristics and processing

algorithms, as well as spatial and temporal coverage. During

1999 the Project concentrated its efforts on the following color

missions: MOS, OCTS and POLDER.

3.2.1MOS Data

On 27 February 1999, the SIMBIOS Project began

operating a receiving station at NASA's Wallops Flight

Facility (WFF) to acquire data from the German Modular

Optoelectronic Scanner (MOS) onboard the Indian IRS-P3

spacecraft. The data from the Wallops groundstation are

processed at NASA's Goddard Space Flight Center, with

routine distribution of Level-0 datasets to the German Remote

Sensing Data Centre (DLR-DFD). Figure 1 shows the region

of coverage over which the IRS-P3 spacecraft is visible to the

Wallops groundstation, with all possible MOS ground tracks

superimposed.

Coverage limits are shown for antenna elevation minima

of 0, 3, and 8.5 degrees. The Wallops station is currently

attempting to acquire the spacecraft at 3-deg elevation, but

some western passes may be limited by obstructions of up to

8.5-deg elevation. After a pass is acquired at Wallops, the raw

files are transferred to the SIMBIOS Project at NASA's

Goddard Space Flight Center via an automated FTP process.

The raw files are then converted to level-0 format through a

software package provided by ISRO. Unfortunately, the level0 software requires human intervention, which limits full
SIMBIOS Project Annual Report

13

Table 1. SIMBIOS Project international collaborations (1988-1999)

SIMBIOS Science Team (NRA-96) SIMBIOS Collaborations: satellite ocean color

Mingxia He

 Ocean Remote Sensing Institute

 Ocean University of Qingdao, China

Gennady K. Korotaev

 Marine Hydrophysical Inst.,

 National Ukrainian Academy Of Science,

 Sevastopol, Ukraine

Oleg Victorovich Kopelevich

 Ocean Optics Laboratory

 Moscow, Russia

Hsien-Wen Li and Wei-Peng Tsai

 College of Science & Engineering

 National Taiwan Ocean University,Taiwan

Sei-ichi Saitoh and Ichio Asanuma

 Dept.of Fisheries Oceanography and Marine

 Sciences, Hokkaido University, Japan

David Antoine

Laboratoire de Physique et Chimie Marines

Villefranche sur Mer, France

Hajime Fukushima

 School of High Technology for Human Welfare

 Tokai University, Japan

Olivier Hagolle

 Centre National d’Etudes Spatialle,

 Toulouse, CEDEX, France

Jean-Marc Nicolas

 Laboratorie d’Optique Atmospherique (LOA)

 Universite’ de Lille, France

A. Neumann, G. Zimmermann and H. Krawczyk,

 DLR Institute of Space Sensor Technology and

Planetary Exploration, Berlin, Germany

Francis Xavier

National Remote Sensing Agency

Hyderabad, India

SIMBIOS Collaborations: in situ data SIMBIOS Collaborations with IOCCG

Pierre-Yves Dechamps

 Laboratorie d’Optique Atmospherique

 Universite’ de Lille, France

Christophe Menkes

 Laboratoire d'Océanographie Dynamique et

de Climatologie, Orstrom, France

Andre Morel

 Laboratoire de Physique et Chimie Marines

Villefranche sur Mer, France

Matt Pinkerton

 Natural Environment Research Council,

Plymouth Marine Lab, England

Marcel Wernand

 Netherlands Institute for Sea Research

 The Netherlands

Giuseppe Zibordi

 Joint Research Centre

 Space Applications Institute

 Ispra (Varese), Italy

Nicolas Hoepffner

 Joint Research Centre

 Space Applications Institute

 Ispra (Varese), Italy

Andre Morel

Laboratoire de Physique et Chimie Marines

Villefranche sur Mer, France

Trevor Platt

Scientific Committee on Oceanic Research

(SCOR)/ IOCCG

 Nova Scotia, Canada

Venetia Stuart

 SCOR, IOCCG

 Nova Scotia, Canada
SIMBIOS Project Annual Report

14

automation and adds some delay to the processing stream.

The resulting level-0 files are made available to DLRDFD for further processing and distribution. In addition, the

SIMBIOS Project is processing the data through level-1B

using the standard software provided by the German Institute

for Space Sensor Technology (DLR-ISST) (Neumann et al.,

1995). All data processed by the SIMBIOS Project is made

available through the MOS browse system at

http://simbios.gsfc.nasa.gov/.

The level-1B data can be processed to level-2 using a

SIMBIOS-developed software tool which applies the standard

SeaWiFS algorithms of Gordon and Wang (1994). This

Multi-Sensor level 1 to level 2 tool (MSL12), which is

distributed with the SeaDAS software package, is currently

capable of processing data from SeaWiFS, MOS, OCTS, and

POLDER using identical algorithms, and it has been applied

in previous studies of MOS-SeaWiFS cross-calibration (Wang

and Franz, 1999).

The addition of a MOS groundstation at NASA's Wallops

Flight Facility adds value to the MOS sensor through

increased geographic coverage. In addition, it increases the

opportunities for locating clear scenes of nearcontemporaneous MOS and SeaWiFS imagery. This data

will be used by the SIMBIOS Project for cross-calibration

studies, atmospheric correction and bio-optical algorithm

development, and data merger studies, and is made freely

available to the public in accordance with the data distribution

policies of DLR-ISST. The direct participation of the

SIMBIOS Project in the MOS project helps to foster

international collaborations that can only serve to enhance the

quality and consistency of future ocean color products.

3.2.2 OCTS Data

The Ocean Color and Temperature Scanner (OCTS) is an

optical radiometer which flew on the Japanese ADEOS

spacecraft from August 1996 to June 1997, collecting 10-

months of global ocean color data (Kawamura, 1998). During

the ADEOS mission lifetime, approximately 450 GB of realtime, 700m-resolution OCTS data was collected by the

SeaWiFS project through NOAA ground stations at Wallops,

Virginia and Fairbanks, Alaska.

The archive consists of 337 scenes of the U. S. East Coast

and 1311 scenes over Alaska. Following the work performed

in 1998 to enhance the algorithms and software used to

process the OCTS data (Reference the 1998 TM here), the

entire U.S. East Coast archive was reprocessed through Level0, and the products were distributed to the Ocean Color

community though the SIMBIOS OCTS browser (available at

http://simbios.gsfc.nasa.gov/).

OCTS Validation

An extensive set of in situ data taken during the time of

the OCTS mission was made available to the SIMBIOS

Project for match-up analysis from the SeaBASS database

(Hooker et al., 1994). Over 600 data points taken on 134

separate days exist in this set. Preliminary processing of these

matchup points was previously performed (McClain and

Fargion, 1999).

Reprocessing of the OCTS in situ matchups to data taken

from the SeaBASS database was performed in mid-1999.

Matchup data from Wallops level 0 data and from level 1B

data files supplied to the SIMBIOS Project by NASDA/EORC

were processed to level 2 using MSL12 and the calibration

coefficients used to process the Wallops data set. As before,

files in the GSFC Wallops archive which matched in situ data

points were processed from level 0 to level 2 using SIMBIOS

navigation methods and calibration, while level 1B data files

supplied to the SIMBIOS Project by NASDA/EORC were

processed to level 2 using SIMBIOS calibration.

Satellite normalized water-leaving radiance (nLw) values

were extracted from the level 2 records and acceptable pixels

within a 1.05-km radius were weighted by the inverse of their

distance to the matchup site and then averaged to derive nLw

values for comparison to in situ data. In the case where no

"bow tie" effect was present in the OCTS scan geometry, this

technique usually resulted in obtaining data from 9 pixels in a

square centered about the in situ data point. Matchup values

were also calculated for an area within a 2-km radius if there

were not enough acceptable pixels within the 1.05-km limit.

In situ data was also reprocessed to generate theoretical

nLw values using ozone data derived from climatology and a

set of lookup values of Rayleigh, k-ozone, and extraterrestrial

solar irradiances developed by Menghua Wang. These

theoretical in situ nLw values were then compared to the

weighted average nLw satellite values. Insofar as possible, the

matchups of satellite to in situ data were judged acceptable by

the same criteria used to judge SeaWiFS matchups to in situ

data . The nLw and chlorophyll a matchup procedure and

analysis for SeaWiFS data are described in Schieber et al. (in

press).

Specifically, matchups were rejected if:

• the time difference between satellite and in situ

measurements was more than 4 hours (6 hours for

chlorophyll);

• difference in solar zenith angle was more than 15o;

• in situ data were from a duplicate cast and had a lower

value of nLw (490) than other casts;

• wavelengths of in situ data differed from OCTS

wavelengths by more than 5 nm ;

• satellite data coefficient of determination (the ratio of

standard deviation to average) was greater than 0.5;

• the standard deviation of the satellite data was greater

than 1⁄2 the value of the in situ measurement;

• the usable number of satellite pixels was less than 5.
SIMBIOS Project Annual Report

15

Figure 1. IRS-P3 visibility map for the Wallops groundstation (courtesy of DLR).

Table 2. Summary of SIMBIOS OCTS Matchup Validation Results

SIMBIOS PROCESSING

WAVELENGTH

Total

Avg

Satellite/In

Situ Ratio

Avg # of 

Pixels/

Match

412 nm 19 1.207 8

443 nm 19 1.048 8

490 nm 20 .9939 8.15

520 nm 13 .9963 10.8

565 nm 9 1.048 9.5

670 nm 7 1.828 11

SeaWiFS matchups routinely screen satellite data for

flagged values and accept or reject them based on which flags,

if any, are present. Comparable tests could not be performed

for the OCTS matchups since the version of SIMBIOS

processing used did not output flag values to the level 2 data

sets. Because of the small number of matchups, those for

which some bands failed the above criteria while other bands

passed were included in the final analysis. Reprocessing of in

situ data increased the number of matchups somewhat, from

13 to 18 acceptable matchups in Band 3, the “best” channel, to

the data processed from NASDA level 1B to level 2 using

SIMBIOS methods. One fewer matchup was deemed

acceptable for Band 3 for the Wallops level 0 data (the point

lost was one where the satellite standard deviation was

unacceptably large). Several sets of nLw matchup data were

accepted using both methods, Table 2 summarizes the results

of the matchups to non-MOBY data.

Data which had 5 or more satellite pixels within a 2-km

radius are included in this Figure 2. The results from the

SIMBIOS processing of the NASDA level 1B data are

generally reasonable for Bands 1-5. The larger ratios of

satellite to in situ data seen in the Wallops data set may be due
SIMBIOS Project Annual Report

16

to the data being taken from only two investigators, from two

different dates. Detailed statistics, matchup plots, tables, and

thumbnail pictures of each matchup may be viewed on the

WWW at http://simbios.gsfc.nasa.gov/~alice/OCTS_MATCH

UP_SUMMARY.html.

Chlorophyll Algorithm Study

OCTS chlorophyll derivations using three different

chlorophyll algorithms were compared to in situ chlorophyll

measurements in the SeaBASS/SeaBAM data set. The

algorithms used are the current chlorophyll algorithm used by

NASDA on OCTS data ("OCTS-C"), the SeaWiFS

chlorophyll algorithm tuned to the OCTS instrument by J.

O'Reilly and S. Maritorena ("OC2"), and chlorophyll deived

from NDPI pigment (R. Frouin). Comparisons of chlorophyll

distributions and time series of in situ data were compared to

OCTS data and to SeaWiFS 8-day chlorophyll averages.

We used in situ data from the Sargasso Sea/Bermuda area

taken between July 1979 and 1990-1998 and comparisons

using all in situ data, then generated the same comparisons

using only in situ data taken between November and June, the

time frame of the OCTS flight. We found that chlorophyll

distributions for the OCTS-C and OC2 algorithms were in

general agreement with the data while the NDPI algorithm

showed a higher distribution (Figure 2). Detailed results of

the study may be found at http://simbios.gsfc.nasa.gov/~ali

ce/Sargasso/chl_comps/Chlorophyll_Comparison.html

3.2.3POLDER Data

The Multi-Sensor level-1 to level-2 (MSL12) software

was enhanced to include processing capabilities for standard

POLDER level-1B products. This capability has enabled the

SIMBIOS Project to perform an independent calibration of

POLDER, using standard SeaWiFS atmospheric correction

algorithms (Gordon and Wang, 1994) and in situ data from the

Marine Optical Buoy (MOBY) (Clark et al., 1997). Since

POLDER can acquire as many as fourteen nearcontemporaneous views of each location, at a variety of

scattering angles, the POLDER data provide the SIMBIOS

Project with an opportunity to make a direct test for geometric

dependencies in the water-leaving radiances retrieved with the

SeaWiFS atmospheric correction alghorithm.

For the present study, the multiple views of each MOBY

matchup were treated independently in deriving the calibration

gains. By inversion of the Gordon and Wang algorithm, each

MOBY water leaving radiance measurement was propagated

to the top of the atmosphere and combined with the predicted

atmospheric path radiance for each POLDER viewing

geometry. The predicted top of atmosphere radiances were

then compared with the POLDER Level-1B radiances to

derive the individual gain corrections required to make the

POLDER measurements match the predicted radiances. The

individual calibration gains were then combined by a simple

average to form the final calibration in each POLDER band.

The results are listed in Table 3, with the equivalent POLDER

project calibration shown for comparison.

Table 3. Standard POLDER ocean color vicarious

calibration coefficients, as compared with

the calibration corrections derived by

SIMBIOS.

Band POLDER SIMBIOS

443 1.072 1.013

490 1.042 0.971

565 1.000 0.953

670 1.000 1.004

765 1.000 1.008

865 1.000 1.000

POLDER Matchup Analyses

Progress has also been made in the latter part of the year

on POLDER data. The CNES has kindly provided the

SIMBIOS Project with POLDER level 1 and level 2 data

corresponding to the SeaBASS data base and to the dates and

locations used in the Sargasso Sea study performed on OCTS

data (web page at http://simbios.gsfc.nasa.gov/~alice/Sargasso

/Sargasso.html).

A preliminary calibration of the POLDER data has been

performed and MSL12 was updated to allow SIMBIOS

processing of POLDER level 1 data to level 2. Due to the

directionality and larger pixel size of the POLDER, different

matchup criteria were used. Acceptance criteria for POLDER

in situ matchups:

• due to the large POLDER pixel size (approximately 7 km.

at the Equator), only a one-to-one match of in situ data to

a unique POLDER pixel was done;

• for investigators having multiple measurements on the

same day, measurements closest in time to the POLDER

overpass were selected. In the case of duplicate in situ

measurements tagged with the same time, those with

highest nLw (490) were used;

• difference in solar zenith angle between POLDER and in

situ less than 15 degrees;

• solar zenith angle measurement less than or equal to 60

degrees; and

• in situ measurements were accepted only if they were

taken between 0900 and 1500 local time (computed

strictly by longitude) for all measurements except

chlorophyll measured in the field, for which a ± 6 hour

time window in either direction was allowed. The time

window for nLws was determined from Bermuda Test

Bed Mooring data which indicated that nLws decrease at

earlier or later times of day.

Due to the directionality property of POLDER, as many

as 14 different satellite matches to a given in situ measurement
SIMBIOS Project Annual Report

17

were theoretically possible. In actuality, the number of

directional matches was usually on the order of 8 to 10.

Simply performing a straight line fit to the data yielded the

results shown in Table 4, which should be regarded as

preliminary. In particular, Table 4 contains results from

MOBY and Marine Optical Characterization Experiment

(MOCE) (D. Clark, PI) scenes which were used in the initial

calibration of the POLDER performed by the SIMBIOS

Project; these results will be omitted in subsequent validation

studies. We also performed matchups of POLDER level 2 data

with data from the SeaBASS data set; our results were

comparable to those obtained by Dr. J-M Philippe at the

Laboratoire d' Optiques Atmospheriques in Lille, France. All

preliminary POLDER matchup results may be found at

http://simbios.gsfc.nasa.gov/~alice/polder_matches/INDEX.ht

ml

3.2.4 Future Validation Activities

In the near future, the SIMBIOS Project plans to attempt

another vicarious calibration of the POLDER, possibly taking

into account effects of the instrument's directionality. In

addition, the Sargasso Sea study performed on OCTS data will

be repeated using POLDER data coincident in locations and

dates. At the conclusion of these efforts, we will intercompare

the POLDER and OCTS by examining data which has been

processed from level 0 or 1 to level 2 using identical

SIMBIOS atmospheric correction methods.

Figure 2. In situ chlorophyll values from 30 box between longitudes –65.70 to –62.70 and

Latitudes 300 and 330. OCTS satellite data for 6 scenes.
SIMBIOS Project Annual Report

18

Table 4. Preliminary POLDER Matchup results: straight line fit to data

WAVE-LENGTH # Matchups Total # Directions Slope Offset

443 nm Band 40 422 .897 -.40

490 nm Band 40 422 .387 .20

565 nm Band 20 227 .658 -.01

0

0.1

0.2

0.3

0.4

0.5

0 0.1 0.2 0.3 0.4 0.5

SeaWiFS τ

a(510)

Cimel τ

a

(500)

(b)

0

0.05

0.1

0.15

0.2

0.25

0.3

0 0.05 0.1 0.15 0.2 0.25 0.3

SeaWiFS τ

a(670)

Cimel τ

a

(670)

(c)

0

0.05

0.1

0.15

0.2

0.25

0.3

0 0.05 0.1 0.15 0.2 0.25 0.3

Bahrain

Bermuda

Dry Tortugas

Kaashidhoo

Lanai

San Nicolas

SeaWiFS τ

a

(865)

Cimel τ

a

(870)

(d)

0

0.1

0.2

0.3

0.4

0.5

0 0.1 0.2 0.3 0.4 0.5

SeaWiFS τ

a(443)

Cimel τ

a

(440)

(a)

Figure 3. The retrieved SeaWiFS aerosol optical thickness compared with the ground in situ measurements from the

various AERONET stations for (a) 440 nm; (b) 500 nm; (c) 670 nm; and (d) 870 nm.
SIMBIOS Project Annual Report

19

3.3 PRODUCT VALIDATION

We are continuing our efforts in comparing and validating

the SeaWiFS aerosol optical products with the in situ

measurements mainly from the data of the AERONET. As in

our previous report (McClain and Fargion, 1999), SeaWiFS

has tendency of overestimating aerosol optical thickness with

respect to the in situ measurements. Herein, some updates of

comparison procedures and new results are presented and

discussed.

SeaWiFS Data Acquisition

The SeaWiFS aerosol optical thickness (AOT) data were

obtained by spatially co-locating a 25x25 pixel grid box

around the pixel containing the ground-based measurement

station, thereby providing a maximum of 625 SeaWiFS

retrievals in each matchup. A spatial homogeneity

(uniformity) test in the retrieved τ a ( ) 865 was then conducted

to screen thin cirrus and high altitude aerosol contamination

because the in situ and satellite measurements are often

looking through different atmosphere paths. Only those

satellite data sets which passed the spatial homogeneity test

were used for the matchup analyses.

In Situ Data Acquisition from Cimel

A select group of the ground stations from AERONET

was chosen. These instruments were located at either coastal

or island stations and were operational for a reasonable length

of time after SeaWiFS went into operation. Table 5 provides

the AERONET station name, location (latitude and longitude),

and the corresponding responsible AERONET PIs. Currently,

efforts are underway to include additional AERONET

stations. The retrieval of data from AERONET has been

automated to facilitate the matchup analyses. Once per month,

a script is automatically run to access the AERONET database

and retrieve τ a data for the predetermined sites.

Table 5. AERONET sites used for aerosol

matchups analyses.

Station Latitude Longitude AERONET PI

Bahrain 26.32 50.50 C. McClain*

Bermuda 32.37 -64.70 B. Holben

Dry Tortugas 24.60 -82.80 K. Voss & H. Gordon

Kaashidhoo 4.97 73.47 B. Holben

Lanai 20.83 -156.99 C. McClain*

SanNicolas 33.26 -119.49 R. Frouin

* SIMBIOS Project Office

For the matchup purpose, the ground-based measurements

from AERONET were first reduced to include only those

records that fall ±3 hr of the SeaWiFS overpass for a given

station. These records include the aerosol optical thickness

measured at the four spectral wavelengths (440, 500, 670, and

870 nm). As an initial quality control step, the data were

averaged and some variation parameters were computed to

screen possible cloud contamination. Only those data sets

which have low temporal variations (stable atmosphere) were

then further reduced to ±1 hr of the SeaWiFS overpass and

used for the matchup analyses. Usually, the Cimel instruments

routinely take one measurement every 15 min near local noon;

therefore, for a given SeaWiFS file, there may be as many as

eight AERONET measurements that qualify as a match for the

2 hr time window. The strategy in the validation study is not

to compromise good data with bad data for the purpose of

more matchups, i.e., it is preferred to screen out some good

data to keep the high quality of data sets.

AOT Results

The SeaWiFS derived aerosol optical thicknesses with

those from the ground in situ measurements were compared.

Figures 3 (a)- 2 (d) provide overall comparison results of

τ a ( ) λ between SeaWiFS and Cimel measurements at the

four wavelengths 440, 500, 670, and 865 nm. The Cimel

measurements were from the AERONET stations listed in

Table 5. The number of data contributed to each plot in

Figure 3 from individual stations, from the top of the list to the

bottom in Table 5, is 9, 8, 5, 2, 1, and 8. The station of Lanai,

therefore, only contributed one point, whereas Bahrain has

nine points in Figures 3(a)- 3(d). The dotted lines in Figure 3

are the 1:1 line. Although the comparison results vary both in

time and location, Figure 3 shows that the comparisons agree

reasonably well at the longer wavelengths (670 and 865 nm)

for most of the AERONET stations.

There is no obvious bias in the retrieved aerosol

optical thicknesses. This implicitly indicates that the

calibration at the SeaWiFS 865 nm is reasonably accurate. At

the short wavelengths, however, it appears that SeaWiFS has

the tendency of overestimating τ a ( ) λ with respect to the in

situ measurements, in particular, for the relatively large

aerosol optical thicknesses (τ a >0.15). This is most evident

with the SeaWiFS τ a ( ) 443 comparison results.

Some possible sources that contributed to the

comparison differences are from both satellite measurements

(calibration, aerosol models, and cloud and thin cirrus

contamination) and in situ data (mainly from instrument

calibration and cloud contamination). More studies are needed

to understand all of these.

AOT Cross Calibration Experiment

During the first week of August 1999 an experiment was

conducted at the “Acqua Alta” Platform of the CNR of Venice

(Italy). This experiment was in collaboration with Dr.
SIMBIOS Project Annual Report

20

Giuseppe Zibordi of the Joint Research Center of Ispra (Italy)

and Dr. Stan Hooker of NASA GSFC. A SIMBAD

radiometer, and Microtops and CIMEL sun photometers were

operating concurrently to allow direct solar and above water

measurements. The CIMEL and Microtops instruments

collected AOT; SIMBAD instrument collected AOT and water

leaving radiances data. On the only clear day, August 3, the

AOT daily averages were computed and are summarized per

wavelength in Table 6. The results presented herein are to be

considered preliminary. In spite of higher AOT from the

Microtops at 440nm, good agreement was observed. The

870nm channel was used as a reference channel. Using the

OC2 algorithm (O’Reilly et al., 1998) we computed the

chlorophyll a based on the remote sensing reflectance ratios at

490nm and 560nm. Water leaving radiances and chlorophylla, are shown in Figure 4. More details on sun photometer

operation and calibration are posted at: http://simbios.gsfc.nas

a.gov/Sunphotometers/calibration.html

3.3.1 SeaBASS INTERFACE

The SIMBIOS Project maintains the SeaBASS as an

archive for in situ products used in scientific analyses (e.g.

product verification and bio-optical algorithm development).

Stored data include measurements of water-leaving radiance,

chlorophyll-a, and other related optical and pigment

measurements collected on ships, moorings, and drifters.

(McClain and Fargion, 1999). Information on the original

SeaBASS design is provided in the SeaWiFS Technical

Report Series Volume 20 (Mueller and Austin 1995). A

current description of the SeaBASS system is available via the

World Wide Web at http://seabass.gsfc.nasa.gov.

The SeaBASS bio-optics database contains data from

over 200 experiments, encompassing more than 9000 data

files. Presently, data are stored as simple, flat (twodimensional) ASCII text with standard metadata headers to

fully define each file. The headers contain information on

date, time, location, investigators involved, values measured,

units, and other related descriptive information. The SIMBIOS

Project designed the format to ensure that data files were

simple, yet comprehensive, globally compatible among

different computer platforms, and effortlessly ingested into the

database. Specific information and examples of the data

format can be referenced at the SeaBASS web site.

The data format has not changed significantly during the

past year of the SIMBIOS effort. A single mandatory

metadata header (“/data_status=” accepting “preliminary”,

“update”, “final”) has been added to aid in tracking the status

of newly submitted data. The SIMBIOS Project uses this

information to determine if a file contains data from a new

cruise (“preliminary”) or updated (e.g. recalibrated or

reprocessed) data from a previous cruise (“update”, “final”).

The “final” status is appropriate when data are not to be

updated again. Similarly, protocols for format checking and

data submission have not been altered over the past year. The

SIMBIOS Project currently uses a PERL script feedback

program known as FCHECK to maintain the standard format

for incoming data files. Contributing researchers can test their

data for compatibility with the SeaBASS format from any

platform by e-mailing their files to

fcheck@seabass.gsfc.nasa.gov. Once the data files meet

SeaBASS format requirements, the contributor may send their

data files and related documents (e.g. cruise reports, readme

and calibration files) to the SeaBASS archive via file transfer

protocol (FTP). The SeaBASS Administrator moves the files

into their appropriate position in the archive and ingests the

files into the SeaBASS database. Password secure web access

to the data files, the database, and supporting documentation is

available at the SeaBASS web site. For additional information

on format checking and data security issues refer to the

SIMBIOS Project 1998 Annual Report (McClain and Fargion,

1999). The procedures for water-leaving radiance, normalized

water-leaving radiance, and chlorophyll-a match-up analyses

have changed little during the past year of the SIMBIOS

effort. Each match-up file format follows a similar logic to

that of the other SeaBASS in situ files. Data are structured in

standard ASCII columnar format with standard metadata

headers; each record, however, has predefined data fields:

• year, month, day, hour, minute, second, latitude,

longitude,

• Lw412, Lw 443, Lw 490, Lw 510, Lw 555, Lw 665,

• Es412, Es443, Es490, Es510, Es555, Es665, Kd490,

chlorophyll-a.

Specific information on the match-up analyses and

protocols may be found in the SeaWiFS Postlaunch Technical

Report Series Volume 9 (Schieber et al., 1999).

Future Plans

The SeaBASS system will undergo several major changes

in the coming year. First, the match-up analysis procedures

will be modified concurrently with the next reprocessing of

SeaWiFS data. The most significant alterations include (1) a

change in Level 2 processing code from ANLY (l2gen) to the

Multisensor Level-1 to -2 (MSL12) program and (2) a

generalized file format which allows for additional field

parameters to be included (e.g. Lw and Es values at wavebands

other than those of SeaWiFS). Second, the Project intends to

reconfigure the SeaBASS database system. The following

activities are considered to be the important in the design of

the new system: (1) increasing the number of tables in the

relational database to improve data normalization, (2)

reconfiguring the system to take advantage of multiple

processors and increased physical storage space, (3)

generating stored system procedures for internal SIMBIOS

Project Office accounting purposes, and (4) including all

metadata and data information into the database to improve its

ability to search for or query archived parameters.
SIMBIOS Project Annual Report

21

Table 6. AOT retrieved on August 3 1999 Averaged between 8am and 12am on Acqua Alta

Platform from CIMEL, Microtops and SIMBAD sun photometers.

CIMEL Microtops SIMBAD

440 nm 0.336 0.360 -

443nm - - 0.324

490nm - - 0.261

500nm 0.273 0.284 -

560nm - 0.203

670nm 0.146 - 0.134

675nm - 0.154 -

870nm 0.080 0.080 0.081

940nm - 0.069 -

Figure 4. Water leaving radiances retrieved from SIMBAD radiometer on August 3, 1999.

Water Leaving Radiance Simbad August 03 1999

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

8 9 10 11 12

GMT

Lw - 

μWcm-2sr-1nm-1

0

0.5

1

1.5

2

2.5

Chl-a - mgm-3

Lw 443nm

Lw 490nm

Lw 560nm

Lw 670nm

Chl-a (OC2 algorithm)
SIMBIOS Project Annual Report

22

Table 8. Table of SIMBIOS supported cruises with services provided.

Cruise Location Begin Date End Date

On-board LAC

Over-flight Prediction

Near Real Time

Imagery

Instrument Pool Use

Principal Investigator

SOIREE 19990101 19990303 ! ! Steve Groom

ANTARES4 19990104 19990223 !!! J. Le Fevre

CalCOFI 19990109 19990131 !!! Greg Mitchell

BBOP/BATS124 19990111 19990115 ! Dave Siegel

INDOEX 19990114 19990401 !!!! Piotr Flatau

FEB99SAB 19990210 19990224 ! ! Ajit Subramaniam

BATS Validation #25 19990302 19990306 Dave Siegel

EPS-A Test Flight 19990316 19990429 ! J.H.M. Hakvoort

Baltic Sea 19990316 19990316 ! Peter Land

Landsort Deep 19990330 19990427 ! Peter Land

Bay of Biscay 19990401 19990416 ! ! Jean-Noel Druon

AR04-99 19990402 19990410 ! ! Douglas Phinney

HOTS 19990413 19990415 ! ! John Porter

N.Pac. Subtrop. Gyre 19990420 19990508 !!! Carrie Leonard

GOCAL99-A 19990421 19990502 ! ! Jim Mueller

AMT8 19990425 19990607 !!! Stan Hooker

OMEX 64PE138 19990426 19990507 ! Marcel Wernand

Japan Sea 19990501 19990615 ! ! Robert Arnone

Yarmouth-Portland 19990510 19991001 !!! Barney Balch

Helgoland 19990511 19990613 ! J.H.M. Hakvoort

HX222 Inner Front 19990520 19990620 ! Stephan Zeeman

HOTS 19990527 19990531 ! John Porter

CARIACO 19990602 19991220 !! ! Frank Muller-Karger

US East Coast 19990616 19990622 ! ! Stephan Howden

AREX-99 19990620 19990805 ! Dariusz Stramski

OCE96-17680 19990623 19990708 ! ! Barney Balch

South China Sea 19990701 19990731 !! ! Richard Miller

EQUALANT 19990706 19990820 ! J. Etcheto

Chukchi Sea 19990707 19990730 !! ! Glenn Cota

HOTS 19990712 19990716 ! ! John Porter

Gotland 19990714 19990815 !!! Peter Land

SML99 19990720 19990723 ! ! Heidi M. Sosik

Bay_of_Biscay 19990722 19990915 ! ! Jean-Noel Druon

Venice Tower Experiment 19990802 19990806 !! ! Giuseppe Zibordi

CalCOFI 19990807 19990829 ! Greg Mitchell

Heincke 99 19990824 19990827 ! ! Hans Barth

US East Coast 19990825 19991015 ! ! Stephan Howden

SEINESAT 19990825 19991001 ! ! Jean-Noel Druon

PROSOPE 19990904 19991003 !!! Stanford Hooker

OSCOPE 19990920 19991030 !!! Rik Wanninkhof
SIMBIOS Project Annual Report

23

Cruise Location Begin Date End Date

On-board LAC

Over-flight Prediction

Near Real Time

Imagery

Instrument Pool Use

Principal Investigator

SeaWiFS Validation Cruise #2 19991001 19991021 ! ! Dennis Clark

Black Sea 19991001 19991031 !!! Robert Frouin

AVARIS-CalCOFI 19991001 19991031 ! Robert Green

CalCOFI 19991003 19991031 ! Greg Mitchell

Cimar5 19991020 19991114 !!! W. Scott Pegau

TrichoToto 19991026 19991129 !!!! Ajit Subramaniam

GoCAL-99B 19991027 19991108 !!! Jim Mueller

Table 8. SIMBIOS Pool Instruments

Instrument Quantity Description Manufacturer Custodian(s)

MicroTops II

Sunphotometer

w/GPS

12 5 channel handheld sunphotometer

w/Garmin GPS-38

Solar Light

Company SIMBIOS Project

HISTAR

Package* 1

2 hyper-spectral absorption/beam

attenuation meters mounted on a cage with

a SeaBird CTD

WETLabs, Inc Zaneveld/Pegau

Hydroscat 6 3 backscattering meter HOBILabs

Siegel

Carder

Mitchell

Pure Water

System 3

Water purification system for calibration

of WETLabs AC-9 and HISTAR

absorption and attenuation meters

Barnstead Zaneveld/Pegau

AC-9 3 absorption/beam attenuation meter WETLabs, Inc.

Cota

Capone

Muller-Karger

SIMBAD 5 5 channel radiometer and sunphotometer Frouin

SeaWiFS

Multichannel

Profiling

Radiometer

2

Free-fall profiling radiometer measuring

Lu(z), Ed(z), Es, Lu(1m) with cables, deck

unit and PC with data acquisition and

processing software

Satlantic, Inc. Capone

Chavez

Micropulse

LIDAR 1 Continuous operation LIDAR system SESI SIMBIOS Project

Prede

Sunphotometer 2 Automated ship-board sunphotometer Prede SIMBIOS Project

Cimel

Sunphotometer 12 Marine-hardened, automated

sunphotometer Cimel SIMBIOS Project

* The two WETLabs Histar instruments for this package have been replaced with two WETLabs AC-9's

 until such time as the Histar instrument provides reliable data.
SIMBIOS Project Annual Report

24

3.3.2 SUPPORT SERVICES

In an effort to improve the quality and quantity of

calibration and validation data sets, the SIMBIOS Project

offers several support services to field investigators. These

services include; scheduling of on-board LAC recording for

SeaWiFS; overflight predictions for operational sensors

(currently SeaWiFS, OCTS and MOS-B); near real time

SeaWiFS imagery for cruise locations; and optical

instrumentation from a pool of investigator- and projectowned instruments. These services may be requested via the

World Wide Web at http://simbios.gsfc.nasa.gov. In return for

these services, the SIMBIOS Project requests that the field

investigators provide in situ validation data to the Project's

bio-optical archive, SeaBASS. Since January of 1999, when

these services were initially offered, the SIMBIOS Project has

supported 47 cruises (Table 7).

Scheduling SeaWiFS On-board LAC Recording

Since much of the world ocean is not covered by a

SeaWiFS HRPT station, high-resolution data may be recorded

onboard the SeaWiFS sensor. As a service to the science

community, the SIMBIOS Project in conjunction with the

SeaWiFS Project can schedule SeaWiFS onboard LAC for

cruises that occur outside HRPT coverage. SeaWiFS has the

ability to record a maximum of 10 minutes of high-resolution

data per downlink. Typically, a 30-second interval is allotted

for LAC target, which corresponds to 180 scan lines or

approximately 200 km along track at nadir. Detailed

information on LAC scheduling is available on the SIMBIOS

web site.

Overflight Predictions for Operational Sensors

For calibration and validation purposes, in situ

measurements should be made as close to the sensor overflight

time as is possible. To aid investigators in determining when

sampling should occur, the SIMBIOS Project offers overflight

predictions for all operational ocean color remote sensors.

Currently, the sensors supported are SeaWiFS, MOS-B and

OCI. With the launch of Terra upcoming, MODIS will be

added to this list. Detailed information on overflight

predictions is available on the SIMBIOS web site.

Near Real Time SeaWiFS Imagery

In addition to providing predictions for satellite overflight

times, the SIMBIOS Project offers near real time imagery of

the operational SeaWiFS products in JPEG format to cruises at

sea. These images provide field investigators with additional

information with which they may maximize in situ sampling

of transient oceanographic features. The default specifications

for the images provided include:

• available LAC, HRPT, and GAC;

• chlorophyll-a and pseudo-true color images;

• 2-degree box about a designated location or the entire

designated region ;

• image width of 600 pixels ;

• minimum percent valid chlorophyll pixels: 5%;

• images may be customized to best accommodate

individual investigators needs. Detailed information on

near real time imagery is available on the SIMBIOS web

site.

Instrument Pool

The SIMBIOS Project provided funding to several of the

science team members for the purchase of in situ ocean optical

instrumentation. The funding was provided with the

stipulation that these instruments would be made available for

three years to an instrument pool to be maintained by the

Project Office. The Project augmented this instrument pool

with atmospheric instrumentation. Table 8 summarizes the

instruments available.

Satellite Data

The SIMBIOS Project collected OCTS data for the East

Coast of the United States while the ADEOS satellite was

operational. These data have been processed using code

developed in house and are available through a browse utility

linked to the SIMBIOS Project's web site. The Project also

routinely collects MOS data for the East Coast of the U.S.

while the instrument is in ocean viewing mode. As with the

OCTS data, these data are made available to the public via the

SIMBIOS Project web site.

3.4 SENSOR ENGINEERING AND

CALIBRATION

Eight SIMBIOS CIMEL sites have been confirmed

(delivered or negotiated) and include Lanai Hawaii (with

backup in Honolulu), Ascension Island, Bahrain, Tahiti,

Wallops Island (Virginia, USA), South Korea, and Erdemli

(Turkey). The next sites projected for implementation by

January 2000 are The Azores and Perth (Australia).

The remaining two SIMBIOS CIMELs, one as a backup,

are deployed at Goddard Space Flight Center. Twelve

Microtops, two SIMBADs and one PREDE Mark II sun

photometer were deployed in several cruises between 1998

and 1999. The data collected by the Project is displayed for

this period in Chapter II, Figure 2.

Sun Photometer Calibration: Non-Polarized Channels

The calibration of the sun photometers was described in

McClain and Fargion (1999). Details on operating the

sunphotometer instrument, calibration and the theoretical

principles are posted at http://simbios.gsfc.nasa.gov/Sunphoto
SIMBIOS Project Annual Report

25

meters/calibration.html.

This year the twelve Microtops, two SIMBAD and two

PREDE sun photometers of the SIMBIOS instrument pool,

were calibrated after each and every cruise deployment. The

in-house processing code was updated. This code allows intercalibration with a CIMEL as the reference instrument based on

the time to time voltage ratios. Some of the updated

modifications allow for the avoidance of TOA or V0

computation for an air mass higher than 3. In this way V0 is

not calculated for low sun zenith angles due to possible

unstable atmosphere. The first and last calibration for the

Microtops #3773, the SIMBAD #972306 and the PREDE

#PS090063 are shown in Table 9.

With the V0 are displayed the standard deviation ∆V0

corresponding to the atmosphere variation during the

calibration or due to the time difference with the CIMEL

reference. Clear days are selected as “calibration” days if they

have a variation ∆V0/V0 less than 1% (Table 9). We have

found that the optics and filters of the instrument can change

quite a lot after one year of use. In the case of the PREDE

#PS090064 the variations could reach 5%. Several factors

lead to the degradation of the calibration and the effect

strongly depends of the wavelength. Thus the Project

recommends a frequent schedule of calibrations for each field

experiment in order to retrieve the most accurate AOT.

 Sun Photometer Calibration: Polarized Channels

The calibration of the polarized version of the CIMEL sun

photometers was described in McClain and Fargion (1999).

 The first polarized sun photometer (#191) of the

SIMBIOS Project was deployed in Erdemli (Turkey). Table 10

displays the calibration results: slope (δp), intercept (P0) and

linear squared fit applied to the degree of polarization given

by the device and plotted versus the degree of polarization

measured by the polarized CIMEL #191.

 Table 10

Instrument # δp Po R2

191 1.0676 -0.0203 1

Above Water Radiometer Calibration

The SIMBAD radiometer is also an above water

radiometer (in addition to being a sun photometer). The optics

and filters are the same but the electronic gain is different. The

calibration is performed using a 6” integrated sphere at GSFC.

Two SIMBAD instruments were calibrated on August 12,

1999. Table 11 shows the reflectance per count obtained using

two lamps or six lamps.

Data Format and Processing Protocol

 A proposal for a standardized data format was presented

and agreed to at the 3rd SIMBIOS team meeting. The

processing protocol retrieves spectral AOT from the raw direct

solar measurements and computes the water vapor amount and

the AOT spectral dependence. The processing code generates

an output file that will be stored in the SeaBASS database.

The data processing was described in McClain and Fargion

(1999).

Table 9. Top of Atmosphere (TOA) signals and standard deviations for the sun photometers determined by transfer

calibration from a calibrated CIMEL at GSFC between August 1998 and September 1999.

Microtops

#3773

440nm 500nm 675nm 870nm 940nm

08-20-1998 1238±7 988±4 1219±5 825±3 1428±8

06-09-1999 1239±5 986±4 1200±1 825±1 1402±9

SIMBAD

#97206

443nm 490nm 560nm 670nm 870nm

08-20-1998 389688±1641 475830±922 403397±954 421155±2357 305400±314

09-23-1999 379513±2390 467164±818 392986±871 415745±932 300079±2204

PREDE

#PS090064

440nm 500nm 675nm 870nm 940nm

10-16-1998 1.36±0.003E-04 2.79±0.02E-04 3.52±0.02E-04 2.77±0.01E-04 2.61±0.01E-04

09-23-1999 1.30±0.002E-04 2.72±0.005E-04 3.40±0.01E-04 2.67±0.004E-04 2.67±0.02E-04

Table 11. Calibration coefficient for SIMBAD # 06 and 09 on August 12, 1999.

SIMBAD

#972306

Lamps 440nm 490nm 560nm 675nm 870nm

6 3.818±0.006 2.192±0.0015 2.432±0.002 4.229±0.002 8.029±0.002 06 2 3.806±0.001 2.159±0.002 2.419±0.002 4.220±0.001 8.035±0.002

09 6 4.931±0.003 2.425±0.002 2.695±0.003 4.312±0.004 8.277±0.0025

2 4.902±0.003 2.390±0.001 2.686±0.0005 4.303±0.0005 8.293±0.001
SIMBIOS Project Annual Report

26

Calibration Round Robin

 NASA personnel carried the SeaWiFS Transfer

Radiometer SXR-II S/N-04 to JPL in July 1999 and took

calibration measurements of the AVIRIS calibration lamp and

plaque. Upon return the SXR-II was tested against the GSFC

large integration sphere and two of its channels (1 and 6) were

found to have significantly changed since the last calibration

in April. Final analysis of the AVIRIS data is delayed until

the problem with the SXR-II is resolved. Tests comparing the

first SXR S/N-01 and the SXR-II S/N-04 are currently in

progress.

Yankee Environmental SQM

 NASA personnel tested the Yankee Environmental

SeaWiFS Quality Monitor (SQM) in a mock sea cruise for

over a month using the SXR-II as the reference instrument.

This field light source met its specifications for stability in

laboratory conditions. The high light setting may be brighter

than desired for calibration of most underwater radiometers.

A final report awaits resolution of the SXR-II problem.

3.5 SIMBIOS COMPUTING

RESOURSES

The SIMBIOS computing facility contains a variety of

equipment types (Figure 5). The main goal of the facility is to

provide computational support for the following areas:

• routine bulk data processing,

• large scale analysis and match-up between sensors,

• focused analysis on data subsets, and

• storage of large sensor data sets.

Co-location of the facility with the SeaWiFS Project

continues to benefit the Project by making available other

resources such as high-quality color printers, network

equipment, and other supporting equipment. Large-scale tasks

such as bulk data processing and large-scale analysis tasks are

performed by two Silicon Graphics (SGI) Origin 2000 servers.

Each system has 6 processors and approximately 3 gigabytes

(GB) of RAM. The influx of large data sets for additional

sensors requires increasing amounts of disk space, especially

when performing comparative analysis. The Data Processing

server has 90 GB of disk space and the Data Analysis server

has 374 GB of total disk space. Long term storage of data sets

is handled by the 6 TB tape library attached to the Data

Analysis server. Silicon Graphics O2 workstations continue to

be the system of choice for software development and focused

analysis tasks. The sizing of the workstations varies with the

task requirements.

SIMBIOS is connected to the Internet via a 100-megabit

link, making network transfer of large data sets more feasible.

Internal connections are also 100 megabit for rapid transfer of

data between the servers and the workstations. Data ingest for

SIMBIOS is also done via removable media including CDROM, 8 millimeter tape, 4 millimeter (DAT) tape, and DLT

media up through DLT 7000. Off-line media storage space is

shared with the SeaWiFS Project.

The scope of the group's efforts expanded over the past

year, including the addition of the POLDER dataset,

installation of a ground station at Wallops Flight Facility to

receive MOS data downlinks, and routine processing of MOS

data at the Greenbelt site. In support of these efforts, the

facility has experienced moderate growth over the past year.

A workstation was added to the Project, as well as additional

local storage for the workstations and high capacity tape

drives for local backup and archival capability.

Each server was upgraded with a FibreChannel interface.

The new interface will allow the servers to participate in the

SeaWiFS Project Storage Area Network (SAN). Connection to

the SeaWiFS SAN will allow the SIMBIOS team to access

SeaWiFS data products and ancillary data at a rate of up to 1

gigabit per second. Participation in the SeaWiFS high

availability server cluster via Silicon Graphics (SGI) FailSafe

software is planned for next fiscal year. Membership in the

cluster will give the Project the capability of automatic

failover of services from one server to another in the event of

a server crash, maximizing resource availability.

REFERENCES

Clark D.K., H.R. Gordon, K.J. Voss, Y.Ge, W. Broenkow, and

C. Trees, 1997: Validation of Atmospheric Correction

Over Oceans. J. Geophys. Res., 102, D14, 17,209-17,217.

Hooker, S.B., C.R. McClain, J.K. Firestone, T.L. Westphal, En. Yeh, and Y. Ge, 1994: The SeaWiFS Bio-Optical

Archive and Storage System (SeaBASS), Part 1. NASA

Tech. Memo. 104566, Vol. 20, S.B. Hooker and E.R.

Firestone, Eds., NASA Goddard Space Flight Center,

Greenbelt, Maryland, 40 pp.

Gordon, H. R., and Wang, M., 1994: Retrieval of waterleaving radiance and aerosol optical thickness over the

oceans with SeaWiFS: a preliminary algorithm. Appl.

Opt. 33:443-452.

McClain, C.R,. and G.S. Fargion, 1999: SIMBIOS Project

1998 Annual Report, NASA Tech. Memo. 1999-208645,

NASA Goddard Space Flight Center, Greenbelt,

Maryland, 105 pp.

Neumann, A., Walzel, T., Tschentscher, C., Gerasch, B.,

Krawczyk, H, 1995: MOS-IRS Data Processing, Software

and Data Products (Preliminary Documentation), DLR

Institute for Space Sensor Technology.
SIMBIOS Project Annual Report

27

Mueller, J.L., and R.W. Austin, 1995: Ocean Optics Protocols

for Validation, Revision 1, NASA Tech. Memo. 104566,

Vol. 25, S.B. Hooker, E. R. Firestone, and J. G. Acker,

Eds., NASA Goddard Space Flight Center, Greenbelt,

Maryland, 67 pp.

O’Reilly, J. E., S. Maritorena, B. G. Mitchell, D. A. Siegel, K.

L. Carder, S. A. Garver, M. Kahru, and C. McClain,

1998: Ocean color chlorophyll algorithms for SeaWiFS,

J. Geophys. Res., 103(C11), 24,937-24,953.

Schieber B.D., C.R. McClain, S.B. Bailey, P.J. Werdell, 1999:

‘Lwn Clorophyll a Matchup Analyses”. In: SeaWiFS

Postlaunch Technical Report Series, Vol. 9, S.B. Hooker

and E.R. Firestone, NASA Goddard Space Flight Center,

Greenbelt, Maryland (in press).

Wang, M., and B. Franz, 1999: Comparing the ocean color

measurements between MOS and SeaWiFS: A vicarious

intercalibration approach for MOS, IEEE Trans. Geosci.

Remote Sens., (in press).

100 Mb/sec

FDDI

Concentrator

1xR10000 Proc.

SGI O2

8 GB disk

576 MB RAM

CD-ROM

Analyst Station

1xR10000 Proc.

SGI O2

50 GB disk

640 MB RAM

CD-ROM

Analyst Station

MOS

Ground Station

at Wallops

Analysis/Data Processing System

SIMBIOS

100 Mb/sec 10 Mbit/sec

SeaWiFS Router

Fast Ethernet

Switch

Ethernet switch

Printers PCs

GSFC FDDI network - 100 Mb/sec

GSFC Ethernet network 10 Mbit/sec

1xR10000 Proc.

SGI O2

320 MB RAM

CD-ROM

26 GB disk

DAT drive

Analyst Station

2.9 GB RAM

DAT tape

CD-ROM

SGI Origin 2000

6 TB tape library

6xR10000 Processors

Data Analysis Server

6xR10000 Processors

3 GB RAM

90 GB disk

DAT tape

CD-ROM

SGI Origin 2000

Data Processing Server

374 GB disk

DLT 7000 drive

1xR10000 Proc.

SGI O2

CD-ROM

DAT drive

Analyst Station

72 GB disk

320 MB RAM

WFF Ethernet network

Figure 5. The SIMBIOS computing facility and equipment types.
SIMBIOS Project Annual Report

28

This research was supported by the

SIMBIOS Project Office

PEER REVIEWED PUBLICATIONS

Barnes, R., R. E. Eplee, and F. S. Patt, 1998: SeaWiFS

Measurements of the Moon. EurOpt Series, Sensors,

Systems, and Next-Generation Satellites II, SPIE, 3498,

311-324

Barnes, R., R. E. Eplee, F. S. Patt, and C. R. McClain 1999:

Changes in the Radiometric Sensitivity of SeaWiFS

Determined from Lunar and Solar-based Measurements.

Applied Optics, 38, 4649-4669.

Mueller, J., C. McClain, R. Caffrey, and G. Feldman, 1998:

The NASA SIMBIOS Program, Backscatter.

Wang, M., 1999: A Sensitivity Study of SeaWiFS

Atmospheric Correction Algorithm: Effects of Spectral

Band Variations. Remote Sens.Environm., 67, 348-359.

Wang, M., 1999: Atmospheric Correction of Ocean Color

Sensors: Computing Atmospheric Diffuse Transmittance.

Applied Optics, 38, 451-455.

Wang, M., 1999: Validation study of the SeaWiFS oxygen Aband absorption correction: Comparing the retrieved

cloud optical thicknesses from SeaWiFS measurements,

Appl. Opt., 38, 937-944.

Accepted

Fargion, G. S., C. R. McClain, H. Fukushima, J. M. Nicolas,

and R. A. Barnes, 1999: Ocean color instrument

intercomparisons and cross-calibrations by the SIMBIOS

Project. In press SPIE,# 3870-68.

Wang, M. and B. A. Franz, Comparing the ocean color

measurements between MOS and SeaWiFS: A vicarious

intercalibration approach for MOS, IEEE Trans. Geosci.

Remote Sensing (to be published in January 2000).

Submitted

Porter J. N., M. Miller, C.Pietras, C. Motell, 1999: Ship Based

Sun Photometer Measurement Using Microtops

Sunphotometer, Submitted J. Atmos. Oceanic. Technol..

Siegel, D.A., M. Wang, S. Maritorena, and W. Robinson,

1999: Atmospheric correction of satellite ocean color

imagery: The black pixel assumption. Submitted to

Applied Optics.

Wang, M., S. Bailey, and C. R. McClain, 1999: Global aerosol

optical thickness distribution from SeaWiFS. Submitted

to Eos, Transactions, American Geophysical Union.

Wang, M. and Bryan A. Franz, 1999: Comparing The Ocean

Color Measurements Between MOS & SeaWiFS: A

Vicarious Intercalibration Approach for MOS. Submitted

to IEEE Trans. Geosci. Remote Sensing.

OTHER PUBLICATIONS

McClain, C.R. and G.S. Fargion, 1999: SIMBIOS Project

1998 Annual Report, NASA Tech. Memo. 1999-208645,

NASA Goddard Space Flight Center, Greenbelt,

Maryland, 105 pp.

Schieber B.D., C.R. McClain, S.B. Bailey, P.J. Werdell, 1999:

‘Lwn Clorophyll a Matchup Analyses”. In: SeaWiFS

Postlaunch Technical Report Series, Vol. 9, S.B. Hooker

and E.R. Firestone, NASA Goddard Space Flight Center,

Greenbelt, Maryland (in press).

PRESENTATIONS

Chou, M.D., P.K. Chan, and M. Wang 1999: Global aerosol

radiative forcing derived from SeaWiFS-inferred aerosol

optical properties, to be presented at AGU Fall Meeting,

Dec. 13-17, San Francisco, California.

Fargion, G. S., C. R. McClain, H. Fukushima, J. M. Nicolas,

and R. A. Barnes, 1999: Ocean color instrument

intercomparisons and cross-calibrations by the SIMBIOS

Project. EOS/SPIE Symposium on Remote Sensing,

Florence, Italy.

Fargion, G.S., 1999: An Overview of SIMBIOS Project.

International Symposoium on Ocean color Remote

Sensing and Carbon Flux by CERES and JUWOC, Chiba,

Japan.
SIMBIOS Project Annual Report

29

Franz, B. A., 1998: A Simple Destriping Algorithm for MOS

Images. Proc. of the 2nd International Workshop on

MOS-IRS and Ocean Color, Berlin.

Franz, B. A.,1999: Status of the MOS Ground Station at

NASA/Wallops. Proc. of the 3rd International Workshop

on MOS-IRS and Ocean Color, Berlin.

Franz, B. A., 1999: An Overview of SeaWiFS Mission.

International Symposoium on Ocean color Remote

Sensing and Carbon Flux by CERES and JUWOC, Chiba,

Japan.

Isaacman, A., B. A. Franz, and R. E. Eplee, Jr., 1999: An

Investigation of Time Variability in-water-Leaving

Radiances Retrieved from the Ocean Color

Measurements, ALPS 99 Conference, Méribel, France.

Wang, M. and B. A. Franz, 1998: A Vicarious Intercalibration

Between MOS and SeaWiFS. Proc. of the 2nd

International Workshop on MOS-IRS and Ocean Color,

Berlin.

Wang, M., S. Bailey, C. R. McClain, C. Pietras and J. T.

Riley, 1999: Remote Sensing of the Aerosol Optical

Thickness from SeaWiFS in Comparison with In situ

Measurements. ALPS 99 Conference, Méribel, France.

Wang, M. and B. A. Franz, 1998: A Vicarious Intercalibration

between MOS and SeaWiFS, Proc. 2nd International

Workshop on MOS-IRS and Ocean Colour, Berlin,

Germany, 95-102.

Wang, M., 1998: A validation of the SeaWiFS O2 A-band

absorption correction, Proc. the 4th Pacific Ocean Remote

Sensing Conference, Qingdao, China, 32-36, 1998.

Wang, M., 1998: Applying the SeaWiFS atmospheric

correction algorithm to MOS, Proc. the 4th Pacific Ocean

Remote Sensing Conference, Qingdao, China, 88-91,

1998.
SIMBIOS Project Annual Report

30

Chapter 4

Validation of Surface Bio-Optical Properties in the Gulf of Maine

as a Means for Improving Satellite Primary Production Estimates

William M. Balch

Bigelow Laboratory for Ocean Sciences, West Boothbay Harbor, Maine

4.1 INTRODUCTION

One of the greatest challenges in providing sea-truth data

for various ocean color sensors is climatology. This is

particularly true in the Gulf of Maine since it is cloudy and

foggy more than it is clear; climatology studies show an

average of about 1 in 4 days of clear skies and that clear days

are slightly more frequent in the late summer and early fall.

Our strategy has been to use a ship of opportunity where one

has a choice of sampling days. This provides much better

flexibility to sample during clear periods with good satellite

coverage. Our SIMBIOS contract is to use the M/S Scotian

Prince ferry as a ship of opportunity, running between

Portland, Maine and Yarmouth (NS). Measurements include

continuous, surface, along-track fluorescence, two

independent measures of backscattering, total light scattering,

absorption, beam attenuation, above-water remote sensing

reflectance, calcite-dependent light scattering, temperature,

and salinity. Expendable Bathythermograph (XBT) drops

allow acquisition of vertical temperature information, useful

for defining isopycnal slope, which affects primary

production. These data are comparable to a previous program

from early 1982, where a Ship Of Opportunity Program

(SOOP) was run on the truck ferry, M/V Marine Evangeline,

which ran along the same transect (Boyd, 1985). These

surface data were combined with satellite-derived sea surface

temperature fields to examine the Maine coastal current

(Bisagni et al., 1996). Unfortunately, this program stopped in

1982. The ongoing SIMBIOS results will dovetail nicely with

the previous work (which also had CZCS coverage) for

studying long-term changes in the Gulf of Maine

hydrography, bio-optics, and biogeochemistry.

The Gulf of Maine is an ideal site for such a SOOP

program. It is a semi-enclosed basin with an average depth of

~150m. Isopycnal slope (and productivity) appears to be

strongly topographically driven, with the water column

becoming isothermal at the 60m isobath around Georges

Bank. Integrated productivity in the region varies seasonally

by a factor of 45x (0.1 to 4.4 gC m-2 d-1; O'Reilly, 1987),

greater than in the California Current (15x variability; 0.2-3.0

gC m-2 d-1). The Marine resources Monitoring Assessment

and Prediction (MARMAP) data base along the eastern

seaboard of the U.S. has been the equivalent to the California

Cooperative Oceanic Fisheries Investigation (CalCOFI) data

base (west coast) in terms of its sheer size and length of

sampling. Unfortunately, MARMAP does not maintain data

collection of pigment or inherent optical properties, thus this

SIMBIOS Project provides unique data for the region. 

4.2 RESEARCH ACTIVITIES

In this SIMBIOS contract, we have completed the

following during the second year:

" May-October '99: Twenty cruises aboard M/S Scotia

Prince completed between Yarmouth, Nova Scotia and

Portland, ME, as required by our contract.

" One 8 day cruise aboard the R/V Linke in the Gulf of

Maine.

" Initial data submissions to be followed by more results as

discrete analyses of POC/PON, PIC, and cell counts are

completed. The final cruise of this year was completed

10/16/99; the following raw data are being worked up for

distribution to the NASA SIMBIOS Project as soon as all

post cruise calibrations are finished (at ~0.5 km

resolution).

Our field measurements include surface flow-through biooptics, and above-water optical measurements, hydrographic

measurements, discrete samples for calibration.

Flow-Through System

Our flow-through system is equipped with several

sensors, with data integration and logging performed by

National Instruments LabView software run on two pentium

processor computers. The system receives time and ship

geographic position continually from a Garmin 220 global

positioning system, the antenna of which is mounted outside

of the ship, off the stern. Seawater first enters a vortex

debubbler (SUNY UDB1), then into a 4 foot tall debubbler,

equipped with a 1mm screen to keep the largest zooplankton

and salps out of the optical instrumentation, then the flow

enters an InterOcean thermal conductivity sensor (see below).

Following the temperature/salinity measurements, the flow

bifurcates into a Turner 10au fluorometer for monitoring
SIMBIOS Project Annual Report

31

underway fluorescence and a tertiary debubbler prior to

measurments of light scattering. The fluorometer is equipped

with a daylight white F4T5D lamp, blue-violet excitation filter

(peak excitation 438nm with half band pass of 380-500nm)

and red emission filter (high pass interference filter passing all

wavelengths >665nm. Due to fast growing bio-fouling

organisms in the Gulf of Maine, the fluorometer is cleaned

regularly.

As for the light scattering measurements, the water

passes from the tertiary debubbler, via peristaltic pump, into a

Wyatt Technologies Model Dawn laser light scattering

photometer at a flow-rate of ~9 ml min-1. The photometer

operates with an 10 mW Argon ion laser (514 nm) which is

directed into the center of a flow-through cuvette, whereupon,

seawater is viewed by 15 photodiodes arranged between

21.54o

 and 158.14o. Included in the 18 detectors are two

photodiodes for laser power monitoring (one prior to passage

through the viewing cuvette, and one post). The laser beam

has a 1/e2

 gaussian beam profile radius of 0.39 mm which

makes the effective viewing volume of the light-scattering

photometer 0.25 ml. All detectors are scanned at rates up to

400 HZ. In fact, for most flow-through applications, we slow

the scanning rate to 200 HZ in order to not sample the same

seawater volume twice.

The LabView software, which controls the Wyatt light

scattering photometer, can be programmed to calculate

averages and standard deviations of seawater volume

scattering data to any desired time period. For field

applications, we typically average the data for about 50

seconds (which then represents an effective volume viewed of

9ml). The statistics are highly informative for understanding

the variance of the optics due to particle types. Because of our

interest in calcite, we also measure seawater pH to verify that

the pH is sufficiently high such that calcite cannot dissolve.

Following the first 50s of measurements done on each raw

seawater sample, another peristaltic pump is activated by the

LabView control system, which injects 0.5% glacial acetic

acid into the flow stream, and mixes it by running it through a

Teflon mixing column. This drops the pH to about 5.8 to

dissolve any calcium carbonate. Once the pH stabilizes at the

more acidic value, volume scattering is re-sampled, and

average backscattering re-calculated. The difference between

the raw and acidified backscattering values represents the

"acid-labile" backscattering. Using field measurements, we

have calibrated this acid-labile backscattering to atomic

absorption estimates of suspended calcite concentration

(r2

=0.83). The time for a complete acidification cycle can be

adjusted, but we have preferred to collect average

backscattering values such that one complete raw/acidification

cycle takes 4 minutes. This means that during any passage,

we would be logging a data point about once every 2000

meters. For sea-truth measurements, this is adequate since

typically a 3 pixel by 3 pixel area from SeaWiFS is viewed

(10.9 km2

).

Water next flows into an AC-9 (Wet Labs, Oregon). This

instrument simultaneously measures spectral beam attenuation

and spectral absorption at nine wavelengths using a dual path

optical scheme. Fundamentally, this consists of two pressure

housings, with the absorption and attenuation beam paths in

between. The absorption light path passes through a reflective

tube while the attenuation light path passes through a nonreflective tube. A rotating filter wheel provides the 9 different

wavelengths, between 412-715 nm. The accuracy of the

attenuation and absorption measurements are +0.005m-1 with

linearity error of +0.1%. With access to attenuation (c) and

absorption (a) information, we calculate b (= c - a).

The last in-flow measurement is done by the Hobie Labs

Hydroscat-2. This instrument is set to view an enclosed, 20l,

sand-blasted, stainless steel containor (painted flat black

within). This vessel has a “sweepable” brush inside to remove

bubbles from the viewing window. The instrument measures

volume scattering at 142o

, and extrapolates to backscattering

using an assumed volume scattering function. It makes

measurements at 470 and 676nm plus chlorophyll

fluorescence.

Above-water optical measurements

Water-leaving radiance and downwelling irradiance (for

calculating remote sensing reflectance) is measured from the

Scotia Prince ferry using a Satlantic SeaWiFS Aircraft

Simulator (SAS). This consists of a radiance sensor mounted

on the port bridge wing, and an irradiance sensor mounted on

the compass deck, aft of the bridge, as far from any potentially

shading structures as possible. The radiance detector views

the water forward of any shipwake, at 40o

 from nadir. The

distance of the sensor to the water is ~30m. The direction of

the sensor is changed periodically, as the sun's position

changed, so, when possible, the sensor is viewing the water

90o

 from the sun's azimuth, free from any sun glint. Protocols

for operation and plaque calibration were made according to

SeaWiFS technical memorandum #25 and the NASA

SeaWiFS SEABOAR Experiment. Data in real time are

filtered for sun glint and sea foam by eliminating data with

irradiance reflectance >15%. Between the hours of 1000 and

1400, all data are logged at 10Hz. Outside of this time,

averages of the glint and foam filtered data are logged every

16 seconds. In addition, we also take Microtops sun

photometer measurements when the sun was visible, and the

data are offloaded for distribution to SeaBASS.

Hydrographic samples

Temperature and salinity of the surface flow stream is

measured with an InterOcean thermal conductivity sensor. It

measures salinity with an accuracy of +0.05 Practical Salinity

Units and temperature to an accuracy of +0.1o

C. Hourly XBT

profiles are used to construct one temperature section per trip

from which we can calculate isotherm slope (strongly related

to gradients in integrated primary production and chlorophyll).
SIMBIOS Project Annual Report

32

Discrete Samples

Every hour a water sample was taken for suspended

CaCO3, particulate organic carbon, chlorophyll, and

microscope counts. The technique of Fernandez et al. (1993)

was used to measure CaCO3 concentrations. Briefly, 500 ml

samples were filtered onto 0.4um pore-size polycarbonate

filters, and rinsing first with filtered sea water, then borate

buffer (pH=8) to remove seawater calcium chloride. Filters

were placed in trace metal free centrifuge tubes with 5 ml

0.5% Optima grade Nitric acid (this will also drive off any

14C activity of the coccoliths). Next, the Ca concentration

was measured using atomic absorption spectrometry.

Chlorophyll and particulate organic carbon were

measured according to the JGOFS protocols (JGOFS, 1996)

H/A filters. A 60ml water sample was taken for

coccolithophore and coccolith counts. Brown glass bottles are

rinsed 3X with each sample prior to final filling. Samples are

preserved with 4% buffered formalin and, after the cruise,

settled in 10 ml counting chambers prior to counting detached

coccoliths and plated coccolithophores (Utermohl, 1931,

1958). Microscope enumeration of detached coccoliths and

plated coccolithophores is made using an Olympus BH2

microscope with polarization optics which allows

quantification of birefringent CaCO3 coccoliths, and

coccospheres. For statistical reasons, 200 coccoliths or cells

were counted from each sample, when available.

All of our data from the previous year have been released

to SeaBASS. The data from the 1999 ferry trips are being

finalized now, with final checks of vicarious calibrations.

They will be released to SeaBASS shortly. The continuous

underway data produced in this work is shown below:

" latitude, longitude, time;

" upwelling radiance (uW cm-2 nm-1 sr-1; at 412, 443, 490,

510, 555, 670 and 685 nm);

" downwelling irradiance (uW cm-2 nm-1; at 412, 443, 490,

510, 555, 670 and 685 nm);

" fluorescence (volts) calibrated to hourly discrete

chlorophyll samples;

" backscattering (m-1; at 470, 514 and 676 nm; total and

acid labile backscattering);

" absorption (m-1; at 412, 440, 488, 510, 555, 630, 650, 676

and 715 nm); and

" attenuation (m-1; at 412, 440, 488, 510, 555, 630, 650, 676

and 715 nm).

4.3 WORK PLAN

Our contract calls for 10 ferry trips next year. We

anticipate no problem completing these trips. Moreover, we

anticipate no problems in timely data work-up and submission

as our processing software is now streamlined for post-cruise

calibrations. We will be shipping the Microtops radiometer

back to Goddard next week.

ACKNOWLEDGEMENTS

The personnel of the Prince of Fundy, Ltd ferry company

have been superb to work with; none of this work could have

been accomplished without their exemplary “can-do” attitude.

They have offered us the opportunity to install a stainless steel

pipe off of their sea chest, so we will not have to install our

sampling arm (which has performed well for 30 trips, or

~5200 miles with only one failure). This will streamline our

operation significantly in coming years.

REFERENCES

Bisagni, J. J., D. J. Gifford, and C. M. Ruhsam, 1995: The

spatial and temporal distribution of the Maine Coastal

Current during 1982. Cont. Shelf Res., 1, 1-24.

Boyd, C. M., 1985: Is secondary production in the Gulf of

Maine limited by the availability of food? Arch.

Hydrobiol. Beih., 21, 57-65.

Fernandez, E., P. Boyd, P. M. Holligan, and D. S. Harbour,

1993: Production of organic and inorganic carbon within

a large scale coccolithophore bloom in the North Atlantic

Ocean. Mar. Ecol. Prog. Ser., 97, 271-285.

JGOFS, 1996: Protocols for the Joint Global Ocean Flux

Study (JGOFS) Core Measurements. Report No. 19, Joint

Global Ocean Flux Study, Scientific Committee on

Oceanic Research, International Council of Scientific

Unions, Intergovernmental Oceanographic Commission,

Bergen, Norway, 170 pp.

Utermöhl, H., 1931: Neue Wege in der quantitativen

Erfassungdes Planktons (mit besonderer Berucksichtigung

des Ultraplanktons). Verh. int. Ver. theor. angew.

Limnol., 5, 567-596.

Utermöhl, H., 1958: Zur Vervollkommnung der quantitaiven

Phytoplankton-Methodik. Mitt. int. Ver. theor. angew.

Limnol., 9,1-38.
SIMBIOS Project Annual Report

33

Figure 1. Plot of satellite chlorophyll a vs. ship-measured chlorophyll a for three 1999 SIMBIOS cruises in the

Gulf of Maine with clear sky coverage, spread over the sampling 1999 period. Both Case I and

particle-laden Case II waters are included in this comparison. Note, that the fit of the 1:1 line is best

for the images in which the sensor was closest to nadir viewing (i.e. the sensor was looking through

the least atmosphere). Our work in 1998 and 1999 has also shown that case II waters penetrate

much farther into the Gulf of Maine than previously thought, causing significant errors in the

estimated chlorophyll.
SIMBIOS Project Annual Report

34

Table 1. List of Cruises and deliverables for FY’99 .

Cruise Location Cruise Name Date

Fluorescence

Backscattering

Calcite-dependent

backscattering

Absorption

Scattering

Temperature

and salinity

MicroTops sun

photometer

Stations

Suspended

calcite

Chlorophyll

POC/PON

Coccolith and

Coccolithoph. Con.

Discrete cell count

Lw and Ed

(Satlantic SAS)

Portland, Maine and

Yarmouth (NV)

Ferry 1 22-23

May 1999

√√√√ 9 √√√√√√

Portland, Maine and

Yarmouth (NV)

Ferry 2 4-5

June 1999

√√√√√√√ 9 √√√√√√

Portland, Maine and

Yarmouth (NV)

Ferry 3 5-6

June 1999

√√√√√√√ 8 √√√√√√

Portland, Maine and

Yarmouth (NV)

Ferry 4 9-10

June 1999

√√√√√√√ 9 √√√√√√

Portland, Maine and

Yarmouth (NV)

Ferry 5 18-19

June 1999

√√√√√√√ 10 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 6 19-20

June 1999

√√√√√√√ 10 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 7 20-21

June 1999

√√√√√√√ 9 √√√√√√

Edward Link, gulf of Maine

And Georges Bank

8d 28 June-5 July 1999 √√√√√√√ 20 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 8 1-2

Aug. 1999

√√√√√√√ 8 √√√√√√

Portland, Maine and

Yarmouth (NV)

Ferry 9 9-10

Aug. 1999

√√√√√√√ 9 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 10 22-23

Aug. 1999

√√√√√√√ 9 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 11 23-24

Aug. 1999

√√√√√√√ 8 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 12 11-12

Sept. 1999

√√√√√√√ 9 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 13 12-13

Sept. 1999

√√√√√√√ 9 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 14 13-14

Sept. 1999

√√√√√√√ 8 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 15 22-23

Sept. 1999

√√√√√√√ 9 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 16 23-24

Sept. 1999

√√√√√√√ 10 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 17 24-25

Sept. 1999

√√√√√√√ 9 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 18 7-8

Oct. 1999

√√√√√√√ 8 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 19 11-12

Oct. 1999

√√√√√√√ 9 √√√√√√

Portland, Maine and

 Yarmouth (NV)

Ferry 20 15-16

Oct. 1999

√√√√√√√ 8 √√√√√√

Total Stations 197
SIMBIOS Project Annual Report

35

This research was supported by the

SIMBIOS contract # 97268

PEER REVIEWED PUBLICATION

Balch, William M., David T. et al. 1999: Optical

backscattering by calcifying algae-Separating the

contribution by particulate inorganic and organic carbon

fractions J. Geophys. Res. 104: 1541-1558.

PRESENTATIONS

Balch, B., D.T. Drapeau, et al. 1998: Backscattering of Light

by Calcium Carbonae and Organic Matter in the Sea.

EOS, Trans AGU, 79:OS7.

Balch, W. M., Drapeau, et al.,1999: Backscattering probability

and calcite-dependent backscattering in the Gulf of

Maine. Proceedings of the ASLO Meeting, Santa Fe.

Balch, W.B., H. R. Gordon, et al. 1999: PIC:POC and the

Remote Sensing of Biogenic Carbon in the Sea. In press

Trans. AGU.
SIMBIOS Project Annual Report

36

Chapter 5

OCTS and SeaWiFS Bio-Optical Algorithm and Product

Validation and Intercomparison in U.S. Coastal Waters

Christopher W. Brown

NOAA/NESDIS, Camp Springs, Maryland

Ajit Subramaniam

University of Maryland, College Park, Maryland

Mary Culver

NOAA Coastal Services Center, Charleston, South Carolina

John C. Brock

USGS Center for Coastal Geology, St. Petersburg, Florida

5.1 INTRODUCTION

Monitoring the health of U.S. coastal waters is an

important goal of the National Oceanic and Atmospheric

Administration (NOAA). Satellite sensors, particularly ocean

color sensors, provide the type of measurements and synoptic

coverage that can be used to operationally observe and

examine the quality of U.S. coastal waters. However, the

algorithms used to derive useful geophysical parameters from

satellite ocean color data, such as chlorophyll biomass, in

coastal waters require development and validation. The

majority of available bio-optical algorithms have been derived

using assumptions valid only for the open ocean. In the open

ocean, it is assumed that other optically active constituents,

such as colored dissolved organic matter (CDOM), vary

proportionately with chlorophyll concentration. This

assumption is generally not valid in coastal waters where other

optically active components and pigment concentrations do

not covary. In addition, backscattering due to suspended

sediments and the influence of the bottom must be taken into

account. In this Technical Memorandum, we evaluate the

Sea-viewing Wide Field-of-view Sensor (SeaWiFS)

chlorophyll a algorithm, OC2, for the South Atlantic Bight

(SAB). The SAB consists of a variety of environments

including coastal and continental shelf regimes, Gulf Stream

waters, and the Sargasso Sea. The biological and optical

characteristics of the region is complicated by temporal and

spatial variability in phytoplankton composition, primary

productivity, and the concentrations of CDOM and suspended

sediment. As such, the SAB is an ideal location to test the

robustness of existing algorithms for coastal use and the

development of new ones.

5.2 RESEARCH ACTIVITIES

Bio-optical measurements were collected at 80 stations

during eight cruises (Table 1) conducted in the South Atlantic

Bight in order to evaluate and validate the SeaWiFS OC2 (v2)

chlorophyll concentration algorithm. The cruises covered a

range of seasons (early spring to late fall) and water types

(shallow, turbid Pamlico Sound to deep, clear Sargasso Sea)

(Figure 1). Optical instruments measured surface spectral

downwelling irradiance, in-water spectral downwelling

irradiance, and upwelling radiance. Although sampling

strategies and instrument packages varied between cruises, a

Biospherical Instruments Profiling Reflectance Radiometer

(PRR) cage was typically deployed off the stern of the vessel

in conjunction with a reference surface unit with matching

channels. The PRR optical data were processed using the

Bermuda Bio-Optics Project (BBOP) processing software

(Siegel et al, 1995). Optical profiles that exhibited evidence

of surface perturbations and the effects of passing clouds were

excluded from analysis. Deployment of additional optical

instruments and the collection of water samples enabled

various parameters to be measured, including chlorophyll and

pigment concentrations, total suspended solids concentration,

and the absorption coefficients of CDOM and particles.

Though chlorophyll and pigments concentrations were

determined using both fluorometric and High-Pressure Liquid

Chromatography (HPLC) techniques, only those estimated

using fluorometry were employed in the present analysis. The

ratio of the above-water downwelling irradiance to the

upwelling radiance propagated through the air-water interface

was used to calculate the remote-sensing reflectance, Rrs(λ), at

each station following the technique of O’Reilly et al. (1998).
SIMBIOS Project Annual Report

37

These in situ estimates of Rrs(λ) were fed into the SeaWiFS

OC2 (v2) algorithm to calculate chlorophyll-a concentration,

OC2, where:

OC2 = -0.0929 + 10 (0.2974-2.2429 X + 0.8358X^2 – 0.00771 X^3)

and

(555)

(490) log10

rs

rs

R

R

X =

To evaluate the geographical and temporal variation in

OC2 performance, a ratio (OC2PI) was calculated as the ratio

of OC2-derived chlorophyll concentration to the

fluorometrically determined chlorophyll concentration (ChlF).

An OC2PI value of less/greater than one indicated

underestimation/overestimation of chlorophyll by OC2. Refer

to Subramaniam et al. (1997a, 1997b, 1997c, 1998, 1999) and

Tester et al. (1995) for details on sampling methodology and

processing.

5.3 RESEARCH RESULTS

In situ chlorophyll (ChlF) values ranged from 0.16 to 5.20

μg/L with mean value of 1.51 μg/L and a median value of

1.03 μg/L. While many of the high chlorophyll stations lay

along the coast and the low chlorophyll (0-1 μg/L) stations

were situated along the outer shelf, no distinct spatial pattern

was discernible in the in situ chlorophyll concentrations. The

absence of any obvious pattern in chlorophyll concentration is

likely due to the temporal span over which the data were

collected and the dynamic nature of phytoplankton biomass in

the SAB. For example, surface chlorophyll concentration at a

station located at the shelf break in September 1997 was 0.33

μg/L while a station occupied at the same position in

November 1998 was 1.11 μg/L. This large variation could be

attributable to interactions of the Gulf Stream with the shelf

waters (McClain et al. 1984). Mapping the values of OC2PI

from all cruises revealed no spatial pattern in the algorithm

performance. No correlation between OC2PI and the

measured chlorophyll was observed, suggesting that small

changes in the coefficients or offsets would not substantially

improve the algorithm. Nor was there a correlation between

total suspended material and ChlF, implying that in-water

scattering was not likely the cause of algorithm failure (data

not shown). A large component of the variability in the

performance of OC2 was explained by separating the data

seasonally into “spring”, i.e. February-May, and “non-spring”,

i.e. June-January (Figure 2). During non-spring months, OC2

performance was high (Table 2). During spring months, it

was low with a seasonal average of 2.13, indicating an

overestimation of chlorophyll concentration using OC2. The

spatial distribution and number of stations in the spring and

non-spring periods were similar, eliminating geographic bias.

The bulk of the variability was attributable to measurements

collected at coastal stations sampled during periods of high

river run-off. The high CDOM content during months of

elevated river discharge yielded low remote-sensing

reflectances at 490 nm, Rrs490, independent of the

chlorophyll content of these waters. We evaluated the

performance of the default SeaWiFS chlorophyll-a algorithm,

OC2 (v2), in the South Atlantic Bight by comparing

radiometrically-derived chlorophyll concentrations and

measured chlorophyll concentrations. The results indicate that

biogeographical provinces alone do not improve OC2

performance in the SAB. Seasonal variation must be taken

into account. The high variability observed in spring is likely

due to the presence of high concentrations of CDOM in shelf

waters. For an algorithm to accurately estimate chlorophyll

concentration in the SAB, it must explicitly include CDOM as

a factor.

ACKNOWLEDGEMENTS

This work was accomplished in partnership with the

NOAA Coastal Services Center (CSC), other federal and state

agencies, and academic institutions. We thank Dr. P. Tester

for the use of her data.

REFERENCES

McClain, C.R., L.J. Pietrafesa, and J.A. Yoder, 1984:

Observations of Gulf Stream-induced and wind-driven

upwelling in the Georgia Bight using ocean color and

infrared imagery. Journal of Geophysics 89, 3705-3723.

O’Reilly, J. E., S. Maritorena, B. G. Mitchell et al., 1998:

Ocean color chlorophyll algorithms for SeaWiFS. Journal

of Geophysical Research 103(C11): 24937-24953.

Siegel, D.A., M.C. O’Brien, J.C. Sorensen, D.A. Konnoff and

E. Fields, 1995: BBOP Data Processing and Sampling

Procedures. Vol: 19, Institute for Computational Earth

System Science, UC Santa Barbara, Santa Barbara, CA,

23pp.

Subramaniam, A., E.M. Armstrong et al., 1997a: NOAA

CSC/CRS Cruise MAR97OCC: OCTS Calibration

Cruise. CSC Technical Report CSC/5-97/001.

Subramaniam, A., E.M. Armstrong et al.,1997b: NOAA

CSC/CRS Cruise MAY96NY: New York Bight Apex

Cruise. CSC Technical Report CSC/6-97/001.

Subramaniam, A., K.J. Waters et al.,1997c: NOAA CSC/CRS

Cruise APR96FER: Gray’s Reef Cruise. CSC Technical

Report CSC/7-97/001.

Subramaniam, A., J.C. Brock et al., 1998: NOAA NMFS

Cruise MAY97OB: Onslow Bay and Pamlico Sound

Cruise. CSC Technical Report CSC/2-98/001.
SIMBIOS Project Annual Report

38

Subramaniam, A., C.W. Brown et al., 1999: Comparison of

algorithms to determine chlorophyll concentration from

satellite coean color in three regions: South Atlantic

Bight. CSC Technical Report 99032-PUB.

Tester, P.A., M.E. Geesey, C. Guo, H.W. Paerl, and D.F.

Millie, 1995: Evaluating phytoplankton dynamics in the

Newport River estuary (North Carolina, USA) by HPLCderived pigment profiles. Mar. Ecol. Prog. Ser. 124:237-

245.

Figure 1. Location of Stations in the South Atlantic Bight.

Table 1. Summary of cruise names, location, dates and sampling platforms used.

Cruise Dates Number of

stations

Location Vessel

FEB96LIT 2/22-23/96 3 Georgia Bight R/V Blue Fin

APR96BF 4/3-5/96 2 Georgia Bight R/V Blue Fin

APR96FER 4/22-25/96 12 Georgia Bight R/V Blue Fin

MAY97OB 5/5/97 and 5/8/97 5 and 4 Onslow Bay NC and

Pamlico Sound NC

R/V Onslow Bay

R/V Chipman

SEP97SAB 9/5-24/97 8 South Atlantic Bight R/V Cape Hatteras

NOV97SAR 11/4-5/97 5 Sargasso Sea R/V Palmetto

APR98SAB 4/5-27/98 17 South Atlantic Bight R/V Cape Hatteras

NOV98SAB 10/27/98-11/23/98 24 South Atlantic Bight R/V Cape Hatteras
SIMBIOS Project Annual Report

39

Figure 2. Spatial distribution of OC2PI for “spring” (Left) and “non-spring” (Right)

Table 2. OC2PI by season and cruise

“Spring” Cruises Average OC2PI “Non-spring” Cruises Average OC2PI

APR98SAB 2.52 SEP97SAB 1.19

APR96FER,BF 1.83 NOV97SAR 1.41

FEBLIT96 3.90 NOV98SAB 0.97

MAY97OB 1.30

Seasonal average 2.13 Seasonal average 1.08

Total stations 43 Total stations 37
SIMBIOS Project Annual Report

40

This research was supported by the

SIMBIOS NASA interagency agreement # 97879

OTHER PUBLICATIONS

Subramaniam, A., E.M. Armstrong et al., 1997a: NOAA

CSC/CRS Cruise MAR97OCC: OCTS Calibration

Cruise. CSC Technical Report CSC/5-97/001.

Subramaniam, A., E.M. Armstrong et al.,1997b: NOAA

CSC/CRS Cruise MAY96NY: New York Bight Apex

Cruise. CSC Technical Report CSC/6-97/001.

Subramaniam, A., K.J. Waters et al.,1997c: NOAA CSC/CRS

Cruise APR96FER: Gray’s Reef Cruise. CSC Technical

Report CSC/7-97/001.

Subramaniam, A., J.C. Brock et al., 1998: NOAA NMFS

Cruise MAY97OB: Onslow Bay and Pamlico Sound

Cruise. CSC Technical Report CSC/2-98/001.

Subramaniam, A., C.W. Brown et al., 1999: Comparison of

algorithms to determine chlorophyll concentration from

satellite coean color in three regions: South Atlantic

Bight. CSC Technical Report 99032-PUB.

PRESENTATIONS

Geesey, M. , M. Culver, A. Subramaniam, G. DiTullio, and J.

Brock. 1998: Optical and biological variability in the

South Atlantic Bight. Conference for Collaborative

Research Activities in the South Atlantic Bight.

Culver, M. E., K. J. Waters, A. Subramaniam, D. A. Phinney,

W. M. Balch, and D. T. Drapeau. 1998: Closure of

inherent and apparent optical properties at a coastal

station in the Gulf of Maine. Ocean Optics XIV.

Subramaniam, A. M.E. Culver, P.A. Tester, C.W. Brown, J.C.

Brock. 1998: An Evaluation of the OC2 SeaWiFS

Algorithm Performance in the South Atlantic Bight.

Ocean Optics XIV.

Eslinger, D. L., M. E. Culver, D. Aurin, R. Swift, and F. Hoge.

1999: A Comparison of Active and Passive Ocean Color

in Southeastern U.S. Coastal Waters. Estuarine Research

Federation.
SIMBIOS Project Annual Report

41

Chapter 6

Validation of Ocean Color Satellite Data Products in Under

Sampled Marine Areas

Douglas G. Capone and Ajit Subramaniam

Chesapeake Biological Laboratory, Solomons, Maryland

6.1 INTRODUCTION

During the period September 1998 to September 1999, we

under took two cruises to fulfill our obligations to the

SIMBIOS program – Indian Ocean Experiment (INDOEX)

and Searcher99. The INDOEX cruise was coordinated with

the Scripps Institution of Oceanography group lead by Dr.

Flatau. Dr. Flatau has been charged with the responsibility of

assembling all the data collected during this field campaign to

submit a comprehensive data report to the SIMBIOS Project.

The Searcher99 cruise was conducted in July-August 1999 in

the Baltic Sea and is described below. We also worked on

developing and implementing a global Trichodesmium

algorithm described below.

6.2 RESEARCH ACTIVITIES

Field Campaign

The R/V Ronald H. Brown left Mauritius on Leg 1 of the

INDOEX cruise on the 22 February 1999 and arrived in Male,

Maldives on 1 March 1999.

Leg 2 of the cruise extended from 4 March to 23 March

1999 and Leg 3 from 26 March to 30 March 1999 (Figure 1,

Table 1). Stations were occupied almost everyday. Each

station consisted of a CTD cast for pigments (fluorometric and

HPLC), absorption – particulate and dissolved, primary

production measurements; an optics cast for MER

measurements of downwelling irradiance, upwelling radiance

and irradiance, AC9 measurements of total absorption,

Hydroscat measurements of spectral backscatter, FRRF

measurements of variable fluorescence; and a SPMR cast for

downwelling irradiance and upwelling radiance. Ten liters of

water (1 niskin bottle) were filtered for Trichodesmium counts

at select stations. On clear days, the SIMBAD and a Spectrix

above-water reflectance radiometer was used to measure

remote-sensing reflectance. The counts data showed that there

was the beginning of a bloom when we headed north (stations

36-39), but we did not find any Trichodesmium after 3 days

when we headed south. Unfortunately, there were no clear

SeaWiFS images of this region during this time. The SPMR

free falling spectroradiometer was used on all stations in legs

2 and 3. Above the surface downwelling irradiance and

upwelling radiance 75 cm below the surface was measured

using the floating reference SMSR.

Figure 1. INDOEX Station Locations (Stations 23-30 Leg2 AEROSOLS, 31-36 Leg 1, 37-

50 Leg2, 51-54 Leg 3). Surface Trichodesmium colonies/L from select stations.
SIMBIOS Project Annual Report

42

Water column profiles of downwelling irradiance and

upwelling radiance were measured using the free-falling

SPMR. The diffuse attenuation coefficient was calculated

from the profile data and was then used to propagate the

upwelling radiance from 75 cm below the surface to water

leaving radiance. This water leaving radiance was then used

with the SMSR downwelling irradiance to calculate the

normalized water leaving radiance (Figure 2). The second

cruise we participated in was in the Baltic Sea with scientists

from the Botany Department and the Department of Natural

Geography at Stockholm University. On these cruises we

made measurements of total and organism specific absorption

spectra, absorption due to detrital material, absorption due to

CDOM, total suspended material. Surface water samples were

also taken for pigment concentrations using HPLC techniques

and chlorophyll a using the spectrophotometric method. We

measured the above-water remote sensing reflectance using a

hyperspectral spectrometer and the aerosol optical thickness

using a sunphotometer. We also made in situ profiles of the

light field at 13 wavelengths using the Satlantic SPMR freefalling spectroradiometer with a floating surface reference. A

total of nine stations were occupied between 27 July and 18

August 1999. Eight of the nine days were clear and had good

satellite images that showed wide spread blooms in central and

southern Baltic proper. We have processed most of the in situ

data and are in the process of matching them to the satellitederived data. Initial analyses of the above-water hyperspectral

reflectance data suggest that the optical model derived for

Trichodesmium is applicable to the Baltic cyanobacterial

blooms. The biggest difference we have noticed is that the

Nodularia blooms are extremely rich in carotenoids,

increasing the absorption around 480 nm. The total absorption

spectra in a bloom show a shoulder at spectra (Figure 3). The

remote sensing reflectance spectra show that the blooms have

a high backscatter.

Development of A Trichodesmium Chlorophyll Specific

Algorithm

We have not yet been successful in inverting the

Trichodesmium optical model to derive an algorithm for

detecting this organism. There are probably many factors that

contribute to the problem including difficulties with

atmospheric correction in the presence of a highly scattering

bloom. While we are still moving forward with attempts to

invert our model, we also proceeded on another approach to

derive a Trichodesmium classification based on training pixels

from Trichodesmium rich waters. We applied this

classification on two years of 9 km, 8-day binned Level 3

SeaWiFS data to map Trichodesmium globally. The map thus

derived showed Trichodesmium in regions and seasons where

they have been historically noted. But we are not quite

satisfied with the robustness of this approach and we will

continue to improve on our techniques as we acquire more

SeaWiFS imagery with concurrent ground truth. We are also

working on applying the empirically derived algorithm on

daily 1-km resolution HRPT data from north-western

Australia and the Gulf of Mexico,

6.3 WORK PLAN

We will participate in the Yellow Trich Road Cruise off

northern Australia in October-November 1999. This cruise is

scheduled to occur at a time when Trichodesmium blooms are

most common in those waters and we look forward to making

significant progress on the algorithm with this data. Initial

analysis of the Baltic SeaWiFS images has given us a better

understanding of patchy surface phenomenon and we intend to

return to the Baltic in summer 2000. But we intend to spend

majority of the time on refining the Trichodesmium algoritm.
SIMBIOS Project Annual Report

43

Figure 2. SPMR/SMSR based normalized water leaving radiance measurements for INDOEX legs 2 & 3.

Figure 3. Absorption spectra of cultures of Nodularia and Aphanizomenon compared to total absorption

measured at stations 3d and 8b.

                    





  

     





                                





                       



        

 



         





           



             











 

  

















Absorption Spectra

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

350 400 450 500 550 600 650 700 750

Wavelength (nm)

Relative absorption units



station 8b

Aphanizomenon

Nodularia

station 3d
SIMBIOS Project Annual Report

44

This research was supported by the

SIMBIOS NASA contract # 97131

PEER REVIEWED PUBLICATIONS

Capone, D.G., A. Subramaniam, J.P. Montoya, M. Voss, C.

Humborg, F. Pollehne and E.J. Carpenter, 1998: An

extensive bloom of the diazotrophic cyanobacterium,

Trichodesmium erythraem, in the central Arabian Sea

during the spring intermonsoon. Marine Ecology

Progress Series. 172:281-292.

Accepted

Carpenter, E.J, J.P. Montoya, J. Burns, M.R. Mulholland, A.

Subramaniam, and D.G. Capone, 1999: Extensive bloom

of a N2 fixing symbiotic association in the tropical

Atlantic Ocean. Marine Ecology Progress Series, in press.

PRESENTATIONS

Cota, G.F., W.G. Harrison, T. Platt, and S. Sathyendranth,

1998. OCTS ocean color and AVHRR observations in the

Labrador Sea. Ocean Sciences Meeting, San Diego, EOS

Transactions 79(1) Suppl: OS81. Feb 9-13

Dupouy, C., J. Neveux, B. Fougnie, S. Colzy, and A.

Subramaniam. 1999. Trichodesmium: an oceanic nitrogen

fixer as detected by POLDER. Symposium ALPS'99,

Colloque International et Ateliers, CNES, 18-23, January

1999, Meribel, France, Ocean Color P-01, pp. 1-5.

Dupouy, C., J. Neveux, A. Subramaniam, M. Mulholland, L.

Campbell, J. Montoya, E. Carpenter, D. Capone. 1999:

SeaWiFS captures a persistent Trichodesmium bloom in

the Southwestern Tropical Pacific Ocean. EOS Trans.

AGU.

Flatau, P., B. G. Mitchell, A. Subramaniam, J. Weldon, J.

Wieland, K. Voss, R. Frouin, and J. Porter, 1999:

Combined ocean color and atmospheric radiometeric

measurements on R/V Ronald Brown ship during the

Indian Ocean Experiment (INDOEX). 10th Conference

on Atmospheric Radiation , 28th June - 2nd July 1999.
SIMBIOS Project Annual Report

45

Chapter 7

Stray Light and Atmospheric Adjacency Effects for Large-FOV,

Ocean Viewing Space Sensors

Kendall L. Carder

University of South Florida, St. Petersburg, Florida

7.1 INTRODUCTION

The radiance of dark targets (e.g. oceans and lakes) when

measured by large-field imagers such as MODIS and

SeaWiFS can be enhanced by stray light within the sensor and

by radiance atmospherically scattered from bright, adjacent

targets. One of the goals of this project is evaluation of this

stray light and estimation of its effect on derived products of

remote color imagery.

7.2 RESEARCH ACTIVITIES

Calibration

In accordance with SeaWiFS protocols, semiannual

calibrations at facilities at the University of Arizona (UA)

were conducted. The handheld radiometers known as Spectrix

(SPX) and the Labsphere reflectance targets are calibrated in

the labs of the Remote Sensing Group (RSG) (P. Slater, S.

Biggar, and K. Thome). Additional calibrations are conducted

at the UA Steward Observatory on nearby Mt. Lemon. RSG

provides calibration services and groundtruth for a host of

hyperspectral satellite sensors including LANDSAT,

SeaWiFS, OCTS, and some European sensors.

Radiometric calibration of the SPX is achieved with a 1m

Spherical Integrating Source (SIS) and the RSG portable

transfer radiometer (Biggar, 1998). Specific details of the SIS

calibration are contained in the calibrations reports for each

period. The red-rich tungsten calibration is supplemented with

a blue-rich, solar-based calibration on Mt. Lemon. The solarbased radiometric calibration (SBRC) method compares the

total downwelling irradiance to the diffuse downwelling

irradiance. The difference in the two measurements is the

direct solar beam which is assumed to be constant (at the top

of the atmosphere) and known from previous work (Thuiller

et al., 1998). The Steward Observatory on Mt. Lemon,

Arizona is at an elevation of 2791m ASL and experiences

light continental aerosol loading. It provides a convenient

location to conduct accurate SBRC's. Two Reagan

autotracking solar radiometers provide the aerosol optical

thicknesses at 10 wavelengths. The calibrations are conducted

in the spring and fall to bracket the field work and to coincide

with the lowest aerosol concentrations at Mt. Lemon.

Field Experiments

 This project collected field data to evaluate the

performance of SeaWiFS. Field sites were selected where

adjacency artifacts would be likely. One site is a deep ocean

canyon surrounded by bright carbonate banks, the Tongue of

the Ocean (TOTO); another is Lake Okeechobee, Florida

where dark water is surrounded by bright vegetation (in the

infra-red, IR). With funding from other sources, additional

field experiments were applied to this study and help with

evaluation of SeaWiFS performance. These included sampling

on Tampa Bay, the West Florida Shelf, Exuma Sound, the San

Juan Islands in Puget Sound, and Lake Tahoe.

Modeling efforts

One aspect of the project was a modeling effort

simulating different atmospheric adjacency scenarios. Two

are included here, one is a hole in the clouds and the other is a

dark target surrounded by bright areas (in the visible but not

the IR). The cloud hole is a 3-D problem requiring a complex

Monte Carlo simulation to generate the atmospheric adjacency

effect. Figure 1 demonstrates how clouds affect downwelling

irradiance at the sea surface. All calculations use Elterman's

(1968) atmosphere with water Fresnel reflectance and about a

2% diffuse reflectance. For a 10 km diameter hole in clouds

and a 400

 solar zenith angle, the Esky_d(550)/F0(550) varies

as observer moves away from hole center. Note that

Esky_d(550)/F0(550)=0.28 for a "no-cloud" scenario and 0.33

near the hole center. The clouds can increase downwelling

irradiance from the sky by 18% even when they are 5 km

away.

The second model is for a dark target surrounded by

bright reflectivity, similar to a 10 km diameter lake or

embayment with a shallow bright banks. The model results

shows that proximity to land does not effect Esky_d(550).

The dark target scenario is a 2D problem and thus much

simpler than the cloud problem. To evaluate stray light

problems on satellite sensors, dark targets like lakes or ocean

areas surrounded by bright land or shoal regions are much
SIMBIOS Project Annual Report

46

easier to correct for atmospheric adjacency effects than are

holes in clouds.

7.3 RESEARCH ACTIVITIES

Tongue of the Ocean

To confirm the results for a dark target surrounded by

bright shallow banks, reflectance measurement were made at

the Northwest Passage of the Tongue of the Ocean (Bahamas)

during SeaWiFS pass on 4 April 1999. The ship results

confirm the uniformity of the reflectance right up to the edge

of the banks. Atmospherically-corrected remote sensing

reflectance measured by SeaWiFS is significantly higher than

the actual reflectance. Samples from the northwest passage of

the Tongue of the Ocean (250

 25’N and 780 00’W) are shown

in Figure 2, demonstrate this effect for a row of SeaWiFS

pixels along the centerline of the canyon. The other sites were

even closer to the edge of the canyon. Using these

reflectances to generate chlorophylls with the Carder global

algorithm can lead to a four fold over estimation compared to

chlorophylls generated from the field reflectance

measurements using the sample pigment algorithm (Figure 3)

which are consistent with fluorometrically measured

chlorophyll a concentrations.

Algorithm Evaluation

The degradation of SeaWiFS infrared bands, which are

used to evaluate the type and amount of aerosol path radiance,

caused a perturbation in the type of aerosol correction to be

made by the SeaWiFS atmospheric correction scheme. This

resulted in over estimation of the blue-richness of the aerosol

scattering. Furthermore, high cirrus clouds have a tendency to

exaggerate this effect, due to enhanced aerosol absorption in

the oxygen band near 762 nm. To obviate the worst effects of

both problems, we developed an aerosol-typing algorithm

using bands 6 and 8 over clear waters. This approach forced

the calibration of band 6 relative to band 8 to provide

normalized water-leaving radiance values at band 6 consistent

with the Gordon and Clark (1981) for scenes with known

aerosol type. For scenes of unknown aerosols, the new 6-8

band combination delivered appropriate aerosol types with

SEADAS. This prevented blue exaggeration of the aerosol

type and prevented excessive removal of blue radiance from

the scene, which otherwise would have resulted in blue-poor

water-leaving radiance values. This approach provided

atmospherically-corrected scenes that did not go negative at

blue wavelengths for gelbstoff-rich (blue-absorbing) areas..

This approach also provided clear water, normalized waterleaving radiance values at 555 nm consistent with Gordon and

Clark (1981) using the calibration factors distributed by the

SeaWiFS Project on 6 January 1998. Furthermore, it provided

a data distribution for clear waters using ratios of bands 1 and

2 versus bands 2 and 5 that are consistent with those found by

Carder et al. (1999) using the SeaBASS in situ data set. Using

the above calibration scheme, SeaWiFS images of the TOTO,

the West Florida Shelf, and regions between were compared to

field data using the default NASA chlorophyll algorithm and

the Carder et al. (1999), MODIS-like, semianalytic

chlorophyll algorithm. For these spring scenes, the pigments

were somewhat packaged with little in the way of

photoprotective pigments. Both algorithms performed

similarly (within 5%) for Case 1 waters. When gelbstoff

absorption overwhelmed the pigment absorption, however, the

semianalytic algorithm delivered chlorophyll values within

25% of measured values, while the default NASA algorithm

over estimated chlorophyll by as much as a factor of 4. These

scenes will be re-evaluated with the new calibrationdegradation curves of SEADAS 3.2 during the next contract

year, but the new results are not expected to deviate

significantly from these results using the 6-8 band

combination except for turbid waters. In terms of evaluating

atmospheric adjacency and stray light effects due to infrared

radiance emanating from the bright foliage surrounding Lake

Okeechobee or blue-green light reflected from the bright

shallow banks surrounding TOTO, our preliminary findings

suggest the following:

• Lake Okeechobee has so much horizontal variability in

the water-leaving radiance field at infrared wavelengths

that it is at times an impractical site at which to evaluate

stray infrared light from its surrounds. It does offer,

however, so much gelbstoff absorption at 412 nm that we

are considering performing atmospheric corrections based

upon the blue end of the spectrum.

• Data we collected at the Friday Harbor Laboratory in the

San Juan Islands suggest that this site provides a viable

alternative to Lake Okeechobee for evaluation of stray

infrared light and/or atmospheric adjacency effects.

PHILLS aircraft data Curtis Davis (NRL) suggests that

one can find a red-edge effect (exaggerated infrared light)

in the water near sunlit tree lines in data collected at

10,000 feet and with visibility in excess of 50 km. These

data will be evaluated next year along with SeaWiFS data

collected at high resolution over Griffin Bay (San Juan

Island) which is surrounded by forest land.

• Field chlorophyll values farther than 2 pixels offshore and

east from bright, shallow banks of the TOTO were not

significantly different than those found farther offshore.

Extreme caution must be taken, however, to avoid

misinterpreting conditions where gelbstoff- and particleladen waters from the shallows are transported offshore.

The semianalytic model (Carder et al. 1999) provided

estimated chlorophyll values from field reflectance

spectra within 15% of measured values, however, with

values largely unaffected by CDOM effects. Seawifs Rrs

data near the banks over estimated by as much as a factor

of two, providing chlorophyll over estimates of 3X for a

station surrounded on three sides by bright carbonate

banks. New AVIRIS data will permit separation of stray
SIMBIOS Project Annual Report

47

light from atmospheric adjacency effects. Next year an

evaluation of the electronic over-shoot, and/or hysteresis

on the west sides of bright targets will also be evaluated

on the eastern edge of the TOTO. More accurate

calibration of the SeaWiFS sensor will help in this effort.

• A recently published paper by Reinersman et al. (1998)

on calibration of aircraft and small footprint, spacecraft

sensors using cloud shadows was dependent upon the

development of a Monte Carlo model of radiance from

single spherical clouds. This model is being modified to

permit evaluation of atmospheric adjacency effects of

clouds on radiance values received by a space sensor

when viewing the ocean through an opening (elliptical

cylinder) in a cloud bank. Algorithms that are more

immune to the adjacency effects of clouds will be sought.

Much of the light scattered into the sensor from clouds

will be from molecules and stratospheric aerosols and thin

cirrus clouds. A strategy using the effect of the oxygen

absorption line on band 7 versus results from bands 6 and

8 may provide an indication of the effective height of any

aerosol scattering for SeaWiFS, whereas MODIS has a

cirrus discriminator built into its data processing scheme

REFERENCES

Biggar, S. 1998: Calibration of a visible and near-infrared

portable transfer radiometer. Metrologia, 35:701-706.

Carder, K.L., F.R. Chen, et al.,1999: Semianalytic Moderate

Resolution Imaging Spectrometer algorithms for

chlorophyll a and absorption with bio-optical domains

based on nitrate-depletion temperatures. Journal of

Geophys. Res. 104(C3): 5403-5421

Elterman, L. 1968: UV, visible, and IR attenuation for

altitudes to 50km . Rep. AFCRL-68-0153, US Air Force

Cambridge Research Laboratory, Bedford, MA.

Gordon, H.R. and D.K.Clark , 1981: Clear water radiances for

atmospheric correction of coastal zone color scanner

imagery. Applied Optics. 20: 4175-4180.

Neckel, H. and D. Labs, 1984: The solar radiation between

3300 and 12 500 Å. Solar Physics, 90: 205-258.

Reinersman, P.R. and K.L. Carder, 1995: Monte Carlo

simulation of the atmospheric point spread function with

an application to correction for the adjacency effect.

Appl. Opt. 34:4453-4471.

Reinersman, P.R., K.L. Carder, and F.R. Chen, 1998:

Satellite-sensor calibration verification with the cloudshadow method. Applied Optics, 37(24):5541-5549.

Thuillier, G. M. Hersé et al., 1998: The visible solar spectral

irradiance from 350-850 nm as measured by the

SOLSPEC spectrometer during the ATLAS 1 Mission,

Solar Physics, 177(1-2): 41-61.

Figure 1. Comparsion of two Monte Carlo models of atmospheric adjacency effects: a 10km hole in the clouds

and 10km lake surrounded by bright banks.

0

0 .1

0 .2

0 .3

0 .4

0 .5

0 .6

0 .7

-1 0 -5 0 5 1 0

D is ta n c e fr o m c e n te r (k m )

Downward diffuse irradiance

 Ed_sky (550) (fraction of TOA value)

H o le in c lo u d D a r k ta r g e t s u r r o u n d e d b y b r ig h t
SIMBIOS Project Annual Report

48

Figure 2. Comparison of remote sensing reflectance from field stations & row of SeaWiFS pixels for 4 April 99.

Figure 3. Comparison of fluorometrically measured chlorophyll concentrations to those derived from SeaWiFS

and field reflectances for TOTO2 sites.

TOTO2 Rrs(550) 

0

0.0005

0.001

0.0015

0.002

0.0025

0.003

0 5 10 15 20

Pixels / stations

Seawifs

Field sites

A C

F



  



   



  



   

TOTO2 Chl Comparison

0

0.5

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1.5

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ABCDEFG

Site

mg/m^3





Measured

Field Rrs-derived

SEAWIFS - derived
SIMBIOS Project Annual Report

49

This research was supported by the

SIMBIOS NASA contract # 97137

PEER REVIEWED PUBLICATIONS

Bissett, W.P., J.J. Walsh, D.A. Dieterle, K.L. Carder. 1999:

Carbon cycling in the upper waters of the Sargasso Sea: I.

Numerical simulation of differential carbon and nitrogen

fluxes. Deep Sea Res. (46)2: 205-269.

Bissett, W.P., K.L Carder, J.J. Walsh, D.A. Dieterle, 1999:

Carbon cycling in the upper waters of the Sargasso Sea:

II. Numerical simulation of apparent and inherent optical

properties. Deep Sea Res. (46)2: 271-317.

Carder, K.L., F.R. Chen, Z.P. Lee, S.K. Hawes, D.

Kamykowski, 1999: Semianalytic Moderate Resolution

Imaging Spectrometer algorithms for chlorophyll a and

absorption with bio-optical domains based on nitratedepletion temperatures. Journal of Geophys. Res.

104(C3): 5403-5421.

D'Sa, E.D., R.G. Steward, A. Vodacek, N.V. Blough, D.

Phinney, 1999: Determining optical absorption of colored

dissolved organic matter in seawater with a liquid

capillary waveguide. Limnol. Oceanogr. 44(4): 1142-

1148.

Lee, Z. P., K.L. Carder, C. D. Mobley, R.G. Steward, and J.S.

Patch, 1998: Hyperspectral Remote Sensing for Shallow

Waters: 1. A Semi-analytical Model. Applied Optics,

37(27): 6329-6338.

Lee, Z., K.L. Carder, C.D. Mobley, R.G. Steward, and J. S.

Patch, 1999: Hyperspectral Remote Sensing for Shallow

Waters: 2. Deriving Bottom Depths and Water Properties

by Optimization. Applied Optics, 38(18): 3831-3843

Lee, Z., K.L. Carder, R.G. Steward, T.G. Peacock, C.O. Davis

and J.S. Patch, 1998: Empirical Ocean Color Algorithms

for Absorption Coefficients of Optically Deep Waters.

Journal of Geophysical Research,103(12): 27,967-27978.

Reinersman, P.R., K.L. Carder, and F.R. Chen, 1998:

Satellite-sensor calibration verification with the cloudshadow method. Applied Optics, 37(24): 5541-5549.

Accepted

D'Sa, E.J., J.B. Zaitzeff, and R.G. Steward, 1999: Remote

salinity and ocean color monitoring: Aspects and

performance in a coastal environment. In International

Conference on Satellite, Oceanography and Society. Ed.

D. A. Halpern.

Zaitzeff, J.B., E.J. D'Sa, C.S. Yentsch, J.L. Miller, R.G.

Steward, R. Ives, 1999: Rapid remote assessments of

salinity contrasts in Florida Bay and bio-optical

variability. In Linkages Between Ecosystems in the

South Florida Hydroscape: The River of Grass Continues.

(Eds) J.W. Porter and K.G. Porter.

Submitted

D'Sa, E.D., J.B. Zaitzeff, and R.G. Steward. 1999: Monitoring

water quality in Florida Bay with remotely sensed salinity

and in situ bio-optical observation. Submitted to

International J. of Remote Sensing.

Hu, C., K.L. Carder, and F. Muller-Karger, 1999:

Atmospheric correction of SeaWiFS imagery over turbid

coastal waters: a practical method. Submitted to Remote

Sensing of Environ.

Hu, C., K.L. Carder, and F. Muller-Karger, 1999:

Atmospheric correction of SeaWiFS imagery: assessment

of alternative bands. Submitted to Appl. Opt.
SIMBIOS Project Annual Report

50

Chapter 8

Bio-Optical Measurements at Ocean Boundaries in Support of

SIMBIOS

Francisco P. Chavez

Monterey Bay Aquarium Research Institute, Moss Landing, California

8.1 INTRODUCTION

The equatorial Pacific is a major component of global

biogeochemical cycles, due to upwelling that occurs from the

coast of South America to beyond 180°. This upwelling has

significant implications for global CO2 fluxes (Tans et al.,

1990; Takahashi et al., 1997; Feely et al., 1999), as well as

primary and secondary production (Chavez and Barber, 1987;

Chavez and Toggweiler, 1995; Chavez et al., 1996; Dugdale

and Wilkerson, 1998; Chavez et al., in press; Strutton and

Chavez, submitted). In addition, this region of the world’s

oceans represents a large oceanic province over which

validation data for SeaWiFS are necessary. This project

consists of a mooring program and supporting cruise-based

measurements aimed at quantifying the spectrum of biological

and chemical variability in the equatorial Pacific and obtaining

validation data for SeaWiFS. The project has the following

general objectives:

" to understand the relationships between physical forcing,

primary production, nutrient supply and the exchange of

carbon dioxide between ocean and atmosphere in the

equatorial Pacific;

" to describe the biological and chemical responses to

climate and ocean variability;

" to describe the spatial, seasonal and inter-annual

variability in near surface plant pigments, primary

production, carbon dioxide and nutrient distributions; and

" to obtain near real-time bio-optical measurements for

validation of SeaWiFS and subsequent ocean color

sensors.

8.2 RESEARCH ACTIVITIES

Moorings

Chavez et al. (1998; in press) and McClain and Fargion

(1999, p.44) describe the configuration of the MBARI biooptical and chemical instruments deployed at 0°, 155°W and

2°S, 170°W; two of the 70 moorings which form the Tropical

Atmosphere Ocean (TAO) array. In addition, MBARI also

maintains smaller bio-optical packages at sites in the

equatorial Pacific: 2°N, 180°; 2°S, 140°W and 2°N, 110°W.

For the time being, the site which was maintained at 2°N,

140°W has been discontinued because of a change in mooring

design at that site which precluded deployment of the

instruments, and the loss of three of the original ten packages,

which has made instrument rotation and timely calibration

more difficult.

From 0°, 155°W and 2°S, 170°W, daily local noon (ie

approximate time of SeaWiFS overpass) bio-optical and

chemical data are transmitted via service ARGOS in near real

time to MBARI, and then via automated FTP to the SeaBASS

database, after some processing and quality control. Higher

frequency, publication-quality data (10 or 15-minute intervals)

are recovered at approximately six month intervals, and sent to

the SeaBASS database after processing and quality control.

Derived products, such as Kλ, OC2V2 chlorophyll, mean

chlorophyll over the upper 20m of the water column (Morel,

1988) and water leaving radiance (Lw) are included in these

data files for validation efforts. Lw is currently calculated via

three different methods:

1. The diffuse attenuation coefficient (Kλ) over the upper

20m of the water column is calculated using Ed3m+ and

Ed20m, then using this Kλ , Lu 20m is extrapolated back to

the surface and multiplied by 0.544 to derive Lu 0m+. This

should be the most reliable method because the 3m+ and

20m instruments are less susceptible to fouling than the

OCR-100s moored at ~1.5m.

2. Using the Satlantic OCP and SPMR optical profile data

from equatorial Pacific cruises in 1997 and 1998, an

empirical relationship between Lu 1.5m and Lu 0m+ was

derived. Thus the Satlantic OCR-100 data (Lu 1.5m-) from

the moorings are used to calculate Lu 0m+. Attenuation

over the upper 1.5m of the water column is likely to have

a negligible effect on the derivation of Lw, but this

method could be improved to account for such variability.

The OCR-100 instruments are protected from bio-fouling

by a TBT ring, which is effective for approximately three

months. Estimates of Lw using this method are probably

inferior to the previous method after this time.
SIMBIOS Project Annual Report

51

3. Lu0m- can be derived from a simple, two point log-linear

extrapolation of Lu 20m and Lu 1.5m to the surface, then

multiplied by 0.544 as above to derive Lu 0m+. For the

same reasons discussed above this method is probably

unreliable after approximately three months.

In situ measurements

Table 1 summarizes the cruises undertaken by MBARI

thus far in support of SIMBIOS. Essentially, the cruise-based

measurements consist of chlorophyll (using the fluorometric

method described by Chavez et al., 1995) and nutrient profiles

(8 depths, 0-200m) obtained at CTD stations between 8°N and

8°S across the Pacific from 95°W to 165°E. On selected

cruises (the 155°W and 170°W meridional transects), primary

productivity (14C) measurements and optical profiles, using

the Satlantic SeaWiFS Profiling Multispectral Radiometer

(SPMR), are also performed. These data are archived at

MBARI and the chlorophyll and optical profile measurements

provided to the SeaBASS database.

8.3 RESULTS

Biogeochemical cycles

Several publications have been produced under MBARI’s

SIMBIOS funding. Chavez et al. (1998) used mooring data

from 0°, 155°W to describe the biological-physical coupling

observed in the central equatorial Pacific during the onset of

the 1997-98 El Niño. Chavez et al. (in press) combine the

physical, biological and chemical data from moorings, ships

and SeaWiFS to provide a comprehensive view of the the

ecosystem’s response to the extreme physical forcings

experienced during the 1997-98 El Niño. Strutton and Chavez

(submitted) summarize the in situ cruise measurements

spanning the period from November 1996 to December 1998,

and use these data to describe the perturbations to chlorophyll,

nutrients and productivity during the same time period.

SeaWiFS Calibration/Validation

The comparisons between MBARI SPMR-derived Lw

and SeaWiFS have revealed very close agreement. Figure 1(a)

shows matchups obtained between October 1997 and June

1998. It should be noted that the 1997 matchups (2 of the 5

shown) were made using the SPMR’s predecessor, the Ocean

Color Profiler (OCP), which was deployed without a surface

reference unit. The data indicate that the OCP/SPMR provide

excellent validation data, and these measurements will

continue. But as with all ship-based matchup data, the

percentage of measurements which meet the stringent criteria

for matchup inclusion is small, which illustrates the

importance of mooring validation data.

During 1998 the SIMBIOS validation team has begun to

incorporate the MBARI mooring data into the

calibration/validation effort. Figure 1(b) summarizes the best

300 matchups (78% of total) of the initial analysis performed

in June 1999.

8.4 WORK PLAN

During 2000 data collection will continue as for 1998 and

1999. The two major mooring installations at 0°, 155°W and

2°S, 170°W are now operating well, as are the smaller biooptical packages at three additional locations (2°N 110°W,

2°S 140°W, 2°N 180°). The program of cruise-based

measurements of chlorophyll, nutrients, primary productivity

and bio-optical profiles will continue on up to eight equatorial

Pacific cruises during 2000, with scheduled SeaWiFS LAC

where applicable, to enhance the probability of obtaining valid

matchups.

During 1999 our data processing and data provision

capabilities have improved, and the majority of the mooring

data can now be downloaded and plotted via the web at:

http://quillback.shore.mbari.org/~bog/mooring.html.The major

data analysis project for 2000 is to improve the algorithms for

derivation of Lw, and to develop a stringent set of quality

control routines.

REFERENCES

Chavez, F.P., and R.T. Barber, 1987: An estimate of new

production in the equatorial Pacific. Deep-Sea Research,

34, 1229-1243.

Chavez, F.P., K.R. Buck, R.R. Bidigare, D.M. Karl, D. Hebel,

M. Latasa, L. Campbell and J. Newton, 1995: On the

chlorophyll a retention properties of glass-fiber GF/F

filters. Limnology and Oceanography, 40, 428-433.

Chavez, F.P. and J. R. Toggweiler, 1995: Modern Processes

and Ancient Records. in Upwelling in the Ocean, C. P.

Summerhayes, K. C. Emeis, M. V. Angel, R. L. Smith,

B. Zeitzschel, Eds. (J. Wiley & Sons, Chichester), 313-

320.

Chavez, F.P., K.R. Buck, S.K. Service, J. Newton and R.T.

Barber, 1996: Phytoplankton variability in the central and

eastern tropical Pacific. Deep-Sea Research, 43(4-6), 835-

870.

Chavez, F.P., P.G. Strutton, and M.J. McPhaden, 1998:

Biological-physical coupling in the central equatorial

Pacific during the onset of the 1997-98 El Niño.

Geophysical Research Letters, 25(19), 3543-3546.

Chavez, F.P., Strutton, P.G., Friederich, G.E., Feely, R.A.,

Feldman, G., D. Foley and M.J. McPhaden, 1999:

Biological and chemical response of the equatorial Pacific

Ocean to the 1997-98 El Niño. Science, in revision.
SIMBIOS Project Annual Report

52

Dugdale, R.C. and F.P. Wilkerson, 1998: Silicate regulation of

new production in the equatorial Pacific upwelling,

Nature, 391, 270-273.

Feely, R.A., R. Wanninkhof, T. Takahashi and P. Tans, 1999:

Influence of El Niño on the equatorial Pacific contribution

to atmospheric CO2 accumulation. Nature, 398, 597-601.

McClain, C.R. and G.S. Fargion., 1999: SIMBIOS Project

1998 Annual Report. NASA Tech. Memo. 1999-208645,

Eds., NASA Goddard Space Flight Center, Goddard,

Maryland, 105pp.

Morel, A., 1988: Optical modeling of the upper ocean in

relation to its biogenous matter content (Case I waters).

Journal of Geophysical Research, 93, 10749-10768.

Strutton, P.G. and F.P. Chavez, 1999: Primary productivity in

the equatorial Pacific during the 1997-98 El Niño.

Submitted to JGR Oceans.

Tans, P.P., I. Y. Fung, T. Takahashi, 1990: Observational

constraints on the global atmospheric CO2 budget,

Science 247, 1431-1438.

Takahashi, T., R.A. Feely, R.F. Weiss, R. Wanninkhof, D.W.

Chipman, S.C. Sutherland and T.T. Takahashi, 1997:

Carbon dioxide and climate change. Proceedings of the

National Academy of Sciences, 94, 8314-8319..

Table 1. Summary of cruises during which in situ data have been obtained by MBARI in support of SIMBIOS. All

cruises were undertaken aboard the NOAA ship Ka’imimoana, with the exception of GP6-98-RB and GP8-99-RB aboard the

NOAA ship Ronald H. Brown. Meridional transects indicate the lines occupied by the ship. Along each line, CTD stations

were performed approximately every degree of latitude from 8°N to 8°S. Measurements consisted of extracted chlorophyll

(Chl) plus nitrate, phosphate and silicate (Nutrients) at 8 depths between 0 and 200m. On selected cruises, primary productivity

(PP) measurements were also made using 14C incubation techniques, and daily optical profiles with the Satlantic Profiling

Multispectral Radiometer (SPMR) were obtained. During GP7-98-KA, GP3-99-KA and GP7-99-KA, a SIMBAD radiometer

was also used, on loan from the SIMBIOS instrument pool.

Cruise ID Dates Meridional transects Measurements

GP6-97-KA 27-Sep-97 to 30-Oct-97 125°W and 140°W Chl, PP, Nutrients, SPMR

GP7-97-KA 06-Nov-97 to 17-Dec-97 155°W, 170°W and 180° Chl, PP, Nutrients, SPMR

GP1-98-KA 05-Feb-98 to 13-Mar-98 95°W and 110°W Chl, Nutrients

GP2-98-KA 18-Apr-98 to 20-May-98 125°W and 140°W Chl, Nutrients

GP3-98-KA 02-Jun-98 to 03-Jul-98 155°W and 170°W Chl, PP, Nutrients, SPMR

GP4-98-KA 07-Jul-98 to 03-Aug-98 165°E and 180° Chl, Nutrients

GP5-98-KA 05-Sep-98 to 09-Oct-98 125°W and 140°W Chl, Nutrients

GP6-98-RB 11-Oct-98 to 13-Nov-98 95°W and 110°W Chl, Nutrients

GP7-98-KA 19-Oct-98 to 13-Nov-98 155°W and 170°W Chl, PP, Nutrients, SPMR

GP8-98-KA 18-Nov-98 to 12-Dec-98 180° and 170°W Chl, Nutrients

GP1-99-KA 22-Jan-99 to 24-Feb-99 125°W and 140°W Chl, Nutrients

GP2-99-KA 30-Apr-99 to 04-Jun-99 95°W and 110°W Chl, Nutrients

GP3-99-KA 30-Jun-99 to 30-Jul-99 155°W and 170°W Chl, PP, Nutrients, SPMR

GP4-99-KA 04-Aug-99 to 01-Sep-99 165°E and 180° Chl, Nutrients

GP5-99-KA 09-Sep-99 to 14-Oct-99 125°W and 140°W Chl, Nutrients

GP7-99-KA 20-Oct-99 to 14-Nov-99 155°W and 170°W Chl, PP, Nutrients, SPMR

GP8-99-RB 1-Nov-99 to 10-Dec-99 95°W and 110°W Chl, Nutrients

GP9-99-KA 18-Nov-99 to 12-Dec-99 180° and 170°W Chl, Nutrients
SIMBIOS Project Annual Report

53

Figure 1. SeaWiFS matchups performed by the SIMBIOS calibration/validation team for in situ data obtained from (a)

the Satlantic SPMR optical profiler and (b) MBARI moorings in the equatorial Pacific.

SeaWiFS Lw490 vs Mooring Lw490

0.1

1

10

0.1 1 10

Mooring Lw490 [uW cm-2 nm-1 sr-1]

SeaWiFS Lw490 [uW cm-2 nm-1 sr-1]

0° 155°W

2°S 170°W

2°N 110°W

2°N 140°

2°N 180°

b

SeaWiFS Lw vs SPMR Lw

0.1

1

10

0.1 1 10

SPMR Lw [uW cm-2 nm-1 sr-1]

SeaWiFS Lw [uW cm-2 nm-1 sr-1]

Lw412

Lw443

Lw490

Lw510

Lw555

a
SIMBIOS Project Annual Report

54

This research was supported by the

SIMBIOS NASA contract # 97134

PEER REVIEWED PUBLICATIONS

Chavez, Francisco P., Peter G. Strutton and Michael J.

McPhaden, 1998: Biological-physical coupling in the

central equatorial Pacific during the onset of the 1997-98

El Niño. Geophysical Research Letters, 25(19): 3543-

3546.

Chavez, Francisco P., Peter G. Strutton, Gernot E. Friederich,

Richard A. Feely, Gene Feldman, Dave Foley and

Michael J. McPhaden, 1999: Biological and chemical

response of the equatorial Pacific to the 1997-98 El Nino.

In Revision Science.

Accepted

Chavez, Francisco P., Dave Wright, Robert Herlien, Michael

Kelley, Farley Shane and Peter G. Strutton, 1999: A

device for protecting moored spectroradiometers from

bio-fouling. In press, Journal of Atmospheric and

Oceanic Technology

Submitted

Strutton, Peter G. and Francisco P. Chavez, 1999: Primary

productivity in the equatorial Pacific during the 1997-98

El Niño. Submitted to Journal of Geophysical Research.

PRESENTATIONS

Chavez, Francisco, Gene Feldman, Michael McPhaden, David

Foley and Peter Strutton, 1998: Remote Sensing of the

Equatorial Pacific during 1997-98. AGU Fall Meeting,

San Francisco, CA.

Friederich, Gernot, Francisco Chavez, Peter Strutton and Peter

Walz, 1998: Bio-optical and Carbon Dioxide Time Series

From Moorings in the Equatorial Pacific During 1997-

1998. AGU Fall Meeting, San Francisco, CA.

Strutton, Peter G., Francisco P. Chavez and Michael J.

McPhaden, 1998: Biological-physical coupling in the

central equatorial Pacific during the 1997-98 El Niño.

Ocean Optics XIV, Kailua-Kona, HI.

Strutton, Peter G., Francisco P. Chavez and Michael J.

McPhaden, 1998: Primary productivity in the equatorial

Pacific during the onset of the 1997-98 El Nino.

AGU/ASLO Ocean Sciences Meeting, San Diego, CA.

Strutton, Peter G., Francisco P. Chavez and Michael J.

McPhaden, 1998: Primary productivity in the equatorial

Pacific during the onset of the 1997-98 El Nino. Pacific

Climate Workshop, Catalina Island.

Strutton, Peter G., Francisco P. Chavez and Michael J.

McPhaden, 1998: In situ measurements of primary

productivity in the equatorial Pacific during the 1997-98

El Niño. AGU Fall Meeting, San Francisco, CA.

Strutton, Peter, Francisco Chavez, David Foley, Brian

Schlining and Michael J. McPhaden, 1999: Remote

Sensing of Biological-Physical Coupling in the Equatorial

Pacific. ASLO Ocean Sciences Meeting, Santa Fe, NM.
SIMBIOS Project Annual Report

55

Chapter 9

Remote Sensing of Ocean Color in the Arctic: Algorithm

Development and Comparative Validation

Glenn F. Cota

Old Dominion University, Norfolk, Virginia

9.1 INTRODUCTION

The purpose of this project is to acquire a large biooptical database, encompassing most environmental variability

in the Arctic ocean, to develop algorithms for phytoplankton

biomass and production and other optically active

constituents. To that end a large suite of bio-optical and

biogeochemical observations are being collected in a variety

of high latitude ecosystems at different seasons. The Optical

Research Consortium of the Arctic (ORCA) is a collaborative

effort between G.F. Cota of Old Dominion University (ODU),

T. Platt and W.G. Harrison of the Bedford Institute of

Oceanography (BIO), S. Sathyendranath of Dalhousie

University and S. Saitoh of Hokkaido University. ORCA has

now conducted 10 cruises and collected about 500 in-water

optical profiles plus a variety of ancillary data. All qualityassured data have been submitted to NASA's SeaBASS data

archive. Observational suites typically include apparent optical

properties (AOPs), inherent optical property (IOPs), and a

variety of ancillary observations including sunphotometery

and biogeochemical profiles. Our algorithm development

efforts address most of the potential bio-optical data products

for SeaWiFS, MODIS and GLI, and provides validation for a

specific areas of concern, i.e. high latitudes and coastal waters.

9.2 RESEARCH ACTIVITIES

Of two scheduled cruises on ships of opportunity neither

were completed. The first cruise (CCG Hudson to the

Labrador Sea) was decreased in duration and slipped two

months. It was cancelled because it conflicted with the second

cruise (USCG Polar Star to the Chukchi Sea). The later

icebreaker cruise was cancelled the day before departure due

to mechanical problems. Consequently, no additional arctic

field data were collected this year. Research efforts were

focussed on data reprocessing and analysis, match-up analysis,

modeling, and synthesis for presentation and publication. Our

Labrador Sea data sets have played a central role in NASA’s

and NASDA’s validation efforts for OCTS. Recent effort has

been concentrated on synthesizing that part of our database.

Satlantic Inc. has recently released new software with

improvements and additional capabilities such as batch

processing. All early optical data sets have been reprocessed

to insure internal consistency and all will be resubmitted to

SeaBASS. In most cases the changes in derived products are

small (<1-2%), but can be 10-15% in the worst cases. PERL

code has been developed to attach SeaBASS style headers for

Satlantic (SPMR/SMSR) and WETLabs (AC-9) profiles. This

code will be made available to the project. Our Satlantic data

from 1994 and 1995 have compromised 412 nm surface

irradiance values, but otherwise these data are of high quality.

The SeaWiFS and SIMBIOS Projects have been informed of

this. The 1998 Labrador Sea (Lab98) data set remains

problematic. The downwelling irradiance Ed sensor

malfunctioned during Lab98, and the data processing required

modifications of Satlantic software. Additional ancillary data

are also being submitted as they become available from our

lab and collaborators. For example, triplicate chlorophylls

were collected concurrently with triplicate optical profiles

during our Labrador Sea cruises, and these are being

submitted with the reprocessed optical data sets.

Data sets also have been made available to additional

investigators. Our current chlorophyll algorithm for the Arctic

was supplied to Bernie Walters for his research on detection of

surface slicks with SAR. Jay O’Reilly has recently compared

his spectral 1324 indices for our entire data set with the

OC2V2 data set. The data sets will soon be made widely

available on the web. Our web site is being updated and

expanded to include optical data, many value-added products,

and a variety of ancillary information. Cruise reports, station

sheets, photos of sky and sea state, instrument specifications,

calibration histories, etc. will be available. Similarly results

from on-going analyses and intercomparisons will be

highlighted.

9. 3 RESEARCH RESULTS

Regional comparisons have been made between in situ

observations and bio-optical models tuned with high latitude

data. High latitude waters have unique bio-optical properties

compared with temperate data and models (e.g. Mitchell 1992,

Sathyendranath et al. 1999a,b). There is a large dynamic

range for biomass, which must be considered in algorithm

development. Diatoms usually dominate phytoplankton

assemblages, but prymnesiophyte blooms may alter bio-
SIMBIOS Project Annual Report

56

optical signatures (Sathyendranath et al. 1999a). Relatively

large diatom cells in polar waters are highly packaged (~90%)

with low chlorophyll-specific attenuation compared with

temperate ecosystems. Attenuation due to soluble matter also

varies regionally with the highest values in our northernmost

study site, the Canadian Arctic Archipelago near Resolute

Bay. Discrepancies between the high latitude bio-optical data

and operational chlorophyll algorithms for SeaWiFS and

OCTS can be marked, especially at bloom concentrations.

Chlorophyll retrievals from the Labrador Sea with OC2V1

were over threefold to high at 25 mg Chl m-3, whereas

OC2V2 yields values twofold to low (Cota et al. 1999).

Similar results are obtained for the Canadian Arctic

Archipelago. Better agreement is found in the Bering Sea, but

our data set covers a very limited range and is dominated by

low values (< 3 mg Chl m-3). Optical models for lower

latitude do not describe the high latitude data sets well.

Sathyendranath et al. (1999a) employed a diatom-specific

absorption spectrum with very low relative chlorophyllspecific absorption to obtain better agreement. Cota et al.

(1999) have confirmed that chlorophyll-specific absorption by

phytoplankton is low relative to temperate ecosystems, and

that soluble absorption by colored dissolved organic matter

(CDOM) constitutes 60 – 95% of total particulate absorption

in the blue and blue-green algorithm channels. Backscattering

must be very low (<0.3%) and an inverse function of

chlorophyll to obtain better agreement in simulations with

HydroLight (Mobley 1994) tuned with our absorption spectra

for various constituents. Several approaches for estimating

primary production in the Arctic are being evaluated. Simple

empirical band ratio algorithms explain 80% and 50% of the

observed variability between surface chlorophyll and

integrated net daily production, respectively. Predictions from

more complex production models are being compared to

observations after being tuned with high latitude data. Yoder's

MODIS production algorithm (pers. comm., Howard and

Yoder 1997) is a depth-integrated model employing satellite

chlorophyll, daily PAR, SST, and climatologies for MLD.

When tuned this model underestimated observed production

with a slope of 0.74 and explained 42% of the variance. This

discrepancy resulted primarily from melting ice, which made

the observed MLD 3-10 times shallower than climatological

estimates. Their estimated KPAR would also be considerably

higher than observed values at higher biomass levels. Another

depth-integrated model by Behrenfeld and Falkowski (1997)

utilizes similar environmental inputs and a temperaturedependent Popt derived from productivity profiles. Their

tuned model also underpredicted production with a slope of

0.55, but explained 56% of the variance. Compound errors in

satellite predictions of production from satellite chlorophyll

could be two to fourfold underestimates. Reasons for the

performance of various models are being explored.

9.4 WORK PLAN

Cruise plans for 2000 include a spring (May) cruise in the

Labrador Sea and a summer (June-July) cruise in the Chukchi

Sea. As proposed ORCA will conduct 1-3 cruises per year on

average. We will contribute critical core observational data as

well as a variety of ancillary bio-optical and biogeochemical

data. All core observations will continue to be delivered

within 90 days (spectroradiometer profiles, fluorometric

chlorophyll, and normally particulate and dissolved absorption

spectra). Additional observations for which ODU has primary

responsibility for will be delivered within 12 months, and

contributions from international collaborators will be

submitted as they become available. Our goal is to make raw

data and derived products generally available via the web but

our site is still under construction. Efforts in 2000 will

concentrate on collection of comprehensive bio-optical data

sets, data analyses, modeling, and publication of results.

Emphasis will be placed on above-water vs. in-water

comparisons.

ACKNOWLEDGEMENTS

Additional support was provided by Canada's Department

of Fisheries and Oceans, Natural Resources Canada, and

NASDA. The author thanks T. Platt, S. Sathyendranath, W.G.

Harrison and S. Saitoh.

REFERENCES

Behrenfeld, M.J. and P.G. Falkowski, 1997: Photosynthetic

rates derived from satellite-based chlorophyll

concentration. Limnol Oceanogr. 42: 1-20.

Cota, G.F., W.G. et al., 1999: Ocean color and temperature

observations in the Labrador Sea. subm J. Geophys. Res..

Howard, K.L and J.A. Yoder, 1997: Contribution of the

subtropical Oceans to global primary production. in: Liu,

C.-T. (ed.) Space Remote Sensing of Subtropical Oceans,

pp. 157-168, Pergamon, London.

Mitchell, B.G., 1992:Predictive bio-optical relationships for

polar oceans & marginal ice zones. J. Mar.Syst.3: 91-105.

Mobley, C. D., 1994. Light and Water: Radiative Transfer in

Natural Waters. Academic Press, San Diego. 592pp.

Sathyendranath, S., G. Cota, et al., 1999a: Remote Sensing of

phytoplankton pigments: A comparison of empirical and

theoretical approaches. in press Intl. J. Rem. Sens.

Sathyendranath, S., T. Platt, V. Stuart, H. Maass and G. Cota,

1999b: Remote sensing of phytoplankton biomass and

primary production. Aquabiology 21: 17-22.
SIMBIOS Project Annual Report

57

This research was supported by the

SIMBIOS NASA contract # 97132

PEER REVIEWED PUBLICATIONS

Sathyendranath, S., G. Cota, V. Stuart, H. Maass and T. Platt,

1999: Remote sensing of phytoplankton pigments: A

comparison of empirical and theoretical approaches. Intl.

J. Remote Sensing in press.

Sathyendranath, S. T. Platt, V. Stuart, H. Maass and G. Cota,

1999: Remote sensing of phytoplankton biomass and

primary production. Aquabiology 21: 17-22.

PRESENTATIONS

Cota, G.F., 1997: Bio-optical properties of high northern

latitude waters. 7th Japan-US Workshop on Ocean Color,

Atami, Japan.

Cota, G.F., 1997: Arctic bio-optical algorithms. National

Space Development Agency/Ocean Color and

Temperature Sensor, Yokihama, Japan.

Cota, G.F. and S. Saitoh, 1997: Bering Sea bio-optical

algorithms. National Space Development Agency, Ocean

Color and Temperature Sensor Meeting, Yokihama,

Japan.

Cota, G.F., 1997: Bio-optical properties of Arctic coastal

waters. ASLO meeting, Santa Fe, New Mexico.

Cota, G.F. and S. Saitoh, 1998: Bering Sea bio-optical

studies. 8th Japan-US Workshop on Ocean Color, Kona,

HI.

Cota, G.F., 1998: Bio-optical variability in Resolute Passage,

Canadian Arctic. Ocean Optics XIV, Kona, HI.

Cota, G.F., W.G. Harrison, T. Platt, and S. Sathyendranth,

1998: OCTS ocean color and AVHRR observations in the

Labrador Sea. Ocean Sciences Meeting, San Diego, EOS

Transactions 79(1) Suppl: OS81.

Cota, G.F., 1998: High latitude bio-optical algorithms.

National Space and Development Agency, Global Line

Imager Meeting, Tokyo, Japan.

Cota, G.F., T. Platt, S. Sathyendranath, and W.G. Harrison,

1998: Remote sensing of ocean color and sea surface

temperature in the Labrador Sea. Canadian

Meteorological and Oceanographic Society Meeting,

Dartmouth, Nova Scotia.

Cota, G.F. and W.G. Harrison, 1998:Climate-driven

variability of primary productivity in the Northwest

Passage. Canadian Meteorological and Oceanographic

Society Meeting, Dartmouth, Nova Scotia.

Cota, G.F., 1999: Satellite-based productivity in the Arctic.

Arctic System Science,Ocean-Atmosphere-Ice Interaction

meeting, Virginia Beach, VA.

Cota, G.F., 1999: Arctic primary production from space.

ASLO Meeting, Santa Fe, NM.

Platt, T., S. Sathyendranath, G. Harrison, G. Cota, 1998:

Remote sensing of the Labrador Sea: Results from the

Ocean Color and Temperature Sensor experiment.

COSPAR Meeting, Nagoya, Japan.

Sathyendranath, S., T. Platt, G.F. Cota, V. Stuart and G.A.

Borstad, 1997: Modeling and interpreting ocean-colour

data. First Workshop on MOS-IRS and Ocean Colour,

DLR Institute of Space Sensor Technology, Berlin,

Germany.

Sathyendranath, S. T. Platt, G. Cota, V. Stuart and G. Borstad,

1997: Modelling and interpreting ocean-colour data. First

Workshop on MOS-IRS and Ocean Colour, DLR Inst.

Space Sensor Technology and Planetary Exploration,

Berlin.

Sathyendranath , S., G. Cota, V. Stuart, H. Maass, and T. Platt,

1998. An ocean-colour model for the Labrador Sea and

comparisons with empirical remote-sensing algorithms.

Ocean Optics XIV, Kona, HI
SIMBIOS Project Annual Report

58

Chapter 10

High Frequency, Long Time Series Measurements from the

Bermuda Testbed Mooring in Support of SIMBIOS

Tommy Dickey, Laura Dobeck, David Sigurdson,

Sarah Zedler, Derek Manov and Xuri Yu

University of California at Santa Barbara, Santa Barbara, California

10.1 INTRODUCTION

Few in situ data are presently available for groundtruthing

and algorithm development for ocean color satellites.

However, mooring methodology allows for collection of very

high temporal resolution, long-term time-series data. Moored

measurements have several important advantages including

the ability to obtain high numbers of "match-up" data for

comparisons with ocean color satellites such as SeaWiFS.

However, the use of moorings for obtaining optical data is a

relatively new and quite challenging approach. To date,

moored radiometric measurements have been attempted by

only a few groups (e.g., Dickey, 1991; Smith et al., 1991;

Clark et al., 1997; Chavez et al., 1997; Dickey et al., 1998a).

Moored optical observations are more difficult than their shipbased counterparts for several reasons (e.g., less frequent

calibration, biofouling, etc.). The Bermuda Testbed Mooring

(BTM) has been used as a mooring-of-opportunity in order to

provide the SIMBIOS program with high frequency, longterm time-series bio-optical data for use in SeaWiFS satellite

calibration and validation activities. The BTM program began

in mid-1994 at a site located about 80km southeast of

Bermuda (31° 43' N, 64° 10' W) in-waters of about 4530m

depth (Dickey et al., 1997, 1998a). A schematic of the BTM

mooring array, a geographic map indicating the mooring

location, and a depiction of the data telemetry system are

shown in Figure 1. Key NASA supported BTM optical

measurements have included: surface downwelling spectral

irradiance (7 λ's, SeaWiFS matched: λ = 412, 443, 490, 510,

555, 665, and 683nm;10nm bandwidth at half power) and

subsurface downwelling spectral irradiance and upwelling

spectral radiance (7 λ's for each, SeaWiFS matched). Data

are collected at 6Hz for 45sec every hour during daylight and

at midnight. Products derived from the measured radiometric

quantities include spectral attenuation coefficients, spectral

reflectance ratios, and water-leaving radiances. These data

provide necessary links to and interpolation of radiometric

data for remotely sensed observations of ocean color (e.g.,

SeaWiFS color imager), which can be used to estimate

biomass and primary productivity globally. A recently

developed telemetry system provides near real-time BTM

radiometric data to the UCSB Ocean Physics Laboratory. We

have also developed a software system to make key data

available to the SIMBIOS Project on a daily basis. Highly

complementary, value-added meteorological, bio-optical, and

physical data products are provided through our

complementary NSF/ONR/NOPP BTM studies (e.g., Dickey

et al., 1998a). Our comprehensive measurements can be used

to relate bio-optical signals to inherent optical properties and

to biogeochemical measurements and to test interdisciplinary

models of phytoplankton productivity and carbon flux. In

addition, these data can be used to study key environmental

parameters (e.g., wind speed, sea-state, etc.), which affect

SeaWiFS determinations of water-leaving radiance.

10.2 RESEARCH ACTIVITIES

The BTM provides very high temporal resolution data as

illustrated by the Deployment 11 (April 1, 1999 – July 20,

1999) spectral upwelled radiance time-series (Figure 2).

During the first year of the project, the proof-of-concept was

demonstrated, particularly by showing that BTM radiometric

data and ship profile radiometric data (collected by the

Bermuda Bio-optical Project (BBOP; e.g., Siegel et al., 1995)

matched quite well when recently calibrated radiometers were

available. This is supported by the strong correlations between

BTM time-series data and BBOP ship-based profile data,

which were available during 15 of the ~130 days of

Deployment 11 (Figure 3). The second year of our project has

focused on determining ways to best assure consistently high

quality data, which can be used for evaluating and

groundtruthing SeaWiFS data as a precursor to algorithm

development. Two important aspects of this particular phase

of the work involve calibration of radiometers and the optimal

deployment of radiometers (number of sampling depths and

placements). In regard to the first issue, continuous in situ

calibration is not possible for moored instruments; therefore,

BTM radiometric data are processed with pre-deployment and

post-deployment factory calibrations. In addition, these data

are compared with available concurrent BBOP shipboard
SIMBIOS Project Annual Report

59

profiling measurements and SeaWiFS data. Most recently, we

have begun to apply a series of quality control and consistency

tests, which were developed by Jay O'Reilly, to the BTM data.

In the past, we have generally deployed radiometers at the

surface and at two subsurface depths, because of limited

numbers of systems. Again, because of the lack of a sufficient

number of radiometers, it has not always been possible to

calibrate all radiometers prior to deployment. For Deployment

11, we added a radiometer system at the 7m depth to

determine if improved estimates of water-leaving radiance

would be obtained. Most recently for Deployment 12, we

added two more radiometer systems bringing the total to 5

subsurface systems. Deployment 12 is still in the field, but

preliminary results from Deployment 11 suggest that use of

three subsurface radiometer systems may improve estimates,

particularly under high wind and sea-state conditions. One of

the key findings of the project thus far is that regular (pre- and

post-deployment) calibration of BTM radiometers is critical.

An especially striking and important highlight of our analysis

of Deployment 11 is that BTM and SeaWiFS determinations

of water-leaving radiance are very similar (Figure 4). We are

presently exploring the effects of wind speed. Hurricane Gert

passed fairly close to the BTM in September 1999

(Deployment 12). Thus, we are hopeful that the high wind

and sea-state conditions accompanying Hurricane Gert will

enable us to better quantify such effects on SeaWiFS and

BTM water-leaving radiance. In summary, we have

demonstrated that moorings-of-opportunity, such as the BTM,

can provide large volumes of useful radiometric measurements

for groundtruthing and algorithm development for ocean color

satellite imagers. Further, it appears that BTM data sets will

be quite useful for developing satellite correction algorithms

for various environmental and undersampling effects.

10.3 WORK PLAN

 Future directions include quantifying effects and biases

arising from different sampling methodologies (e.g.,

undersampling by ships and satellites) as well as investigating

the wind speed and sea-state effects on SeaWiFS-derived

water-leaving radiance. Related studies of ocean eddies and

hurricanes, which pass the BTM, are also underway (e.g.,

McGillicuddy et al., 1998; McNeil et al., 1999; Dickey et al.,

1998b).

ACKNOWLEDGMENTS

 Data used for comparing ship-based and BTM data were

shared by David Siegel and Margaret O'Brien. SeaWiFS data

were provided for comparisons by the SIMBIOS Office,

which also gave important input and suggestions for our study.

The Bermuda Testbed Mooring program is supported by the

NASA SIMBIOS program, the National Science Foundation,

the Office of Naval Research, the National Ocean Partnership

Program, and the University of California, Santa Barbara.

REFERENCES

Chavez, F.P., J.T. Pennington, R. Herlein, H. Jannasch, G.

Thurmond, and G.E. Friedrich, 1997: Moorings and

drifters for real-time interdisciplinary oceanography, J.

Atmos. Ocean. Tech., 14, 1199-1211.

Clark, D.K., H.R. Gordon, K.J. Voss, Y. Ge, W. Broenkow,

and C. Trees, 1997: Validation of atmospheric correction

over the oceans, J. Geophys. Res., 102, 17,209-17,217.

Dickey, T., 1991: The emergence of concurrent highresolution physical and bio-optical measurements in the

upper ocean, Rev. of Geophys., 29, 383-413.

Dickey, T.D., D. Frye, H.W. Jannasch, E. Boyle, and A.H.

Knap, 1997: Bermuda sensor system testbed, Sea Tech.,

April 1997, 81-86.

Dickey, T., D. Frye, H. Jannasch, E. Boyle, D. Manov et al.,

1998a: Initial results from the Bermuda Testbed Mooring

Program, Deep-Sea Res. I, 45, 771-794.

Dickey, T., D. Frye, J. McNeil, D. Manov, N. Nelson, D.

Sigurdson, H. Jannasch, D. Siegel, A. Michaels, and R.

Johnson, 1998b: Upper ocean temperature response to

Hurricane Felix as measured by the Bermuda Testbed

Mooring, Mon. Wea. Rev., 126, 1195-1201.

McGillicuddy, D.J., A.R. Robinson, D.A. Siegel, H.W.

Jannasch, R. Johnson, T.D. Dickey, J.D. McNeil, A.F.

Michaels, and A.H. Knap, 1998: New evidence for the

impact of mesoscale eddies on biogeochemical cycling in

the Sargasso Sea, Nature, 394, 263-266.

McNeil, J. D., H. Jannasch, T. Dickey, D. McGillicuddy, M.

Brzezinski, and C. M. Sakamoto, 1999: New chemical,

bio-optical, and physical observations of upper ocean

response to the passage of a mesoscale eddy, accepted, J.

Geophys. Res., 104, 15,537-15,548.

Siegel, D.A., A.F. Michaels, J.C. Sorensen, M. O’Brien, and

M.A. Hammer, 1995: Seasonal variability of light

availability and utilization in the Sargasso Sea, J.

Geophys. Res., 100, 8675-8713.

Smith, R.C., K.J. Waters, and K.S. Baker, 1991: Optical

variability and pigment biomass in the Sargasso Sea as

determined using deep-sea optical mooring data, J.

Geophys. Res., 96, 8665-8686.
SIMBIOS Project Annual Report

60

Figure 1. Schematic of the Bermuda Testbed Mooring (BTM) array, geographic map indicating BTM

site, and diagram showing data telemetry system and data flow.
SIMBIOS Project Annual Report

61

Figure 2. Time-series of BTM 14m upwelling radiance for 7 SeaWiFS wavelengths during BTM

Deployment 11.
SIMBIOS Project Annual Report

62

Figure 3. Comparison of BTM and BBOP time-series of surface downwelling irradiance, water-leaving

radiance, and upwelling radiance at 7, 14, and 34m. These 15 days were selected because

concurrent BBOP data were available. BBOP data are shown as x's. All data are for the

490nm wavelength.
SIMBIOS Project Annual Report

63

Figure 4. Top panel shows BTM time-series of wind speed. The lower panels show waterleaving radiance as a function of wavelength as determined from the BTM radiometer

measurements (asterisks) and SeaWiFS (circles). Wind speed for the individual

comparisons are indicated.
SIMBIOS Project Annual Report

64

This research was supported by the

SIMBIOS NASA contract # 97127

PEER REVIEWED PUBLICATIONS

Dickey, T. D., D. Frye, H. W. Jannasch, E. Boyle and A. H.

Knap, 1997: Bermuda sensor system testbed. Sea Tech.,

April 1997, 81-86.

Dickey, T., D. Frye, H. Jannasch, E. Boyle, D. Manov, D.

Sigurdson, J. McNeil, M. Stramska, A. Michaels, N.

Nelson, D. Siegel, G. Chang, J. Wu, and A. Knap, 1998:

Initial results from the Bermuda Testbed Mooring

Program. Deep-Sea Res. I, 45, 771-794.

Dickey, T., D. Frye, J. McNeil, D. Manov, N. Nelson, D.

Sigurdson, H. Jannasch, D. Siegel, A. Michaels, and R.

Johnson, 1998: Upper ocean temperature response to

Hurricane Felix as measured by the Bermuda Testbed

Mooring. Mon. Wea. Rev., 126, 1195-1201.

McGillicuddy, D. J., A. R. Robinson, D. A. Siegel, H. W.

Jannasch, R. Johnson, T. D. Dickey, J. D. McNeil, A. F.

Michaels, and A. H. Knap, 1998: New evidence for the

impact of mesoscale eddies on biogeochemical cycling in

the Sargasso Sea. Nature, 394, 263-266.

Stramska, M. and T. D. Dickey, 1998: Short term variability

of the underwater light field in the oligotrophic ocean in

response to surface waves and clouds. Deep-Sea Res. I,

45, 1393-1410.

PRESENTATIONS

Dickey, T., 1999: Recent Advances in Interdisciplinary

Technologies and Their Potential Utilization in Ocean

Observing Systems. Proceedings of the International

Symposium: The Ocean Observing System, St. Raphael,

France.

Dickey, T. D., X. Yu, L. Dobeck, S. Zedler, D. Sigurdson, and

D. Manov, 2000: Optimal Utilization of Remotely-Sensed

Color Data for Ocean Carbon Cycle Studies. AGU/ASLO

Ocean Sciences Meeting, San Antonio, Texas.

Griffiths, G., R. Davis, C. Eriksen, D. Frye, P. Marchand, and

T. Dickey, 1999: Towards new platform technology for

sustained observations. Proceedings of the International

Symposium: The Ocean Observing System, St. Raphael,

France.

Manov, et al., 1998: Design of bio-optical and physical

systems for moorings: Bermuda Testbed and Coastal

Mixing and Optics. AGU/ASLO, San Diego.

McNeil ,et al., 1998: Bio-optical and chemical observations of

the response of the upper ocean to the passage of a

mesoscale eddy at the Bermuda Testbed Mooring.

AGU/ASLO, San Diego.

Send, U., R. Weller, S. Cunningham, C. Eriksen, T. Dickey,

M. Kawabe, R. Lukas, M. McCartney, S. Osterhuis, 1999:

Oceanographic Time-series observations. Proceedings of

the International Symposium: The Ocean Observing

System, St. Raphael, France.

Sigurdson, et al., 1998: Design of a near real-time telemetry

system for the Bermuda Testbed Mooring (BTM).

AGU/ASLO, San Diego.

Sigurdson, D. E., D. V. Manov, T. D. Dickey, D. E. Frye, and

J. Kemp, 2000: Results from the Near Real-Time

Telemetry System on board the Bermuda Testbed

Mooring (BTM). AGU/ASLO Ocean Sciences Meeting,

San Antonio, Texas.

Zedler, et al., 1998: Time series observations and model

simulations of Hurricane Felix (August 1995).

AGU/ASLO, San Diego.
SIMBIOS Project Annual Report

65

Chapter 11

Satellite Ocean Color Validation Using Merchant Ships

Robert Frouin and David L. Cutchin,

Scripps Institution of Oceanography, University of California San Diego, California

Pierre-Yves Deschamps

Laboratoire d'Optique Atmospherique, Universite des Sciences et Technologies de Lille

Villeneuve d'Ascq, France

11.1 INTRODUCTION

A measurement program for satellite ocean color

validation based on ships of opportunity and specific

instrumentation, the SIMBAD radiometer, was developed to

complement dedicated experiments at sea, which are

expensive, cannot sample the wide range of oceanic and

atmospheric conditions expected to be encountered, and

generally provide a few match-ups. The radiometer is

portable, easy to operate, and measures the basic ocean-color

variables, namely aerosol optical thickness and water-leaving

radiance, in typical spectral bands of ocean-color sensors.

Importantly, the ship is not required to stop, making it possible

to make measurements along regular routes traveled by

merchant ships in the world's oceans.

For water-leaving radiance, the radiometer views the

ocean surface from the side of the ship lit by the sun, outside

the sun glint, at a nadir angle of 45 degrees and a relative

azimuth angle of 135 degrees. A vertical polarizer reduces the

skylight reflected in the instrument's field of view. For aerosol

optical thickness, the radiometer views the sun like a classic

sun photometer. The same optics (with a field of view of 2.5.

degrees) and detectors are used in both sun- and oceanviewing modes. The radiometric measurements are made

simultaneously in five spectral bands centered at 443, 490,

560, 670, and 870 nm, but the sun and ocean surface are

viewed sequentially. Downward solar irradiance at the surface,

a variable that must be known to normalize water-leaving

radiance, is not measured but calculated, which can be done

accurately when the sky is clear or partly cloudy (<30% cloud

coverage) with the sun not obscured by clouds. This defines

the sky conditions under which the SIMBAD radiometer

should be operated. To achieve adequate sampling, a series of

ten radiometers was built for use in two complementary

networks, one operated by the Scripps Institution of

Oceanography (SIO), University of California San Diego, and

the other by the Laboratoire d'Optique Atmospherique (LOA),

University of Lille. Arrangements have been made with

suitable merchant ships, and officers trained to make

SIMBAD measurements. Some of the ships, for example M/V

Micronesian Navigator (SIO network), and M/V Toucan

(LOA network) have been providing data routinely. The

SIMBAD datasets include values of aerosol optical thickness,

Angstrom coefficient, water-leaving radiance, marine

reflectance, downward solar irradiance, and ancillary variables

such as fractional cloud coverage and wind speed. They are

available at http://genius.ucsd.edu/~frouin/ and

http://www.loa.univ-lille1.fr/~poteau/.

11.2 RESEARCH ACTIVITIES

During the second year of the project, collection of

SIMBAD data sets during research campaigns and merchant

ship voyages of opportunity intensified, bringing to 376 the

number of data sets collected by the SIO network under clear

or mostly clear skies within a few hours of SeaWiFS overpass.

The objectives were to improve the sampling of oceanic and

atmospheric conditions, compare marine reflectance measured

by SIMBAD and more classic (e.g., MER-type) radiometers,

and perform a first evaluation of SeaWiFS-derived marine

reflectance. Efforts also focused on developing an operational,

PC portable processing code for SIMBAD data.The research

cruises and merchant ship voyages accomplished by the SIO

network since the launch of SeaWiFS are listed below (Table

1) with general location or route, date, and name of the

operator. The exact location of the data sets is displayed in

Figure 1. Most of the data sets were acquired at latitudes

between -40 and 40 degrees, but the three major oceans were

sampled.

Table 1. SIMBAD research and merchant ship voyages.

" CalCOFI 9710, 20 September - 08 October 1997,

Southern California Bight (Wieland).

" M/V Asian Challenger, 26 October - 04

November 1997, Valparaiso-Auckland (Cutchin).

" R/V Melville, 02 November 1997 - 07 June 1998,

San Diego-Acapulco-Callao-Valparaiso-Easter-
SIMBIOS Project Annual Report

66

Papeete-Honolulu (Comer).

" M/V Nacre, 20 December 1997 - 03 January

1998, Honolulu-Coronel (Cutchin).

" CalCOFI 9802, 23 January - 10 February 1998,

Southern California Bight (Subranamian).

" CalCOFI 9804, 02 April - 24 April 1998,

Southern California Bight (Mitchell).

" M/V Chevron Mississipi, 18 May - 23 May 1998,

Honolulu-Valdez (Cutchin).

" NAN 9807, 06 July -10 July 1998, Cape Cod

(Shieber).

" M/V Mokihana, 20 July - 15 August 1998,

Oakland-Guam-Taiwan-Japan-Oakland

(Bousseloub).

" CalCOFI 9807, 09 July - 27 July 1998, Southern

California Bight (Wieland).

" M/V Micronesian Navigator, 30 August - 14

October 1998, California-Micronesia-PhilippinesCalifornia (Sumogat).

" M/V Mokihana, 04 September - 21 September

1998, Oakland-Guam-Taiwan-Japan-Oakland

(Bousseloub).

" CalCOFI 9809, 13 September - 01 October 1998,

Southern California Bight (Frame).

" R/V Ka'imimoana, 19 October - 11 December

1998, Equatorial Pacific (Strutton).

" R/V Cape Hatteras, 21 October - 01 December

1998, Beaufort-Jacksonville (Subranamian).

" M/V Micronesian Navigator, 03 November - 29

December 1998, California-MicronesiaPhilippines-California (Sumogat).

" M/V Micronesian Navigator, 01 January - 15

March 1999, California-Micronesia-PhilippinesCalifornia (Sumogat).

" CalCOFI 9901, 09 January - 29 January 1999,

Southern California Bight (Frame).

" R/V Ron Brown, 14 January - 18 February 1999,

Charlston-CapeTown-Mauritius (Frouin).

" R/V Ron Brown, 22 February -02 April 1999,

INDOEX, Mauritius-Maldives (Flatau).

" R/V Bellows, 12 April - 29 April 1999, Tongue of

the Ocean II, Bahamas (Shieber).

" R/V New Horizon, 23 May 1999, Southern

California Bight (Chavez).

" R/V Oceania, 20 June - 08 July 1999, TromsoLongyearbyen (Stramski).

" R/V Revelle, 24 June - 17 July 1999, Sea of Japan

(Mitchell).

" R/V Ka'imimoana, 27 June - August 3 1999,

Equatorial Pacific (Strutton).

" CalCOFI 9908, 05 August - 27 August 1999,

Southern California Bight (Wieland).

11.3. RESEARCH RESULTS

The ability of the SIMBAD radiometer to reduce reflected

skylight was justified theoretically and verified experimentally

(Appl. Opt., 38, 3844, 1999). Residual skylight is correctable

to 10-4 in reflectance units, which for most oceanic waters

corresponds to 1% of the marine reflectance in the blue and

green. Polarization of sunlight by the water body is small for

the viewing geometry (scattering angles between 148 and 158

degrees), and one should be able to correct the residual effects

to within 5% relative accuracy.

The diffuse marine reflectance measured by the

radiometer was compared with that measured by an

underwater MER system during various CalCOFI cruises (13

comparison sets) and the Aerosols99 cruise (8 comparison

sets). Figure 2 displays the two types of measurements.

Agreement is good in the four spectral bands considered (to

within 10-15% in the blue and green); there is no apparent

bias. Even though the number of points is not sufficient to

compute meaningful statistics, the comparison attests to the

quality of the SIMBAD marine reflectance.

SeaWiFS-derived normalized water-leaving radiance was

evaluated against SIMBAD measurements (Figure 3). Only 15

match-ups were obtained in clear and turbid waters (but not

coastal waters) during the period considered, September 1997

through July 1998. The scatter between the two types of

water-leaving radiance is large, but the SeaWiFS values are

generally higher than the SIMBAD values in the blue and

green, suggesting an underestimation by SeaWiFS of the

chlorophyll-a concentration in open oceanic waters. This is

apparent in the higher SeaWiFS 443/555 and 490/555

reflectance ratios (not shown here).

A code to process SIMBAD data was delivered to the

SIMBIOS Project office. It requires as input "sun", "dark", and

"sea" data files, calibration coefficients for "sun" and "sea"

data, surface pressure, Dobson amount, wind speed, cloud

fraction, cloud optical thickness, and name of the output file.

Default values are used for wind speed, Dobson amount, and

cloud optical thickness when these variables are not known or

available. The output file contains sun and viewing geometry,

aerosol optical thickness, Angstrom coefficient, downward

solar irradiance, raw marine reflectance, corrected marine

reflectance, water-leaving radiance, normalized water-leaving

radiance, and "remote-sensing" reflectance. The code was

adapted (Sean Bailey) for use on PCs; the executable is

available from the SIMBIOS Project office.

11.4. WORK PLAN

During the third year of the project, the SIO network will

be extended to include additional Micronesian ships, namely

M/V Micronesian Heritage and M/V Micronesian Nations.

These ships, like M/V Micronesian Navigator, have the bridge

forward, making it easy to avoid ship-generated foam. A

collaborative effort is envisioned with the ORSTOM Center of

Noumea, New Caledonia, which has been using merchant

ships to collect physical oceanography data for several

decades. Participation in research campaigns during which

water-leaving radiance and/or aerosol optical thickness are

measured by other instrumentation (e.g., CalCOFI campaigns)

will continue, allowing further evaluation of the SIMBAD

data. But to increase the number of match-ups, the focus will
SIMBIOS Project Annual Report

67

be shifted toward ships that do not carry out the same type of

measurements as the SIMBAD radiometer. An evaluation of

the SeaWiFS-derived marine reflectance and aerosol optical

thickness will be performed using the SIMBAD data collected

by the SIO and LOA networks. The differences between

SeaWiFS and SIMBAD water-leaving radiances will be

analyzed as a function of aerosol optical thickness, Angstrom

coefficient, radiation geometry, and wind speed.

An advanced SIMBAD instrument, SIMBADA, will be

designed and built by the University of Lille. It will be lighter

and more compact, will operate without any cables, will have

improved electronics, reduced noise, a larger internal memory,

better batteries with internal charger, easier display of viewing

geometry, and will measure in eight spectral bands instead of

five. An option being considered is the remote acquisition of

downward solar irradiance, allowing the instrument to make

quality marine reflectance measurements in clear as well as

cloudy, even overcast conditions. A prototype will be tested at

the SIO pier and onboard ship during CalCOFI campaigns.

The objective is the realization of a series of at least 10

advanced instruments by the end of 2000.

ACKNOWLEDGMENTS

The authors wish to thank all the officers and scientists

that have collected SIMBAD data, J. McPherson for

developing the SIMBAD processing code, S. Baily for

adapting the code to PC, A. Poteau for processing SIMBAD

data and helping with the maintenance of SIMBAD

radiometers, B. Shieber for providing SeaWiFS match-up

data, and C. Pietras for helpful discussions. This work has

been carried out with the support of the National Aeronautics

and Space Administration under contract NAS-97135, the

Scripps Institution of Oceanography, the Centre National

d'Etudes Spatiales, and the Centre National de la Recherche

Scientifique.

Figure 1. Location of SIMBAD datasets collected since SeaWiFS launch.
SIMBIOS Project Annual Report

68
SIMBIOS Project Annual Report

69

This research was supported by the

 SIMBIOS NASA contract # 97135

PEER REVIEWED PUBLICATIONS

Fougnie, B., P.-Y. Deschamps, and R. Frouin, 1999: Vicarious

Calibration of he POLDER ocean color spectral bands

using in situ measurements. IEEE Trans.Geos. Rem. Sen.,

37, 1567-1574.

Fougnie, B., R. Frouin, P. Lecomte, and P-Y. Deschamps,

1999: Reduction of kylight reflection effects in the abovewater measurement of marine iffuse reflectance. Appl.

Optics, 38, 3844-3856.

Nakajima, T., A. Higurashi, K. Aoki, T. Endoh, H.

Fukushima, M. Toratani,Y. Mitomi, B. G. Mitchell, and

R. Frouin, 1999: Early phase analysis of CTS radiance

data for Aerosol remote sensing. IEEE Trans. Geo. Rem.

Sen.,37, 1575-1585.

Schwindling, M. P.-Y. Deschamps, and R. Frouin, 1998:

Verification of erosol models for satellite ocean color

remote sensing, J. Geophys. Res.,103, 24,919-24,935.

PRESENTATIONS

Fougnie, B., P.-Y. Deschamps, R. Frouin, B. G. Mitchell,

1998: Measuring water-leaving radiance with a

polarization radiometer: theory and experimental

verification. EOS Trans., 79, No. 1, 99.

Frouin, R., P.-Y. Deschamps, B. G. Mitchell, and M. Kahru,

1998: The Normalized Difference Phytoplankton Index

for satellite ocean color applications. EOS Trans., 79, No.

1, 161.

Gross, L., R. Frouin, S. Thiria, and M. Crépon, 1998: Neural

networks to retrieve phytoplankton pigment concentration

from satellite-derived spectral ocean reflectance. EOS

Trans., 79, No. 1, 161.

Tratt, D. M., R. Frouin, and D. L. Westphal, 1999: A Southern

California perspective of the April, 1998 trans-Pacific

Asian dust event. Proceedings,10th Conference on

Coherent Laser Radar, Mt. Hood, Oregon, June 28 – July

2, 1999, 137-140.
SIMBIOS Project Annual Report

70

Chapter 12

High Altitude Measurements of Radiance at High Spectral and

Spatial Resolution for SIMBIOS Sensor Calibration,Validation,

and Intercomparisons

Robert O. Green, Betina Pavri and Thomas G. Chrien

NASA, Jet Propulsion Laboratory, Pasadena, California

12.1 INTRODUCTION

The objective of this research is to calibrate and validate

the on orbit radiometric characteristics of SeaWIFS with

underflights of NASA’s calibrated Airborne Visible/Infrared

Imaging Spectrometer (AVIRIS). This objective is feasible

because AVIRIS measures the same spectral range as

SeaWIFS at higher spectral resolution (Figure 1). The AVIRIS

sensor flies at 20 km altitude on a NASA ER-2 near the top of

the absorbing and scattering portions of the atmosphere.

Conversion of AVIRIS data to top-of-the-atmosphere radiance

is achieved through the use of the MODTRAN atmospheric

modeling package. AVIRIS measures the solar reflected

spectrum from 370 nm to 2500 nm through 224 contiguous 10

nm wide spectral channels. Data are acquired as images of

11km width by up to 800 km extent with 20 m spatial

resolution. The stability and repeatability of AVIRIS

calibration has been and continues to be validated through a

series of inflight calibration experiments. With pre- and postflight calibrations of AVIRIS, coupled with the on-board

calibrator, calibration accuracy of better than 2% spectral, 3%

radiometric and 3% spatial have been achieved.

The calibration and validation objective of this project is

pursued for the following reasons: (1) Calibration is essential

for the quantitative use of SeaWIFS and other SIMBIOS

sensor data; (2) Calibration in the laboratory of spaceborne

sensors is challenging; (3) Satellite sensors are subjected to

aging on the ground and to trauma during launch; (4) The

Earth orbit environment is significantly different than the

laboratory calibration environment; (5) Through years of

effort AVIRIS has been demonstrated to be well calibrated;

and (6) AVIRIS can match the spectral and spatial observation

characteristics near the top of the atmosphere at the time of

SeaWIFS measurements.

The approach taken for the SIMBIOS Project has been to:

(1) Determine the calibration accuracy of AVIRIS with high

confidence in the laboratory, in flight, and on the runway

before flight; (2) Underfly the SeaWIFS satellite sensor with

AVIRIS matching observation geometry and addressing

weather, satellite, aircraft, sensor, and location issues; (3)

Correct AVIRIS spectral image data to the top of the

atmosphere radiance; (4) Convolve AVIRIS spectral channels

to SeaWIFS bands; (5) Determine and extract matching areas

with correct observation geometry; (6) Compare and analyze

the matchup data and repeat acquisitions for monitoring.

In 1999: (1) AVIRIS data were acquired for SIMBIOS

investigators; (2) intercomparisons between AVIRIS and other

radiometric calibration standards were made; and (3) AVIRIS

underflew the SeaWIFS satellite sensor. The current results of

the 1999 year activities are given in this report.

12.2 RESEARCH ACTIVITIES

Laboratory Cross Comparisons

In 1999 three efforts were undertaken for cross

comparison of laboratory radiometric standards. An initial

effort was made in April to compare the AVIRIS 1999

radiometric standard with a SIMBIOS ocean radiometer. The

results were highly variable. Upon further analysis it was

concluded that the differences in the apertures and

instantaneous fields of view of the AVIRIS and the SIMBIOS

ocean radiometer did not support this cross comparison.

In June of 1999, the SIMBIOS Transfer Radiometer

(SXR) became available. In this timeframe, an effort was

made to use the SXR to cross compare the AVIRIS and

SIMBIOS absolute radiometric standards. Initial analysis of

these data were promising, however, the SXR did not give

good repeatability before and after the measurements in the

AVIRIS calibration laboratory. This was the first use of the

SXR and future measurements with the AVIRIS calibration

standards are expected.

Finally, the Landsat Transfer Radiometer (LXR) was able

to view the AVIRIS radiometric calibration standard in the

June 1999 timeframe. The LXR is similar, but has a longer

heritage than the SXR. Analysis of the cross comparison of

the LXR and AVIRIS 1999 radiometric standard was

completed with good stability before and after the

measurements. Results of this analysis are given. In the 440

nm region the agreement was 1.08%, in the 655 nm region the

agreement was 1.45% in the 830 nm region the agreement was

1.35%.
SIMBIOS Project Annual Report

71

The AVIRIS radiometric standard is a reflectance panel

illuminated by a calibration quartz-halogen lamp. This

standard provides a smooth and repeatable radiometric output

between the measured LXR wavelength regions. These

characteristics suggest that the AVIRIS 1999 calibration

agreement will be comparable across the spectral range

spanned by the LXR measurements. The results with the LXR

are consistent with the expected uncertainty of 2% to 3% of

the AVIRIS 1999 radiometric calibration standard in the

spectral region.

Analysis of 990807 SeaWIFS Underflight

On the 7th of August 1999 AVIRIS successfully

underflew the SeaWIFS satellite sensor off the east coast of

the United States. To compare SeaWIFS and AVIRIS data, the

data sets must be warped into the same geometric space, so

that direct comparisons are available between pixels which

match in space, time, illumination angle, and observation

angle. AVIRIS has a 15° scan angle. In order to match the

~20° view angle of SeaWIFS, the AVIRIS ER-2 platform is

flown in a circle, with the plane banked at 20°. AVIRIS is

typically flown in two circles during the time of a SeaWIFS

overpass. Once the two data sets are projected into the same

geometric space, the SeaWIFS region and AVIRIS region

with overlapping observation geometry can be selected, and

the resulting radiance compared.

Results for the 990807 AVIRIS underflight were

calculated for two cases: matching illumination/observation

angles to within 2°, and matching geometry to within 5°.

Radiometric calibration agreement ranges from 2% to 12%

across the eight SeaWiFS bands, with band 6 having the

largest discrepancy.

12.3 WORK PLAN

In 1999, under this component of the SIMBIOS effort,

AVIRIS data have been acquired for SIMBIOS investigators,

three radiometric calibration standard cross comparison

experiments have been orchestrated, and one successful

underflights of SeaWIFS by AVIRIS was completed. The

AVIRIS data acquired for the SIMBIOS investigators has

been delivered to them and to the SIMBIOS Project (Table 1).

Based on repeatability analysis only one of the cross

comparison experiments was deemed successful. The results

from this experiment show that the AVIRIS 1999 radiometric

calibration standard agrees with the Goddard Space Flight

Center Landsat Transfer Radiometer at the 2% level. This is

consistent with the level of uncertainty expected and

consistent with the calibration and validation objectives of this

activity. On the 7th of August 1999 AVIRIS successfully

underflew the SeaWIFS satellite sensor. Analysis of these

data show radiometric calibration agreement ranging from 2%

to 12% across the eight SeaWIFS bands. Analysis is

continuing to review this comparison and attempt to tighten

the confidence in the result.

A second successful underflight was completed on the 1st

of October 1999. Comparison of the 7 August and 1 October

1999 result will provide insight into the repeatability of this on

orbit calibration and validation experiment. In November of

1999 a new radiometric calibration standard will be integrated

into the AVIRIS sensor laboratory. This 3000 degree cavity

blackbody source will give an additional check on the absolute

radiometric calibration of AVIRIS. This new standard may

also allow tightening of the AVIRIS absolute radiometric

calibration to 1% across the full spectral range. Results of

these new activities and there impact of this SIMBIOS effort

will be reported in the future.

ACKNOWLEDGMENTS

This research was carried out at the Jet Propulsion

Laboratory/California Institute of Technology, Pasadena,

California, under contract with the National Aeronautics and

Space Administration. This research was funded as part of the

SIMBIOS Project at the Goddard Space Flight Center of the

National Aeronautics and Space Administration.
SIMBIOS Project Annual Report

72

Table 1. AVIRIS data have been measured for the SIMBIOS Project in 1997, 1998, and 1999. Given below is a

summary of this data and the status of delivery at various levels of processing. The following

calibrated AVIRIS radiance data were delivered to the SIMBIOS Project in 1999.

Data set PI Target

f970410t01p02_r03 Robert O. Green CalCOFI Boat Overpass

f970520t01p02_r02 Robert O. Green OCTS underpass

f971002t01p02_r02 Robert O. Green CalCOFI Boat Overpass

f971002t01p02_r03 Robert O. Green SEAWIFS underpass

f980530t01p02_r06 Robert O. Green SEAWIFS underpass

f981031t01p01_r02 Kendall L. Carder Lake Okeechobee

f981031t01p01_r03 Kendall L. Carder Sarasota Bay

f981031t01p01_r04 Kendall L. Carder Tampa Bay

f981116t01p02_r03 Kendall L. Carder Tampa Bay

f990521t01p02_r02 Kendall L. Carder Lake Okeechobee 3

f990521t01p02_r03 Kendall L. Carder Lake Okeechobee 1

f990521t01p02_r04 Kendall L. Carder Lake Okeechobee 2

f990524t01p02_r02 Kendall L. Carder Bahamas 2

f990524t01p03_r01 Kendall L. Carder Bahamas 2

f990524t01p02_r01 Kendall L. Carder Bahamas 1

f990807t01p02_r03 Robert O. Green SEAWIFS underpass

Additional data that have been acquired and will be delivered as calibrated radiance are:

f991001t01p02_r05 Robert O. Green SEAWIFS underpass

f991013t01p02_r09 Robert Frouin 4 meter Whitecaps

Data analyzed and generated for this project have been delivered for the following SEAWIFS underpasses:

f970520t01p02_r02 Robert O. Green AVIRIS convolved to OCTS bands

AVIRIS geocorrected data (circles)

OCTS scene subset (geocorrected)

f971002t01p02_r03 Robert O. Green AVIRIS convolved to SEAWIFS bands

AVIRIS geocorrected data (circles)

SEAWIFS scene subset (geocorrected)

f990807t01p02_r03 Robert O. Green AVIRIS convolved to SEAWIFS bands

AVIRIS geocorrected data (circles)

SEAWIFS scene subset (geocorrected)

Data analyzed and generated for this project will be delivered for the following SEAWIFS underpasses:

f991001t01p02_r05 Robert O. Green AVIRIS convolved to SEAWIFS bands

AVIRIS geocorrected data (circles)

SEAWIFS scene subset (geocorrected)
SIMBIOS Project Annual Report

73

0

1

2

3

4

5

6

7

370 420 470 520 570 620 670 720 770 820 870 920 970

Wavelength (nm)

Ocean Radiance Spectrum

SeaWiFS Visible Near-Infrared Bands 

AVIRIS Spectral Channels (224 from 370 to 2500 nm) 

0

1

0

1

ROG970110

Solar Absorptions

H2O

H2O

H2O

H2O

O2

Ozone Absorption

Figure 1. This plot shows the eight SeaWIFS bands and the AVIRIS spectrally contiguous channels in

the region from 370 to 1000 nm. A high spectral resolution modeled plot of the typical

upwelling spectral radiance for an ocean target is shown in blue.

This research was supported by the

SIMBIOS NASA interagency agreement

PRESENTATION

Green, R.O., B. Pavri, and M. Shimada, 1998: On-Orbit

Calibration of ADEOS OCTS with AVIRIS Underflight,

Proc. Seventh Airborne Earth Science Workshop, Jet

Propulsion Laboratory, JPL Pub. 97-21, Vol. 1, pp 205-

212.

Green, R. O., B. Pavri, J. Faust, O. Williams, and C. Chovit,

1998: Inflight Validation of AVIRIS Calibration in 1996

and 1997. Summaries of the Seventh JPL Airborne Earth

Science Workshop, Vol. 1.

Oaku, H., M. Shimada, and R. O. Green, 1998: OCTS

Absolute Calibration Using AVIRIS. IGARSS, Seattle.

Pavri, B., T. G. Chrien, and R. O. Green, 1999:

Intercomparison of Standards for Radiometric

Calibration. Presented at the Eighth JPL AVIRIS Science

and Applications Workshop.

Shimada, M., H. Oaku, Y. Mitomi, H. Murakami, R. O.

Green, G. Mitchell, H. Kawamura, 1999: Calibration of

the Ocean Color and Temperature Scanner. IEEE

Geoscience and Remote Sensing, a special issue of

ADEOS.
SIMBIOS Project Annual Report

74

Chapter 13

Merging Ocean Color Data from Multiple Missions

Watson W. Gregg

NASA/Goddard Space Flight Center, Greenbelt, Maryland

13.1 INTRODUCTION

Oceanic phytoplankton may play an important role in the

cycling of carbon on the Earth, through the uptake of carbon

dioxide in the process of photosynthesis. Although they are

ubiquitous in the global oceans, their abundances and

dynamics are difficult to estimate, primarily due to the vast

spatial extent of the oceans and the short time scales over

which their abundances can change. Consequently, the effects

of oceanic phytoplankton on biogeochemical cycling, climate

change, and fisheries are not well known.

In response to the potential importance of phytoplankton

in the global carbon cycle and the lack of comprehensive data,

the NASA and the international community have established

high priority satellite missions designed to acquire and

produce high quality ocean color data. Seven of the missions

are routine global observational missions: OCTS, POLDER,

SeaWiFS, MODIS-AM, MERIS, GLI, and MODIS-PM. In

addition, there are several other missions capable of providing

ocean color data on smaller scales. Most of these missions

contain the spectral band complement considered necessary to

derive oceanic pigment concentrations (i.e., phytoplankton

abundance) and other related parameters. Many contain

additional bands that can provide important ancillary

information about the optical and biological state of the

oceans.

Any individual ocean color mission is limited in ocean

coverage due to sun glint and clouds. For example, one of the

first proposed missions, the SeaWiFS, can provide about 45%

coverage of the global ocean in four days and only about 15%

in one day (Gregg and Patt, 1993).

Objectives

We propose to investigate, develop, and test algorithms

for merging ocean color data from multiple missions. We

seek general algorithms that are applicable to any retrieved

ocean color data products, and that maximize the amount of

information available in the combination of data from multiple

missions. Most importantly, we will investigate merging

methods that produce the most complete coverage in the

smallest amount of time, nominally, global daily coverage.

We will also assess the ability to produce fuller coverage in

larger time increments, including 4-day, 8-day (weekly),

monthly, seasonal and annual. We intend to develop methods

that are not mission-specific, but take advantage of the unique

characteristics of the missions as much as possible.

13.2 RESEARCH ACTIVITIES

Work has focused on 1) defining the problems and

opportunities provided by the existence of multiple sensors, 2)

analysis of past sensors to provide insights into the

characteristics, drawbacks, and advantages of individual

sensor responses in the context of merging, and 3) analysis,

development, and testing of candidate merger algorithms.

Defining Problems and Opportunities of Multiple Missions

A) First we assessed the global coverage improvements

possible by the 6 global missions. These results show

that significant scientific advantages can accrue from

assembling and merging data from the multiple satellite

platforms proposed for ocean color in the next decade.

The principal advantages are increased ocean coverage in

less time, and new observations of the daily dynamics of

phytoplankton abundances, resulting from different

observation times of co-located ocean areas. Data from

three satellites can increase ocean coverage by 58% for

one day, and 45% for four days. Additional satellites

produce diminishing returns, however. This latter point

is not necessarily an adverse finding, since each mission

has a limited life expectancy and in-flight problems are,

unfortunately, still not rare in the satellite business.

Using observations from pairs of missions, as much as 14

hour time differences at co-located points can be

realistically achieved at high latitudes, even considering

the distribution of land masses and ice cover. Smaller

time differences are observed at lower latitudes, but 5 to

7 hour differences are still available. Furthermore,

massive numbers of these co-located pairs are available,

suggesting that routine scientific studies of diel

phytoplankton variability can be supported. These results

were published in the IEEE Transactions on Geoscience

and Remote Sensing (Gregg et al., 1998).

B) More detailed analyses emphasized seasonal and regional

coverage improvements and was limited to the

SeaWiFS/MODIS combination, since these are the two
SIMBIOS Project Annual Report

75

missions planned for launch next. The results showed

that the launch of EOS AM-1 provides an opportunity to

potentially improve ocean color observations by

combining data from the SeaWiFS and MODIS missions.

The sensors have different scanning characteristics and

are flying on different platforms in different orbits. The

results suggested that very large improvements in

coverage frequency (daily to four-day) can be obtained

by combining data from both sensors: 40-47% increases

in global coverage over SeaWiFS alone in one day, and >

100% in areas near the solar declination. Four-day

increases are slightly smaller for global coverage, 29-

35%, but meridional percent increases are similar to the

one-day case. These differences are due to reduced sun

glint contamination obtained by tilting (SeaWiFS), and

scanning away from the maximum glint region

(MODIS), due to its 10:30 AM equator crossing time,

and due to the large scan width of MODIS. The results

show that SeaWiFS and MODIS are very complementary

ocean color missions that can provide more complete

observations of ocean processes at high frequency if data

are combined. These results were published in the IEEE

Transactions on Geoscience and Remote Sensing (Gregg

and Woodward, 1998). A more detailed paper with more

fully defined results was published as a NASA Technical

Memorandum (Woodward and Gregg, 1998).

C) Assessed potential capability for improving ocean color

observations by selecting complementary mission orbits.

Considering that observations are severely hampered by

cloud cover and sun glint, a possibility exists for using

multiple missions to improve the coverage of the oceans

in shorter time scales. In fact, only about 10-18% of the

oceans are observed in a single day, even by so-called

global observational missions, due to these two ocean

color contaminants. Analysis of a 7-day period of cloud

cover from the International Satellite Cloud Climatology

Project (ISCCP), show that 12% new surface area is

available for viewing each day. This translates to an

increase of about 0.5% per hour of separation in viewing

times. Thus if the ocean could be viewed by 2 different

satellites 4 hours apart, 2% more ocean area could be

observed. This represents a coverage increase of about

13%. If 2 satellites were placed in Earth orbit with

equator crossing times 4 hours apart, the improvement in

coverage by these 2 satellites over a single one is about

60%. Furthermore, by managing the orbits of the 2

satellites, nearly complete sun glint avoidance can be

achieved, further improving the ocean coverage. The

best improvements can be made by 2 satellites in the

same node, whose orbital positions are adjusted to view

the sun glint contaminated areas of the other. If scan

edges are useful for quantitative ocean color observations

(the validity of which is unknown at this time), then only

2 polar-orbiting satellites are necessary. If not, a third

satellite is necessary, preferably in a low inclination orbit

where losses in coverage in the tropics by the polar

orbiters can be best compensated (polar orbiters overlap

coverage at high latitudes, and the scan edges are

necessary only near the equator). However, the best

configuration is 3 geostationary satellites, which provide

complete global coverage routinely with a viewing time

separation that can maximize cloud and sun glint

avoidance, with a single polar orbiter to provide high

latitude coverage. This option is considered expensive at

the present time, however.

Analysis of Past Sensors

Investigations with OCTS began before the failure of

ADEOS, in an effort to characterize its ocean color data for

use with a merging activity with SeaWiFS. The loss of data

from the sensor precludes its use in merging, but the similarity

of some aspects of sensor design with MODIS suggests that

significant understanding of the capabilities and deficiencies

of MODIS data can be facilitated through a thorough analysis

of OCTS data. In fact, we have found this to be true. Initial

observations just after failure of OCTS suggested 6 problem

areas: band registration, image striping, cloud noise,

navigation, calibration, and bright target response (Gregg,

1997). Analysis of the first three led to solutions that improved

imagery substantially (Gregg, 1998; Gregg, 1999).

Particularly the methods for reducing image striping is a

useful method for a problem expected to occur in MODIS

imagery. Analysis of geolocation, radiometric stability and

accuracy, and bright target responses were characterized

(Gregg et al., 1999). The results here also have implications

for MODIS.

Analysis of OCTS imagery indicated three areas of

impairment for quantitative scientific research applications: 1)

band misalignments, 2) image striping, and 3) image noise.

These impairments are caused by 1) band offsets in the sensor

design, 2) detector radiometric response variability, and 3)

cloud contamination (primarily) and the band offset design

(partially), respectively. The band offset design has potentially

serious implication for ocean color research, given the

presence of small scale variability, the requirement of multiple

bands to produce ocean color geophysical outputs, and the

sensitivity of the algorithms. A nearest neighbor band-to-band

co-registration method produces the best results, with the least

image noise, best cloud identification potential, and most

accurate depiction of the actual full spectral suite at a given

location. The offset design, however, still produces

inconsistencies in a spectral understanding of each OCTS

IFOV, and therefore provides a limitation on the sensor's

ultimate capability. We found it effective to handle image

striping by linearizing detector responses to the extent

possible, and then applying a median filter to a quasichlorophyll product to smooth out the individual detector

responses. Location of the total radiances used to produce the

median filtered quasi-chlorophyll are retained and enable

smoothing of the total radiances, after which a straightforward
SIMBIOS Project Annual Report

76

application of atmospheric correction can be performed. The

net effect of both band co-registration and image striping

reduction is to reduce the actual spatial resolution from < 1 km

to about 5 km. A multi-step method for identifying and

removing cloud effects was found to be a reasonably effective

method.

The OCTS archive collected by NOAA and NASA over

the US East Coast and Gulf of Mexico appears to contain a

geometric offset of 4 to 5 pixels in the along-track direction.

Analyses of scan edges indicate that an adjustment to the tilt

produces the most reliable agreement to a high resolution land

data file. Analysis using an island matching algorithm

confirm that an adjustment to the tilt reduces the along-track

bias: from about 5 pixels to 1.5 pixels for the tilted segment of

operations Mar. 18, 1997 to end of mission, and from 2.6 to

less than 0.3 pixels for the nadir pointing operations for Dec.

15, 1996 to Mar. 18, 1997.

OCTS appears to exhibit near field scatter effects in its

imagery. These effects are substantial in magnitude, and have

a spectral character, but are limited to approximately the

dimensions of the focal plane (30 pixels wide by 10 pixels

long). Not all bright targets exhibit these near field effects,

nor do the effects always last the width of the focal plane.

Most land features in the data set do not appear to produce

effects as large as clouds, which is consistent with their

relative brightness. Far field scatter effects are difficult to

demonstrate conclusively, since haze or sub-saturating clouds

cannot be ruled out. However, large cloud features nearly

always produce successively decreasing reflectance far from

their locations, and extending in all directions. The effects

also appear to be non-spectral, which conforms to the effects

of far field scatter. However, these effects, if they are in fact

sensor-derived, are not large although long lasting, and do not

necessarily produce adverse effects on ocean chlorophyll

estimates because of the error-correcting nature of the

atmospheric correction algorithms. Exceptions may occur in

the presence of large amounts of troposheric aerosols, whose

scattering properties differ greatly from those of far field

scatter and sub-saturating clouds. In any event, similar

problems, e.g., sub-saturating clouds and thick haze, are

encountered by all ocean color sensors, and probably do not

have a large impact on the derivation of ocean properties.

However, these effects could impact aerosol analyses over the

oceans.

OCTS aerosol bands exhibit substantial short term

variability, producing daily differences in aerosol reflectance

ratios of 5 to >10%. Determination of longer term trends in

the stability of the aerosol bands is inconclusive, because of

the apparent long-term signal is much smaller than the short

term variability, and because a complete seasonal cycle is not

available due to the untimely loss of the mission after 9

months. Atmospheric correction appears to reduce the

magnitude of this short term variability when observing

normalized water-leaving radiances, which exhibit daily

variability of only about 1-5%. Seasonal variability also

appears to exist, although observations in other areas of the

oceans are necessary to conform that these are not sensor

effects. Similarly, long-term trends of the sensitivity of OCTS

Bands 1-5 are inconclusive because of these daily and

seasonal effects, which exceed the apparent mission lifetime

effect. Comparison of calibration adjustment factors derived

from 6 in situ data sources with those obtained from an

independent in situ data set (Shimada et al., 1998) show good

agreement in the bands used to evaluate the optical state of

water (Bands 1-5). Maximum differences in these bands are <

4%, and differences 1% or less are observed in Bands 1 and 2.

Aerosol bands differ up to 5% in Bands 6 and 7 and 11% in

Band 8, but are attributed to a measurement of Band 8 by an

aircraft underflight by Shimada et al. (1998) , while Band 8 is

assumed unadjusted from its pre-flight value here, due to our

inability to evaluate it by any other means. However, the

relative adjustments to Band 7 used here produce λ (765,865)

values in open ocean near 1, which are expected under most

conditions, as opposed to about 1.15 using the Shimada

corrections, which is somewhat higher than expected.

Analysis and Development of Merging Algorithms

Efforts have began on developing merging algorithms.

We are investigating four possible approaches:

• simple splicing/averaging, where data from 2 or more

satellites are averaged where they coexist at grid points,

and use of a single satellite in gaps where only one exists,

• subjective analysis, where specific dependences and

deficiencies are identified using knowledge about sensor

environmental conditions and co-located observations are

merged using different weighting functions for the

sensors,

• the Conditional Relaxation Analysis Method (CRAM),

where the best data are selected as interior boundary

conditions into a merged set using Poisson's equation, and

• optimal interpolation, where merging occurs by weighting

individual sensor data to minimize spatial covariance

function.

All forms have been implemented in software, and

analysis of conceptual strengths and weaknesses has begun.

Analysis of SeaWiFS and simulated MODIS can provide

insight into operational aspects of the algorithms, but flight

data are necessary to refine these conclusions.

REFERENCES

Gregg W.W. and F.S. Patt, 1994: Assessment of tilt capability

for spaceborne global ocean color sensors. IEEE Trans.

Geosci. Remote Sens. 32: 866-877.

Gregg W.W., F.S. Patt, and R.H. Woodward, 1997:

Development of a simulated data set for the SeaWiFS
SIMBIOS Project Annual Report

77

mission. IEEE Transactions on Geoscience and Remote

Sensing 35: 421-435.

Reynolds R.W., 1988: A real-time global sea surface

temperature analysis. J. Clim. 1:75-86.

Shimada M. and others, 1998: Calibration and validation of

the ocean color version-3 product from ADEOS OCTS.

J. Oceanogr. 54: 401-416.

This research was supported by the

SIMBIOS NRA

PEER REVIEWED PUBLICATIONS

Gregg, Watson W., F.S. Patt and W.E. Esaias 1999: Initial

Analysis of Ocean Color Data from the Ocean Color and

Temperature Scanner. II. Geometric and Radiometric

Analysis, Applied Optics 38: 5692-5702.

Gregg, Watson W., 1999: Initial Analysis of Ocean Color Data

from OCTS. I. Imagery Analysis, Applied Optics 38: 476-

485.

Gregg , Watson W. and R.H. Woodward 1998: Improvements in

high frequency ocean color observations: Combining data

from SeaWiFS and MODIS. IEEE Transactions on

Geoscience and Remote Sensing 36:1350-1353.

Gregg, Watson W., W.E. Esaias, G.C. Feldman, R. Frouin, S.B.

Hooker, C.R. McClain, and R.H. Woodward., 1998:

Coverage opportunities for global ocean color in a multimission era. IEEE Transactions on Geoscience and Remote

Sensing 36:1620-1627.

OTHER PUBLICATIONS

Woodward, Robert H. and W.W. Gregg 1988: An assessment

of SeaWiFS and MODIS ocean coverage. NASA

Technical Memorandum 208607, 45 pp

PRESENTATIONS

Bontempi, Paula S., W.W. Gregg, and J.A. Yoder 1998: Initial

observations of springtime surface chlorophyll-a in shelf

waters off the southeastern United States by the Ocean

Color and Temperature Sensor (OCTS). EOS, Transactions,

American Geophysical Union 79: 28.

Conkright, M.E., W.W. Gregg, and C. Stephens, 1998:

Historical chlorophyll data sets: Intercomparison of the

NODC and NASA. EOS, Transactions, American

Geophysical Union 79: 91.

Gregg, Watson W., 1998: Initial assessment of ocean color data

from the OCTS mission. EOS, Transactions, American

Geophysical Union 79: 28.

Gregg, W.W. and M.E. Conkright, 1998: Blended in situ and

remotely-sensed ocean chlorophyll data sets. EOS,

Transactions, American Geophysical Union.

Gregg, W.W. and M.E. Conkright, 1999: Initial results from a

global blended ocean chlorophyll analysis. Proceedings

of the 79th AMS annual meeting, 10th symposium on

global change studies.

Gregg, Watson W., 1999: Considerations for Future Ocean

Color Sensors. in Proceedings of the 8th Japan/US Working

Group on Ocean Color (JUWOC), J. Ishizaka and J.

Campbell, eds., Earth Science and Technology Organization

98P0A1-D009, Shibaura, Minato-ku.
SIMBIOS Project Annual Report

78

Chapter 14

Validation of Bio-Optical Properties in Coastal Waters: A Joint

NASA-Navy Project

Richard L. Miller

NASA, Stennis Space Center, Mississippi

14.1 INTRODUCTION

This project is a joint effort between NASA’s Earth

System Science Office and the Naval Oceanographic Office

(NAVOCEANO) at the John C. Stennis Space Center, MS.

The collaboration reflects a partnership developed by NASA

and NAVOCEANO over seven years to share resources and

expertise in the collection of ocean optics, hydrographic,

biological, and remotely sensed data to support each agency’s

goals in coastal research. NAVOCEANO provides ship time,

instrumentation, and operational support during oceanographic

surveys while NASA provides expertise in data collection,

computer programming and modeling, and data processing

and analysis.

This SIMBIOS Project was established to provide data

collected in the South China Sea, Gulf of Thailand and

adjacent coastal waters. This project is designed to provide

NASA with cost-effective access to in-water optics and

ancillary data in coastal waters representing diverse turbid

environments, and if successful, will help provide an effective

mechanism for interagency cooperation and data exchange.

14.2 RESEARCH ACTIVITIES

NAVOCEANO hydrographic surveys 621198 (USNS

Bowditch, 11 - 30 September 1998) and 261299 (USNS Silas

Bent, 8 - 22 July 1999) were completed in the Gulf of

Thailand and South China Sea, respectively. The SIMBIOS

Project investigators comprise the optics team of these

surveys, one of three primary operations: optics,

bioluminescence, and basic hydrography. Vertical profiles

were acquired by each operations team following a dense grid

of selected stations.

The equipment employed during survey 621198 included

a SIMBIOS Project Microtops II Sunphotometer, a GER

(Geophysical Environmental Research, Inc.) 1500 hand-held

spectroradiometer (300 -100 nm, effective 1 nm bandwidth), a

SBE-19 CTD (Sea-Bird Electronics, Inc.), a WetStar flowthrough fluorometer (Wet Labs, Inc.), 2 SeaTech

transmissometers (490 nm and 532 nm), and a Seapoint

turbidity meter. Several optical instruments (e.g., Satlantic

SPMR, AC-9) and supporting computer hardware did not

arrive at port of departure prior to sailing. Furthermore,

weather conditions limited sampling during this survey to

about 10 days. Vertical profiles were taken at 80 stations using

a single package containing the CTD, WetStar,

transmissometers and the turbidity meter. Above-water remote

sensing reflectance spectra were taken during the day (11

stations) given appropriate conditions of solar zenith angles

(avoidance of sun glint), sea state, and cloud clover. A

Spectralon 10% reference placard was used a reflectance

standard. Two PC-based programs were written to acquire and

analyze GER reflectance spectra and calculate remote sensing

reflectance following the methods outlined in Mueller and

Austin (1995) and Lee et al. (1997).

The equipment employed during survey 621198 included

a SIMBIOS Project Microtops II Sunphotometer, a GER

(Geophysical Environmental Research, Inc.) 1500 hand-held

spectroradiometer, a SBE-19 CTD (Sea-Bird Electronics,

Inc.), 2 AC-9s (Wet Labs, Inc.), a Satlantic SPMR (SeaWiFS

Profiling Multispectral Radiometer) and a TRSBII (Satlantic,

Inc.) Power and communications to the AC-9s and CTD were

provided by MODAPS (Modular Ocean Data and Power

System, Wet Labs, Inc.). The CTD and AC-9s were deployed

at 76 stations. The inflow tubes of one AC-9 were fitted with a

0.2 μm inline filter to partition the total spectral absorption

and beam attenuation into dissolved and particulate fractions.

Temperature, salinity and scattering corrections were applied

to all AC-9 data. Scattering corrections used either Method 1

of the Zaneveld Method (AC-9 User Guide, Wet Labs, Inc).

A branching algorithm was used based on the a715 nm / b715

nm ratio to select which scattering method was applied.

Method 1 was used for ratios greater than 0.35. The Zaneveld

Method was used for ratio values <= 0.35. The Satlantic

SPMR and TRSBII were deployed at 38 stations during the

day when the solar zenith angle was less than 600

 and profiles

analyzed using the vendor-supplied PROSOFT analysis

program. GER above-water reflectance spectra were obtained

at 33 stations and processed as outlined above. Comparison

between in-water (Satlantic) and above-water (GER) estimates

of remote sensing reflectance is now underway.

Discrete Water Samples: At most stations, discrete water

samples were collected at select depths (based on profiling

transmissometer and fluorometer data) using Niskin Bottles

mounted on a hydrographic CTD rosette. These water samples
SIMBIOS Project Annual Report

79

were filtered for analysis of fluorometric chlorophyll a and

phaeopigments, HPLC pigments, CDOM absorption, particle

absorption (QFT), and total suspended mater. All samples

were collected and processed following the procedures of

Mueller and Austin (1995). HPLC pigments determined were

chlorophyll a, chlorophyll b, peridinin, fucoxanthin, 19’hex,

prasinoxanthin, alloxantin, lutein, zeaxanthin, diadinoxanthin,

canthaxantin, and β-carotene. Absorption spectra were

determined for total, detrital, and phytoplankton components

following the hot-methanol extraction technique (Kishino et

al., 1985). Corrections for path-elongation were performed

following the method of Mitchell (1990). CDOM absorption

spectra were collected using a Perkin-Elmer Lambda 3

spectrophotometer. The number of samples collected for each

analysis were (Survey 621198; 261299): HPLC (35; 54),

fluorometic chl a (33; 53), total suspended mater (33; 77),

CDOM absorption (33; 36), and particle absorption (18; 54).

14.3 RESULTS

The lack of equipment on survey 621198 in the Gulf of

Thailand significantly handicapped the full collection of data

as proposed, but allowed the development deployment,

acquisition, and analysis procedures for the GER reflectance

spectra. Hence, a SIMBIOS year 2 “replacement” cruise was

planned and conducted as survey 261299 in the South China

Sea. This cruise was able to follow the proposed work plan

with regards to data collection and processing. In general,

instrument calibration and data collection followed the

guidelines provided by the proposal. Intermittent problems

were again encountered with the MODAPS system restricting

the number of deployments The problem was isolated as a

grounding-loop problem that will be corrected in future

cruises.

A major milestone related to data release was

accomplished in late April 1999. Under the command of the

CMNMOC NAVOCEANO was formally granted permission

to release ocean optics data collected by NAVOCEANO to the

SIMBIOS program for algorithm development and digital

product generation. From this approval, the project is currently

integrating the data collected into a unified dataset for

regional algorithm development.

14.4 WORK PLAN

The project is actively processing the data from the three

surveys completed as part of this SIMBIOS Project. Given the

formal release of the data, the project directed all activities to

providing quality control, formatting, and instrument

calibration to transmit this large collection of data to the

SeaBASS archive. A significant set of these data have been

submitted to the SIMBIOS program office.

The project will conduct at least one additional survey in

both the Gulf of Thailand and the South China Sea. Data

collected during the life of the project will be analyzed as

described in the original proposal. A Hydroscat-2 (442 and

589 nm) will be deployed. Regional bio-optical algorithms

will be developed. A comparison between in-water, abovewater, and SeaWiFS remote sensing reflectance will be made.

REFERENCES

Kishino, M., N. Okami and S. Ichimura. 1985: Estimation of

the spectral absorption coefficients of phytoplankton in

the sea. Bull. Mar. Sci. 37: 634-642.

Lee, Z. P., K. L. Carder, R. G. Steward, T. G. Peacock, C. O.

Davis and J. L. Mueller, 1997: Remote-sensing

reflectance and inherent optical properties of oceanic

waters derived from above-water measurements. In

Proceedings of SPIE Ocean Optics XIII, Vol. 2963, 160-

166.

Mitchell, B. G. 1990: Algorithms for determining the

absorption coefficients of aquatic particulates using the

quantitative filter technique (QFT). SPIE Ocean Opt. X

1302:137-148.

Mueller, J.L. and R.W. Austin. 1995: Ocean Optics Protocols

for SeaWiFS Validation, Revision 1. NASA Tech. Memo.

104566, Vol. 25. S.B. Hooker, E.R. Firestone, and J.G.

Acker, Eds.,NASA Goddard Space Flight Center,

Greenbelt, Maryland, 67 pp.
SIMBIOS Project Annual Report

80

Chapter 15

Bio-Optical Measurement and Modeling of the California Current

and Polar Oceans

B. Greg Mitchell and Piotr Flatau

Scripps Institution of Oceanography, University of California San Diego, California

15.1 INTRODUCTION

This SIMBIOS Project contract supports in situ oceanic

optical observations in the California Current and Southern

Ocean. The principal objectives of this research are to

validate standard or experimental products through detailed

bio-optical and biogeochemical measurements, and to

combine ocean optical observations with advanced radiative

transfer modeling to contribute to satellite vicarious

radiometric calibration and algorithm development.

In collaboration with the California Cooperative Oceanic

Fisheries Investigation (CalCOFI) and US Joint Global Ocean

Flux Study (JGOFS) programs, our sampling efforts have been

focused primarily on the California Current and Antarctic

waters, with the purpose of generating a high-quality,

methodologically consistent data set encompassing a widerange of oceanic conditions. In the past year we have

collaborated with other SIMBIOS PIs to collect data in the

Atlantic and Indian Oceans and we are merging our Office of

Naval Research (ONR) sponsored Sea of Japan data set to the

SIMBIOS database. The combined data base we have

assembled includes stations which cover the clearest

oligotrophic waters to highly eutrophic blooms and red-tides,

and provides a coherent set of observations to validate biooptical algorithms for pigments, inherent optical properties

and primary production. This unique and comprehensive data

is utilized for development of experimental algorithms (e.g.

high-low latitude pigment transition, phytoplankton

absorption, photosynthesis, and cDOM).

15.2 RESEARCH ACTIVITIES

Field methods and data

The Southern California Bight region, from San Diego to

just north of Point Conception, has one of the longest, most

comprehensive time-series of marine observations; the

CalCOFI. This region experiences a large dynamic range of

coastal and open ocean trophic structure, and has been

extensively studied with respect to its regional optical

properties in an effort to develop regional ocean color

algorithms (e.g. Smith and Baker 1978, Mitchell and Kiefer

1988, Sosik and Mitchell 1995). During the second year of

our contract, we participated in 3 CalCOFI cruises in the

California Current region as part of the CalCOFI program.

The Southern Ocean is a large, remote region, which

plays a major role in global biogeochemical cycling. Despite

evidence that bio-optical relationships in these waters can

diverge significantly from lower-latitude waters (e.g. Mitchell

and Holm-Hansen 1991), Antarctic waters have been underrepresented in the databases (e.g. SeaBAM) used to formulate

and test modern ocean color algorithms. During the past year,

we have analyzed detailed observations collected in year 1 of

our SIMBIOS Project and have published novel algorithms for

retrieval of particulate organic carbon (Stramski et al., 1999)

and have submitted a detailed optical model for Southern

Ocean waters (Reynolds et al., submitted).

On all cruises, an integrated underwater profiling system

was used to collect optical data and to characterize the water

column. The system included an underwater radiometer

(Biospherical Instruments MER-2040 or MER-2048)

measuring depth, downwelling spectral irradiance (Ed) and

upwelling radiance (Lu) in 13 spectral bands. A MER-2041

deck-mounted reference radiometer (Biospherical Instruments

Inc) provided simultaneous measurements of above-surface

downwelling irradiance. Details of the profiling procedure,

characterization and calibration of the radiometers, data

processing and quality control are described in Mitchell and

Kahru (1998). The underwater radiometer was also interfaced

with 25 cm transmissometers (SeaTech or WetLabs), a

fluorometer, and SeaBird conductivity and temperature

probes. When available, additional instrumentation integrated

onto the profiling package included AC9 absorption and

attenuation meters (WetLabs Inc.), and a Hydroscat-6

backscattering meter (HobiLabs).

In conjunction with in situ optical measurements, discrete

water samples were collected from a CTD-Rosette

immediately before or after each profile for additional optical

and biogeochemical analyses. Pigment concentrations were

determined fluorometrically and with HPLC. Spectral

absorption coefficients (300-800 nm) of particulate material

were estimated by scanning particles concentrated onto

Whatman GF/F (Mitchell, 1990) in a dual-beam

spectrophotometer (Varian Cary 1). Absorption of soluble

material was measured in 10 cm cuvettes after filtering
SIMBIOS Project Annual Report

81

seawater samples through 0.2 um pore size polycarbonate

filters. We have also been collecting detailed measurements

of other optical and phytoplankton properties including

phycoerythrin pigment, size distribution using a Coulter

Multisizer, photosynthesis, and particulate organic matter

(carbon and nitrogen).

15.3 RESEARCH RESULTS

a) Chlorophyll algorithms

CalCOFI data represents approximately 30% of the data

used by O’Reilly et al. (1998) for development of the

operational SeaWiFS Ocean Color 2 version 2 algorithm

(OC2v2). We have evaluated this algorithm compared to a

CalCOFI-specific regional algorithm (CAL-P6) using matchups collected during CalCOFI cruises (Kahru and Mitchell, in

press). At this time the atmospheric correction or calibration

errors in the retrieval of LWN create larger errors in chl-a

retrieval than differences between OC2v2 and CAL-P6. For

the Southern Ocean, however, there is a significant bias in the

OC2v2 algorithm, which warrants a focused effort – at low

chlorophyll a OC2v2 underestimates chlorophyll a, and it

overestimates at high chl-a. Figure 1 illustrates the LWN

(490)/ LWN(555) ratio plotted against chl-a for our combined

RACER and JGOFS Southern Ocean data sets. This region

has been shown to have bio-optical algorithms that are

different than low latitude regions such as CalCOFI (Mitchell

and Holm-Hansen, 1991; Mitchell, 1992; Arrigo et al., 1998).

Our results underscore the eventual need for specific regional

algorithms to obtain more accurate estimates of chlorophyll a

and primary production from ocean color remote sensing.

Regional algorithms will require procedures to allow transition

from low latitude to high latitude without introducing errors at

the lower latitudes. Unfortunately, there is relatively little data

in the polar front region; we have less than 20 observations

from JGOFS, and there are no reports of other data in this

region. Also lacking in the polar Southern Ocean data sets are

combined pigment and optical observations in the extremely

low chlorophyll regions that can be observed in the SeaWiFS

imager for the southern Pacific Ocean sector west of the Drake

Passage, and the southern Indian Ocean sector west of

Kerguelan Island. These two regions represent very low

satellite-derived chlorophyll which never exceed values of 0.2

mg chlorophyll a m-3.

b) LWN match-ups: in situ instrument intercomparison

During INDOEX, we deployed our Biospherical

Instruments MER-2048 and the SIMBIOS pool Satlantic

SPMR radiometer at the same stations. The MER-2048 was

deployed from the ship's stern A-frame, with potential

contamination by ship's shadow, and the SPMR was deployed

in free-fall mode, which would have no ship shadow artifacts.

Figure 2A is a scatter plot for SeaWiFS channels of LWN

derived from the two systems. Overall, the correspondence is

excellent with no bias relative to the 1:1 relationship. Figure

2B is a plot of MER-2048 and SPMR derived spectral LWN

compared to SeaWiFS derived LWN for a clear sky match-up.

The issues of poor LWN retrieval reviewed by Kahru and

Mitchell (in press) and Mitchell and Flatau, 1998 are evident.

Evaluation of atmospheric correction schemes

The SIMBIOS Project has defined a need to evaluate the

atmospheric correction algorithms for SeaWiFS, and convened

a workshop which led to the proposal of 6 separate

atmospheric correction schemes. We evaluated all 6 schemes

with our match-up data (25 match-ups, 17 of which are from

CalCOFI). Evaluation of satellite-retrieved normalized waterleaving radiances (LWN) was done by comparing SeaWiFS

HRPT images with in situ data collected concurrently (± 4

hours). HRPT data were processed to LWN using SeaDAS

3.3 software (Fu et al. 1998; update 004 released 9/1/99). The

level 2 generation atmospheric correction module of this

version of SeaDAS was modified by the SIMBIOS Project

with 6 candidate codes to be evaluated. Satellite values were

derived as averages over 3 x 3 pixel areas centered at the in

situ measurement. In summary, these comparisons reveal

under-estimation of the SeaWiFS-retrieved LWN using the

“baseline” algorithm compared to in situ measurements; the

discrepancies were larger for pooled data greater than 1 mg

chl m-3. An example of the SeaWiFS retrieved problem is

illustrated in Figure 2B. The differences were generally

smallest in the 555 nm band, and largest at shorter

wavelengths. Some of the proposed atmospheric correction

revisions improved the underestimation, but none of the

candidate algorithms was capable of retrieving accurate LWN

for SeaWiFS bands 1 and 2. Part of the problem at short

wavelengths may be attributed to calibration errors rather than

issues related to the zero water leaving radiance assumptions

or aerosol models of the base line processing.

15.4 WORK PLAN

Our participation in the quarterly CalCOFI cruises in the

California Current will continue throughout the next period.

We also hope to carry out at least 1 cruise to the Southern

Ocean as well as additional cruises in Korean waters. We will

continue data processing from previous cruises, including

CalCOFI, JGOFS, INDOEX and Japan/East Sea. Specific

attention will be placed on developing routine processing

schemes for our AC9 and Hydroscat data. We will continue

our modeling efforts to improve our understanding of regional

bio-optical properties and their relationship to biogeochemical

parameters (e.g. Reynolds et al, submitted). Our goal is to

develop appropriate regional parameterizations for semianalytical inversion models for the retrieval of inherent optical

properties as well as biogeochemical properties besides

chlorophyll a from satellite ocean color data.
SIMBIOS Project Annual Report

82

REFERENCES

Arrigo, K.R., D.H. Robinson, D.L. Worthen, B. Schieber and

M.P. Lizotte, 1998: Bio-optical properties of the

southwestern Ross Sea. Journal of Geophysical Research.

103(C10): 21,683-21,695.

Fu, G., K. Settle and C.R. McClain, 1998: SeaDAS: The

SeaWiFS Data Analysis System. Proceedings of the

Fourth Pacific Ocean Remote Sensing Conference,

Qingdao, China, 73-77.

Kahru, M. and B.G. Mitchell, 1999: Empirical chlorophyll

algorithm and preliminary SeaWiFS validation for the

California Current. International Journal of Remote

Sensing,. In Press.

Mitchell, B.G., 1990: Algorithms for determining the

absorption coefficient of aquatic particulates using the

quantitative filter technique (QFT). In: Ocean Optics X,

Spinrad, R., ed. 137-148.

Mitchell, B.G. and O. Holm-Hansen, 1991: Bio-optical

properties of Antarctic Peninsula waters: Differentiation

from temperate ocean models. Deep-Sea Research I.

38(8/9): 1,009-1,028.

Mitchell, B.G., 1992: Predictive bio-optical relationships for

polar oceans and marginal ice zones. Journal of Marine

Systems. 3: 91-105.

Mitchell, B.G. and M. Kahru, 1998: Algorithms for SeaWiFS

standard products developed with the CalCOFI biooptical data set. Cal.Coop.Ocean.Fish.Invest.R. 39: 133-

147.

Mitchell, B.G. and D.A. Kiefer, 1988: Variability in pigment

specific particulate fluorescence and absorption spectra in

the northeastern Pacific Ocean. Deep-Sea Research I.

35(5): 665-689.

Mitchell, B.G. and P.J. Flatau, 1998: Bio-Optical

measurement and modeling of the California Current and

Polar Oceans. In: SIMBIOS Year End Technical

Memorandum. pp. 10

[http://simbios.gsfc.nasa.gov/Documents/yrend/97130_yr

98.pdf]

O'Reilly, J.E., S. Maritorena, B.G. Mitchell, D.A. Siegel, K.L.

Carder, S.A. Garver, M. Kahru and C. McClain, 1998:

Ocean color chlorophyll algorithms for SeaWiFS. Journal

of Geophysical Research. 103(C11): 24,937-24,953.

Reynolds, R.A., D. Stramski and B.G. Mitchell, 1999: A

chlorophyll-dependent semi analytical reflectance model

from derived from field measurements of absorption and

back scattering coefficients within the Southern Ocean.

Journal of Geophysical Research. In Press.

Smith, R.C. and K.S. Baker, 1978: The bio-optical state of

ocean waters and remote sensing. Limnology and

Oceanography. 23: 247-259.

Sosik, H.M. and B.G. Mitchell, 1995: Light absorption by

phytoplankton, photosynthetic pigments, and detritus in

the California Current System. Deep-Sea Research I.

42(10): 1,717-1,748.

Stramski, D., R.A. Reynolds, M. Kahru and B.G. Mitchell

(1999) Estimation of particulate organic carbon in the

ocean from satellite remote sensing. Science. 285: 239-

242.
SIMBIOS Project Annual Report

83

Figure 1. The relationship between log transformed values of LWN(490)/LWN(555) versus chlorophyll a for Southern

Ocean data. Curves represent the SeaWiFS OC2v2, Mitchell 1992, and our latest Southern Ocean algorithm

SPGANT.

Figure 2. A. Scatter plot of LWN estimates for several stations during INDOEX derived from data using our

Biospherical Instruments MER 2048 and the SIMBIOS pool Satlantic SPMR.

B. Spectral plot of LWN derived from SeaWiFS and from two different in-water profilers.

0.00

0.50

1.00

1.50

2.00

2.50

0.00 0.50 1.00 1.50 2.00 2.50

SPMR-Lwn

MER2048/2041-Lwn2

Lw n2-412

Lw n2-443

Lw n2-490

Lw n2-510

Lw n2-555

"1-1"

A

AI-43, 990312a.d01

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

350 400 450 500 550 600 650 700

Wavelength, nm

Lwn

Lw n1-412

MER2048/2041-Lw n2

SPMR

SeaWiFS S1999071075812.L2

B
SIMBIOS Project Annual Report

84

This research was supported by the

SIMBIOS NASA contract # 97130

PEER REVIEWED PUBLICATIONS

Kahru, M. and B.G. Mitchell, 1999: Empirical chlorophyll

algorithm and preliminary SeaWiFS validation for the

California Current, Remote Sensing Letters, International

Journal of Remote Sensing in press.

Mitchell, B.G. and M. Kahru, 1998: Algorithms for SeaWiFS

standard products developed with the CalCOFI biooptical data set. CalCOFI Reports, Vol. 39: 133-147.

Nakajima, T., A. Higurashi, K. Aoki, T. Endoh, H.

Fukushima, M. Toratani, Y. Mitomi, B.G. Mitchell and R.

Frouin, 1999: Early phase analysis of OCTS radiance data

for aerosol remote sensing, IEEE Transactions, 37(3):

1,575-1,585.

O'Reilly, J.E., S. Maritorena, B.G. Mitchell, D.A. Siegel, K.L.

Carder, S.A. Garver, M. Kahru, C. McClain, 1998: Ocean

Color Chlorophyll Algorithms for SeaWiFS, Journal of

Geophysical Research, 103(C11), 24,937-24,953.

Submitted

Reynolds, R.A., S. Stramski and B.G. Mitchell, 1999: A

chlorophyll-dependent semianalytical reflectance model

derived from field measurements of absorption and

backscattering coefficient within the Southern Ocean.

Submitted to Journal of Geophysical Research.

Stramska, M., D. Stramski, B.G. Mitchell and C.Mobley,

1999: Estimation of the absorption and backscattering

coefficients from in-water radiometric measurements,

Submitted to Limnology and Oceanography.

PRESENTATIONS

Flatau, P.J., B. Bichnevicius, B.G. Mitchell, 1998:Vicarious

calibration of the absorption and scattering measurements

in the California Current, AGU Ocean Science Meeting,

San Diego.

Fougnie, B., P.-Y. Deschamps, R. Frouin, and B.G. Mitchell,

1998: Measuring Water-Leaving Radiance with a

Polarization Radiometer: Theory and Experimental

Verification, AGU Conference, San Diego.

Frouin, R., P.-Y. Deschamps, B.G. Mitchell and M. Kahru,

1998: The Normalized Difference Phytoplankton Index

for Satellite Ocean Color Applications, AGU Ocean

Science Meeting, San Diego.

Kahru, M. and B.G. Mitchell, 1998: Empirical chlorophyll

algorithm for the California Current, AGU,San Francisco.

Reynolds, R.A., M. Kahru, J.D. Wieland, D. Stramski and

B.G. Mitchell, 1998: An evaluation of SeaWiFS ocean

color chlorophyll algorithms within the Southern Ocean,

AGU, San Francisco.
SIMBIOS Project Annual Report

85

Chapter 16

SIMBIOS Normalized Water-Leaving Radiance Calibration and

Validation: Sensor Response, Atmospheric Corrections, Stray

Light and Sun Glint

James L. Mueller

Center for Hydro-Optics and Remote Sensing, San Diego State University, California

16.1 INTRODUCTION

This SIMBIOS contract supports acquisition of match up

radiometric and bio-optical data to validate SeaWiFS and

other ocean color satellites, and experiments to evaluate

uncertainty budgets and protocols for in situ measurements of

normalized water leaving radiance.

16.2 RESEARCH ACTIVITIES

Two cruises (GoCAL98B in Nov-Dec 1998 and

GoCAL99A in April 1999) were completed in the Gulf of

California during the second year of the contract. These

cruises were carried out aboard a Mexican research vessel in

collaboration with Drs. H. Maske, R. Lara-Lara, and S.

Alvarez-Borrego at the Centro de Investigacion Cientificay de

Educacion Superior de Ensenada (CICESE) in Ensenada,

Mexico, and with Drs. R. Zaneveld and S. Pegau of Oregon

State University (OSU), Corvallis (SIMBIOS Contract NAS5-

97129). Radiometric profiles, HPLC and fluorometric

chlorophyll a samples, and inherent optical properties (OSU)

were measured at 32 and 37 station locations during

GoCAL98B and GoCAL99A, respectively. Station

distributions during each cruise covered the entire Gulf, in a

pattern similar to that illustrated in Fig. 1 for previous years.

Due to persistent cloud cover over the Gulf of California in

November-December 1998, we obtained no match-ups with

SeaWiFS coverage during GoCAL98B. Better weather

conditions resulted in 5 match-ups with SeaWiFS coverage

during GoCAL99A. All radiometers used in GoCAL cruises

were calibrated at CHORS.

Data from GoCAL97 and GoCAL98A were submitted to

the SeaBASS archives. Analyses of data from GoCAL98B

and GoCAL99A are in progress (a delivery schedule waiver

was requested and approved). A significant engineering effort

has been devoted to the development of a unique instrument

system to support the proposed protocol experiments, and to

outfitting a small research boat to provide an appropriate

platform from which to conduct the experiments. The inwater profiling component of the system includes sensors to

measure hyperspectral downwelling irradiance, upwelling

radiance, absorption and beam attenuation, as well as

conductivity, temperature, depth, and chlorophyll a

fluorescence. The package is deployed on an umbilical tether,

and its vertical motion is effected by buoyancy adjustment.

Installed aboard the boat are hyperspectral radiometers to

measure incident irradiance, radiance leaving the water

surface, and sky radiance, and ancillary instruments including

an ultrasonic anemometer, a Class A digital barometer, a

shielded air temperature and relative humidity sensor, a

magnetic heading, roll and pitch unit, a GPS receiver, and a

fathometer. Data acquisition and control of the separate

instruments are integrated using a network of microcontrollers

linked to a central PC. Water samples for pigment and

absorption analysis are obtained using bottles deployed from a

davit. All the components of this system are in hand, and

integration is proceeding at CHORS. Financial costs for the

radiometric and IOP system, and for the boat, are shared

between this contract, other CHORS contracts and grants, and

SDSU Foundation cost-sharing funds.

16.3 RESEARCH RESULTS

Using data from GoCAL95 (pre-SIMBIOS), GoCAL97

and GoCAL98A (Figure 1), we determined that the SeaWiFS

algorithms for chlorophyll a and K(490) are not significantly

different from regression fits to the data in this region (Trees,

Mueller and Maske 1999). We also showed that the

correlations between fluorometric and HPLC determinations

of chlorophyll a concentration were high for each cruise, but

the slopes of the relationships varied strongly between cruises

(Trees, Mueller and Maske 1999). In collaboration with

colleagues at OSU and CICESE, data from the GoCAL series

of cruises were used for match-up comparisons between in situ

and SeaWiFS determinations of normalized water leaving

radiance (Barnard et al. 1998) and to characterize the

distribution of bio-optical properties in the Gulf of California

(Pegau et al. 1998).

The K(490,z) and Kpar(z) profile data from the station

locations illustrated in Fig. 1 were analyzed to derive families

of regression models using the remote sensing optical depth

K(490)-1, which corresponds to the 37% light level, to predict
SIMBIOS Project Annual Report

86

penetration to the 0.3% light level at 490 nm. Through a

process of trial and error, the Gulf was divided into three

separate bio-optical provinces: the central island region, the

basin N. of the islands, and the southern remainder of the

Gulf. Separate relationships were determined relating K(490)-

1 to the 490 nm 10%, 3%, 1% and 0.3% light levels in each

province. A similar analysis for each province was used to

predict the depth of the euphotic zone, assumed to correspond

to the 1% level for Epar(z), in the N. Gulf basin (Fig. 2) and in

the other provinces. A manuscript base on these results has

been submitted, and is in review, for publication in a special

issue of Ciencias Marinas (a bilingual Spanish/English journal

published in Mexico).

16.3 WORK PLAN

We will complete the integration and software

development for the profiler and above-water radiometric

system, and associated boat equipment, and begin engineering

field tests in the near future. Once the system and boat are

fully operational, we will use them to carry out the proposed

protocol experiments. In the near future, we will also begin

using the boat and instrument system to obtain match-up

validation data during SeaWiFS, and hopefully MODIS,

overpasses.

We will continue to support the GoCAL99B, and

subsequent cruises in the Gulf of Mexico, albeit not

necessarily by participating in the cruises per se. We will

provide logistic support to the cruises, calibration services for

the CICESE PRR and OSU Satlantic radiometers, and

analyses and SeaBASS archival of the PRR profiles,

fluorometric chlorophyll a concentrations, and HPLC pigment

concentrations.

REFERENCES

Barnard, A.H., J.R.V. Zaneveld, W.S. Pegau, J.L. Mueller,

and C.C. Trees, 1999: SeaWiFS ocean color in the Gulf of

California: validation. Ocean Optics XIV, Kaialua-Kona,

HI.

Pegau, W.S., A.H. Barnard, J.R.V. Zaneveld, J.L. Mueller, H.

Maske, R. Lara-Lara, S. Alvarez-Borrego, E. ValdezHolguin and R. Cervantes-Duarte, 1999: Optical

variability in the Gulf of California. Ocean Optics XIV,

Kaialua-Kona, HI.

Trees, C.C., J.L. Mueller, and H. Maske, 1999: Remotely

sensed pigment algorithms in the Gulf of California:

comparisons between coastal and oceanic areas.

Presented at the ASLO 1999 Aquatic Sciences Meeting,

Santa Fe.

This research was supported by the

SIMBIOS NASA contract # 97126

PEER REVIEWED PUBLICATIONS

Barnard, A.H., J.R.V. Zaneveld, W.S. Pegau, J.L Mueller, H.

Maske, R. Lara-Lara, S. Alvarez-Borrego, and E. ValdezHolquin. 1999: The determination of PAR levels from

absorption coefficient profiles at 490 nm. Ciencias

Marinas, in press.

Mueller, J.L., J.R.V. Zaneveld, W.S. Pegau, E. Valdez, H.

Maske, S. Alvarrez-Borrego, and R. Lara-Lara. 1997:

Remote sensing reflectance: preliminary comparisons

between in-water and above-water measurements, and

estimates modelled from measured inherent optical

properties. SPIE, 2963: 502-513.

Zaneveld, J.R.V., W.S. Pegau, A.H. Barnard, J.L. Mueller, H.

Maske, E. Valdez, R. Lara-Lara, and S. Alvarez-Borreo.

1997: Prediction of euphotic depths and diffuse

attenuation coefficients from absorption profiles: A

model based on comparison between vertical profiles of

spectral absorption, spectral irradiance, and PAR. SPIE,

2963: 585-590

PRESENTATIONS

Pegau, W.S., A.H. Barnard, J.R.V. Zaneveld, J.L. Mueller, H.

Maske, R. Lara-Lara, S. Alvarez-Borrego, E. ValdezHolguin, and R. Cervantes-Duarte, 1998: Optical

variability in the Gulf of California. Ocean Optics XIV

Conference Papers, Volume 2, Kailua-Kona, HI.
SIMBIOS Project Annual Report

87

Figure 1. Station locations for cruises GoCAL95, CoCAL97 and GoCAL98A

Figure 2. Depth of the euphotic zone (1% depth for Epar) in meters versus remote sensing

depth K(490)-1 (m) for stations N. of the Mid-Gulf Islands in 1997 and 1998.
SIMBIOS Project Annual Report

88

Chapter 17

Validation of Carbon Flux and Related Products for SIMBIOS:

the CARIACO Continental Margin Time Series and the Orinoco

River Plume

Frank Muller-Karger and Chuanmin Hu

University of South Florida, Department of Marine Science, St. Petersburg, Florida

Ramon Varela

Fundacion La Salle de Ciencias Naturales, Punta de Piedras, Edo. Nueva Esparta, Venezuela

17.1 INTRODUCTION

This SIMBIOS investigation focuses on validating ocean

color satellite products using monthly observations from the

Cariaco Basin (a coastal upwelling site), and seasonal extreme

measurements within the plume of the Orinoco River. During

1998-1999, this SIMBIOS Project focused on three major

areas:

• monthly bio-optical data collections at 10.5 N, 64.67 W

(the multidisciplinary CArbon Retention In A Colored

Ocean / CARIACO station),

• bio-optical sampling of seasonal extremes of the Orinoco

River plume,

• radiometric and atmospheric correction of SeaWiFS data.

Our main objective was to augment the SeaWiFS matchup database and a database of observations in Case-II waters.

We also participated in other SIMBIOS activities, including

the SIMBIOS PI meeting in Annapolis and cal/val activities

under Ken Carder's SIMBIOS program. We have actively

pursued the characterization of the calibration of SeaWiFS

satellite data, contributed to the improvement of SeaWiFS data

processing software, particularly the SeaDAS package, and

developed a scheme for atmospheric correction over turbid

waters. Our second-year activities are summarized below.

17.2 RESEARCH ACTIVITIES

The core of this SIMBIOS Project continues to be the

CARIACO oceanographic time series station described in the

SIMBIOS Project 1998 Annual Report. The series station is

located at 10.50 N, 64.66 W, and our observations consist of:

• 1 to 3 monthly cruises with a fully-equipped, modern

oceanographic vessel;

• mooring with 4 sediment traps (200, 400, 800, 1200 m;

capturing bi-weekly sample integrations);

• varved (laminated) sediment core analyses.

The monthly oceanographic cruises provide information on:

• composition, levels, and light absorption properties of

organic particulate and dissolved matter;

• pigments, HPLC, taxonomy of phytoplankton and general

classification of bacteria;

• biological productivity (phytoplankton and bacteria);

• the physical/chemical characteristics of the water,

including nutrient and oxygen levels;

• carbonate system; and

• meteorological and tide gauge observations.

Prior to October 1998, we conducted subsurface

radiance/irradiance profiles using a Biospherical Instruments

MER2048 in conjunction with a MER2041 Deck Cell. Since

October 1998, we have used a split-level PRR-600. Both MER

and PRR-600 casts were performed in October to help crossreference the observations made with these instruments. The

PRR-600 is more appropriate for measurements in some of the

high-chlorophyll waters sampled. The PRR-600 bands are:

• 7 bands Ed, Es (412, 443, 490, 532, 555, 665, 683 nm)

• 7 bands Lu (412, 443, 490, 532, 555, 665, 683).

Above-water measurements are made with a Photo

Research Hyperspectral Colorimeter Model PR650, which is a

calibrated, hand-held radiometer (8 nm resolution). Derived

products include Lw (Water-Leaving Radiance), Rrs (Remotesensed reflectance) and K (attenuation coefficient). In

addition, a full suite of measurements is made which includes:

particulate material and pigment absorption, HPLC,

fluorometric determinations of Chl concentration, pH,

Alkalinity, Primary Productivity, POC, DOC absorption and

concentration, nutrients, sun photometry, oxygen, and salinity.
SIMBIOS Project Annual Report

89

Cruise reports for each cruise, detailing station location and

observations collected, have been submitted to the SIMBIOS

Project.

Our emphasis to date in data analysis has been to

characterize the relationship between vertical flux and primary

productivity, as a necessary step prior to examining the

connection between bio-optical properties and various flux

parameters. Primary production followed a seasonal cycle,

with significantly higher production observed starting in

January and lasting through May each year. Average depthintegrated production between January and April 1996 was

1,784 mg C m-2 d-1 but reached 2,674 mg C m-2 d-1 in 1997.

May 1996 showed an extreme production value of 6,860 mg C

m-2 d-1, while May 1997 was about 2,500 mg C m-2 d-1, or

close to the seasonal average for that year.

We are now starting to examine the values for 1998,

which yield a total of about 1,360 mg C m-2 d-1 between

January and April 1998. Clearly, 1998 was strongly affected

by El Niño. The upwelling cycle of 1997 showed higher

seasonal production primarily as a result of the more frequent

ventilation events. In contrast, productivity during JuneDecember was 1,051 mg C m-2 d-1 and 865 mg C m-2 d-1 in

1996 and 1997, respectively. Annual integrated production

was 686 gC m-2 y-1 and 536 gC m-2 y-1 in 1996 and 1997,

respectively. Vertical flux of carbon was a minimum in

January, with about 0.03 mgC m-2 d-1 at 275 m, and 0.006 gC

m-2 d-1 at 1,225 m. By March flux had increased to 0.17 gC m2

 d-1 at 275 m and 0.06 gC m-2 d-1 at 1,225 m. Over the course

of the sampling period, settling carbon flux was 5.6% of

integrated primary production at 275 m and about 1.7% at

1,225 m. There was no seasonality in the proportion of vertical

flux to primary production, in contrast with the prevailing

view of the relationship between new production and total

production.

The Orinoco River Plume

Three cruises to the Orinoco River delta and plume have

been conducted to date, namely between 23-29 June 1998

(Figure 1), 25 and 30 October 1998 (Figure 1), and 23 and 26

February 1999. We seek to build a set of robust Case-II

observations to assess the validity of the SeaWiFS retrievals in

the plume. These data will be important for proper

interpretation of the global ocean color satellite data since

river plumes cover significant areas near continental margins.

We used the same instrumentation described above (MER,

PRR-600) for underwater light profiles and above-water

spectral remote-sensing reflectance observations. Observations

were conducted both away from the coast and very close to the

coast, including some of the delta tributaries. The latter

observations were conducted from a small boat using only the

PRR-600 and above-water, hand-held instrumentation.

The Orinoco Plume data span a very broad range of

remote sensing reflectance values. Figure 2 shows a

progression in hyperspectral reflectance curves going from

offshore plume station 4 (Figure 1) to station 16, located

within about 2 km of the mouth of Caño Macareo, the largest

active tributary to the Orinoco delta. The river plume data are

also being used by Joe Salisbury and Charles Vorosmarty at

the University of New Hampshire for automated modeling of

river water impact off the continent of South America, in a

model linked to terrestrial hydrology. Cruise reports, detailing

station locations and observations collected, have been

submitted to the SIMBIOS Project.

Radiometric and atmospheric correction of SeaWiFS data:

Under leadership of Dr. Chuanmin Hu, a postdoctoral research

associate, we have continued to study the performance of the

SeaWiFS Gain and Calibration Tables. Dr. Hu also developed

an alternative atmopsheric correction scheme of turbid coastal

waters, in which the epsilon, aerosol model number, t(765)

and t(865) are optimized for “turbid” pixels. Specifically, the

atmospheric correction parameters are determined through

nearest-neighbor searches of adjacent Case-I water pixels, and

these parameters are then applied over the respective turbid

pixels.

This method yields significant improvement in estimates

of chlorophyll relative to concurrent field observations, and

minimizes the number of negative water-leaving radiance

retrievals. The method also shows promise for applications

over shallow-water regions. Dr. Hu has also implemented a

band 6 / band 8 atmospheric correction algorithm in SeaDAS

and is preparing a manuscript on results of comparisons with

the products derived using the band 7 / band 8 algorithm. We

have implemented an extensive SeaWiFS batch processing

system for use with IDL and SeaDAS. We also implemented a

series of convenient SeaWiFS data analysis tools based on

IDL and IDL On the Net (ION), to allow analyses over the

world wide web. In an effort to assess MODIS algorithms, we

have continued with the implementation of Ken Carder's

algorithms in SeaDAS.

Instrumentation

We acquired a split-level PRR-660 instrument from

Biospherical Instruments and a hyperspectral hand-held fiberoptic sensor from Analytical Spectral Devices. The latter will

help obtain observations between 340 and 1,200 nm. Our older

PR-650 instrument only provided observations between 380

and 780 nm, which is inadequate to study the near-infrared

reflectance of highly turbid waters. We continue to test the ac9, which has to date been used on 4 cruises to the Gulf of

Mexico and the West Florida Shelf. We have had problems

with noise in the instrument and therefore have not sent it to

Venezuela on the Orinoco cruises.

The MICROTOPS unit from the SIMBIOS Project Office

is used routinely at the time of bio-optical observations during

each cruise. Bio-chemical and pigment samples are being

analyzed at various locations, while data archival is

centralized at our Remote Sensing Lab at the University of

South Florida.
SIMBIOS Project Annual Report

90

17.3 WORK PLAN

We will continue to occupy the CARIACO station on a

monthly basis. In addition, we plan to conduct three cruises to

the Orinoco River plume, specifically in October 1999 and in

February and October 2000. Analysis of data and samples will

continue. We are currently advancing several manuscripts that

describe the seasonal cycle in bio-optical properties at the

CARIACO station, the atmopsheric correction for turbid

waters, and digitization sensitivity of the SeaWiFS data.

ACKNOWLEDGEMENTS

This work was supported by the National Science

Foundation (NSF Grant OCE 9216626), the National

Aeronautics and Space Administration (NASA Grants NAG5-

6448 and NAS5-97128), and the Consejo Nacional de

Investigaciones Cientificas y Tecnologicas (CONICIT,

Venezuela). Many people have contributed substantially to the

success of this program, and if they are not mentioned here it

is by plain oversight on the author's part.

We are indebted to the personnel of the Fundacion La

Salle de Ciencias Naturales/Estacion de Investigaciones

Marinas Isla Margarita (FLASA/EDIMAR) for their

enthusiasm and professional support. In particular we thank

FLASA's Director, Dr. Hermano Gines, for his confidence in

our activities and the crew of the R/V Hermano Gines

(FLASA) for their able support at sea. Field bio-optical

measurements were conducted primarily by Natasha Rondon

and John Akl of FLASA. They, and Yrene Astor and Ana

Lucia Odriozola have processed the majority of the data to

satisfy the SeaBASS report formats. Jonathan Garcia (also at

FLASA) has processed the samples for particulate and

dissolved absorption coefficients. Juan Capelo and Javier

Gutierrez (FLASA) have assisted with the primary production

observations. Robert Thunell and Eric Tappa (U. South

Carolina) maintain the sediment trapping program and process

our particulate samples (POC, PON). Mary Scranton and

Gordon Taylor (SUNY) conduct bacteria productivity studies.

Dissolved Organic Carbon samples were processed by David

J. Hirschberg of State University of New York at Stony

Brook.
SIMBIOS Project Annual Report

91

Figure 1. Cruise track for Orinoco Plume cruise SIMBIOS 1, conducted 23-29 June, 1998 (left). Cruise

track for Orinoco Plume cruise SIMBIOS 2, conducted 27-30 October, 1998 (right).

Figure 2. Remote sensing reflectance data obtained with the hand-held Spectrascan PR-650 instrument.
SIMBIOS Project Annual Report

92

This research was supported by the

SIMBIOS NASA contract # 97128

PEER REVIEWED PUBLICATIONS

Perez, R., F. E. Muller-Karger, M. Merino, I. Victoria, N.

Melo, S. Cerdeira. 1999. Cuban, Mexican, US researchers

probing mysteries of Yucatan Current. Earth In Space.

Vol. 12, No. 1. p. 10-14.

Thunell, R. E. Tappa., R. Varela, M. Llano, Y. Astor, F.

Muller-Karger, and R. Bohrer. 1999: Increased marine

sediment suspension and fluxes following an earthquake.

Nature 398, 233-236.

Accepted

Hu, C., K. L. Carder, and F. E. Muller-Karger, 1999:

Atmospheric correction of SeaWiFS imagery over. Turbid

coastal waters; a pratical method. Remore Sensing of

Environment (in press)..

Müller-Karger, F. E., and C. Fuentes-Yaco, 1999:

Characteristics of wind-generated rings in the eastern

tropical Pacific Ocean. Journal of Geophysical Research

(in press).

Tang, D. L., I-H. Ni, D. R. Kester, and F. E. Müller-Karger, .

1999: Remote sensing observations of winter

phytoplankton blooms southwest of the Luzon Strait in

the South China Sea. Marine Ecology Progress Series, (in

press).

Thunell, R., R. Varela, M. Llano, J. Collister, F. MullerKarger, and R. Bohrer. 1999: Organic carbon fluxes and

regeneration rates in an anoxic water column: sediment

trap results from the Cariaco Basin. Limnology and

Oceanpgraphy (in press).

Zhang, M., K. Carder, Z. Lee, F. E. Muller-karger, and D. B.

Goldgof. 1999. Noise reduction and atmospheric

correction for coastal applications of Landsat Thematic

mapper imagery. Remote Sensing of the Environment. (In

press).

Submitted

Muller-Karger, F. E., R. Varela, R. Thunell, M. Scranton, R.

Bohrer, G. Taylor, J. Capelo, Y. Astor, E. Tappa, T. Y.

Ho, and J. J. Walsh, 1999: The annual cycle of primary

production in the Cariaco Basin: implications for vertical

export of carbon along a continental margin. Submitted to

Journal of Geophysical Research.

Muller-Karger, F. E., 1999: The spring 1998 NEGOM cold

water event: remote sensing evidence for upwelling and

for eastward advection of Mississippi water (or: How an

errant LC anticyclone took the NEGOM for a spin).

Submitted to Gulf of Mexico Science.

PRESENTATIONS

Del Castillo, C. E., F. Gilbes, P. G. Coble, and F. E. MullerKarger. 1998. Optical Characteristics of Dissolved

Organic Matter During a Bloom on the West Florida

Shelf. Ocean Optics. Hawaii.

Hu, C., K. L. Carder, and F. Muller-Karger. 1998 Preliminary

algorith to derive chlorophyll pigment concentration and

DOM absorption in turbid coastal waters from SeaWiFS

imagery. PORSEC Quingdao, China, Proceedings, 888-

892.

Hu, C., F. Muller-Karger, K. L. Carder, and Z. Lee. 1998. A

method to derive optical properties over shallow waters

using SeaWiFS. SPIE Meeting, Kona, Hawaii.

Proceedings.

Perez, R., F. E. Muller-Karger, I. Victoria, N. Melo, S.

Cerdeira. 1999. Cuban, Mexican, US Researchers Probing

Mysteries of Yucatan Current. EOS. AGU Transactions.

Volume 80, No. 14, p. 153.
SIMBIOS Project Annual Report

93

Chapter 18

The Bermuda Bio-Optics Program (BBOP)

David A. Siegel

ICESS, University of California at Santa Barbara, Santa Barbara, California

18.1 INTRODUCTION

The Bermuda BioOptics Project (BBOP) is a

collaborative effort between the Institute for Computational

Earth System Science (ICESS) at the University of California

at Santa Barbara (UCSB) and the Bermuda Biological Station

for Research (BBSR, D. A. Siegel [UCSB] and N. B. Nelson

[BBSR] P.I.'s). This research program is designed to

characterize light availability and utilization in the Sargasso

Sea and provide an optical link by which biogeochemical

observations may be used to evaluate bio-optical models for

pigment concentration, primary production, and sinking

particle fluxes from satellite-based ocean color sensors.

18.2 RESEARCH ACTIVITIES

The Bermuda Bio-Optics Program (BBOP) collects

detailed profiles of AOPs and IOPs in conjunction with the US

JGOFS Bermuda Atlantic Time-series Study (BATS) in the

mesotrophic waters of the Sargasso Sea. Cruises are

conducted monthly with additional cruises during the spring

bloom period, January through May. Continuous profiles of

apparent optical properties (AOPs) are collected in the upper

200m. Radiometer deployments are planned to optimize

match-ups with the BATS primary production incubations and

with SeaWiFS overpasses. The primary optical measurements

are downwelling vector irradiance and upwelling radiance,

Ed(z,t,λ) and Lu(z,t, λ), respectively. Our derived products

include profiles of remote sensing reflectance (Rrs(z, λ) and

down- and upwelled attenuation coefficients (Kd(z, λ), Ku(z,

λ), and are reported in near-real time with ~98% reliability.

The sampling package also includes a second mast-mounted

radiometer with wavebands similar to those on the underwater

instrument for measuring incident downwelling vector

irradiance, Ed(0+,t, λ). and calculating daily incident solar

radiation during primary production incubations. In addition

to radiometer data, samples for fluorometric chlorophyll-a are

collected daily near noon (local time) and results are delivered

to the SIMBIOS Project with the AOP data. Table 1 contains

a list of data products collected by BBOP and/or BATS, which

are relevant to SIMBIOS.

We are collecting data on both above- and in-water

inherent optical properties (IOPs). Discrete samples for

determining the absorption spectra of particulates, a ph(z, λ)

and a d(z, λ), and CDOM (ag(z, λ)) are collected according to

Nelson et al (1998). Particulate absorption spectra are

determined using the quantitative filter technique (Mitchell,

1990) and CDOM absorption according to Nelson et al (1998).

We have continued the collection of above-water R+rs(l)

spectra using the Analytical Spectral Devices FieldSpec

spectrometer (ASD, Boulder CO). Spectral beam absorption

measurements (a(z, λ) and c(z, λ), WET Labs AC-9) have

been discontinued because the baseline absorption of Sargasso

Sea water is nearly the same as that of the deionized water

used for the calibration making it difficult to discern a signal

(Brody et al, in prep).

18.3 RESEARCH RESULTS

We have continued our work on the local dynamics of nonchlorophyll light attenuation, providing an explanation for the

patterns observed in the Sargasso Sea. The significant

seasonal cycle in the ratio of Kd(412) to Kd(443) (Siegel and

Michaels 1996) was found to be the result of seasonal changes

in the concentration of CDOM, which, on average, comprises

more than one-half of the total non-water absorption

coefficient at 440nm. The distribution of CDOM was found to

be influenced by mixing, photo-bleaching and microbial

production, with turnover times of 90 - 110 days (Nelson et al.

1998, Nelson and Carlson, in prep). This work implies, for the

first time in the blue ocean, a link between microbial

community activity and CDOM dynamics (Figure 1).

The Sargasso Sea near Bermuda is mesotrophic,

characterized by both eutrophic and oligotrophic conditions

during different times of the year. Although low chlorophyll a

stocks and primary production rates prevail for the most of the

year, there is a short spring bloom characterized by somewhat

higher concentrations and rates, traditionally assumed to be

controlled by winter mixing and the resultant nutrient influx.

However, these accepted mechanisms of nutrient supply have

accounted for less than half of the annual nutrient flux

required by new production estimates. Using evidence from

BATS-CTD surveys, moored instruments, satellite altimetry

and eddy-resolving model simulations, Siegel, et al (1999a)

and McGillicuddy et al (1998) illustrated the importance of

mesoscale eddies to new production in the Sargasso Sea

(Figure 2). This work has demonstrated that eddy pumping

(the process by which mesoscale eddies induce isopychnal
SIMBIOS Project Annual Report

94

displacements that lift nutrient-replete waters into the euphotic

zone) and entrainment into the mixed layer during wintertime

convection are the two dominant mechanisms transporting

new nutrients into the euphotic zone at this site. Smaller

contributions are made by mixing in the thermocline and

wind-driven transport. The sum of all physical new nutrient

supplies effectively balances geochemical estimates of annual

new production. These calculations do not include biological

sources of new nutrients (e.g. nitrogen fixation), and the

inclusion of these may result in an overestimate of total

nutrient supply.

Using a 6-year time series of BBOP and BATS data with

site-specific and previously published global models, Sorensen

and Siegel, (1999) and Siegel et al. (1999b) illustrated the

problems associated with modeling both integrated primary

production (∫PP) and effective quantum yield (φc, mol C Ein1) in the Sargasso Sea. Siegel et al (1999b) found that all

models of primary production performed poorly, accounting

for less than 40% of the variance in ∫PP. Part of the failure of

global primary production models to encapsulate the variance

is due to the small range of values in ∫PP observations and the

small variance to be explained. Additionally, nearly one-half

of ∫PP occurs under light saturated conditions. More

importantly, the assumptions of steady state and balanced

growth required by production models are not met by the

“snapshot” nature of optical or satellite measurements and

boundaries must be placed on how empirical models for ∫PP

are developed, validated and applied to satellite ocean color

data sets. Sorensen and Siegel (1999) showed that although

the time series showed φc values to be highly variable, few

parameters correlated consistently and rationally with φc. The

low predictive capability of published models using a variety

of parameters demonstrates that we have yet to develop a

predictive understanding of the important photophysiological,

ecological and methodological processes controlling primary

production.

REFERENCES

Brody, E.A., D.A. Siegel, M. C. O’Brien, S. Wolfe. (in prep).

An In Situ Assessment of Inherent Optical Property

Variability in the Sargasso Sea.

McGillicuddy, Jr., D.J., A.R. Robinson, D.A. Siegel, H.W.

Jannasch, R.Johnson,T.D. Dickey, J. McNeil, A.F.

Michaels and A.H. Knap, 1998: Influence of mesoscale

eddies on new production in the Sargasso Sea. Nature,

394, 63-265.

Mitchell, B.G., 1990: Algorithms for determining the

absorption coefficient for aquatic particles using the

quantitative filter technique. Ocean Optics X,

Proceedings of S.P.I.E. 1302, 137-142.

Nelson, N.B. and Carlson (in prep) .Microbial production of

chromophoric dissolved organic matter in the Sargasso

Sea.

Nelson, N.B., D.A. Siegel, and A.F. Michaels, 1998: Seasonal

dynamics of colored dissolved material in the Sargasso

Sea, Deep Sea Research I, 45, 931-957.

Siegel, D.A., E. Fields and D.J. McGillicuddy, Jr., 1999a:

Mesoscale motions, satellite altimetry and new production

in the Sargasso Sea. Journal of Geophysical Research,

104, 13359-13379.

Siegel, D.A., T.K. Westberry, M.C. O'Brien, N.B. Nelson,

A.F. Michaels, J.R. Morrison, E.A. Caporelli, J.C.

Sorensen, S.A. Garver, E.A. Brody, J. Ubante and M.A.

Hammer, 1999b: The Bermuda BioOptics Project: Biooptical modeling of primary production from spacesensible variables. Submitted to Deep Sea Research, II.

Sorensen, J. and D.A Siegel, 1999: Variability and models of

the effective quantum yield of carbon assimilation in the

Sargasso Sea. Accepted for publication in Deep Sea

Research II.
SIMBIOS Project Annual Report

95

Figure 1. Mean profile of CDOM absorption dynamics (dCDOM/dt, m-1 d-1) for pooled summertime 1994 and 1995 data from the BATS

site (from Nelson, et al 1998). Solid and dashed lines are the fitted model using 1994 and 1995 bacterial production estimates,

respectively. The linear correlation coefficient (r2) between the pooled data and the model predictions is 0.83.

Figure 2. An example of the eddy pumping calculation using sea level anomalies (SLA) at the BATS site from 1993-1995 (from Siegel, et al

1999a). a) time-filtered SLA time series, gray regions denote upwelling events, b) cumulative uptake for 4 euphotic zone depths

in units of moles N m-2. The uptake rate is equal to the cumulative uptake divided by the total time (here, 1101 days).
SIMBIOS Project Annual Report

96

TABLE 1: A partial list of measurements made by BBOP & BATS

BBOP

Direct Measurements:

Ed(z,λ) Downwelling vector irradiance (410,441,465,488,510,520,555,565,589,625,665 & 683 nm)

Ed(0+,λ) Incident irradiance (340,390,410,441,465,488,520,545,565,589,625,665 & 683 & 350-1050 nm)

Lu(z,λ) Upwelling radiance (410,441,465,488,510,520,555,565,589,625,665 & 683 nm)

atp(λ) Particulate absorption spectrum by QFT

ad(λ) Detrital particle absorption spectrum by MeOH extraction

ays(λ) Colored dissolved absorption spectrum

Eo(z,λ) Scalar irradiance at 441 and 488 nm

Ff(z) Natural chlorophyll fluorescence using a broadband upwelled radiance sensor

chl-fl(z) Chlorophyll fluorescence with a SeaTech fluorometer

c(z,660) Beam attenuation coefficient at 660 nm with SeaTech 25 cm transmissometer

T(z) & S(z) Temperature and conductivity with SeaBird probes

chl-a(z) Discrete chlorophyll a determinations via Turner fluorometry (for next day delivery)

Primary Derived Products:

LwN(λ) Normalized water leaving radiance (410,441,465,488,510,520,555,565,589,625,665 & 683 nm)

RRS(0-,λ) In-water remote sensing reflectance (410,441,465,488,510,520,555,565,589,625,665 & 683nm)

RRS(0+,λ) Above-water remote sensing reflectance (350 to 1050 nm)

aph(λ) Phytoplankton absorption spectrum (= ap(λ) - adet(λ))

Kd(z,λ) Attenuation coefficient for Ed(z,λ) (410,441,465,488,510,520,555,565,589,625,665 & 683 nm)

KL(z,λ) Attenuation coefficient for Lu(z,λ) (410,441,465,488,510,520,555,565,589,625,665 & 683 nm)

<PAR(z)> Daily mean photosynthetically available radiation at depths of the in situ C14 incubations

b(z,λ) Spectral scattering coefficient (= c(z,λ) - a(z,λ))

U.S. JGOFS BATS (NSF) and Related Biogeochemistry Sampling Programs

Primary Production (in situ 14C incubation) Sinking flux (sediment trap array)

Phytoplankton pigments (fluorometric & HPLC) Nutrients (NO3+NO2, SiO4, PO4)

CO2 system (alkalinity, TCO2 and pCO2) Continuous atmosphere & surface pCO2

Dissolved oxygen (continuous & discrete) Zooplankton biomass & grazing

POC & PON (POP infrequently) DOC & DON (DOP infrequently)

Full water column, WOCE-standard CTD profile Bacterial abundance and rates

Phytoplankton abundance by flow cytometry Coccolithophore abundance

Validation spatial cruises (5 days, 4cruises/year) Deep ocean sediment sinking rates
SIMBIOS Project Annual Report

97

This research was supported by the

SIMBIOS NASA contract # 97125

PEER REVIEWED PUBLICATIONS

Dickey, T., D. Frye, J. McNeil, D. Manov, N. Nelson, D.

Sigurdson, H. Jannasch, D. Siegel, T. Michaels and R.

Johnson, 1998: Upper ocean response to Hurricane Felix

as measured by the Bermuda Testbed Mooring. Monthly

Weather Review, 126, 1195-1201.

Dickey, T., D. Frye, H. Jannasch, E. Boyle, D. Manov, D.

Sigurdson, J. McNeil, M. Stramska, T. Michaels, N.

Nelson, D. Siegel, G. Chang and J. Woo, 1998:

Preliminary results from the Bermuda testbed mooring

program. Deep Sea Research, I, 45, 771-794.

Garver, S.A., and D.A. Siegel, 1997: Inherent optical property

inversion of ocean color spectra and its biogeochemical

interpretation: I. Time series from the Sargasso Sea.

Journal of Geophysical Research., 102, 18,607-18,625.

McGillicuddy, Jr., D.J., A.R. Robinson, D.A. Siegel, H.W.

Jannasch, R. Johnson, T.D. Dickey, J. McNeil, A.F.

Michaels and A.H. Knap, 1998: Influence of mesoscale

eddies on new production in the Sargasso Sea. Nature,

394, 263-265.

McGillicuddy, Jr., D.J., R.J. Johnson, D.A. Siegel, A.F.

Michaels, N. Bates and A.H. Knap, 1999: Mesoscale

variability of ocean biogeochemistry in the Sargasso Sea.

Journal of Geophysical Research, 104, 13381-13394.

Nelson, N.B., D.A. Siegel, and A.F. Michaels, 1998: Seasonal

dynamics of colored dissolved material in the Sargasso

Sea. Deep Sea Research, I, 45, 931-957.

O'Reilly, J., S. Maritorena, B.G. Mitchell, D.A. Siegel, K.L.

Carder, M. Kahru, S.A. Garver, C.R. McClain, 1998:

Ocean color algorithms for SeaWiFS. Journal of

Geophysical Research, 103, 24,937-24,953.

Siegel, D.A, and W.G. Deuser, 1997: Trajectories of sinking

particles in the Sargasso Sea: Modeling of statistical

funnels above deep-ocean sediment traps. Deep-Sea

Research, I , 44, 1,519-1,541.

Siegel, D.A., E. Fields and D.J. McGillicuddy, Jr., 1999:

Mesoscale motions, satellite altimetry and new production

in the Sargasso Sea. Journal of Geophysical Research,

104, 13359-13379.

Accepted

Nelson, N.B., N.R. Bates, A.F. Michaels, and D.A. Siegel,

1999: Impact of spatial variability of pCO2 on air-sea

CO2 exchange in the Sargasso Sea. Accepted for

publication in Deep Sea Research, II.

Sorensen, J.C., and D.A. Siegel, 1999: Variability and models

of the effective quantum yield of carbon assimilation in

the Sargasso Sea, Accepted for publication in Deep Sea

Research, II.

Submitted

Toole, D.A., D.A. Siegel, D.W. Menzies, M.J. Neumann and

R.C. Smith, 1999: Remote sensing reflectance

determinations in coastal environments - Impacts of

instrumental characteristics and environmental variability.

In review in Applied Optics.

Siegel, D.A., M. Wang, S.Maritorena and W. Robinson, 1999:

Atmospheric correction of satellite ocean color imagery:

The black pixel assumption. Submitted to Applied Optics.

Siegel, D.A., M.C. O'Brien, T.K. Westberry, N.B. Nelson,

A.F. Michaels, J.R. Morrison, E.A. Caporelli, J.C.

Sorensen, S.A. Garver, E.A. Brody, J. Ubante and M.A.

Hammer, 1999: The Bermuda BioOptics Project: Biooptical modeling of primary production from spacesensible variables. Submitted to Deep Sea Research, II.

OTHER PUBLICATIONS

O'Brien, M.C., D.W. Menzies, D.A. Siegel and R.C. Smith,

1999, Calibration History of Several Marine

Environmental Radiometers. SeaWiFS Post Launch

Technical Report Series, NASA Tech. Memo. 1999-

206892. In press.

PRESENTATIONS

Brody, E.A., D.A. Siegel, M.C. O'Brien, E.A. Caporelli and

N.B. Nelson. 1997: Temporal patterns of IOPs in the

Sargasso Sea. Presented at the 1997 ALSO Aquatic

Sciences Meeting. Sante Fe.
SIMBIOS Project Annual Report

98

Fields, E.A., D.A. Siegel and D.J. McGillicuddy, 1998:

Mesoscale motions, satellite altimetry and

biogeochemical processes in the Sargasso Sea. Presented

at the AGU Ocean Sciences Meeting. San Diego, Trans.

Amer, Geophys. Union, Eos, 79, no. 1, OS22D-9.

Garver, S.A., and D.A. Siegel, 1997: Global Application of a

nonlinear inherent optical property inversion model.

Presented at the 1997 ALSO Aquatic Sciences Meeting.

Sante Fe.

Michaels, A.F., D.A. Siegel, R. Johnson, N. Nelson, N. Bates

and A. Knap, 1998: Hydrostation S, the Bermuda Atlantic

Time-series Study and decadal variability in the Sargasso

Sea. Presented at the AGU Ocean Sciences Meeting. San

Diego. Trans. Amer, Geophys. Union, Eos, 79, no. 1,

OS21I-4.

Nelson, N.B., C.A. Carlson, N.L. Krupp, and D.A. Siegel,

1997: Dynamics of chromophoric dissolved organic

material (CDOM) in the Sargasso Sea. Presented at the

1997 ALSO Aquatic Sciences Meeting. Sante Fe.

O'Brien, M.C., D. Menzies, D.A. Siegel and R.C. Smith, 1998:

Long-term calibration history of several marine

environmental radiometers. Presented at the AGU Ocean

Sciences Meeting. San Diego.. Trans. Amer, Geophys.

Union, Eos, 79, no. 1, OS32A-2.

Peterson, A.R, D.A. Siegel, S.A. Maritorena and S.A. Garver,

1999: Optimal tuning of semi-analytical ocean color

algorithms for the global ocean. Presented at the 1999

ASLO Aquatic Sciences Meeting, Sante Fe.

Shih ,A.S., D.A. Siegel, N.B. Nelson, M.C. O'Brien and S.A.

Garver, 1998: Modeling of optical property

characteristics: Analyses of observations from the

Sargasso Sea. Presented at the AGU Ocean Sciences

Meeting. San Diego, Trans. Amer, Geophys. Union, Eos,

79, no. 1, OS12B-9.

Siegel, D.A, E. Fields, D.J. McGillicuddy and A.F. Michaels,

1997: Mesoscale motions, satellite altimetry and

biogeochemical processes in the Sargasso Sea. Presented

at the 1997 ALSO Aquatic Sciences Meeting, Sante Fe.

Siegel, D.A., 1998: Spectral data assimilation for merging

satellite ocean color imagery, Presented at the Ocean

Optics XIV Meeting, Kona HI.

Siegel, D.A., 1999: Orthothogonal views of the global ocean

biosphere using SeaWiFS. Presented at the 1999 ASLO

Aquatic Sciences Meeting, Sante Fe.

Siegel, D.A., M. Lorenzi-Kaiser, and S. Maritorena, 1999:

Alternative views of the global ocean biosphere using

SeaWiFS. Opening Science Address, SeaWiFS Science

Team Meeting, Moss Landing, CA, May 1999.

Siegel, D., J. Yoder, S. Doney, N. Nelson, M. Kennelly, M.

Lorenzi-Kaiser, 1999: Satellite Views of the North

Atlantic Spring Bloom, To be presented at 1999 AGU

Fall Meeting.

Westberry, T.K., D.A. Siegel, N.B. Nelson and M.C. O'Brien,

1999: Regional modeling of primary production in the

Sargasso Sea. Presented at the 1999 ASLO Aquatic

Sciences Meeting, Sante Fe.
SIMBIOS Project Annual Report

99

Chapter 19

Spectral Data Assimilation for Merging Satellite Ocean Color

Imagery

David A. Siegel and Stéphane Maritorena

ICESS, University of California at Santa Barbara, Santa Barbara, California

19.1 INTRODUCTION

The Sensor Intercomparison and Merger for Biological

and Interdisciplinary Oceanic Studies (SIMBIOS) project was

initiated "to develop a methodology and operational capability

to combine data products from these various ocean color

missions in a manner that ensures the best possible global

coverage and best exploits the complementary missions of the

sensors" (GSFC ocean color group, 1995). The objective of

our program is to develop and validate an ocean color data

merging capability based on the use of (normalized) waterleaving radiances through a semi-analytical model.

The rationale for merging data at the normalized waterleaving radiance level is that such approach potentially allows

a good consistency in an extended suite of final products (as

opposed to Chl-a only). Another important aspect of this

approach is that redundancies in the spectral bands from the

various sources of data can be used for consistency checks

while the different wavebands result in increased spectral

information used by the model.

The core of the procedure is thus termed “Spectral Data

Assimilation” as the spectral water-leaving radiances from

various ocean color data sources are merged through the use

of a model. The complete SDA procedure includes various

steps which can be summarized as:

" Matchup process (space and time windows where data

from different sources are available);

" Atmospheric correction;

" BRDF correction;

" Surface effects and normalization;

" Semi-analytical Bio-optical model.

Our currently funded activities in SIMBIOS are mainly

oriented toward step 5 however we are conducting several

analysis related to steps 2 to 4.

19.2 RESEARCH ACTIVITIES

Atmospheric correction of SeaWIFS

In the initial workplan, we were not supposed to deal with

the atmospheric correction procedure. However because of the

occurrence of highly underestimated water-leaving radiances

in SeaWiFS data we have worked in that area as good waterleaving radiances from SeaWiFS are essential for our work. In

collaboration with M. Wang and W. Robinson from the

SIMBIOS Project, we assessed the role of the near-infrared

(NIR) “Black-pixel” assumption in the SeaWiFS data

processing scheme and proposed a method to correct for its

effects. We used bio-optical models to generate normalized

water-leaving reflectances in the NIR which are then

incorporated in the SeaWiFS atmospheric processing scheme.

This approach showed significant improvements in the

SeaWiFS radiometric data and Chl-a retrievals in highly

productive waters. A paper is submitted to Applied Optics

(Siegel et al., submitted).

Matchup data sets

We also worked with the SIMBIOS and MOBY matchup

data sets we received from the SIMBIOS Project. Regular

interactions with members of the SIMBIOS Project (B.

Schieber, S. Bailey, G. Eplee) helped getting familiar with the

data. The SeaWiFS data and the in situ measurements

contained in the SIMBIOS and MOBY data sets are the data

which we will use for the development and testing of the

“Data Merger”.

The Garver/Siegel model

The Garver/Siegel model code (Garver and Siegel, 1997)

was originally written in FORTRAN. An IDL version of it has

been developed and tested (for consistency) against the

FORTRAN version. The IDL code is used for development

and testing of the procedure. It has been adapted so it can

handle multiple data sets which is a requirement of the

merging procedure. The first tests of SeaWiFS and in situ data

merging were successfully conducted in September 1999.
SIMBIOS Project Annual Report

100

Model tuning

The other important aspect we have been working on is

the parameterization of the Garver/Siegel model and the

implications of that parameterization at varying scales. Our

approach on this is twofold: we are testing the model when

implemented with parameterizations available in the literature

and we are using a global optimization technique (Simulated

annealing).

We applied simulated annealing to synthetic and real

ocean data sets of remote sensing reflectance (Rrs) for three

parameters: chlorophyll concentration (Chl), non-algal

absorption coefficient (acdm) and particulate backscattering

coefficient (bbp). The real ocean data set is an extended

version of the SeaBAM data.

The optimization procedure accurately retrieves model

parameter values but the quality of retrievals is sensitive to the

noise in the data. This stresses the need for high quality data

sets that include the parameters involved in the semi-analytical

formulations. Parameterization resulting from the simulated

annealing procedure on real data has been tested on SeaWiFS

imagery.

19.3 WORK PLAN

Next year we will concentrate on aspects associated with

the propagation of uncertainties throughout the system and the

derivation of uncertainty estimates for the final merged

products. The benefits of increased spectral information

resulting from data sources with different characteristics will

be assessed. Consistency checks using band redundancies will

also be investigated. A test merging SeaWiFS, MOS and in

situ data will be considered. A paper about the “tuning” of the

Garver/Siegel semi-analytical model using both the literaturebased and the simulated annealing procedure will be submitted

sometime during the year. We are also planning on hiring

someone to help building a “complete” Ocean Color data set

(AOPs + IOPs) for development and validation of semianalytical models.

REFERENCES

Garver, S.A., and D.A. Siegel, 1997: Inherent optical property

inversion ofocean color spectra and its biogeochemical

interpretation: I. Time seriesfromthe Sargasso Sea.

Journal of Geophysical Research., 102, 18,607-18,625.

Siegel, D.A., M. Wang, S. Maritorena and W. Robinson,

1999: Atmospheric correction of satellite ocean color

imagery: The black pixel assumption. Submitted to

Applied Optics

This research was supported by the

SIMBIOS NASA contract # 98083

PEER REVIEWED PUBLICATIONS

Siegel, D.A., 1998: Spectral data assimilation for merging

satellite ocean color imagery. Extended abstract

published on the CD proceedings from Ocean Optics XIV.

Submitted

Siegel, D.A., M. Wang, S.Maritorena and W. Robinson, 1999:

Atmospheric correction of satellite ocean color imagery:

The black pixel assumption. Submitted to Applied Optics.

PRESENTATIONS

Peterson, A.R, D.A. Siegel, S.A. Maritorena and S.A. Garver,

1999: Optimal tuning of semi-analytical ocean color

algorithms for the global ocean. Presented at the 1999

ASLO Aquatic Sciences Meeting, Sante Fe.

Siegel, D.A., 1998: Spectral data assimilation for merging

satellite ocean color imagery, Presented at the Ocean

Optics XIV Meeting, Kona HI.

Siegel, D.A., 1999: Orthothogonal views of the global ocean

biosphere using SeaWiFS. Presented at the 1999 ASLO

Aquatic Sciences Meeting, Sante Fe.
SIMBIOS Project Annual Report

101

Chapter 20

SIMBIOS Data Product and Algorithm Validation with Emphasis

on the Biogeochemical and Inherent Optical Properties

J. Ronald V. Zaneveld, W. Scott Pegau, and Andrew H. Barnard

College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, Oregon

20.1 INTRODUCTION

The purpose of our funded component of the SIMBIOS

program is to address and quantify the relative accuracy of the

various ocean color remote sensing products by means of

product and algorithm validation. In order to accomplish

these goals, we have been collaborating in an international

research program in the Gulf of California designed to

examine the spatial and temporal bio-optical variability in this

region. In addition, we also participate in various cruises of

opportunity to supplement our validation data set.

Our long-term objectives are to; a) collect optical and

biochemical data in oceanic and coastal regions of interest, b)

provide collected data to the SeaBASS database, SIMBIOS

Project office, and other interested users, c) maintain and

update instrumentation and data archiving and dissemination

systems, and d) determine spatial and temporal error fields for

the biological and geophysical data products from the various

ocean color missions.

20.2 RESEARCH ACTIVITIES

During the past contract period, we have participated in 5

field campaigns, collecting an extensive amount of

radiometric, inherent optical property, aerosol optical

thickness, and physical data (Table 1). The five field

campaigns included a cruise offshore of Oregon, two Gulf of

California cruises, a cruise with Dr. Francisco Chavez

(MBARI), and a cruise of opportunity with Drs. Vivian

Montecino (University of Chile) and Giovanni Daneri

(University of Vaparaiso).

We have maintained and utilized the optical

absorption/attenuation profiling system for use in the

SIMBIOS instrument pool. We also maintain 3 water filtration

systems as a part of the SIMBIOS equipment pool. Recently,

we have developed a self-recording small inherent optical

property, CTD and radiometer profiling system for small boat

operations. In the past year we have worked extensively on

building an inline optical sampling system to be deployed on a

commercial ferry in the Gulf of California.

Currently, we are receiving all of the SeaWiFS HRPT

Level 1A (HMBR) data for the West Coast of North America

including the Gulf of California from the DAAC. This data is

being processed to various levels for use in the validation of

ocean color products and to build an extensive time series of

SeaWiFS imagery for the Gulf of California. We have also

been involved in a collaborative effort with Drs. Knut Stamnes

and Bingquan Chen at the Stevens Institute of Technology

investigating atmospheric correction of SeaWiFS imagery.

20.3. RESEARCH RESULTS

A detailed analysis of the spectral characteristics of the

absorption, attenuation, and scattering data collected in the

Gulf of California over the past 5 years has been completed

(Pegau, et al., 1998; 1999). In situ data collected in the Gulf

of California during two separate research cruises, were used

in an investigation into the validation of SeaWiFS satellite

measurements (Barnard, et al., 1998). Radiometric data

collected during a recent cruise in the Gulf of California were

used to validate the normalized water leaving radiance

estimated by the SeaWiFS satellite. The results of this work

show that the blue wavelengths are greatly underestimated by

the SeaWiFS sensor due to inaccurate atmospheric correction

(Figure 1).

In order to correctly invert the remotely sensed

reflectance to obtain the optical properties, we developed a

method for the appropriate depth averaging of remotely sensed

optical parameters (Zaneveld, et al., 1998). This method was

used to investigate the influence of vertical structure on the

remotely sensed signal. The results of this work were

presented at the ASLO Aquatic Sciences meeting in Santa Fe,

(Barnard, et al, 1999).

Based on the consistent relationships resolved by an

earlier study (Barnard, et al, 1998), we developed a method to

obtain closure between the inherent optical properties and

remotely sensed reflectance measurements (Barnard, et al.,

1999). The results of this model showed that inversion of the

remotely sensed reflectance to obtain the absorption

coefficient is possible if the spectral relationships of the

absorption coefficient are known. 
SIMBIOS Project Annual Report

102

We are continuing to work on developing this model to

include determination of the absorption coefficient due to

CDOM and particulate materials. A recent model that

spawned as a result of this research was the determination of

photosynthetically available radiation light levels using

profiles of the absorption coefficient (Barnard, et al.,1999).

20.4. WORK PLAN

In the upcoming SIMBIOS contract period, we have 3

research cruises planned. We will be participating in the

NASA sponsored MODIS initialization cruise (MODE-5) the

R/V Melville offshore of Baja California and within the Gulf

of California from October 1 to October 21. We also have 2

cruises planned for the Gulf of California, one following the

MOCE-5 cruise, and a spring cruise with the dates still to be

announced.

We are also currently negotiating with Dr. Carlos Garcia

(University of Rio Grande) for ship time on cruises he has

planned in early 2000 off Brazil. We anticipate participating

in other cruises in the next year, as the opportunity arises. We

will also be working on the installation of an in-line

fluorometer on the trans-Gulf ferry to provide a monthly

transect of chlorophyll fluorescence data in the Gulf of

California.

We plan to continue to investigations on the inherent and

apparent optical properties of the Gulf of California, as well as

continuing our work with ocean color algorithm validation and

development. We are continuing to work with Drs. Stamnes

and Chen to investigate new methods of atmospheric

correction of SeaWiFS data in the Gulf of California.

We will be continuing to process SeaWiFS level 1A

(HMBR) data in order to investigate the various temporal and

spatial scales of absorption and chlorophyll variability in the

Gulf of California. We will also be incorporating AVHRR

SST Pathfinder satellite data produced by Dr. Strub (OSU)

into this analysis.

REFERENCES

Barnard, A.H., W.S. Pegau, and J.R.V. Zaneveld. 1998.

Global relationships in the Inherent Optical Properties of

the oceans. J. Geophys. Res., 103:24,955-24,968.

Barnard, A.H., J.R.V. Zaneveld, and W.S. Pegau. 1998.

SeaWiFS ocean color in the Gulf of California:

Validation. Ocean Optics XIV Conference Papers,

Volume 2, Kailua-Kona, HI.

Barnard, A.H., J.R.V. Zaneveld, and W.S. Pegau. 1999.

Remotely sensed reflectance and the absorption

coefficient: Closure and inversion. Applied Optics, 38:

5108-5117.

Barnard, A.H., J.R.V. Zaneveld, W.S. Pegau, J.L Mueller, H.

Maske, R. Lara-Lara, S. Alvarez-Borrego, and E. ValdezHolquin. 1999. The determination of PAR levels from

absorption coefficient profiles at 490 nm. Ciencias

Marinas, in press.

Barnard, A.H., J.R.V. Zaneveld, W.S. Pegau, and T.J. Cowles.

1999. Assessing a key implicit assumption in ocean color

remote sensing: Optical homogeneity. ASLO Aquatic

Sciences meeting, Santa Fe, NM.

Pegau, W.S., A.H. Barnard, J.R.V. Zaneveld, J.L. Mueller, H.

Maske, R. Lara-Lara, S. Alvarez-Borrego, E. ValdezHolguin, and R. Cervantes-Duarte. 1998. Optical

variability in the Gulf of California. Ocean Optics XIV

Conference Papers, Volume 2, Kailua-Kona, HI.

Pegau, W.S., J.R.V. Zaneveld, A.H. Barnard, H. Maske, S.

Alvarez-Borrego, R. Lara-Lara, R. Cervantes-Duarte.

1999. Inherent optical properties in the Gulf of

California. Ciencias Marinas, in press.

Zaneveld, J.R.V., A.H. Barnard, W.S. Pegau, and E. Boss.

1998. An investigation into the appropriate depth average

of remotely sensed optical parameters. Ocean Optics XIV

Conference Papers, Volume 2, Kailua-Kona, HI.

Table 1. Summary of cruises and in situ data collected

Cruise Name

IOP

Profiles

Radiometric

Profiles

Sunphotometer

AOT

Surface Chlorophyll

samples

Sky/seastate photos

Offshore Oregon 150 0 14 days 56

Gulf of California 1998 31 11 6 days 0 X

Gulf of California 1999 36 19 11 days 0 X

Coastal California 6 0 0 0

Coastal Chile 22 22 0 0 X

Total 245 52 31 days 56
SIMBIOS Project Annual Report

103

Figure 1. Spectral comparison of the normalized water leaving radiance measured in situ (black) and as

determined by SeaWiFS using the Gordon and Wang (blue), Siegel (green) and Stumpf (red)

atmospheric correction algorithms for 5 days of match-up data in the Gulf of California (April 21,

24, 26, 28, and 30, 1999).

0.1

0.2

0.3

0.4

0.5

0.6

0.7

400 440 480 520 560

Wavelength (nm)

nLw (μW/cm2/sr)

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

400 440 480 520 560

Wavelength (nm)

nLw (μW/cm2/sr)

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

400 440 480 520 560

Wavelength (nm)

nLw (

μW/cm2/sr)

-1.2

-0.8

-0.4

0

0.4

0.8

1.2

400 440 480 520 560

Wavelength (nm)

nLw (μW/cm2/sr)

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

400 440 480 520 560

Wavelength (nm)

nLw (μW/cm2/sr)
SIMBIOS Project Annual Report

104

This research was supported by the

SIMBIOS NASA contract # 97129

PEER REVIEWED PUBLICATIONS

Barnard, A.H., W.S. Pegau, and J.R.V. Zaneveld. 1998:

Global relationships in the Inherent Optical

Properties of the oceans. J. Geophys. Res.,

103:24,955-24,968.

Barnard, A.H., J.R.V. Zaneveld, and W.S. Pegau. 1999:

Remotely sensed reflectance and the absorption

coefficient: Closure and inversion. Applied Optics,

in press.

Barnard, A.H., J.R.V. Zaneveld, W.S. Pegau, J.L

Mueller, H. Maske, R. Lara-Lara, S. AlvarezBorrego, and E. Valdez-Holquin. 1999: The

determination of PAR levels from absorption

coefficient profiles at 490 nm. In press Ciencias

Marinas.

Pegau, W.S., J.R.V. Zaneveld, A.H. Barnard, H. Maske,

S. Alvarez-Borrego, R. Lara-Lara, R. CervantesDuarte. 1999: Inherent optical properties in the

Gulf of California. In press Ciencias Marinas.

Zaneveld, J.R.V and W.S. Pegau. 1998: A model for the

reflectance of thin layers, fronts, and internal waves

and its inversion. Oceanography. 11: 44-47.

PRESENTATIONS

Barnard, A.H., J.R.V. Zaneveld, and W.S. Pegau. 1997:

Comparison of inherent optical properties across a

variety of oceanic regimes for application to remote

sensing. ALSO Aquatic Sciences, Sante Fe.

Barnard, A.H., J.R.V. Zaneveld, and W.S. Pegau. 1998:

Bio-optical maps derived from ocean color imagery

using a backscattering independent algorithm.

AGU/ASLO 1998 Ocean Sciences Meeting, San

Diego.

Barnard A.H., J.R.V. Zaneveld, and W.S. Pegau. 1998:

SeaWiFS ocean color in the Gulf of California:

Validation. Ocean Optics XIV Conference Papers,

Volume 2, Kailua-Kona, HI.

Barnard, A. H., J. R. V. Zaneveld, W. S. Pegau, and T. J.

Cowles. 1999: Assessing a key implicit assumption

in ocean color remote sensing algorithms: Optical

homogeneity. ASLO Aquatic Sciences Meeting,

Sante Fe.

Mueller, J.L., J.R.V. Zaneveld, W.S. Pegau, E. Valdez,

H. Maske, S. Alvarrez-Borrego, and R. Lara-Lara.

1997: Remote sensing reflectance: preliminary

comparisons between in-water and above-water

measurements, and estimates modelled from

measured inherent optical properties. SPIE, 2963:

502-513.

Pegau, W.S., A.H. Barnard, J.R.V. Zaneveld, J.L.

Mueller, H. Maske, R. Lara-Lara, S. AlvarezBorrego, E. Valdez-Holguin, and R. CervantesDuarte. 1998: Optical variability in the Gulf of

California. Ocean Optics XIV Conference Papers,

Volume 2, Kailua-Kona, HI.

Zaneveld, J.R.V., W.S. Pegau, A.H. Barnard, J.L.

Mueller, H. Maske, E. Valdez, R. Lara-Lara, and S.

Alvarez-Borreo. 1997: Prediction of euphotic

depths and diffuse attenuation coefficients from

absorption profiles: A model based on comparison

between vertical profiles of spectral absorption,

spectral irradiance, and PAR. SPIE, 2963: 585-590.

Zaneveld, J.R.V, A.H. Barnard, and W.S. Pegau. 1998:

A nearly backscattering independent algorithm for

the retrieval of spectral absorption from remotesensing reflectance. AGU/ASLO 1998 Ocean

Sciences Meeting, San Diego.

Zaneveld, J.R.V., A.H. Barnard, W.S. Pegau, and E.

Boss. 1998: An investigation into the appropriate

depth average of remotely sensed optical

parameters. Ocean Optics XIV Conference Papers,

Volume 2, Kailua-Kona, HI.
SIMBIOS Project Annual Report

105

Chapter 21

Atmospheric Correction Algorithms for ocean Color Remote

Sensing

Piotr Flatau

Scripps Institution of Oceanography, University of California, San Diego, California

21.1 INTRODUCTION

During the past 15 months the international group of

about 15 scientists (Table 1) have been involved in

preparation and execution of comprehensive ocean optics

and atmospheric radiation studies during the Indian

Ocean Experiment (INDOEX). Seven members of this

Ocean Color and Aerosol Characterization group

participated between February and April of 1999 in

scientific cruise on the R/V Ronald H. Brown. Our main

purpose was to:

• Collect comprehensive, simultaneous, in-water and

above-water data for the atmospheric correction

process studies.

• Characterize state of the atmosphere during the

INDOEX including aerosol optical thickness (AOT),

vertical distribution of aerosols and clouds

microphysics as well as inherent optical properties

of aerosols and phytoplankton.

• Intercompare AOT and remote sensing reflectance

(Rrs) measurements obtained with different

radiometers and develop algorithms for state-of-theart above the water instrumentation.

• Develop atmospheric science applications of the

ocean color data by interacting with the INDOEX

community.

Table 1. INDOEX PI’s

K. Aoki

Piotr Flatau

Howard Gordon

Mati Kahru

Krzysztof Markowicz

Mark Miller

Greg Mitchell

T. Nakajima

Jessica Nolan

Mike Reynolds

Ajit Subramaniam

Ken Voss

Judd Welton

John Wieland

The uniqueness of this project is based on the fact

that (a) we performed comprehensive above the water

and in-water measurements and that (b) we were part of

the large atmospheric science aerosol project (INDOEX).

The results up to date, including technical reports,

were collected in the INDOEX Ocean and Aerosol

Characterization Group CD-ROM available upon request

at http://atol.ucsd.edu/~pflatau .

21.2 RESEARCH ACTIVITIES

1. Vertical measurements of aerosols and clouds were

made using a micro-pulse lidar system (MPL). The

MPL Lidar is part of the SIMBIOS instrumentation

pool. The MPL system used during INDOEX was

operated at the full laser power supply setting of 1

W. The data are stored in 1 hour binary files with

each record containing a header followed by the

signal in ph/sec at successive 75 m increments up to

a preset range (30 km). The MPL was operated

successfully from February 22 to March 15, 1999.

The original MPL system was removed and a new

MPL was installed on March 15. The MPL ran nonstop with the exception of several hours during midday when the system was turned off to avoid direct

sunlight from entering the MPL, which would

damage the detector. The SRAB(r) data acquired

during the cruise is available at the following NASA

web-site: http://virl.gsfc.nasa.gov/mplnet/indoex_

 ship/mainpage.htm

2. During the INDOEX cruise on R/V Ronald Brown,

an integrated underwater profiling system was used

to collect optical data and to characterize the water

column. The system included an underwater MER2048 radiometer (Biospherical Instruments Inc., S/N

8772) measuring depth, downwelling spectral

irradiance (Ed), upwelling spectral irradiance (Eu)

and upwelling radiance (Lu) at 12 spectral bands

from 340-665 nm and a MER-2041 deck-mounted

reference radiometer (Biospherical Instruments Inc.,

S/N 8739) measured downwelling irradiance over

the same range. The MER-2048 was also interfaced
SIMBIOS Project Annual Report

106

to a 25 cm transmissometer (SeaTech Inc.), a

fluorometer (Wetlabs Inc.), and conductivity and

temperature probes (Sea-Bird Electronics Inc.).

3. Aerosol optical thickness (AOT) measurements

during the INDOEX were performed between

February 26, 1999 (Julian Day 57) and March 30,

1999 (Julian Day 89. The AOT was studied using 4

instruments SIMBAD, Microtops handheld

sunphotometer, PREDE sunphotometer, and

shadowband instrument. Separate reports provide

information about these different instruments.

4. Interaction with research groups who collected

extensive atmospheric aerosol characterization data

including mass spectrometry, single scattering

albedo, aircraft, and numerical modeling datasets on

R/V Ronald H. Brown and in the region of tropical

Indian Ocean and Arabian Sea.

21.3 RESULTS

Remote sensing reflectance

In general, the INDOEX relationships between

LWN and chlorophyll a are similar to the respective

relationships for the CalCOFI dataset (Figure 1). The

INDOEX chl a values are mostly low, with just one

station over 1 mg m-3. The minimum chl concentration in

the CalCOFI dataset is 0.05 while INDOEX has values

as low as 0.03 mg m-3.

The inherent scatter is due to, among others, variable

light field, surface conditions, variations in the

absorption and scattering characteristics (e.g. Gordon et

al., 1988). In the log-log space the relationship can be

fitted with a cubic polynomial. The non-linearity

(curvature) of this relationship is more evident at shorter

wavelengths (e.g. 412 nm and even more so in the UV

region). LWN can be calculated from the relationship

log(LWN) = a0 + a1 * C + a2 * C 2

 + a3 * C 3. The

coefficients of the polynomial (a0 to a3) are given in

Figure 1.

At 412 nm the INDOEX LWN values are generally

higher compared to CalCOFI values at similar chl values.

This is an indication of reduced concentration of the

colored dissolved or detrital organic matter (CDOM). A

conspicuous feature is a cluster of high LWN (665)

values. High reflectance at 665 nm is probably caused

by chl fluorescence. The causes of the increased chl

fluorescence need to be studied.

Vertical aerosol distribution

Preliminary scanning of the entire data set has

identified four groups of similar data. These groups are

largely defined by latitude, and are listed below: (a)

Southern Latitudes, (b) Mid-Latitudes, (c) Northern

Latitudes, (d) Northern Arabian Sea (Northern-most

point of cruise). Figure 2 display daily plots of SRAB(r)

for Southern Latitude displays an example of lidar data

taken in the relatively clean Southern Indian Ocean (midday coordinates ~11.19o

 S, ~59.25o E). The plot shows a

well defined MBL to about 1 km, with some weak

aerosol returns up to about 2 km. The AOD measured in

this region (< 0.1) was lower than AOD measured in the

other regions. This region was relatively free of upper

level cirrus, but did contain occasional packets of

cumulous in the MBL and up to ~10 km. This was the

cleanest region encountered during the INDOEX cruise.

NOTE: Starting just after 20:00 UTC, a cirrus layer from

15 to 16 km can be seen.

Aerosol optical thickness and size distribution

derived from PREDE sunphotometer as a function of

latitude. Between JD55 and 57 the optical thickness was

less than 0.1 in all channels. During the ITCZ crossing

(days 58-59) the optical thickness increased to 0.2 at

500nm. In that time the ITCZ was localized between 2-

4S. The reason for this increase is that in proximity of

the Equator the westerlies limit transport of pollution

from Northern to Southern Hemisphere. After the ITCZ

crossing the optical thickness increased even further. The

Angstrom coefficient shows similar behavior. It is 0.3 in

proximity of 10S and 1.4 in vicinity of 4N. This indicates

that concentration of small particles is increasing towards

North. However, during February 27, 1999 (JD57) we

observed sudden drop in the Angstrom coefficient value,

which is related to sub-visual cirrus in vicinity of the

ITCZ. At the beginning of Leg 2 the AOT was initially

high (0.4 at 500nm) but its value decreased fast and was

0.1 in the middle of the Arabian Sea. At the same time

Angstrom coefficient was decreasing. At 15N it was 0.5

which indicates that the antycyclonic circulation in this

region was responsible for the mineral dust transport

from the Somali Desert region.

21.4 WORK PLAN

Our short term goals are threefold:

• intercompare AOT measurements and compare them

with the SeaWiFS atmospheric correction;

• intercompare nLw and Rrs and compare them with

the SeaWiFS water leaving radiance and remote

sensing reflectance;
SIMBIOS Project Annual Report

107

• characterize large scale aerosol distribution using the

MATCH model, NCAR/NCEP reanalysis, and

AVHRR data and intercompare them with the

SeaWiFS derived AOTs.

These tasks have been already initiated. Our long

term goals are to:

• develop improved atmospheric correction algorithms

for the regional basins; and

• to develop atmospheric science applications of the

ocean color data by interacting with the INDOEX

community modeling and data assimilation efforts.

Figure 2. Lidar data taken in the relatively clean Southern Indian Ocean ~11.19o

 S, ~59.25o E.
SIMBIOS Project Annual Report

108

Figure 1. INDOEX relationships between LwN and Chlorophyll a
SIMBIOS Project Annual Report

109

This research was supported by the

SIMBIOS NASA contract # 97139

PRESENTATIONS

Flatau, P.J.; Piskozub, J.; Zaneveld, J.R.V., 1998:

Asymptotic light field in the presence of a bubblelayer. Proceedings of Ocean Optics XIV

Conference, Kona, Hawaii.

Flatau, Piotr J, Greg Mitchell, Ajit Subramaniam, John

Wieland, E Judd Welton, Krzysztof Markowicz,

Jessica Nelson, Ken Voss, Howard Gordon, R

Michael Reynolds, Mark Miller, Teruyuki

Nakajima, Ken Rutlidge, Mati Kahru , 1999: Ocean

Color and Aerosols. AGU Fall Meeting, San

Francisco.

Flatau, Piotr J., Greg Mitchell, Ajit Subramaniam, Judd

Welton, Krzysztof Markowicz, Jessica Nolan, Mati

Kahru, Ken Voss, Mike Reynolds, T.Nakajima,

Mark Miller, John Wieland, 2000: Comprehensive

ocean color measurements during the 1999

INDOEX Project. AGU Ocean Sciences Meeting,

San Antonio, Texas.

Miller Mark, M., R. Michael Reynolds, Mary Jane

Bartholomew, 1999: Aerosol Optical Thickness and

Diffuse radiance Measurements During INDOEX

1999. AGU Fall Meeting, San Francisco.

Nolan Jess, Greg Mitchell, 2000: Effects of Nutrients

and Light on the Maximum Quantum Yield of

Carbon Fixation and Variable Fluorescence in the

Indian Ocean. AGU Ocean Sciences Meeting, San

Antonio, Texas.

Subramaniam, A., Jessica Nolan, John Wieland, Mati

Kahru, B. Greg Mitchell, 2000: An Optical Biogeographical Description of the Indian Ocean

During the 1999 Spring Intermonsoon. AGU Ocean

Sciences Meeting, San Antonio, Texas.

Welton, Ellsworth Judd, Piotr J. Flatau, Kenneth J.

Voss, Howard R. Gordon, Krzysztof Markowicz,

James R. Campbell, James D. Spinhirne, 1999:

Measurements of the Vertical Distribution of

Aerosols and Clouds During INDOEX 1999 Using

Micro-pulse Lidars, AGU Fall Meeting, San

Francisco.
SIMBIOS Project Annual Report

110

Chapter 22

Validation of the SeaWiFS Atmospheric Correction Scheme

Using Measurements of Aerosol Optical Properties

Mark A. Miller, R. M. Reynolds and Mary Jane Bartholomew

Brookhaven National Laboratory Upton , New York

22.1 INTRODUCTION

The goal of the research described below is to

validate the assumptions about aerosol scattering

properties that are required to compute water-leaving

radiance from ocean color satellite radiance

measurements. Satellite-to-surface measurement

comparisons can be made in the 765-870 nm wavelength

band, while modeled aerosol optical properties used in

the satellite water-leaving radiance retrievals must be

compared with the surface measurements at shorter

wavelengths. Because the modeled aerosol properties at

wavelengths less than 765 nm are based on the optical

properties in the 765-870 nm wavelength band, the first

order validation problem is the credibility of the satellite

aerosol measurements in those bands. At shorter

wavelengths, the validity of the assumed aerosol model

is the key issue.

The research outlined below is an effort to measure

the aerosol optical properties from 870-380 nm over the

world’s oceans and coastal zones. These measurements

can then be compared with satellite measurements of

aerosol optical properties in the 765-870 nm wavelength

band and with the models used in satellite water-leaving

radiance retrievals at shorter wavelengths. Measuring

the aerosol optical properties from ships at sea is done

with sun photometry of varying sophistication, while

aerosol optical properties in coastal zones are

continuously monitored by the Aerosol Robotic Network

(AERONET). These measurement systems are used as

ground truth to evaluate atmospheric correction

algorithms used in satellite ocean color retrievals.

There are two primary types of sun photometer used

to measure the aerosol optical depth: narrow field-ofview radiometers aimed at the solar disk and rotating

shadow-band radiometers. The latter are wide-field-ofview radiometers that employ an occulting apparatus to

add directional capabilities. Just as narrow-field-of-view

radiometers must be accurately aimed, a pitfall for

measurements on ships at sea, conventional shadow-band

radiometers also require exact orientation. Development

of the Fast-Rotating Shadow-band spectral Radiometer

(FRSR), a hybrid form of the original shadow-band

radiometer design, has removed the orientation

requirement, whereupon shipboard use of shadow-band

radiometers has been encouraged. As compared to landbased units, shipboard fast-rotating shadow-band

radiometers require much faster rotation of the occulting

arm, faster-response silicon detectors, higher data

sampling rates, and more sophisticated data analysis. As

part of a multi-agency effort between NASA SIMBIOS

and the Department of Energy’s Atmospheric Radiation

Measurement (ARM) program, the Brookhaven National

Laboratory has developed a shipboard FRSR. It

measures spectral global and spectral diffuse irradiance

with 2-minute resolution, which are used to calculate the

2-minute spectral direct-normal irradiance as a function

of solar zenith angle. From these data, the aerosol

optical thickness can be computed during clear periods

using the Langley regression technique, or continuously

if high quality extraterrestrial calibration coefficients are

known. In addition, the diffuse irradiance measured by

the FRSR can be used to evaluate fractional cloudiness,

thereby providing a means to test cloud filtering

algorithms used in satellite ocean color retrievals.

22.2 RESEARCH ACTIVITIES

The BNL shipboard FRSR has progressed from a

prototype to an operational instrument during the past

year. The original FRSR instrument plus three new units

constructed for ARM and the University of Miami were

deployed aboard 4 different ships along with a variety of

other aerosol-oriented instrumentation including handheld sun photometers. Data coverage exceeded 46 weeks

and parts of all three oceans were sampled (Table 1).

The field experiments conducted during this period were

AEROSOLS99, INDOEX, JASMINE, and NAURU99

and at the conclusion of these cruises, all of the FRSR

and hand-held units used to collect data were moved to

Hawaii and calibrated at Mauna Loa over a 20-day

period. In parallel with the shipboard aerosol

measurements, an analysis of satellite and surface-based

optical properties continues using SeaWiFS and

AERONET data. Results of an analysis of match-up

data are presented in last year’s report and progress has
SIMBIOS Project Annual Report

111

been made in producing a more reliable match-up dataset

during the past year. A key finding of last year’s

analysis was that the match-up algorithm did not

effectively filter clouds as indicated by aerosol optical

thickness pixel-to-pixel variability that was not

physically realistic. To address this problem, a new

cloud filter package was implemented in the

SeaWiFS/AERONET match-up code (Sean Bailey,

personal communication). The result was a much more

stringent set of quality checks that resulted in a vastly

improved match-up analysis. An unfortunate trade-off

was that the size of the revised match-up dataset was

considerably smaller, thereby severely restricting the

statistical significance of the match-up analysis in coastal

zones. Within the next few months, a more significant

dataset should accumulate and a second analysis will be

performed, so this aspect of our research is not discussed

in this report.

22.3 RESEARCH RESULTS

Extensive deployment of the FRSR and hand-help

sun photometers along with a thorough Mauna Loa

calibration provide a foundation for the research results

discussed here. The Langley calibrations performed on

Mauna Loa with the FRSR were in excellent agreement

with Langley calibrations at intermediate locations

during the three-ocean cruise. This calibration test

shows that the FRSR is able to hold its calibration for

long periods (i.e. months) even when operated

continuously at sea. Moreover, the experiments increase

confidence in the aerosol optical thickness (AOT)

computed continuously from the cruise data.

A 5-day comparison between the FRSR and three

hand-held sun photometers was made during the

AEROSOLS99 experiment on-route between Norfolk,

VA and Cape Town, South Africa. The hand-held sun

photometers were operated in close proximity to the

FRSR with different operators simultaneously making

AOT measurements at discrete times during each day.

As aforementioned, all the instruments used in these

comparisons were post-calibrated at Mauna Loa and the

same processing algorithm was used to compute AOTs

from the raw signal values. Results showed that the

FRSR AOTs agree with the AOTs from hand-held sun

photometers. Two of the three well-calibrated hand-held

sun photometers were in excellent agreement with the

FRSR, while the third generally registered higher values

of AOT despite its accurate calibration. This

discrepancy suggests that there was some problem with

the routine operation of this third hand-held sun

photometer, perhaps low-batteries or movement of the

device into and out of the air-conditioned laboratory

between measurements. These comparisons suggest that

multiple sun photometer measurements may be the most

efficient means of evaluating data quality and identifying

suspect measurements.

The AEROSOLS99 cruise lasted approximately 2-

weeks and traversed at least three important aerosol

regimes: Northern Hemisphere maritime aerosol, a

plume of continental aerosol off Africa, and Southern

Hemisphere aerosol. The FRSR and hand-held sun

photometers detected the increase in AOT into the

African dust/biomass-burning plume from an AOT of 0.1

0.5 AOT at 870 nm (Figure 1). Changes in the aerosol

characteristics were also indicated by changes in the

Angstrom exponent, which suggested that the aerosol in

the African plume was considerably smaller in average

size than the background sea-salt aerosol. The INDOEX

and NAURU99 cruises provided additional data that is

currently being analyzed. Preliminary results indicate

that the FRSR functioned well in the variety of aerosol

and sea conditions that were encountered.

In summary, we have collected a 46-week data set

covering portions of three oceans that includes AOTs,

global irradiance, and diffuse irradiance in a variety of

conditions. Characteristics from various regimes are

being quantified and results-to-date suggest that this data

set provides information that can be directly applied to

SeaWiFS atmospheric correction validation studies. Of

particular importance is the size of the database. An

autonomous instrument such as the FRSR that operates

continuously can be deployed for long periods on ships

of opportunity, thereby substantially increasing the odds

of a ocean color satellite match-ups.

22.4 WORK PLAN

During the coming year, in addition to expanding

our measurement database through field deployments of

the FRSR, we will analyze the database collected during

the past year and construct SeaWiFS/FRSR/AERONET

match-ups for the purpose of evaluating atmospheric

correction algorithms. Seminal to this effort is a

comparison between the AOTs measured with the FRSR

during AEROSOLS99 and INDOEX and those measured

with hand-held sun photometers, lidars, PREDE, and

SIMBAD. These efforts are being organized under the

umbrella of special issues of the Journal of Geophysical

Research and scientific coordinators for these projects

have been selected.

In addition, we are currently engaged in an analysis

of the data collected during all previous field

deployments with the following questions are being

addressed:

• What are the observable differences between

sea-salt aerosol, bio-mass burning by-products,

Saharan dust, and other marine aerosols, and are
SIMBIOS Project Annual Report

112

these differences accurately detected by

SeaWiFS?

• What is the climatology of clear-sky diffuse

irradiance over the world’s oceans and is it

possible to develop models to compute diffuse

irradiance if only the global irradiance is

known?

• In partly cloudy conditions, is there a distinct

signature that discriminates optically thin clouds

and optically thick aerosol thereby allowing the

two to be identified from space and/or the

surface?

• Are there observable differences in the diffuse

irradiance in partly cloudy conditions that are a

function of climatological regime or cloud type?

Table 1: Cruise summaries for FY99 deployments of the 4 FRSR’s (1 NASA/DOE, 2 DOE, and 1

University of Miami) built by Brookhaven National Laboratory.

Platform Experiment Location Other AOT data Duration

R/V Ron

Brown

Aerosols99 Atlantic Ocean Microtops, SIMBAD, lidar 1 month

INDOEX Indian Ocean Microtops, SIMBAD, PREDE, lidar 1 months

JASMINE Indian Ocean, TWP 1 month

Nauru99 TWP Microtops, lidar 1 months

R/V Mirai Nauru99 TWP Microtops 1.5 months

Island of

Nauru

Nauru TWP Full complement 2 months

CC Polar

Sea

U. Miami TWP-N. Pacific Microtops 2.5 months

Pierre

Raddisson

U. Miami Greenland Sea 2 months

R/V

Mellville

SIMBIOS Gulf of California Full complement 1 month

Figure 1. Aerosol optical thickness for three days during the AEROSOLS99 cruise
SIMBIOS Project Annual Report

113

This research was supported by the

SIMBIOS NASA interagency agreement # 97888

PEER REVIEWED PUBLICATION

Porter, J.N., M.A. Miller, C. Motell, and C.Pietras, 1999:

Use of hand-held sun photometers for measurements

of aerosol optical thickness at sea. Submitted to J.

Atmos. Ocean. Tech..

Reynolds, R.M., M.A. Miller, and M.J. Bartholomew,

1999: Design, operation, and calibration of a

shipboard fast-rotating shadowband spectral

radiometer. Submitted to J. Atmos. Ocean. Tech..

PRESENTATIONS

Miller, M.A., R. M. Reynolds, and M.J. Bartholomew,

1999: Aerosol optical thickness and diffuse

irradiance measurements during INDOEX, AGU

Meeting.

Reynolds, R.M. and M.A. Miller, 1999: Instrument

demonstration at the 9th Annual ARM Science Team

Meeting, 1999, San Antonio, Texas.

SIMBIOS Project Annual Report

115

Chapter 23

Measurements of Aerosol, Ocean and Sky Properties at the HOT

Site in the Central Pacific.

John N. Porter and Ricardo Letelier

Hawaii Institute of Geophysics and Planetology, University of Hawaii, Honolulu, Hawaii

23.1 INTRODUCTION

Monthly cruises have been made to the Hawaii Ocean

Time (HOT) series site (~100 km north of Oahu) since

October 1988. The goal of these cruises is to make

hydrography, chemistry, and biology observations (PI: Dave

Karl and Roger Lucas). Measurements are typically made at a

near coastal station (Kahe) on the first day to test the

equipment and to obtain coastal shallow water (~1500m)

observations. The second and third days are spent at the HOT

site. On the morning of the fourth day, measurements are

made at the HOT site and noon time measurements are made

at the Hale-ALOHA station near the mooring before returning

to port by early the next morning. The locations of the three

stations are:

• Kahe (21.34o

 N, 158.27o W)

• HOT (22.75o

 N, 158.0oW)

• Hale-ALOHA buoy (22.43o

N, 158.0oW).

The routine HOT measurements are available during the

summer following the year of the observations. The 1998

measurements will therefore become available during the

summer of 1999. The data sets can be obtained at the National

Oceanographic Data Center (NODC) or from the HOT web

site http://kahana.soest.hawaii.edu/hot/hot_jgofs.html.

23.2 RESARCH ACTIVITIES

Microtops Sun Photometer Measurements

Beginning with the HOT89 cruise, aerosol optical depth

measurements were made with two Microtops sun

photometers. A time series of aerosol optical depths is shown

in Figure 1a for 440 and 1020 nm. The other wavelengths

were consistent with these in that the annual cycle is clear for

the shorter wavelengths but is not so evident at the longer

wavelengths. This suggest the spring time Asian transport

during 1998 brought significant accumulation mode aerosol to

the Central Pacific which is most likely due to anthropogenic

aerosol. A similar feature is seen in the SeaWifs images

processed for the HOT region. This is shown in Figure 1b

which shows the ratio of aerosol scattered light at two

wavelengths (780 and 860 nm) (eps_78). Larger ratio values

correspond to smaller aerosol and smaller values to larger

aerosol. Similar to the aerosol optical depth measurements, the

eps_78 suggest a seasonal cycle of smaller aerosol over the

HOT site during the spring time. Aerosol optical depth

measurements were made at 380, 440, 500, 675, 870 and 1020

nm, column integrated water vapor and ozone concentrations

were also derived.

 These measurements have been submitted to the

SeaBASS archive. Comparisons between ship and satellite

optical depths are shown in Figure 2. The best comparisons

are shown as blocks and the x values are cases where ship and

satellite were close. but not the same. In general the agreement

is within 0.03 but several outliers are present. These outliers

usually occur with a flat spectral shape which may be dust.

Marine Shadowband Radiometer

During the past two years we have been working on a

marine shadowband radiometer which will save aerosol

optical depths and downwelling irradiance at ~20

wavelengths. This system uses a gimbaled cosine response

detector and a rotating shadowband arm which shadows the

detector. A temperature controlled CVI Laser spectrometer is

used to collect the light which is saved on a PC104 computer.

The system has been tested on several cruises and the gimbal

works well. We are planning to take the rebuilt version on the

October 1999 HOT cruise.

Radiometric Calibration Facility

Radiometric calibration is being maintained by

comparisons with the MOBY calibration facility (thanks to

Dennis Clarke) and through Optronics calibration. This

includes an integrating sphere and an irradiance lamp. We are

also hoping to take part in the upcoming SIRREX calibration

effort in Hawaii.

In-Water Optics Measurements

As part of this SIMBIOS effort, routine optical

measurements have been made at each of the HOT stations.
SIMBIOS Project Annual Report

116

Measurements are made simultaneously with a Profiling

Reflectance Radiometer (PRR) and a Tethered Spectral

Radiometer Buoy (TSRB). These instruments provide

measurements in the visible wavelength range of downwelling

irradiance and upwelling radiance at the sea surface and at

depth. These measurements have been made since the HOT89

cruise (January 1998) by Karl et al. and are processed by R.

Letelier and J. Bartlett. Deployment and calibration

procedures follow the recommended protocols for SeaWiFS

calibration and validation. Immediately following each

monthly HOT cruise, the PRR data are processed and

submitted to SeaBASS. The processed PRR and TSRB data

are also available online for use by the scientific community

(http://picasso.oce.orst.edu/ORSOO).

This web site also provides details of the measurement

locations, instrumentation, and deployment procedures. The

optical data resulting from this ongoing effort will aid in the

interpretation of the temporal and spatial variability of the

constituents of Hawaiian waters.

23.3 WORK PLAN

Microtops Calibration and Processing

Christophe Pietras has maintained calibration of the

SIMBIOS pool of Microtops hand held sun photometers by

performing cross calibration with the Cimel sun photometer

network. We have separately maintained a calibration effort

by making Langley plot calibration efforts at the Mauna Loa

observatory. Pending approval by the SIMBIOS Project, we

hope to make a coordinated effort by performing Langley plot

calibration and comparisons with the set of Cimel sun

photometers at the Mauna Loa observatory.

Sean Bailey has recently implemented protocols to

process Microtops ship based sun photometer measurements

(technical memorandum, Porter, Miller, Pietras, Motell, 1999).

As this process is somewhat subjective, we would like to

coordinate with Sean to compare his and our techniques.

Sky and Surface Radiometer

We are developing a radiometer to measure sky and ocean

surface radiance on ship platforms. The system uses a wideangle camera and a tilt meter to determine the viewing

geometry and a spectrometer to measure the sky or the

aureole. The scattering angle is derived from the position of

the sun in the camera image and a tilt meter. The system has

been constructed but requires very careful angular calibration

which we hope to get to in the near future.

Measurements of the Aerosol Scattering and Absorbing

Coefficients and the Aerosol Phase Function

During 1998 a prototype polar nephelometer was built to

measure the aerosol phase function (Porter et al., Hilo Ocean

Optics meeting in 1998). We are now building an improved

version with three wavelengths (1064, 532, 355 nm) which

will measure the aerosol scattering coefficient and aerosol

phase function from ~3 to 177 degrees. A ground based

version is near completion and will be used on the HOT

cruises. A particle absorption photometer has also been

ordered and will be used to measure the aerosol absorption

coefficient. The spectral dependence of aerosol absorption will

also be determined in post processing. We are also looking

into collaborative efforts with Dr. Barry Huebert and Dr.

Luann Becker to characterize the in-organic and organic

species on the filter. These aerosol filter measurements will be

made on all HOT cruises.

Modeling Efforts

We have several topics we would like to address using

modeling efforts. These include algorithms to derive

information on the aerosol type from sun photometer

measurements, studies of the surface reflection problem, and

satellite retrievals of aerosol type and the wavelength

dependence of aerosol radiance. These modeling studies will

be based on the aerosol models used in the SeaWiFS Data

Analysis System (SeaDAS) algorithm as well as the more

realistic aerosol models currently available.

In order to study these effects we have been working on

an atmospheric Monte Carlo model. Due to time constraints,

this has taken several years but is now complete. The model

has been compared successfully with the Nakajima RTRN

algorithm for a Lambertian surface. A Cox and Munk model

modified for whitecaps will be used for the final calculations.
SIMBIOS Project Annual Report

117

Figure 1. Left panel shows time series of aerosol optical depth (380 nm) at the HOT site. Right panel shows eps_78 derived

from SeaWifs for the HOT site.

Figure 2. Comparison between Seawifs and ship derived aerosol optical depths (870 nm). 

This research was supported by the

SIMBIOS NASA interagency agreement # 97136

PEER REVIEWED PUBLICATION

Porter, John N., Tom F. Cooney and Craig Motell, 1998:

Coastal aerosol phase function measurements with a

custom polar nephelometer. Ocean Optics XIV

Conference, Kona, Hawaii.

.
SIMBIOS Project Annual Report

118

Chapter 24

Assessment of the Contribution of the Atmosphere to

Uncertainties in Normalized Water-Leaving Radiance: A

Combined Modeling and Data Analysis Approach.

Knut Stamnes and Bingquan Chen

 Department of Physics and Engineering Physics, Stevens Institute of Technology, New Jersey

24.1 INTRODUCTION

 Our research for the SIMBIOS program has been focussed

on modeling and simulation studies aimed at developing an

improved atmospheric correction algorithm. Based on our

original proposal and discussions at the SIMBIOS team

meetings and workshops, the objectives of our research can be

summarized as follows:

(a) Use our radiative transfer model for the coupled

atmosphere-ocean system to simulate the radiation field at

any desired level and in any desired direction in the

atmosphere and ocean so as to provide a firm connection

between the signal received by the satellite sensor and by

a sensor looking down into the water column just above

the surface and just below it.

(b) Use the simulations to quantify the influence of

atmospheric aerosols on the top-of-the-atmosphere (TOA)

radiance, and to quantify the error in the retrieved waterleaving radiance as a function of uncertainties in the

aerosol optical properties, mass loading and vertical

extent.

(c) Use the model simulations in conjunction with validation

measurements taken by other SIMBIOS investigators (for

satellite overpasses) to assess our understanding of the

radiative transfer process in the coupled atmosphereocean column, and to examine the extent to which the

model provides a realistic prediction of simultaneously

measured in situ water-leaving radiance and the radiance

received by the satellite sensor.

(d) Modify and improve an existing atmospheric correction

algorithm, based on the work above, as needed by

constructing new look-up tables that take into account

scattering by ocean particles.

(e) Develop an atmospheric correction algorithm for ocean

color imagery that will work also in the presence of

strongly absorbing aerosols.

24.2 RESEARCH ACTIVITIES

I. We have mainly been working on numerical radiative

transfer modeling experiments using a

comprehensive radiative transfer model for the

coupled atmosphere-ocean system to (a) simulate the

radiation transfer process in the coupled atmosphereocean system so as to provide a firm connection

between the signal received by the satellite sensor

and by a sensor looking down into the water column

just above the surface and just below it; (b) assess the

effects of scattering ocean particles on the waterleaving radiance (Lw) at NIR wavelengths, especially

for high latitudes where large solar zenith angles are

common; and (c) examine the validity and

consequence of the basic assumption commonly used

in atmospheric correction of ocean color imagery,

namely, that the water-leaving radiance at NIR

wavelengths is negligible, using a comprehensive

radiative transfer model for the coupled atmosphereocean system with an existing bio-optical model of

the open ocean and common aerosol models.

II. We have carried out preliminary work on algorithm

development for atmospheric correction to (a)

examine the existing algorithm developed by Gordon

and co-workers for atmospheric correction of ocean

color imagery; (b) use a state-of-the-art radiative

transfer model for the coupled atmosphere-ocean

system to simulate the process of atmospheric

correction; (c) study possible new approaches to

atmospheric correction; and (d) construct lookup

tables for a new and efficient algorithm.

III. We have begun processing of satellite data as well as

field-data.
SIMBIOS Project Annual Report

119

IV. Collaborations with other PIs in the SIMBIOS

program and collaborations with other investigators

in ocean optics and atmospheric correction: (a) We

have had close collaborations with Dr. Mueller's

group and Dr. Zaneveld's group. We have had a few

mini-workshops among our groups. (b) We have

been collaborating with Drs. J.J. Stamnes and O.

Frette at the University of Bergen, Norway on the

problems of atmospheric correction as well as biooptical models appropriate for use in open ocean and

coastal waters.

24.3 RESEARCH RESULTS

I. Numerical radiative transfer modeling

We have found that the relative contribution of the waterleaving radiance to the total TOA radiance at NIR

wavelengths depends on (a) the scattering characteristics of

particles in the near-surface ocean water, described by their

shape, size, and refractive-index distributions, which in turn

determine the scattering phase function; (b) the aerosol optical

depth; (c) the ocean particle concentration; and (d) the sunsatellite geometry.

Our simulations show that for common aerosol loadings

over the open ocean (aerosol optical depths in the range 0.08-

0.11) the water-leaving radiance at NIR wavelengths (e.g., 865

nm) is usually not negligible. This is particularly important

when the aerosol loading is low because then the contribution

from the water-leaving radiance to the total radiance received

by the satellite sensor is relatively larger, and will if ignored

introduce significant errors in atmospheric correction. Under

pristine atmospheric conditions with low aerosol loading the

assumption that the water-leaving radiance at NIR

wavelengths can be ignored becomes questionable when the

ocean chlorophyll concentration is high because the NIR

water-leaving radiance may then contribute significantly to the

TOA radiance. Under such circumstances neglect of the NIR

water-leaving radiance may result in a significant

overestimation of the aerosol loading.

This implies that the aerosol model picked for the

atmospheric correction will be wrong. When this erroneous

aerosol model is used to estimate the aerosol contribution in

the visible and to subtract it from the measured TOA radiance

in order to infer the water-leaving radiance, substantial errors

are possible that in extreme cases could lead to negative

water-leaving radiances. The assumption that the waterleaving radiance is zero at NIR wavelengths is generally

questionable for some case I waters. In case II waters this

assumption is even less valid due to significant scattering in

the NIR spectral region from inorganic particles. Therefore the

aerosol optical depth predicted by existing methods/algorithms

will be overestimated in both case I and case II waters. This

deficiency can be overcome by using a radiative transfer

model for the coupled atmosphere-ocean system to retrieve the

correct aerosol optical properties at NIR wavelengths.

II. Atmospheric correction

We have obtained preliminary results of an atmospheric

correction algorithm for ocean color imagery for weakly as

well as strongly absorbing aerosols. Implementation is

underway, and papers are being prepared. Compared to

Gordon’s atmospheric correction algorithm, our algorithm has

the following improvements: (a) It includes multiple scattering

in a rigorous one-step manner. (b) It uses a combination of

NIR and visible bands to choose correct aerosol model and

vertical structure so as to provide proper atmospheric

correction for both weakly and strongly absorbing aerosols. (c)

It provides aerosol optical depth and vertical structure, as well

as diffuse atmospheric transmittance, water-leaving radiance,

and chlorophyll concentration in a self-consistent manner.

24.4 WORK PLAN

" We will continue algorithm development and testing

using simulated data.

" We will implement the algorithm within the “MSL12”

software to allow us to test it off-line against match-up

data. This work will be done in collaboration with Dr. Jim

Muller and the OSU group (Drs. Zaneweld, Pegau, and

Bernard).

" We will implement the algorithm within SeaDAS and

apply it to SeaWiFS data for further testing and

evaluation. This work will be carried out in collaboration

with the SIMBIOS office.

" We will make algorithm available to other SIMBIOS PIs

for additional evaluation and testing.
SIMBIOS Project Annual Report

120

This research was supported by the

 SIMBIOS NASA contract # 97138

PEER REVIEWED PUBLICATIONS

Chen, Bingquan, Knut Stamnes, et al., 1999: Water-leaving

radiance in the NIR spectral region and its effects on

atmospheric correction of ocean color imagery. In press

Journal of Advanced Marine Science and Technology

Society

PRESENTATIONS

Yan, Banghua, Knut Stamnes, and Bingquan Chen, 1999: A

Generalized Algorithm for Atmospheric Correction of the

Ocean Color Imagery: Feasibility Simulation. AGU 1999

Spring Meeting in Boston.
SIMBIOS Project Annual Report

121

Chapter 25

Validation of the Water-Leaving Radiance Data Product

O.V.Kopelevich

Ocean Optics Laboratory, P.P.Shirshov Institute of Oceanology, Moscow, Russia

25.1 INTRODUCTION

 The objective of this research is to assess an accuracy of

data products derived from satellite ocean color data. Specific

goals include an assessment of accuracy of the atmospheric

correction algorithms for variety of meteorological and

oceanological conditions and of the bio-optical algorithms for

different water cases. Along with the operational SeaWiFS

chl-a algorithm, the semianalytic algorithm developed by our

group was validated. Such kind of bio-optical algorithms

could solve the problem of Case II waters but they place much

more severe requirements to atmospheric correction than the

SeaWiFS operational algorithm.

The latter only uses the Lwn values at 490 and 555 nm

whereas the semianalytic algorithm needs the correct Lwn

values at all SeaWiFS spectral bands including 412 nm. That

is the reason why a close attention should be paid to the

atmospheric correction algorithm for solving the Case II

problem.

25.2 RESEARCH ACTIVITIES

In 1999 we did not carry out any validation cruise and

worked on analysis of data obtained during our previous

cruises in the Black and Aegean Seas in October 1997 and in

the Barents Sea in August-September 1998. Validation of the

atmospheric correction and bio-optical algorithms was

performed by direct comparison between values of the waterleaving radiance Lwn(λi), i=1-5, aerosol optical thickness τa

(865), and chlorophyll concentration measured and derived

with different algorithms. Also SeaWiFS Level 2 data for the

Black, Mediterranean, and Barents Seas have been collected

since September 1997 to use them for monitoring these

regions as well as to analyze them for revealing defects of

different origin.

25.3 RESEARCH RESULTS

Negative Lwn values.

We found negative Lwn412 values not only in highly

 productive waters where they are due to the effect of non-zero

NIR reflectance, but also in not so productive waters of the

Black Sea and even in oligotrophic waters of the Eastern

Mediterranean. In Figure 1 the negative Lwn values at 412 nm

are seen as dark areas in the averaged monthly distribution in

the Eastern Mediterranean in April 1998. One of such areas is

located near the Nile run-off and its existence can be

explained by the effect of non-zero NIR reflectance, but the

other, north of Crete, is with rather clear waters. The negative

Lwn values are most frequent at 412 nm but they are also

observed at 443 nm and even at 555 nm. Sometimes Lwn is

positive at 412 nm but negative at greater wavelength for one

and the same pixel. The most probable reason of that is a

wrong choice of the aerosol optical model in the SeaWiFS

atmospheric correction procedure. Dependence of results of

the atmospheric correction on the scan angle. Our analysis

shows that results of the atmospheric correction depend on the

scan angle. Figure 2 presents results of comparison between

the Lwn values derived at small (less than 20o

) and large

(greater than 30o

) scan angles for different spectral bands and

averaged over the half-degree square south-west of Crete. The

spatially averaged Lwn values are calculated for 9 days with

the small scan angle (triangles) and 8 days with large scan

angle (squares), and it is seen that the Lwn values calculated at

the small scan angle are higher than the ones at the large scan

angle. The minimum difference in values is observed at 490

nm, the most pronounced is at 412 and 555 nm. As well as in

the case of negative Lwn values, the observed difference can

be explained by a wrong choice of the aerosol optical model

which probability is higher when observation is made at the

large scan angle.

Comparison between SeaDAS 3.2 and SeaDAS 3.1 versions of

the atmospheric correction.

We suspect that SeaDAS 3.2 atmospheric correction can

be worse than SeaDAS 3.1 version. As it is seen from Table 1

where the results with two versions are compared for two

stations in the Black and Aegean Seas, SeaDAS 3.2 reduces

errors in retrieval of the τa 865 values comparing with SeaDAS

3.1, but SeaDAS 3.2 also changes a spectral dependence of

Lwn reducing Lwn412 by 13-28% and magnifying the other

Lwn values by 3-21%; the errors on the chlorophyll values are

increased by 16-71%.
SIMBIOS Project Annual Report

122

The strange maxima in the Lwn distribution.

The rather strange maxima in the Lwn distribution were

found when we tried to use the SeaWiFS Level 2 data for

study of mesoscale variability in the Eastern Mediterranean.

An example of such maxima west of Crete is shown in Figure

3. Such kind of maxima appear while data are mapped using

an isoline technique; they look quite real in amplitude and

measure up to tens of kilometers in dimensions but show

suspiciously short life time and may form chain or “multicell”

structures. They can result in errors in estimate of the mean

values and show unrealistically complicated the Lwn

distribution in homogeneous ocean regions. The visual

analysis of initial data showed that the occurrence of such

maxima could be connected with inefficiency of elimination

of cloud effects. It can be related to “Stray light and

atmospheric adjacency effects” studied by K.Carder and

resulted from the scattering by edges of clouds or stray light

within the SeaWiFS sensor or from high cirrus clouds. Such

kind of effects should be kept in mind while studying ocean

mesoscale variability with satellite ocean color data.

Validation of the bio-optical algorithms.

Table 2 presents results of comparison between

chlorophyll-a concentrations (mg.m-3) measured and retrieved

by different bio-optical algorithms at several stations in the

Black Sea (Stations 1-3), the Aegean Sea (Stations 4, 5), and

the Barents Sea (St. 1088-1281). Because of the poor quality

of atmospheric correction in the Barents Sea, the in situ

measured Lwn values were taken as the initial data for the

Chlorophyll retrieval with the bio-optical algorithms; the

SeaWiFS algorithm was the OC2 operational algorithm. The

author’s algorithm was the semianalytic algorithm based on

the low-parametric model for seawater absorption and

backscattering and the analytic formula for ocean radiance

reflectance; it can be used for deriving chlorophyll, seawater

absorption and backscattering coefficients (Burenkov et al.,

1999; Kopelevich et al., 1998).

The extreme right column in Table 2 shows values of the

ratio between the absorption coefficients of gelbstoff and

phytoplankton pigments at 440 nm. The β value is an

important parameter which can be used as an indicator of

failure of the SeaWiFS empirical algorithm; our analysis

showed that the critical value is about 2. As it is seen from

Table 2, in the Black and Aegean Seas where the β values are

2.6-5.9 the SeaWiFS algorithm overestimates the chlorophyll

concentration about twice; the similar situation in the Barents

Sea with the exception of the Pechora Basin (Stations 1090-

1157). In the Pechora Basin, which is under strong influence

of the Pechora-river discharge and the βvalues are more than

12 and even exceed a hundred; the SeaWiFS algorithm

overestimates the chlorophyll concentration by a factor of 4.4

- 22.6. The semianalytic algorithm provides much better

agreement between the calculated and measured chlorophyll

concentration: the mean error is equal to 15% for stations in

the Black and Aegean Seas, 48% for stations in the Pechora

Basin, and 27% for other stations in the Barents Sea.

25.3 WORK PLAN

" In 2000 we plan to make a comparative validation of the

SeaWiFS atmospheric correction algorithm and the new

algorithm to be developed by our group.

" Our cruise plans for 2000 are not yet finalized.

ACKNOWLEDGMENTS

This research was carried out by the group from

P.P.Shirshov Institute of Oceanology including Drs. V.

Burenkov, G. Karabashev, S. Sheberstov, S. Ershova, M.

Evdoshenko.

REFERENCES

Burenkov, V. I., O. V. Kopelevich, S. V. Sheberstov, S. V.

Ershova, M. A. and A. Evdoshenko, 1999: Bio-optical

characteristics of the Aegean Sea retrieved from satellite

ocean color data. In press: The Eastern Mediterranean as

a Laboratory Basin for the Assessment of Contrasting

Ecosystems, P. Malanotte-Rizzoli, Ed..

Kopelevich, O.V., D. B. Rogozkin, and S. V. Sheberstov,

1998: Results of application of the new atmospheric

correction method to the Pacific Ocean color simulated

data set. Proc. PORSEC’98, Vol. 1, M-X. He and G.

Chen, Eds., Secretariat, Qingdao, China, 54-58
SIMBIOS Project Annual Report

123

Figure 1. The negative monthly values of Lwn412 (dark) observed in the Eastern Mediterranean (April 1998)

Figure 3. False maxima in distribution of Lwn412 (left image ) and Lwn555 (right image) observed west

of Crete while data are mapped with an isoline technique (08/08/98).

20 22 24 26 28 30 32 34 36

31

32

33

34

35

36

37

20.0 20.5 21.0 21.5 34.5

35.0

35.5

36.0

36.5

r

20.0 20.5 21.0 21.5 22.0

2.0 2.2 2.4 0.4 0.5 0.6
SIMBIOS Project Annual Report

124

Figure 2. Comparisons between the Lwn values derived under conditions of small (triangles) and large (squares)

scan angles (July-august 1998).

0.0

0.1

0.2

0.3

0.4

0.5

nL

555 nm

0.0

0.2

0.4

0.6

0.8

1.0

510 nm

0.0

0.3

0.6

0.9

1.2

1.5

490 nm

0.0

0.5

1.0

1.5

2.0

443 nm

150 175 200 225 days

0.0

0.5

1.0

1.5

2.0

412 nm

Nadir

Inclined
SIMBIOS Project Annual Report

125

Table 1. Comparison between the values of the water-leaving radiances (W. m-2μ -1. sr -1), aerosol optical thickness τa

865,

 & chlorophyll concentration (mg. m-3) measured and derived from SeaWiFS data with SeaDAS 3.1 and

SeaDAS 3.2 versions; ∆, % is the relative discrepancy between derived and measured data.
SIMBIOS Project Annual Report

126

Table 2. Comparison between chlorophyll-a concentrations (mg⋅m-3) measured and retrieved by author’s and

operational SeaWiFS algorithms at different stations in the Black Sea (St.1-3), the Aegean Sea (St. 4, 5), and

the Barents Sea (St. 1088-1281). β is the ratio between the absorption coefficients of gelbstoff and

phytoplankton pigments at 440 nm.

t. Coordinates Chl

meas.

Chl auth. Chl SeaWiFS β

1 42.51 N, 39.52 E 0.35 0.23 0.68 4.3

2 42.96 N, 35.60 E 0.57 0.56 1.20 3.4

3 42.90 N, 31.60 E 0.45 0.56 1.12 2.6

4 39.32 N, 25.12 E 0.089 0.086 0.21 5.9

5 39.61 N, 25.79 E 0.076 0.088 0.18 5.2

1088 70.42 N, 47.58E 0.16 0.25 0.63 5.7

1090 70.18N, 52.42E 0.5 0.77 3.3 12.7

1095 68.97N, 58.47E 0.79 0.21 10.4 114

1112 69.09N, 58.29E 0.42 0.62 9.5 36.7

1125 69.50N, 57.25E 0.23 0.06 2.8 76.2

1126 69.67N, 57.24E 0.18 0.19 2.7 33.3

1157 70.54N, 52.79E 0.25 0.17 1.09 15.0

1174 69.25N, 41.00E 1.39 1.03 1.0 2.3

1183 71.50N, 41.00E 0.38 0.32 0.81 3.8

1196 74.75N, 41.00E 0.13 0.14 0.28 3.6

1209 78.00 N, 41.00E 0.16 0.17 0.25 2.8

1281 76.00N, 42.27E 0.27 0.41 0.44 2.2
SIMBIOS Project Annual Report

127

Chapter 26

 Intensive and Extensive Field Programs for Data Product

Validation of OCTS/ADEOS and GLI/ADEOSII

Sei-ichi Saitoh and Kosei Sasaoka

Department of Fisheries Oceanography and Marine Science,

Faculty of Fisheries, Hokkaido University, Hakodate, Japan

 26.1 INTRODUCTION

Increased international cooperation in satellite ocean

color remote sensing of the global and coastal oceans is very

timely owing to the large number of sensors planned for

launch over next 10 years. The Advanced Earth Observing

Satellite (ADEOS) was successfully launched August 17th

1996 by the National Space Development Agency of Japan

(NASDA). ADEOS has eight earth observation sensors

including the Ocean Color and Temperature Scanner (OCTS)

which has 8 bands in visible and near infrared region for

receiving the chlorophyll a concentration in the sea and 4

bands in thermal region for retrieving sea surface temperature

(Saitoh, 1995). Although the ADEOS lifetime was relatively

short (about 10 months), OCTS left a huge, invaluable data

set for oceanographic research (Kawamura and The OCTS

Team, 1998). NASDA has already started to develop

advanced ocean color sensor Global Imager (GLI) which will

be mounted on ADEOS II. We realize the importance of

best use of those scheduled missions by developing a

methodology and operational capability to combine data

products from various ocean color missions in a manner that

ensures the best possible global coverage, and exploits best

complementary missions of the sensors (NASA, 1996). We,

Japanese ocean color science community, decided to

participate the SIMBIOS program for contribution of best

and comprehensive utilization several ocean color missions

including OCTS/ADEOS and GLI/ADEOS II. Our main

objectives were:

• enhance Cal/Val activities for OCTS and GLI through

the intensive and extensive

• field program in the northwestern North Pacific

• validate the data products of OCTS/ADEOS,

SeaWiFS/orbview-2 and GLI/ADEOS II

• develop regional bio-optical algorithm

• comparison OCTS with SeaWiFS

• keep and validate the heritage from OCTS to GLI

In the past, we have already carried out the validation

and development of bio-optical algorithm in the waters

around Japan using ship and moored optical buoy system

(Saitoh et al., 1997; Kishino et al., 1997a, 1997b; Ishizaka et

al., 1997).

26.2 RESEARCH ACTIVITIES

Ocean color variability at KNOT station

We applied ocean color remote sensing data sets

both OCTS from October 1996 to June 1997 and SeaWiFS

from September 1997 to July 1999, in order to grasp the

temporal and spatial variability of chl-a distribution at the

Japan JGOFS time series station KNOT (Kyo-do Northwest

Pacific Ocean Time Series) (at 44°N, 155°E) and its adjacent

waters in the Subarctic north-western North Pacific, and to

understand the mechanisms of chlorophyll-a distribution

during 1996-1999. Furthermore to analyze short-term

variability, we carried out synoptic ship observations at Stn.

KNOT and its adjacent waters.

Field programs for validation of SeaWiFS

Eight cruises were carried out in the study area,

northwestern North Pacific from May 1998 to May 1999

(Figure 1). Radiometric profiles and fluorometric chlorophyll

a samples, and inherent optical properties were measured in

the same period. We conducted subsurface

radiance/irradiance profile using a Biospherical Instruments

MER2040 in conjunction with a MER2041 Deck Unit. The

MER2040/2041 bands are :

• 13 bands Ed, Es (412, 443, 465, 490, 510, 520, 555, 565,

625, 665, 670, 683, 710nm );

• 13 bands Lu (412, 443, 465, 490, 510, 520, 555, 565,

625, 665, 670, 683, 710nm )
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26.3 RESEARCH RESULTS

Relatively low chlorophyll-a concentration (about 0.3–

0.8mg/m3

) dominated throughout the year at the station

KNOT, but remarkable peak was seen in bloom period (in

May and October), winter (in November and December) and

summer (in August 1998). In adjacent sea area, most

remarkable high chl-a (more than 10mg/m3

) was seen

northward to station KNOT along the Kuril-Islands and

adjacent waters in May 1999, moreover high concentration

remain over a month during the bloom season. Year-to-year

variability of chl-a was seen. Chl-a (about 1.4mg/m3

) at the

Stn.KNOT in November 1997 was higher than that in

November during 1996-1999. Chl-a around the center of

Western Sub-arctic Gyre in October 1998 was higher than

that in October 1997.

Using data from the study area, northwestern North

Pacific (Figure 1), we determined the match-up between the

weekly SeaWiFS chlorophyll a and in-situ chlorophyll a for

eight cruises (Figure 2). Total sample number and r2

 are 62

and 0.82, respectively.

26.4 WORK PLAN

We will continue to gather bio-optical data sets at station

KNOT and adjacent waters. In January 2000, we will have an

interdisciplinary cruise in the northwestern North Pacific

including Stn. KNOT by R/V Mirai. In March 2000, we will

have a research cruise in Funka Bay, coastal region of

Hokkaido Island by T/S Oshoro-Maru. In July 2000, we will

operate bio-optical cruise in the Gulf of Alaska and the

Bering Sea through the IARC/NASDA project. In September

2000, we will go to East-China Sea for sampling CASE-II

water data sets by R/V Hakuho-Maru.

ACKNOWLEDGEMENTS

This work was partly supported by National Space

Development Agency of Japan (NASDA) through the

ADEOS/ADEOS-II project.

REFERENCES

Ishizaka, J., I. Asanuma, N. Ebuchi, H. Fukushima, H.

Kawamura, K. Kawasaki, K. Kishino, M. Kubota, H.

Masuko, S. Matsumura, S. Saitoh, Y. Senga, M.

Shimanuki, N. Tomii, and M. Utashima, 1997:Time

series of physical and optical Parameters off Shimane

Japan, during Fall of 1993: First observation by moored

Optical buoy system for ADEOS data verification, J.

Oceanogr., 53, 245-258.

Kawamura, H. and The OCTS team, 1998:OCTS Mission

Overview, J. Oceanogr., 54, 383-399.

Kishino, M., Ishizaka, J., Satoh, H., Kusaka, K., Saitoh, S.,

Miyoi, T. and Kawasaki, K., 1997a: Optical

characteristics of seawater in the North Pacific Ocean, in

Ocean Optics XIII, Proc. SPIE Int. Soc. Opt. Eng., 2963,

173-178.

Kishino, M., Ishizaka, J., Saitoh, S., Senga, Y. and Utashima,

M., 1997b: Verification plan of ocean Color and

temperature scanner atmospheric correction and

phytoplankton pigment by moored optical buoy system,

J. Geophys. Res., 102, D14, 17197-17207.

Saitoh, S., 1995: OCTS on ADEOS, 473-480, Eds. by M.

Ikeda and F. Dobson, In " Oceanographic Application of

Remote Sensing", CRC Press.

Saitoh, S., T. Miyoi and M. Kishino, 1997: Development of

bio-optical algorithm for ocean color remote sensing in

the sub-Arctic North Pacific Ocean, in Ocean Optics

XIII, Proc. SPIE Int. Soc. Opt. Eng., 2963, 766-771.
SIMBIOS Project Annual Report

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Figure 1. Map of the observation area, ship transect and stations in this study
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Figure 2 Comparison between in-situ and SeaWiFS chlorophyll a concentration

GLOSSARY

ACE Aerosol Characterization Experiment

ADEOS Advanced Earth Observation Satellite

AERONET Aerosol Robotic Network

AM-1 Not a acronym, used to designate the

morning platform of EOS

AOP Apparent Optical Properties

AOT Aerosol Optical Thickness

APV Autonomous Profiling Vehicle

ARGOS Not an acronym, but the name given to the

data collection and location system on the

NOAA Operational Satellites.

ASCII American Standard Code for Information

Interchange

AVHRR Advanced Very High Resolution

Radiometer

AVIRIS Advanced Visible and Infrared Imaging

Spectrometer

BATS Bermuda Atlantic Time-series Study

BBOP Bermuda Bio-Optics Profiler

BBSR Bermuda Biological Station for Research

BNL Brookhaven National Laboratory

BTM Bermuda Test Mooring

Cal/Val Calibration and Validation

CalCOFI California Cooperative Oceanic

Fisheries Investigation

CALVAL Calibration Validation

CARICO Carbon Retention in a Colored Ocean

Case-1 Water whose reflectance is determined by

absorption.

Case-2 Water whose reflectance is significantly

influenced by scattering.

CCD Charge-Coupled Device

CDOM Chromophoric Dissolved Organic Matter

CHN Carbon, Hydrogen and Nitrogen

CHORS Center for Hydro-Optics and Remote

Sensing

CICESE Centro de Investigation Cientifica y de

Edcacion Superior de Ensenada

CIMEL The name of a sun photometer

manufacturer

CNES Centre National d’Edudes Spatialle

CONICIT Consejo Nacional de Investigaciones

Cientifica y Technologicas (Venezuela)

CRAM Conditional Relaxation Analysis Method

CTD Conductivity-Temperature-Depth

CZCS Coastal Zone Color Scanner

DAAC Distributed Active Archive Center

DLR Deutshe Forshungsanstalt f r Luft-und

Raumfarhrt (German Aerospace Center)

DMF Dimethylformamide

DOC Dissolved Organic Carbon

DoD Department of Defense

DOE Department of Energy

ECOHAB Ecology of Harmful Algal Blooms

EEZ Exclusive Economic Zone

EORC Earth Observation Research Center

EOS Earth Observing System

FFP Firm-Fixed Price

FOV Field of View

ftp File transfer protocol

FWHM Full Width Half Maximum

GAC Global Area Coverage, coarse resolution

satellite data with a nominal ground resolution at nadir of approximately 4 Km

GB Gigabyte, or about one billion bytes

GF/F Not an acronym, but a specific type of glass

fiber manufactured by Whatman.

GLI Global Imager

GoCal Gulf of California

GPS Global Positioning System

GSFC Goddard Space Flight Center

HIVE High-Latitude Intercomparison and

Validation Experiment

HOBI Hydro-Optics, Biology and Instrumentation

HOT Hawaii Ocean Time series

HPLC High Performance Liquid Chromatography

HQ Headquarters

HRPT High Resolution Picture Transmission

ICESS Institute for Computational Earth

Science System

IDL Interactive Data Language

INDOEX Indian Ocean Experiment

IOCCG International Ocean Color Coordinating

Group

IOP Inherent Optical Properties

IR Infrared

IRS Indian Remote Sensing Satellite

ISCCP International Satellite Cloud

Climatology Project

ISPO Interim SIMBIOS Project Office

JGOFS Joint Global Ocean Flux Study

JPL Jet Propulsion Laboratory

LAC Local Area Coverage, fine resolution

satellite data with a nominal ground resolution at nadir of approximately 1Km

LIDAR Light Detection and Ranging Instrument

LED Light Emitting Dicode

LOA Laboratorie d’Optique Atmospherique

MARMAP Marine Resources Monitoring, Assessment

and Prediction

MBARI Monterey Bay Aquarium Research Institute

MB Megabyte, or about one million bytes

MER Multispectral Environmental Radiometer

MERIS Medium Resolution Imaging Spectrometer
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MFRSSR Marine Fast Rotating Shadow-band

Spectral Radiometer

MISR Multi-angle Imaging SpectroRadiometer

MOBY Marine Optical Buoy

MODAPS Modular Ocean Data and Power System

MODIS Moderate Resolution Imaging

Spectroradiometer

MOS Modular Optoelectronic Scanner

MSL12 Multi-Sensor level-1B to level-2 code

MTPE Mission to Planet Earth

NASA National Aeronautics and Space

Administration

NASDA National Space Development Agency

of Japan

NAVOCEANO Naval Oceanographic Office

NDBC National Data Buoy Center

NIMBUS Not an acronym, but a series of NASA

experimental weather satellites containing a

wide variety of atmosphere, ice, and ocean

sensors.

NIST National Institute of Standards and

Technology

NOAA National Oceanic and Atmospheric

Administration

NODC National Oceanographic Data Center

NOPP NIMBUS Observation Processing System

NRA NASA Research Announcement

NSF National Science Foundation

NSPO National Space Program Office

NTOU National Taiwan Ocean University

OCI Ocean Color Imager

OCTS Ocean Color and Temperature Sensor

ONR Office of Naval Research

ORCA Optical Research Consortium of the Arctic

OSC Orbital Sciences Corporation

OSU Oregon State University

PAR Photosynthetically Available Radiation

PHILLS Hyperspectral Imager for Low Light

Spectroscopy

PI Principal Investigator

PM-1 Not a acronym, used to designate the

afternoon platform of EOS

POLDER Polarization Detecting Environmental

Radiometer (France)

PRR Profiling Reflectance Radiometer

R&D Research and Development

R/V Research Vessel

ROCSAT Republic of China (Taiwan) Satellite

platform for the OCI sensor.

RR Round-Robin

SAB South Atlantic Bight

SBE Sea-Bird Electronics

SCOR Scientific Committee on Oceanic Research

SDDC Science Data Distribution Center

SeaOPS SeaWiFS Optical Profiling System

SeaBAM SeaWiFS Bio-optical Algorithms Miniworkshop

SeaBASS SeaWiFS Bio-optical Archive and Storage

System

SeaDAS SeaWiFs Data Analysis System

SeaWiFS Sea-viewing Wide Field-of-view Sensor

SIMBAD The name of a sun photometer

SIMBIOS Sensor Intercomparison and Merger for

Biological and Interdisciplinary Oceanic

Studies

SIO Scripps Institution of Oceanography

SGI Silicon Graphics, Inc.

SIRREX SeaWiFS Intercalibration Round-Robin

Experiment

SLOWDROP Slow Descendent Rate Optical Profiler

SMSR SeaWiFS Multispectral Surface

Reference

SOOP Ship of Opportunity Program

SOW Statement of Work

SPMR SeaWiFS Profiling Multi-channel

Radiometer

SQM SeaWiFS Quality Monitor

ST Science Team

TB Terabytes

TOA Top of the Atmosphere

TOMS Total Ozone Mapping Spectrometer

TOTO Tongue of the Ocean

TSM Total Suspended Matter

TSRB-II Tethered Spectral Radiometer Buoy - II

XBT Expendable Bathythermograph
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