NASA/TMm2002-104606, VoL 22

Technical Report Series on Global

Modeling and Data Assimilation

Max J, Suarez, Editor

Volume 22

A Coupled Ocean-Atmosphere Radiative

Model for Global Ocean Biogeochemical

Models

I_ttson W. Gregg

August 2002
The NASA STI Program Office ... m Profile

Since its founding, NASA has been dedicated to

the advancement of aeronautics and space

science. The NASA Scientific and Technical

hlf()rmation (STI) Program Office plays a key

part in helping NASA maintain this important

role.

The NASA STI Program Office is operated by

Langley Research Center, the lead center for

NASA's scientific and technical information.

The NASA STI Program Office provides access

to the NASA STI Database, the largest collection

of aeronautical and space science STI in the

world. The Program Office i s also NAS A' s

institutional mechanism for disseminating the

results of its research and development activities. These results are published by NASA in the

NASA STI Report Series, which includes the

following report types:

, TECHNICAL PUBLICATION. Reports of

completed research or a major significant

phase of research that present the results of

NASA programs and include extensive data or

theoretical analysis. Includes compilations of

significant scientific and technical data and

information deemed to be of continuing

reference value. NASA's counterpart of

peer-reviewed formal professional papers but

has less stringent limitations on manuscript

length and extent of graphic presentations.

, TECHNICAL MEMORANDUM. Scientific

and technical findings that are preliminary or

of specialized interest, e.g., quick release

reports, working papers, and bibliographies

that contain minimal annotation. Does not

contain extensive analysis.

, CONTRACTOR REPORT. Scientific and

technical findings by NASA-sponsored

contractors and grantees.

CONFERENCE PUBLICATION. Collected

papers from scientific and technical

conferences, symposia, seminars, or other

meetings sponsored or cosponsored by NASA.

SPECIAL PUBLICATION. Scientific, technical, or historical information from NASA

programs, projects, and mission, often concemed with subjects having substantial public

interest.

TECHNICAL TRANSLATION.

English-I angu age translations of foreign scientific and technical material pertinent to NASA's

mission.

Specialized services that complement the STI

Program Office's diverse offerings include creating custom thesauri, building customized databases, organizing and publishing research results...

even providing videos.

For more information about the NASA STI Program

Office, see the following:

, Access the NASA STI Program Home Page at

http://ww w.sti.nasa.gov/STI-homepage.html

o E-mail your question via the Internet to

help@ sti.nasa.gov

* Fax your question to the NASA Access Help

Desk at (301) 621-0134

, Telephone the NASA Access Help Desk at

(301) 621-0390

Write to:

NASA Access Help Desk

NASA Center for AeroSpace Information

7121 Standard Drive

Hanover, MD 21076---.1320
NASA/TM_2002-104606, VoL 22

Technical Report Series on Global

Modehn_, and Data Assimilation

Max J. Suarez, Editor

Goddard Space Flight Center; Greenbell; Maryland

Volume 22

A Coupled Ocean-Atmosphere Radiative

Model for Global Ocean Biogeochemical

Models

Watson W. Gregg

Goddard Space Flight Center, Greenbelt Matyland

National Aeronautics and

Space Administration

Goddard Space Flight Center

Greenbelt, Maryland 20771

August 2002
NASA Center for AeroSpace Inlbrmation

7121 Standard Drive

Hanover, MD 21076-1320

Price Code: A17

Available from:

National Technical In[brmation Service

5285 Port Royal Road

Springfield, VA 22161

Price Code: A10
1 Introduction

Knowledge of oceanic irrMiance is critical for realistic simulation of ocean biogeochemistry. Since irradiance affects ocean thermodynamics and physiological processes of

biota in the oceans, it may affect the abundances and distributions of phytoplankton,

and potentially affect the uptake of carbon dioxide.

In order to understand the effects of irradiance on phytoplankton abundances and primary production in the global oceans, we require a reasonably realistic simulation of

the irradiance reaching the ocean surface, and propagating through the water column.

The simulation must explicitly include the effects of atmospheric optical constituents

on surface irradiance, processes occurring at the air-sea interface, and the results of

these effects in the water colunm taking into account the optical properties of the water,

phytoplankton, and dissolved detrital materials. In this paper we describe atmospheric

and oceanic radiative transfer models, combined as the Ocean-Atmosphere Radiative

Model (OARM) that provide a reasonably complex and realistic representation of atmospheric radiative processes and the irradiance availability in the oceans.

2 Ocean-Atmosphere Radiative Model (OARM)

2.1 Atmospheric Component

The atmospheric radiative model is based on the Gregg and Carder (1990) spectral

model for clear skies, and relies on Slingo (1989) for spectral cloud transmittance. The

clear sky model of Gregg and Carder (1990) was derived from Bird and Riordan (1986),

but was limited to the spectral range of photosynthetically available radiation (PAR),

defined as 350-700 nm. It also contained increased spectral resolution and marine

atmospheric and surface reflectance conditions. It compared within _+6.6% root mean

square (RMS) with surface observations of spectral irradiance and +5.1% RMS with

integrated PAR (Gregg and Carder, 1990). This model is extended for OARM from the

PAR spectral domain to the entire solar spectrum, from 200 nm to 4 uln, representing

>99% of the total solar irradiance impinging on the top of the atmosphere. For computational efficiency, the spectral resolution is degraded froln 1 nm used in Gregg and

Carder (1990) to a variable resolution appropriate for the spectral absorbing properties

of the major atmospheric optically active gases, specifically ozone, water vapor, oxygen, and carbon dioxide (Table 1). The spectral resolution is fixed at 25 nm for the

PAR range, which is the region of interest for phytoplankton photosynthesis.

A modification to the clear sky model is the use of spectral surface reflectance in the

presence of sea foam based on observations by Frouin et al. (1996), and confirmed by

Moore et al. (1998). This modification accounts for the fact that some of the reflectance by sea foam is due to bubbles located slightly below the surface. This produces

some absorption by sea water before reflecting the light out of the water. Since longer
Table 1. Atmosphericopticaldatafor ()ARM.1 iswavelength(nm),Foisextraterrestrial

irradiance(W/m2), tr is Rayleigh optical thickness(dimensionless),aozis ozone

absorptioncoefficient(cm-1),awvis water vapor absorption coefficient (cm-1), ao2 is

oxygen absorption coefficient (cm-_), and a_o2is carbon dioxide absorption coefficient

(cm-_). A data file is available online at sahno.gsfc.nasa.gov,

pub/outgoing/oarm/atmo25.dat.

1 F_, tr aoz aw_ 802 a_o2

250 16.5280 2.8229 80.8836 0.0000 0.0000 0.0000

325 41.0035 0.8742 0.3584 0.0000 0.0000 0.0000

350 12.7915 0.5925 0.0016 0.0000 0.0000 0.0000

375 27.1180 0.4768 0.0001 0.0000 0.0000 0.0000

400 35.1935 0.3643 0.0000 0.0000 0.0000 0.0000

425 42.1795 0.2833 0.0008 0.0000 0.0000 0.0000

450 49.1940 0.2238 0.0040 0.0000 0.0000 0.0000

475 49.7700 0.1791 0.0121 0.0000 0.0000 0.0000

500 48.3945 0.1451 0.0279 0.0000 0.0000 0.0000

525 46.4935 0.1189 0.0529 0.0000 0.0000 0.0000

550 46.5160 0.0983 0.0832 0.0000 0.0000 0.0000

575 46.1380 0.0820 0.1140 0.0148 0.0000 0.0000

600 44.1230 0.0690 0.1176 0.0851 0.0000 0.0000

625 42.0468 0.0584 0.0967 0.0016 0.0058 0.0000

650 39.5245 0.0498 0.0643 0.0408 0.0000 0.0000

675 37.8730 0.0427 0.04116 0.0009 0.2333 0.0000

700 18.7465 0.0382 0.0261 0.1074 0.1299 0.0000

725 66.8775 0.0319 0.0132 0.1462 0.0000 0.0000

775 59.9900 0.0244 0.0072 0.0065 1.1176 0.0000

850 102.2358 0.0168 0.0020 0.0568 0.0001 0.0000

950 84.7899 0.0108 0.0000 4.9142 0.0000 0.0000

1050 67.8772 0.0072 0.0000 0.0279 0.0002 0.0002

1150 56.0762 0.0050 0.0000 17.5902 0.0000 0.0000

1250 46.1106 0.0032 0.0000 0.0479 0.0028 0.0005

1350 37.3780 0.0026 0.0000 115.3197 0.0000 0.0003

1450 31.8313 0.0020 0.0000 95.2031 0.0000 0.0023

1550 27.2524 0.00115 0.0000 0.0364 0.0000 0.0014

1650 22.7691 0.0012 0.0000 0.0082 0.0000 0.0010

1750 18.6144 0.0009 0.0000 2.0008 0.0000 0.0001

1900 27.9521 0.0007 0.0000 228.9211 0.0000 0.0087

2200 33.6300 0.0004 0.0000 0.2550 0.0000 0.0118

2900 32.5775 0.0001 0.0000 314.7111 0.0000 0.0256

3700 7.2635 0.0000 0.0000 0.9158 0.0000 0.0003

2
wavelengthsaremuchmorestronglyabsorbingthanshorterones,theneteffectis reduction of _" ) " , foam reflectance at longer wavelengths. Based on t rc ums data (Frouin et

al., 1996) foam reflectance is treated as

F(1) = a + a ln[T (1)l + a ln[T (1)] 2 + a ln[T (1)p ' l< 900nm

0 1 w 2 w 3 w

(1)

where F is a factor to adjust foam reflectance for spectral dependence, 1 is wavelength

in nm, T w is the transmittance of water

T = exp[a (1) + 0.5b (1)1

W W W

(2)

where aw and b w are the spectral absorption and scattering coefficients of seawater,

respectively. The 0.5 factor for b wrepresents the backscattered portion. In Eq. 1, a0,

al, a2, and a3 are empirical coefficients to produce a best fit to the published data of

Frouin et al. (1996), and are 0.9976, 0.2194, 0.0554, and 0.0067, respectively.

At and above 900 nm, aw is nearly completely absorbing, and a new parameterization is

used

|:(l) = bo + bll + b212+ b3P " 1 2 900 nm (3)

where b o, by b e, and b 3 are defined similarly to their counterparts in Eq. 1, and are

5.026, -0.0114, 9.552x10 -6, and----2.698x10 -9, respectively.

Total foam reflectance rf now includes spectral dependence through

r_.(WA) = r_.(W)F(1) (4)

where W is the wind speed (ms -j) and rf (W) is defined as in Gregg and Carder (1990).

Total surface reflectance is the sum of the specular and foam contributions, which now

have a spectral dependence

r (W,1)= r (W) + r (W.l) (5)

d dsp f

r (W.1)= r (W) + r (W.1) (6)

s ssp f

where i d and r represent the direct and diffuse surface reflectance components, and the

subscript sp represents specular reflectance (Gregg and Carder, 1990).

Under cloudy skies, OARM utilizes the cloudy sky model of Slingo (1989). This model

computes irradiance transmittance through clouds based on the liquid water path and

the cloud droplet effective radius using a Delta-Eddington approximation of the twostream approach. It is used for shortwave cloud forcing in the National Center for

Atmospheric Research Community Climate Model 3 (Kiehl et al., 1998).

3
In ourimplementationof theSlingo(1989)model,gaseousabsorptionby ozone,oxygen, carbondioxide, andwater vapor,occursbeforecloud transmittance,andEarth

curvatureeffects(Kasten,1966)areaccountedfor. Theclouddropletradiusis setto a

constant11.8urn,whichrepresentsthemeanoceanicvalueobservedin aglobalsurvey

(Hartet al., 1994).

The clear andcloudy sky modelstrack two irradiancestreamsto the oceansurface:

directanddiffuse(Fig. 1). Themagnitude,spectral,anddirectionaleffectsof clouds

onirradiancereachingtheoceansurfaceareillustratedin Fig. 2 for aliquid waterpath

of 80gin-2.Thiswaterpathvalueproducesaboutone-halftheirradianceof clearskies

for thesamesolarzenithangle(30°),atmosphericopticalgasesandmolecularandparticulatescattering.Cloudsclearlychangetheamountof irradiancereachingtheocean

surface,butalsodirectionalqualitybyapportioningalargerpercentageto difi\tserather

thandirect,which predominatesunderclearskies. Thespectralefl'ectsof cloudsare

shownmoreclearlyin Table2, whereproportionsof differentpartsof thevisiblespectrum arelistedwith andwithout clouds. Cloudyskybluespectra(350-400nln) representalargerproportionof total PARthanclearsky spectra(20.5%),while cloudysky

red spectra(650-700nm) representa smallerproportion(-9.4%). Theseresultsconfirm observationsby Siegelet al. (1999).

............................ ! t:__........................................ _ /

" _ / CO 2 .................................................. '_eater vapor i_ i_ .........

/"............................Ozone Oxygei} .................................... Q:J! __"-\,, > ...................................... ,...............

Molecules, aerosols ,.,_--_" ........ _" ' _"

... \ /"

"_ -x J

.z -

Ed \ ........ \ .............

1 _ D E d Es

}";! Es 1- p _ _",,

air _'_,/., _ _;£? J ": \\,

sea ;"_ _r , ,,

_' \\

"\ y E E k. s

E d

Figure 1. Depiction of the pathways of irradiance under clear and cloudy skies, and

in the oceans. The sizes of the arrows indicate the relative proportions of direct (Ea)

and diffuse (E) ilTadiance for clear skies and cloudy skies. Some of the surface

i_Tadiance is reflected off the sea surface (l-r). These pathways continue into the

ocean where an additional diffuse upwelling (E) path exists.

4
Surface Irradiance Spectra

1.2

"7

E

_=

E

_=

m

J / \ .....

-'\ cleat', direct

0.8

cloudy, diffuse "\

0/i

clear° difluse

0.2

cloudy, direct

o

Wavelength (rim)

Figure 2. Spectr_ surface irradiance just below the sea surface (after spectral surface reflectance) for clem" skies and cloudy skies. The cloudy sky simulation represents the effects

of 80 g m e liquid water path, which produces about half the total surface solar irradiance as

the clear sky model for the same solar zenith angle and atmospheric optical properties.

Table 2. Comparison of proportion of blue irradiance to

red irradiance under clear and cloudy skies. Cloudy sky

used a liquid water path of 80 g m-2, which produces a

reduction just under the sea surface of about half that for

clear skies.

Percent of PAR

350-400nm 650-700 nm

Clear 11.2% 17.0%

Cloudy l 3.5 % 15.4%

Difference 20.5% -9.4%

()ARM requires external cloud properties (cloud cover and liquid water path), as well

as surface pressure, wind speeds, relative humidity, precipitable water, and ozone.

Climatologies of cloud variables were created using a 5-year record of International

Satellite Cloud Climatology Project (ISCCP)-D2 monthly mean data made available by

the NASA/Goddard Earth Sciences Distributed Active Archive Center (GES-DAAC).

Climatologies of surface pressure, wind speeds, relative humidity, precipitable water

were created using National Center for Environmental Prediction (NCEP)Reanalyses

for the years 1978-2000 (Kalnay et al., 1996). Climatological ozone was derived from

a 20.5 year record beginning in 1978 of several Total Ozone Mapping Spectrometer

(TOMS) sensors, again made available by the GES-DAAC.

5
2.2 Oceanic Component

The oceanic portion of OARM tracks three irradiance streams in the water column:

downwelling direct, downwelling diffuse, and upwelling diffuse (Fig. 1). A complete

mathematical description of the oceanic component is described in the Appendix. However, the highlights of the model are described in the following.

The direct downwelling stream contains the irradiance directly transmitted by the sun,

traversing the air-sea interface, and proceeding forward at an angle described by the

solar zenith angle modified by the refractive index of seawater. Each scattering and

absorbing event in the water column removes irradiance froln the direct downwelling

stream.

Whereas the downwelling direct irradiance receives no contributions in the water colunto and steadily decreases as the result of absorption and scattering processes, the

downwelling diffuse irradiance gains forward-scattered downwelling direct irradiance

and backscattered upwelling diffuse irradiance in the water column. This irradiance

stream travels along a path defined as the average cosine for downwelling diffuse irradiance. This is considered constant in OARM at 0.83 (Sathyendranath and Platt, 1988).

The difl'use upwelling stream is composed entirely of backscattered direct and dill;use

downwelling irradiance. It is derived from the two-stream model of Aas (1987), with

contributions from both the downwelling direct and downwelling diffuse explicitly included, similarly to Ackleson et al. (1994). The diffuse upwelling stream can represent

10% of the total at some wavelengths. We track only one scattering event for each of

the oceanic layers for computational convenience. This approximation is effective for

the open ocean domain, but would become erroneous in waters containing very large

amounts of optically active constituents.

Application of the oceanic portion of OARM requires that the absorption and scattering

properties of the water column be specified. In this effort we include fixed contributions by seawater and chromophoric dissolved organic matter (CDOM), and variable

contributions by five different phytoplankton groups. Water absorption and scattering

properties are taken from Smith and Baker (1981) for the range 200-800 rim, Circio and

Petty (1951) for the range 800nln-2.5mln, and Maul (1985) for the range 2.5---4.0mm.

A reanalysis of seawater absorption for 380-729 nln (Pope and Fry, 1997), is substituted lot the Smith and Balker (1981) estimates (Table 3). CDOM absorption is taken

from Carder et all. (1989), which includes a humic acid component and a fulvic acid

component.

Phytoplankton specific absorption coefficients are derived by taking spectra from the

published literature and normalizing to the absorption at 440 mn [a'p(440)] to obtain

normalized specific absorption spectra [a*p(1)] N for each of the five phytoplankton groups

(see Appendix). The resulting spectra exhibit substantial inter-group variability (Fig.

3).

6
Table 3. Spectral seawater absorption (a_) and total scattering (bw) coefficients (m-_).

Derived from Smith mid Baker (1981) for the spectral ranges 200-370 nm and 730-800

nm, Pope and Fry (1997) for the range 380-720 nm, Circio and Petty (1951) for the

range 800nm-2.5nm, and Maul (1985) for the range 2.5-4nm.

l(nm) aw bw

250 0.6112 0.0567

325 0.0762 0.0187

350 0.0461 0.0135

375 0.0182 0.0100

400 0.0063 0.0076

425 0.0051 0.0058

450 0.0083 0.0045

475 0.0119 0.0036

500 0.0215 0.0029

525 0.0407 0.0023

550 0.0550 0.0019

575 0.0849 0.0016

600 0.1995 0.0014

625 0.2850 0.0012

650 0.3512 0.0009

675 0.4559 0.0007

700 0.6433 0.0007

725 1.4449 0.0006

775 2.3900 0.0004

850 3.7382 0.0002

950 27.4805 0.0000

1050 119.3470 0.0000

1150 67.1800 0.0000

1250 94.9976 0.0000

1350 363.1256 0.0000

1450 1118.6070 0.0000

1550 944.8757 0.0000

1650 519.5995 0.0000

1750 646.7179 0.0000

1900 3768.5610 0.0000

2200 2628.0830 0.0000

2900 437623.000 0.0000

3700 1338404.00 0.0000

7
::_>_:$;>diato m!-

550 575 400 425 450 47"_ "_00 S2"_ SSO "_7"_ 600 62"_ (_5(I (_75 700

Spectral Scattering

0.0g _<_ea wafer/I0

"_ _ _, --x_-chlor ophytes 0.0/

x'*Jl_ - .._..c oct u ]ithophore_'

0.06 ............................... _*"l_'_R'2";_'_" -_-------------------_ ._,_dlnoflagella_es '

"5" 0.05

a

0,04 ,,,>.._ _._..

,_ 0.0.3

o oi _'_C7 "_ ........ _"_"_ _

350 375 400 423 430 473 500 _2_ 550 57S 600 62S 6S0 67'_ vn,"_

_;_vele_gtl_ (ran)

Figure 3. Spectral absorption (top) and scattering (bottom) for oceanic constituents in the oceanic component of OARM. Units for seawater absorption and

scattering coeKiceints are m _, chlorophyll-specific absorption and scattering

coefficients for phytoplankton groups have units of m e mg 1. Note that seawater

absorption coefficients have been scaled by a factor of 0.1, and seawater scattering coefficients have been scaled by a factor of 10 to fit on the plot.

Phytoplankton specific scattering coefficients are obtained from measurements at 590

nm and extended to the entire spectrum from information on specific attenuation coefficients (Bricaud et al., 1988; see Appendix). Again substantial group-dependent variability is apparent in the scattering spectra (Fig. 3). Additionally, knowledge of the specific

backscattering coefficient is required for the oceanic model. These values are derived

from the probability of backscatter (see Appendix).

All calculations are performed in energy units (W m-2), in conformance to the absorption

and scattering derivations. When summing the mean irradiance in the oceanic layers of

an Ocean General Circulation Model (OGCM), irradiance is converted to quantum flux

(retool quanta m a s-_) to enable photoadaptatmn and growth kinetics to occur in accordance with the prevalence of laboratory analyses.
3 Discontinuities in the Cloud Data Set

The ISCCP cloud cover and liquid water path data exhibited spatial discontinuities

(Fig. 4). These discontinuities typically occurred in three general locations: the central

Indian Ocean, western Atlantic Ocean, and the central Pacific Ocean. The Indian Ocean

discontinuity was always the most obvious and persistent, the Pacific Ocean discontinuity was second, and the Atlantic Ocean discontinuity was diminished relative to the

Indian and often not apparent. The discontinuities were always narrowest at the equator and became wider toward high latitudes (Fig. 4). As such, they resembled the coverage typical of geostationary satellites. Similar observations have been noted by Norris

(2000). These discontinuities were apparent in nearly every month and year of the data

record, although the locations differed monthly on occasion and sometimes differed

between the cloud cover and liquid water path data sets.

The ISCCP data set is a compilation of radiances fl*olll many different satellites, but is

generally derived from two series of geostationary and polar-orbiting missions. The

radiances are combined and Level-3 products (geophysical variables such as tile cloud

cover and liquid water path of interest here) are derived and mapped to a standard Earth

grid (Rossow et al., 1996). Although on-orbit failures and launch delays affect the

coverage of the Earth by these two satellite series at any one time, there are usually

three geostationary satellites, located in the western Pacific near 140°E (the GMS series), in the eastern Atlantic near 0 ° (the METEOSAT series), and in the eastern Pacific

near 90°W (the GOES series). Data from these three geostationary series are the priority for the ISCCP-D2 archive (Rossow et al., 1996). Unfortunately, the GMS and

METEOSAT satellites do not cover the central Indian Ocean, which is filled in by tile

NOAA polar-orbiting series. This geo-stationary gap lies over the Indian Ocean discontinuity, immediately suggesting a cause. METEOSNF and GOES coverages overlap in the central western Atlantic Ocean, corresponding to the second discontinuity. In

cases of overlap, tile ISCCP procedures are to preferentially use the data with the lowest solar zenith angle (Rossow et al., 1996). GOES and GMS overlap in the central

Pacific again corresponding to the location of the Pacific discontinuity.

Considering the effort devoted to inter-calibration among the diverse satellite sources

by the ISCCP project (Rossow et al., 1996), we suspected that these discontinuities

resulted from satellite/sensor inter-calibration inconsistencies that may have been too

subtle to appear in the Level-1 data but re-appeared in tile I,evel-3 products as a result

of extended processing. We attempted to ameliorate tile effects of the sensor

di scontinuities in the I,evel-3 data, assuming that Level- 1 inter-calibration procedures

by the ISCCP effort have been exhaustive. We first located the area of discontinuity in

each monthly record. We eliminated all values that existed in the apparent discontinuities,

by specifying a location in the center of the discontinuity at the equator, and its width,

and then re-creating its shape in tile mapped Level-3 image by applying a cosine function. The eliminated values produced gaps in the images of cloud cover and liquid

water path (Fig. 4).

9
iiii_;_**'?!ii" ,,,: 2:._i _ "" .4_;_iiiiiii_ii_i_'_x',_p'_'il

JUL 1989 Cloud Cover- ISCCP Cloud Cover- Gaps

:_,_/..... " _£::_ ....... _ . ::::::::::::::::::::::::::::::::::::::::: _,_::. !:-_!_: ""..... :_i_i_ii:_:_:_:: _

Cloud Cover- Objective Analysis Cloud Cover- ()A/Blend Result

JUL 1989 Liquid _Vater Path- ISCCP Liqoid Water Path- Gaps

................ _ _ .... _ .... _, _%; :_::::::::::_\_ .........._ .... _:_ ..........................

INliilii_iN!!!i_i!!!!!!!!!!i!!N_i_!!!ill _i_i_m liiiili',iiiiiii_,iii!N!!iN!!i!INii_,_!i!iiiii!!!!! _l

Liquid Water Path- Objective AnMysis LiqNd Water Path- O/A Blend Result

Figure 4. Depiction of the discontinuities in the ISCCP cloud cover (top 4

panels) and liquid water path (bottom 4 panels) data sets for July 1989. This

sequence shows the discontinuities in the upper left (note especially the central Indian Ocean), elimination of data occurring in these areas in the upper

right, reconstruction using objective analysis in the lower left panel, and the

final reconstruction where the edges of the reconstructed gaps are taken from

objective analysis to serve as an interior boundary condition for the blended

analysis.

10
To reconstruct data in the newly created gaps, we first applied the Successive Correction Method (SCM), using the Barnes method (Daley, 1991). We applied a radius of

influence of 100 kin. This method is often referred to as objective analysis. The SCM

re-created data in the gaps in conformance with the spatial structure of the data outside

the gaps produced by the geostationary satellites. However, it also produced a new

discontinuity at the meridional center of the gaps where the spatial structure trends of

the two geostationary satellites were in disagreement (Fig. 4). Thus we limited our

application of SCM to a small number of gridded pixels inside tile gap on each side.

The number varied from 4-12 depending upon tile size of the gaps, but 4 was used most

often. Since these pixels are very close to the valid data provided by the geostationary

satellites, we assumed these data to represent a "truth field", and then applied the blended

analysis of Reynolds (1988) to reconstruct the remainder of the gaps. This method

produces a bias correction given a set of internal boundary conditions represented by

the "truth field", while adhering to the spatial structure of the original data in the gap

area before elimination. This bias correction quality is the desired characteristic sought

for this problem. The method has been used successfully in reconstructing sea surface

temperature fields from satellite data using i_l situ observations (Reynolds, 1988,

Reynolds et al., 1989), as well as for chlorophyll concentrations (Gregg and Conkright,

2001). The resulting image fields indicated little apparent discontinuity, while retaining spatial structure of the original fields, even in tile gap-eliminated regions (Fig. 4).

4 Comparison of OARM with Surface Solar Irradiance Data

OARM results were compared to surface solar irradiance data produced by ISCCP

(Bishop et al., 1997) to evaluate its performance. The ISCCP surface solar irradiance

data represent monthly means integrated over the solar spectrum. OARM is a spectral

and directional model over the same spectral domain. The comparison was performed

only for the Jan. 1989-May 1991 using coincident monthly mean atmospheric optical

variables (not the climatologies discussed earlier). This time period was selected because of the coincident availability of ISCCP cloud data from the GES-DAAC and

TOMS ozone data. Although the ISCCP surface solar irradiance data represented the

output from a model (Frouin et al., 1989), it has been tested extensively against field

measurements with excellent results (Bishop et al., 1997). The comparison performed

here involved integrating the surface spectral irradiance computations of OARM across

the entire solar spectrum, and over the direct and diffuse components, with surface reflectance neglected. Thus we effected a one-to-one comparison with data, that indicated the performance of the spectral and directional OARM.

The comparison between OARM integrated spectral and directional irradiance exhibited a large degree of correspondence with ISCCP surface solar irradiance for the 29

month record under investigation (Table 4). Mean coefficient of determination (r 2) was

0.97, with RIMS of 12.1% and an average error of-4.0%. Minimum and maximum r2

was 0.96 and 0.98, respectively. The minimum RMS was 9.9% occurring in Jun. 1989

and the maximum was 15.1% occurring in Mar. 1990. The maximum was primarily the

11
resultof disagreementsoccurringin theAntarcticOcean.Theminimumaverageerror

was-7.3% andthemaximumwas-1.2%. Thenegativesignontheaverageerrorindicatesbias:OARM wastypically lowerthanISCCP.

Table 4. Comparison of OARM surface solar irradiance integrated over the solar

spectrum and over direct and diffuse components with total surface solar irradiance

data from ISCCP over a 29-month period from Jan. 1989 to May 1991.

Mean Minimum Maximum

r _ 0.97 0.96 0.98

RMS 12.1% 9.9% 15.1%

Average Error -4.0% -7.3% -1.2%

Representative scatterplots of OARM and ISCCP total surface irradiance for four seasons indicated the correspondence between the two (Fig. 5). The vast majority of the

points in each month fall on a one-to-one line, but OARM had a substantial number of

lower computed irradiances in the mid-range (about 120-250 W m-:) than ISCCR Outliers well below the one-to-one line indicated differences in ice masking data sets used

here: ISCCP used a radiance threshold (Bishop et al., 1997) while OARM used ice

sheet distributions from the NASA Data Assimilation Office. In Feb. 1990, Aug. 1990,

and Nov. 1989 the comparison indicated slightly higher estimates by OARM at low

irradiance levels (< 50 W m -2) than ISCCR This was due to Earth curvature effects that

were accounted for in OARM, but not in ISCCR

'_ 200

,ooI

:0 iiii

0

I00 200 300 400

400 :i!........................................ :.................................. :...................................... ?.............................. i: i;"::_

i ............. :;{

. _s'; .+i

.-. 300i: ::_:::':-':".:i )i

200i)i j: ! .'..... ,. _

_4" ,OOi ! f _. :,:_c : r2 = 0.975 ii

0 ;: t_ _ :i

0 I00 200 300 400

ISCCP (W m _)

- 300

_

200

t_

<

0 100

400

_- 300

_-_ 200

<

CI 100

0

0

........ ,............ ,...._., .......... .,.... .......... ,.._., ._.:..... ,. ,............:,:

._.--

0 100 200 300 400

............................................................................... 7::I

100 200 300 400

]SCCP @V m _)

Figure 5. Scatterplots of surface i_Tadiance produced by OARM integrated

over the entire solar spectral domain and over the direct and diffuse paths, and

the ISCCP data for 4 representative months.

12
Distributionsof integratedsurfaceirradiancefor Feb.andSep.1990(Figs. 6 and7)

illustratedthenatureof theagreementbetweenOARM andtheISCCPdatasets.General featuresof surfaceirradiancewere in agreementthroughouttheglobal domain,

especiallyovertheoceanicportions. TheISCCPdataexhibitedsmoothingof the retrievedradiancefields (J.K.B.Bishop,personalcommunication,1999).Theinputcloud

fields usedby OARM werenot smoothed.This gaveriseto someof the differences

observedin the statisticalanalyses.Overall,thesedistributionsof surfaceintegrated

irradiancereflectedthecorrespondenceobservedin thestatisticalanalyses.

Acknowledgements.Wewishto thankNOAA/NCEPfor Reanalysisproducts(surface

pressure,wind speed,relativehumidity, andprecipitablewater),NASA/GES-DAAC

for providingISCCPcloudandTOMS ozoneproducts,theISCCPprojectfor producing the clouddata,andthe NASA TOMS Projectfor producinganddistributing the

ozonedata.NancyCasey(ScienceSystemsandApplications,Inc., I,anham,Mill))provided graphicalanalysis,plots, andanalysisof ISCCPcloudcoverandliquid water

pathdata. This work wassupportedunderNASA Grant(RTOP)971-622-51-31.Atmosphericandoceanicopticaldatadescribedin thispaperareavailablevia anonymous

ftp at sahno.gsfc.nasa.gov, in pub/outgoing/oarm.

13
ISCCP Mean Surface Irradiance {W m-2), February 1990

- ..................................................... ¢:-:-_:-:-_:-:-__ _i_ i

-180 -90 0 90 180

iSCCP Mean Surface Irradiance (W m-2), February 1990

-180 -90 0 90 180

Figure 6. C(ntour image of total surface irradiance from ISCCP

for February 1990 and the spectrally and directionally integrated

OARM.

14
ISCCP Mean Surface Irradiance (W m-z), September 1990

-45

.790

-180 -90 0 90 180

45

0

-90 0 90 180

Figure 7. As in Figure 6 for September 1990.

15

Appendix

Mathematical description of the oceanic component of OARM

The oceanic portion of OARM tracks three irradiance streams in the water column:

downwelling direct, downwelling difl\_se, and upwelling diffuse. We track only one

scattering event for each of the oceanic layers for computational convenience.

The direct downwelling stream is modeled as

Ed()V,k) = Ed()V,k-I)T d()V,k)T d()V,k) (A1)

where E d is the downwelling direct spectral irradiance at level k in the water column

(corresponding to the layer definitions of an OGCM, where k = 1 is the surface layer,

and k is positive downward), Tad iS the spectral transmittance of the direct stream after

absorption, and Tsd iS the transmittance after scattering

T d= exp(-a/Ba(0 w) Az) (A2)

T d = exp(-b/Bd(0 w) Az) (A3)

(;<-dependences have been dropped), where a is the total absorption coefficient of the

water in OGCM layer k, b is the total scattering coefficient, %(0w) is the average cosine, or path length in the water column as a function of the downwelling zenith angle

0 w, and kz is tile thickness of the OGCM layer in question. The downwelling zenith

angle is related to the solar zenith angle 0 by the index of refraction of seawater

Ud(0w) = COS0w (A4)

OW= sin-l[sin0/n] (A5)

where n is the seawater refractive index, parameterized as 1.341 (Austin, 1974).

The downwelling diffuse irradiance gains forward scattered downwelling direct irradiance and backscattered upwelling diffuse irradiance in tile water column

Es(k ) = E(k- 1)T s(k)Ts_(k)+F[ 1-Ts_(k)] + l:;d(k- 1)Td(k ) {t:[1 -T d(k)] }

+ E(k+ 1)T(k) {B [1-]' (k)] } (A6)

where E s is the downwelling diffuse irradiance at OGCM layer k, T and T are the

diffuse transmittances after absorption and scattering, respectively, F and B are tile

probabilities of forward and back scattering, respectively, T and'lT' are the upwelling

diffuse transmittances after absorption and scattering, respectively, and E is the up17
wellingdiffuseirradiance.T, T, T u,andTsuaredefinedsimilarlyto theirdownwelling

direct counterparts,exceptthat _*dis replacedby _._.for downwellingdirectirradiance,

andby _._.for upwellingdiffuseirradiance.Theyareconsideredconstantin OARM at

0.83 (SathyendranathandPlatt, 1988)and0.4 (Kirk, 1981),respectively. Thefirst

term ontheright-handsideof Eq.A5 representstransmittanceafter scatteringandabsorptionforthedownwellingdiffusestream,plustheadditionof theforward-scattered

component.Thesecondterm representsforwardscatteringfrom thedownwellingdirectstreamfromthelayerabove,andthethird termrepresentsbackscatteredirradiance

from theupwellingdifl'usestreamfrom thelayerbelow. Thebackscatteringprobability B is definedas

B = bib (A7)

wherebbis thebackscatteringcoefficient. Theforwardscatteringprobabilityis simply

F = 1.....B (AS)

Thediffuseupwellingstreamis derivedfromthetwo-strealnmodelofAas(1987),with

contributionsfrom both the downwelling direct and downwelling diffuse explicitly included, similarly to Ackleson et al. (1994). After experimentation, we found that the

average cosine for downwelling difluse irradiance _._.could be substituted for the direct

average cosine without incurring > 1 _.tmoles quanta m -2 s-_ error, except in the computation of irradiance leaving the ocean surface. With these assumptions, the integral form

of the Aas (1987) model reduces to

E(k) = [Ed(k-I )+E (k-l)l exp((zAz) ((Z+Cs)/bu (A9)

c, = 0.5 {(c -%) .....[(c -c )2-4(b b -c c )] _j2} (A10)

c = (a+r bb)/,u s (AI 1)

c = (a+r bb)/g_ (A12)

b_ = r_bb/,% (A13)

b = rubJ{t _ (A14)

where rs and ru are dimensionless shape factors to represent the mean backscatter coefficient (Aas, 1987), and are assumed constant at 1.5 and 3.0, respectively (Ackleson et

al., 1994).

Phytoplankton specific absorption coefficients a*p()V) are derived by taking spectra from

the published literature and normalizing to the absorption at 440 nm [a*p(440)] to obtain normalized specific absorption spectra [a*p(X)] N for each of the five phytoplankton

groups. Diatom and chlorophyte [a*p()_)] Nare taken from Sathyendranath et all. (1987),

18
cyanobacteriafrom Bricaud et al. (1988),coccolithophoresfrom Morel andBricaud

(1981),anddinoflagellatesfrom Ahnet al. (1992). Thenthe specificspectrala*p0'_)

values are derived using mean values at 440 nm. Diatom a'p(440) represents the mean

of 5 observations containing 4 different spp., chlorophytes 6 observations from 4 spp.,

cyanobacteria 5 observations from 3 spp., coccolithophores 3 observations of 1 spp.,

and dinoflagellates 1 spp, all from the references listed above. CDOM absorption is

taken from Carder et al. (1989)

aCDOM(X)= Ch a'h00 + Cf a*f(k) (AI 5)

where acDoN iS the absorption coefficient of CDOM (m-_), C represents the concentration (rag m -3) of a humic acid component (subscript h) and a fulvic acid component

(subscript f), and a* is the specific absorption coefficient of the two components

a*h(X) = 1.302x10 '4 exp[450-(?0] (A16)

and

a'f()0 = 5.0xl 0 .6 exp[450-(X)] (A17)

(Carder et all., 1989). Ch and C_.are fixed as 1.0 and 10.0 mg l'J(1-3, respectively (Ackleson

et al., 1994).

Phytoplankton specific scattering coefficients are obtained from measurements at 590

mn and extended to the entire spectrum from information on specific attenuation coefficients (Bricaud et all., 1988). Diatom and chlorophyte specific scattering coefficient

at 590 nm, b'd(590) and b* (590), are the mean of 5 observations and 6 observations,

respectively, from Morel (1987), Bricaud and Morel (1986) and Bricaud et al. (1988).

Cyanobacteria b'y(590) is the mean of 8 observations from Morel (1987), Bricaud and

Morel (1986), Bricaud et al. (l 988) and Ahn et al. (1992). Coccolithophore b*o(590) is

derived from the mean of 3 observations from Bricaud and Morel (1986), Bricaud et al.

(1988), and Ahn et al. (1992). Dinoflagellate b'f(590) is derived from a single observation by Ahn et all., (1992).

Measured chlorophyll-specific attenuation coefficients (Bricaud et al., 1988) suggested

1) a slight negative linear spectral trend for diatoms, 2) a spectrally flat profile for

chlorophytes and coccolithophores, 3) a slight negative trend for cyanobacteria, with a

local maximum corresponding to phycoerythrin absorption. But Bricaud et all. (1983)

observed a strong spectral dependence for Emiliana huxleyi, which we adopt here. Given

this information and knowledge of C*p(590) for each phytoplankton group

c* (590) = a'p(590) + b'p(590) (A18)

19
welit thetotal attenuationspectraof Bricaudet al. (1988)by

C*d(X) = C'd(590) .....4.3X10-4(X-590) (A19)

c*o(X)= c*c(590) (A20)

c*y0v)= c*y(590)- 8.0xl0-4()%-590) (A21)

C*o0V) = C*o(590 ) ....8.95x10-40,_-590) (A22)

C*f ()v) = C*f(590) (A23)

assuming no spectral dependence for dinoflagellates.

The specific total backscattering coefficients are derived by subtraction

b*i0v ) = c*i0v ) - a*i()v ) (A24)

where the subscript i indicates the phytoplankton group of interest, diatoms (d),

chlorophytes (c), cyanobacteria (y), coccolithophores (o), and dinoflagellates (f).

Additionally, knowledge of the specific backscattering coefficient is required for the

oceanic model. These values are derived from the probability of backscatter

bb(X) = B x b(X) (A25)

We assume no spectral dependence in b b, and use a constant value of 0.002 for diatoms

(Morel, 1988), 0.00071 for chlorophytes, 0.0032 for cyanobacteria (Ahn et al. 1992),

0.00071 for coccolithophores, and 0.0029 for dinoflagellates (both from Morel, 1988).

Ahn et al. (1992) suggested a spectral dependence for cyanobacteria but generally none

for the other groups.

Phytoplankton respond to the mean irradiance availability in the isopycnal layers in

which they reside. This is especially important in an OGCM sinmlation with discrete

numerical layers. OARM computes irradiance at the vertical boundaries of the model

layers. Derivation of accurate mean irradiance within each model layer is essential for

simulating realistic phytoplankton responses and primary production estimates in the

context of variable cloud cover and thickness.

We approach this problem by deriving a lookup table of factors to convert irradiance at

boundaries to the mean within the layer. The lookup table incorporates depth, chlorophyll concentration, and phytoplankton group as array indices. CDOM is assumed

constant, but variability could be incorporated by addition of another dimension in the

lookup table. The table is created applying the oceanic model in advance with the

20
assumptionthat _.ltd = 1 uniformly. Computation of mean irradiance is

E, avg(z) = M(kz,chl,p) {lEt(z- 1)+Et(z)]/2 } (A26)

where M is a factor obtained from the lookup table incorporating layer thickness (kz),

chlorophyll concentration (chl), and phytoplankton group (p), and E t is the total irradiance. Note that this computation is non-spectral, although the computation of irradiance at the layer boundaries is spectral. The effect of the computation for average

irradiance is not subtle - lookup table factors range from 0.0009 at high chlorophyll

concentrations and 200 m layers to 0.95 at low chlorophyll and shallow layers (<_ 5 m).

21

References

Aas, E., 1987: Two-stream irradiance model for deep waters. Appl. Opt. 26: 2095-2101.

Ackleson, S.G., W.M. Balch, and P.M. Holligan, 1994: Response of water-leaving

radiance to particulate calcite and chlorophyll a concentrations: A model for Gulf

of Maine coccolithophore blooms. J. Geophys. Res. 99: 7483-7499.

Ahn, Y.-H., A. Bricaud, and A. Morel, 1992: Light backscattering efficiency and related

properties of some phytoplankters. Deep-Sea Res. 39:1835-1855.

Austin, R.W., 1974: The remote sensing of spectral radiance from below the ocean

surface. In: Optical aspects of oceanography, N.G. Jerlov and E. SteemannNielsen, eds. pp 317-344, Academic Press.

Bird, R.E. and C. Riordan, 1986: Simple solar spectral model for direct and diffuse

irradiance on horizontal and tilted planes at the Earth's surface for cloudless

atmospheres. J. Clim. Appl. Meteorol. 25: 87-97.

Bishop, J.K.B., W.B. Rossow, and E.G. Dutton, 1997: Surface solar irradiance from the

International Satellite Cloud Climatology Project 1983-1991. J. Geophys. Res.

102: 6883-6910.

Bricaud, A., A.-L. Bedhomme, and A. Morel, 1988: Optical properties of diverse

phytoplanktonic species: experimental results and theoretical interpretation. J.

Plank Res. 10: 851-873.

Bricaud, A. and A. Morel, 1986: Light attenuation and scattering by phytoplanktonic cells: a

theoretical modeling. Appl. Opt. 25: 571-580.

Bricaud, A., Morel, A., and L. Prieur, 1983: Optical efficiency factors of some

phytoplankton. Limnol. Oceanogr. 28: 816-832.

Carder, K.L., R.G. Steward, G.R. Harvey, and P.B. Ortner, 1989: Marine humic and

fulvic acids: their effects on remote sensing of ocean chlorophyll. Limnol.

Oceanogr. 34: 68-81.

Circio, J.A. and C.C. Petty, 1951: The near infrared absorption spectrum of liquid water.

J. Opt. Soc. America. 41: 302-308.

Daley, R., 1991: Atmospheric data analysis, Cambridge Univ. Press, Cambridge. 457

pp.

Frouin, R., M. Schwindling, and P.-Y. Deschamps, 1996: Spectral reflectance of sea

foam in the visible and near-infrared; In situ measurements and remote sensing

implications. J. Geophys. Res. 101: 14361-14371.

23
Frouin, R., D.W. Lingner, and C. Gautier, 1989: A simple analytical formula to compute

clear sky total and photosynthetically available solar irradiance at the ocean

surface. J. Geophys. Res. 94:9731-9742.

Gregg, W.W. and M.E. Conkright, 2001: Global seasonal climatologies of ocean

chlorophyll: Blending in situ and satellite data for the CZCS era. J. Geophys. Res.

106: 2499-2515.

Gregg, W.W. and K.L. Carder, 1990: A simple spectral solar irradiance model for

cloudless maritime atmospheres. LimnoL Oceanogr. 35:1657-1675.

Han, Q., W.B. Rossow, and A.A. Lacis, 1994: Near-global survey of effective droplet

radii in liquid water clouds using ISCCP data. J. Clim. 7: 465-497.

Kalnay, E., and 21 others, 1996: The NCEP/NCAR 40-year reanalysis project. Bull Am.

Meteorol. Soc. 77: 437-471.

Kasten, F., 1966: A new table and approximate formula for relative optical air mass.

Geophys. Bioklimatol. B 14: 206-223.

Kiehl, J.T., J.J. Hack, GB. Bonan, B.A. Boville, D.L. Williamson, and P.J. Rasch, 1998:

The National Center for Atmospheric Research Community climate model:

CCM3. J. Clim. 11: 1131-1149.

Kirk, J.T.O., 1981: Estimation of the scattering coefficient of natural waters using

underwater irradiance measurements. Aust. J. Mar. Freshwater Res. 32: 533-539.

Maul, G.A., 1985: Introduction to satellite oceanography. Martinus Nijhoff Publishers,

Boston, MA, USA., 606 pp..

Moore, K.R., K.J. Voss, and H.R. Gordon, 1998: Spectral reflectance of whitecaps:

Instrumentation, calibration, and performance in coastal waters. J. Atmos.

Oceanic Tech. 15: 496-509.

Morel, A., 1988: Optical modeling of the upper ocean in relation to its biogenous matter

content (Case I waters). J. Geophys. Res. 93: 10749-10768,

Morel, A. 1987: Chlorophyll-specific scattering coefficient of phytoplankton. A simplified

theoretical approach. Deep-Sea Res. 34:1093-1105.

Morel, A. and A. Bricaud, 1981: Theoretical results conceming light absorption in a

discrete medium, and application to specific absorption of phytoplankton. Deep-Sea

Res. 28: 1375-1393.

Norris, J.R, 2000: What can cloud observations tell us about climate variability? Space Sci.

Rev., 94, 375-380.

24
Pope, R.M. and E.S. Fry, 1997: Absorption spectrum (380-700 nm) of pure water. II.

Integrating cavity measurements. Appl. Opt., 46, 8710-8723.

Reynolds, R.W., 1988: A real-time global sea surface temperature analysis. J. Clim., 1,

75-86.

Reynolds, R.W., C.K. Folland, and D.E. Parker, 1989: Biases in satellite-derived seasurface temperatures. Nature, 341,728-731.

Rossow, W.B., A.W. Walker, D.E. Beuschel, and M.D. Roiter, 1996: International

Satellite Cloud Climatology Project (ISCCP): Documentation of new cloud

datasets. 155 pp. Available on intemet at http://isccp.giss.nasa.gov/

documents, html.

Sathyendranath, S. and T. Platt, 1988: The spectral irradiance field at the surface and in

the interior of the ocean: a model for applications in oceanography and remote

sensing. J. Geophys. Res., 93, 9270-9280.

Sathyendranath, S., L. Lazzara, and L. Prieur, 1987: Variations in the spectral values of

specific absorption of phytoplankton. Limnol. Oceanogr., 32, 403-415.

Siegel, D.A., T.K. Westberry, and J.C. Ohlmann, 1999: Cloud color and ocean radiant

heating, J. Clim., 12, 1101-1116.

Slingo, A., 1989: A GCM parameterization for the shortwave radiative properties of water

Cloud. J. Atmos. Sci., 46, 1419-1427.

Smith, R.C. and K.S. Baker, 1981: Optical properties of the clearest natural waters (200-

800nm). Appl. Opt., 20, 177-184.

25
I Form Approved

REPORT DOCUMENTATION PAGE OMBNo. 0704-0188

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources,

gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this

collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson

Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington, DC 20503.

1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED

June 2002 Technical Memorandum

4. TITLE AND SUBTITLE 5. FUNDING NUMBERS

Technical Report Series on Global Modeling and Data Assimilation

Volume 22--A Coupled Ocean-Atmosphere Radiative Model for Global Ocean

Bio_eochemical Models Code 971

6. AUTHOR(S)

Watson W. Gregg

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS (ES)

Goddard Space Flight Center

Greenbelt, Maryland 20771

9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS (ES)

National Aeronautics and Space Administration

Washington, DC 20546-0001

8. PEFORMING ORGANIZATION

REPORT NUMBER

2002-02197-0

10. SPONSORING/MONITORING

AGENCY REPORT NUMBER

TM-2002-104606, Vol. 22

11. SUPPLEMENTARY NOTES

12a. DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified-Unlimited

Subject Category: 22

Report available from the NASA Center for AeroSpace Information,

7121 Standard Drive, Hanover, MD 21076-1320. (301) 621-0390.

12b. DISTRIBUTION CODE

13. ABSTRACT (Maximum 200 words)

An ocean-atmosphere radiative model (OARM) evaluates irradiance availability and

quality in the water column to support phytoplankton growth and drive ocean

thermodynamics. An atmospheric component incorporates spectral and directional

effects of clear and cloudy skies as a function of atmospheric optical constituents, and

spectral reflectance across the air-sea interface. An oceanic component evaluates the

propagation of spectral and directional irradiance through the water column as a function

of water, five phytoplankton groups, and chromophoric dissolved organic matter. It

tracks the direct and diffuse streams from the atmospheric component, and a third stream,

upwelling diffuse irradiance. The atmospheric component of OARM was compared to

data sources at the ocean surface with a coefficient of determination (r2) of 0.97 and a

root mean square of 12.1%.

14. SUBJECT TERMS

Ocean-Atmosphere Radiative Model (OARM)

17. SECURITY CLASSIFICATION

OF REPORT

Unclassified

18. SECURITY CLASSIFICATION

OF THIS PAGE

Unclassified

NSN 7540-01-280-5500

19. SECURITY CLASSIFICATION

OF ABSTRACT

Unclassified

15. NUMBER OF PAGES

33

16. PRICE CODE

20. LIMITATION OF ABSTRACT

UL

Standard Form 298 (Rev. 2-89)

Prescribed by ANSI Std. Z39.18

298-102