Improvement andValidation of Version 2
GLI Ocean Products

H. Murakami, K. Sasaoka, K. Hosoda,
H. Fukushima, M. Toratani, R. Frouin,G. Mitchell, A. Tanaka, J. Ishizaka, M. Kishino,
H. Kawamura, F. Sakaida, S. Saito, I. Barton,
C. Dupouy, A. Siripong, K. Yokouchi,
Y. Kiyomoto, H. Saito, S. Yamao, D. Clark,
P-Y. Deschamps, and collaborators...

ADEOS-2 workshop, December 2004
1

0. Introduction• We achieved minimum level of the ocean products to thefirst data release (version 1) in Dec. 2003• In Nov. 2004, we released “version 2” products to catch up
with today's other sensor products and have someadvantages.
• This presentation includes;
1. Characteristics of the Ver. 2 Algorithms
2. Validation Results
3. Summary and Plan2

1. Ver.2 Algorithms
New features of the ver.2 ocean algorithms• Atmospheric correction (nLw, aerosol, and PAR)• In-water algorithms (CHLA, SS, CDOM, and K490)• Sea surface temperature

Algorithm: H. Fukushima*1, M. Toratani*1, A. Tanaka*2, J. Ishizaka*2,M. Kishino*2, R. Frouin*3, H. Kawamura*4, and F. Sakaida*4*1 atmospheric correction, *2 SS, *3 PAR, *4 SST
Analysis & integration: H. Murakami and K. Hosoda
31.1 Atmospheric Correction(Sunglint and Absorptive Aerosol Corrections)Ver.1 CHLA

Ver.2 (using same L1B)

Carbonic aerosol
from natural fires

2003/05/09 around the Korean Peninsula

1. Sunglint correction estimates surface reflectance using SeaWinds Level3 wind speed data
2. Absorptive aerosol correction estimates aerosol absorption using CH1(380nm) observation and simulated nLw _380 by in-water optical model4

1.2 Suspended Solid Concentration (SS)New features of Ver.2 SS (neural network)

Ver.1 SS (Ver.1 nLw)

1. Parameters in the in-water optical model are
refined by newly collected in-situ measurements.
The model makes training data for the neuralnetwork (NN).
Ver.1 SS was lower than in-situ SS
Ver.2 SS improved the under estimation
Ver.1 SS (Ver.2 nLw)
Ver.2 SS5

1.3 Potosynthetically Available Radiation (PAR)New features of Ver.2 PAR algorithms:
1. Diurnal variability of clouds is considered statistically (using aregional diurnal albedo climatology based on 5 years of ERBS data;monthly, 2.5 degree resolution, 16 local times from 05:30 to 20:30 )2. Surface albedo parameterization is modified (as a function of sun
zenith angle and fractions of direct and diffuse incoming sunlight)(a)(a) Ver.2 PAR on 2003/05/17(b) Ver.2 − Ver.1(c) GLI observation local time

(b)

(c)

6

1.4 Sea Surface Temperature (SST)
New features of Ver.2 SST algorithm:
1. MCSST coefficients was remade using new L1B :- stripe noise correction (simulate ver.2 radiance),- geometric correction (ver.1)
2. 3.7µm (CH30) was included in the nighttime MCSST
coefficients (separated for day and night)
3. Electric noise correction is applied to MTIR data
4. Cloud screening scheme was refined→ RMSE decreased from 0.83 to 0.66 K (0.74 to 0.70) indaytime (nighttime)7

1.5 Electric Noise Correction (Version 2 SST)

Ver.2 SST

Ver.1 SST

2004/04/10 East Japan8

2. Validation
Results
Match-up analysis and comparison with other satellite
datasets:• nLw and Tau_a• In-water products• PAR• SSTIn-situ observation and data analysis:
Validation PI, Algorithm PI, GAIT, and collaborators
92.1 In-situ Observations (ocean color)• Available match up data was increased (about twice) after Ver.1• Clear match-ups: 50~400 nLw (~300: SIMBADA), and 30-150 in-waterparameters
CalCOFI (April 2003)
Mitchell (SIO), Frouin (SIO),
Hokkaudo Univ.

SIMBADA cruises
Deschamps et al.

Gulf of Thai
Siripong
MOBY
Clark

SST around
Australia
Barton

New Caledonia
Dupouy1 SIMBADA_20030204
2 CALCOFI_20030404
3 IMECOCAL20030408
4 P500304_20030424
5 MOBYSWMD000000
6 SURF_CAL20030404
7 ngsktros20030320
8 ishysmpl20030414
9 redtides20030722
10 ishysmpl20031017
11 _03058Na20030510
12 _03421Na20030421
13 030519Ka20030519
14 030711Na20030711
15 031017Ka20031017
16 ____NPEC20030501

17 ___
18 __Tansei20030705
19 KH0302__20031001
20 Hakodate20030211
21 TKYOSGMI20030415
22 newcaled20030227
23 __YK030120030413
24 __YK030520030707
25 __YK030620030801
26 SPINUP__20030412
27 SY0306__20030526
28 _____GOT20031009
29 SURF_IME2003040630 jettrios20030923
31 jettrios20030926
32 ChibaTHY20030503

Japanese Univ. and Institutes
Ishizaka (Nagasaki), Kishino (Tokyo-Ocean), Saito (Hokkaido),
NFRI (Seikai-ku, Tohoku), NPEC, JCG, JAMSTEC, EORC, etc. 10

2.1 In-situ Match Up Observations
instruments

targets

wavelength nm

PRR600/610
under & above

412, 443, 490, 520,565, 670 and PAR+

MER2040/2041 !downward irradiance (Ed )−!upward radiance (Lu )under & above−!sky irradiance (Es )Free Fallunder & above

TRIOSabove onlynLw

downward irradiance (Ed+)+!upward radiance (Lu )+!downward radiance (Ls )!

Calculate water leaving
412, 443, 465, 490, radiance (Lw) by
510, 520, 555, 565, upward radiance profile
625, 665,670,683 Lu.
and PARnLw is normalized by
Lw, Ed and F0.
380, 400, 412, 443,455, 490, 520, 555,565, 620, 665, 683,
705 and PAR

350-950nm
1nm intervals

normalize Lu by Ed, F0and sea surface
reflection factor.

112.2 Match-up Results (Version 1 nLw)
• Problems of the Ver.1 nLw were large scatter at 380nm and negative nLwlarge scatter

Ver.1 tests
including thenew match ups
nLw (380-625nm) , Tau_865,
andangstrom_520
X-axis： in-situ,Y-axis: GLI

12

2.2 Match-up Results (New Vical + Ver.1)• Large scatter of nLw 380nm is improved by vicarious calibrationconsidering time and scan-angle.

improved

Ver.1 tests
using new vicalcoefficientsnLw (380-625nm) , Tau_865,
andangstrom_520
X-axis： in-situ,
Y-axis: GLI

13

2.2 Match-up Results (Version 2 nLw)
• Negative nLw is improved by the absorptive aerosol correction(accuracy and available data number).
too high
improved

Ver.2 tests
using new vicalcoefficientsnLw (380-625nm) , Tau_865,andangstrom_520

improved

X-axis： in-situ,
Y-axis: GLI14

2.2 Absorptive Aerosol Correction
Tau_a 865

Absorptive aerosol influenced
frequently around Japan

Ver.1
CHLA

Ver.2
CHLA

nLw in blue channel is too highIt makes better, but theabsorptive factors and in-watermodel should be refined more.
2003/04/10 East Japan15

2.3 Match-up Results (Version 1 in-waterparameters)• Sample number is increased by collection and reanalysis of in-situ data
• Accuracy in the coastal area was not enough. (coastal: . . . a>0.05 or b>0.1)
CHLA

Ver.1 offshore

SS5 kmCDOM.
.

×.

.
.

a=land/total areabK490

Ver.1 coastal

162.3 Match-up Results (Version 2 in-waterparameters)• Available data number is increased by the atmospheric correction algorithm• SS algorithms are revised in Ver.2.
• Accuracy in the coastal area is still not enough.
CHLASSCDOM
K490

Ver.2 offshore
improvedtoo low

Ver.2 coastal

172.4 Results of Each Cruises (Version 1 nLw_443)• nLw_443nm

NumberRMSR = RMSD / In-situ Average

Many SIMBADA
cruises ~300

red tide

TRIOS
automatic
above-waterobservations
Ariake-kai

avg: 0.405

Green: all, Blue: Offshore, Red: Coastal
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2.4 Results of Each Cruises (Version 2 nLw_443)• Available data number is increased by the level-2 algorithm• Some cases better, and some cases worse.
(X: in-situ, Y: GLI)
NumberRMSR = RMS(Y-X) / X-averageworse

To be improved
the in-situ dataanalysis

increasedimproved

avg: 0.441

Green: all, Blue: Offshore, Red: Coastal
192.4 Results of Each Cruises (Version 1 CHLA)• CHLA(X: in-situ, Y: GLI, linear scale)
NumberRMSR = RMS((Y-X)/X)

Coastal sites

Gulf of Thai land
Toyama-wan

Ariake-kai
0.576

Green: all, Blue: Offshore, Red: Coastal
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2.4 Results of Each Cruises (Version 2 CHLA)• Available data number is increased by the level-2 algorithm• Some cases better, and some cases worse.
NumberCHLA
Gulf of Thai land

increased

Baja California

improvedworse0.677

Green: all, Blue: Offshore, Red: Coastal
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2.5 In-situ Match-ups (Version 1 & 2 SST)
Ver.1
1. GTS data (buoys) is used forthe match up.
2. New SST coefficients arederived using new L1B:
• Stripe noise correction(simulate ver.2 radiance),

RMSE=0.83K

RMSE=0.74K

RMSE=0.66K

RMSE=0.70K• Geometric correction (ver.1)
3. 3.7µm (CH30) is used fornighttime SST

Ver.2

4. Cloud screening→improved by 0.04~0.17K

22

2.5 In-situ Match-ups (Version 2 SST)

Temporal change of estimation error of the SSTBias and RMSE
from April toOctover 2003
Unit: °C
Bias decreased by 0.05~0.1K during 6 months, RMSE changed and peaked inAugust 2003.
The reasons may be temporal changes of MTIR channel sensitivity and noisecharacteristics

23

2.6 Comparison with Other Satellite (CHLA)• GLI, Terra MODIS and Aqua MODIS on 17 Oct. 2003
• CHLA by SeaWiFS, Terra and Aqua MODIS are different In high and low ranges.
• After this vical, Terra & Aqua MODIS CHLA are agreed well with SeaWiFS one.

24

2.6 Comparison with Other Satellite (CHLA)• GLI with SeaWiFS, Terra MODIS and Aqua MODIS on 17 Oct. 2003
• GLI CHLA in low CAHL range has a problem ? Or due to channel
difference used in in-water algorithm ?

25

2.6 Comparison with Other Satellite• GLI CHLA 17 Oct. 2003
Zoom
aroundJapan26

2.6 Comparison with Other Satellite• SeaWiFS 17 Oct. 2003
Zoom
aroundJapan27

2.6 Comparison with Other Satellite• Terra MODIS CHLA (calibrated by the
GLI vical scheme) 17 Oct. 2003

5. ProductZoomaroundJapan28

2.6 Comparison with Other Satellite• Aqua MODIS CHLA (calibrated by theGLI vical scheme) 17 Oct. 2003

5. ProductZoomaroundJapan

29

2.7 Comparison with Other Satellite (PAR)• GLI PAR was validated by SeaWiFS PAR, TAO and GMS irradiance

GLI monthly 2003/07

PAR distribution
and data range
agree well.
Validations byGMS, objective
analysis and In-situ
irradiance data arealso performed.
SeaWiFS monthly 2003/07
30

3. Summary and Plan

Future products: GLI 250m nLw_543 Kinki area Japan, 1 (left) and 9 (right) Oct. 2003

H. Murakami, K. Sasaoka, K. Hosoda, and Ocean PIs
ADEOS-2 workshop, December 200431

3.1 Ver.2 Validation Summary• By the ver.2 revisions of vical and ocean algorithms, accuracy ofnLw, CHLA (coastal area), SS (offshore) and SST is improved.
• Coastal retrieval should be investigated further.
Parametertarget

Ver. 1Ver. 2

Note

Normalized waterleaving radiance(NWLR)!380nm is improved by ~15% by the new vical.
CH01-09
CH01-09：!Available data is increased by 10 /60%
40 /70%,40 /80%−35∼+50%(offshore/coast)
CH10-12
CH10-12/−50∼+100%!Low signal in >600nm causes large error.
offshore/coast
160 /110%120 /90%
!Absorptive aerosol is corrected. Problem in(offshore/coast) (offshore/coast)absorption rate

Photo syntheticallyavailable radiation(PAR)−10∼+10%(10km monthly)

Chlorophyll-aconcentration (CHLA)
Absorption of coloreddissolved organic
matter (CDOM)
Suspended solid
concentration (SS)

11%

~12%

!Comparison to TAO buoy and SeaWiFS!difference from SeaWiFS was increased due toconsidering diurnal cycle in GLI Ver.2−35∼+50%60 /350%70/ 240%/−50∼+100%(offshore/coast) (offshore/coast)
offshore/coast!Available data is increased by 10 /60%
(offshore/coast)!QC of in-situ data should be refined
80 /70%80 /70%−50∼+100%!Still problems in coastal areas!CDOM is under estimated!SS by NN is improved offshore but scattered
100 /60%
90 /260%−50∼+100%in coastal areas

Attenuation coefficientsat 490nm (K490)−35∼+50%

50 /60%50 /60%

Bulk sea surface
temperature (SST)

0.6K

0.83/0.74K

0.66/0.70K(day/night)!Match up data number is increased!Error was temporally changed by MTIR Cal ?

32

3.2 Status of Action Items for Ver.2
dateitemsReanalyze MUD using reprocessed (geo/radiometric) L1B→Done!Consider vical coefficients and their temporal change→Done!Improve absorptive aerosol →Done!Further study of in-water optical model in the coastal area(absorption, scattering, surface reflection coefficients)→Revised SS but still problems!Improve cloud detection →Done (SST and OC)!Applying the latest GLI algorithms to the MODIS NRT processing→test was done, continue to be operational!Improve sunglint correction using AMSR wind speed →Done (SeaWinds)!Switching saturation alternative bands, and try to use 710nm →Cancel!Consider diurnal cycle of cloud amount (PAR) →Done!Evaluate SS and CDOM algorithm in global coastal area →continue!Improve water vapor correction for SST →3.7um in nighttime SST!

From
Ver.1
(2003/12)
toVer.2(2004/11)→ Most of the items were realized in the Ver.2,
but still have coastal problems

33

3.3 Next Targets and Action Plandate

items
Improve spectral characteristics of absorptive aerosol!Improve parameterization of in-water optical model inGLI 250mnLw_543
the coastal area~50km!Investigate Atmos.Corr. and CHLA estimation using 250m data
!Investigate combined use of multi-sensor/satellite datasets (SST andothers)!Evaluate primary production algorithms (research product)!Study of fluorescence algorithm and its application (research product)!

after
Ver.2 tothemission
goal

For the next mission (SGLI) target: “Coastal area research and monitoring”
1. Construct coastal-area optical algorithms until SGLI launch.
← Make database of optical and CHLA observations in the coastal area
2. Describe and parameterize physical + biological processes in the coastal area3. Encourage science and data-user communities← Demonstration of coastal data application and study using GLI and othersatellite data34