Detailed Reports on the Validationof the SGLI Products
1. Summary
2. Land Products
3. Atmosphere Products
4. Ocean Products
5. Cryosphere Products

別1 - 1

1. Summary of the Validation of SGLI L2 Products
GCOM-C Success criteria (data production aspect only)
Level
Standard
Products

Minimum Success[L + 1yr]

Full Success[L + 5yr]Complete the Cal.& Val. phase and Achieve standard
start data distribution of more than accuracies of all
20 products achieving the releasestandard products
threshold accuracy

Results of the Post-Launch Validation
Level/Area[TheAtmosphere
Land [9]number of products][8]

Extra Succees[L + 5yr]

Achieve the target
accuracy of one ormore products

Ocean [7]Cryosphere[4]

Total [28]Release thresholdachieved

9

8

7

4

28

Standard accuracy
threshold achieved

1

4

3

1

9

Target accuracy achieved

0

2

1

0

3

 The release thresholds (the first accuracy target) of all L2 standard products havebeen achieved. In addition, the evaluation results indicate that nine (and three) L2
products have already reached the levels of the standard accuracy for the fullsuccess (and the target accuracy for the extra success) at this stage.

6-2

1. Summary of the Validation of SGLI L2 Products
Accuracy Requirements of SGLI L2 products and Current Evaluation Status (1/2)

Vegetation and carbon cycle
Cloud

Atmospheretemperature

Land

Surface reflectanceArea Group ProductRelease threshold

Standard accuracy

Target accuracy

Precise geometric correction◎<1 pixel<0.5 pixel<0.25 pixel

Atmospheric corrected reflectance(incl. cloud detection)○

0.3 (<=443nm),
0.2 (>443nm) (scene)

0.1 (<=443nm),
0.05 (>443nm) (scene)

0.05 (<=443nm),
0.025 (>443nm) (scene)

Vegetation index○

Grass:25% (scene),
forest:20% (scene)

Grass:20% (scene),
forest:15% (scene)

Grass:10% (scene),
forest:10% (scene)

Above-ground biomass○

Grass:50%, forest: 100%

Grass:30%, forest:50%

Grass:10%, forest:20%

Vegetation roughness index○

Grass & forest: 40% (scene)

Grass & forest:20% (scene)

Grass & forest:10% (scene)

Shadow index○

Grass & forest: 30% (scene)

Grass & forest:20% (scene)

Grass & forest:10% (scene)

fAPAR

○

Grass:50%, forest: 50%

Grass:30%, forest:20%

Grass:20%, forest:10%

Leaf area index○

Grass:50%, forest: 50%

Grass:30%, forest:30%

Grass:20%, forest:20%

Surface temperature○<3.0 K (scene)<2.5 K (scene)<1.5 K (scene)

Cloud flag/Classification

10% (with whole-sky camera)

Incl. below cloud amount

Incl. below cloud amountClassified cloud fraction☆
☆

20% (on solar irradiance)

15% (on solar irradiance)

10% (on solar irradiance)

Cloud top temp/height◎

1K

3 K/2 km (top temp/height)

1.5 K/1 km (temp/height)

Water cloud OT/effective radius○

10%/30% (CloudOT/radius)

100% (as cloud liquid water)

50% / 20%

Ice cloud optical thickness

○
○
○
◎

30%

70%

20%

0.1 (Monthly τa_670,865)

0.1 (scene τa_670,865)

0.05 (scene τa_670,865)

0.15 (Monthly τa_380)

0.15 (scene τa_380)

0.1 (scene τa_380 )0.15 (Monthlyτa_670,865)

0.15 (scene τa_670,865)

0.1 (scene τa_670,865)

Aerosol over the ocean
aerosolStatus*1

Land aerosol by near ultra violet
Aerosol by Polarization*1 Symbols denote as follows; 〇: the release threshold achieved, ◎: the standard accuracy achieved, ☆: the target accuracy achieved.

6-3

1. Summary of the Validation of SGLI L2 Products
Accuracy Requirements of SGLI L2 products and Current Evaluation Status (2/2)
Area Group ProductRelease threshold

Standard accuracy

Target accuracy

Normalized water leaving radiance(incl. cloud detection)◎

60% (443~565nm)

50% (<600nm)
0.5W/m2/str/um (>600nm)

30% (<600nm)
0.25W/m2/str/um (>600nm)

Atmospheric correction parameters○

80% (AOT@865nm)

50% (AOT@865nm)

30% (AOT@865nm)

Photosynthetically available radiation◎

20% (10km/month)

15% (10km/month)

10% (10km/month)

Chlorophyll-a concentration○−60~+150% (offshore)−60~+150%−35~+50% (offshore),−50~+100% (coast)

Suspended solid concentration○−60~+150% (offshore)−60~+150%−50~+100%

Colored dissolved organic matter○−60~+150% (offshore)−60~+150%−50~+100%

temperatur
Sea surface temperaturee☆

0.8 K (daytime)

0.8 K (day & night time)

0.6 K (day & night time)

Snow and Ice covered area (incl. cloudArea/
detection)
distributionOkhotsk sea-ice distribution

○

10%

7%

5%

○

10%

5%

3%

Snow and ice surface Temperature◎

5 K (vicarious val with other sat.
2K
data and climatology)

1K

Snow grain size of shallow layer○

100% (vicarious val with50%
climatology between temp-size)

30%

Ocean

Ocean
color

In-water

Cryosphere

Status*1(vicarious val withother sat. data)

Surfaceproperties*1 Symbols denote as follows; 〇: the release threshold achieved, ◎: the standard accuracy achieved, ☆: the target accuracy achieved.

6-4

1. Summary of the Validation of SGLI L2 Products

Schedule for the version-up of SGLI products
H28

H30

H29

H32

H31

H33

H34

10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3 4 - 5 - 6 7 - 8 - 9 10-11-12 1 - 2 - 3

Development of prelaunch algorithm
Review for theDevelopment
Completion

Sensor operation
Cal.※

Review for the Ver.1 data
release (minimum success)

GCOM-C launch

Initialcheck-out

Evaluation of the sensor
performance

Review for the Ver.2
data release

Ver.1

First-Light

Postnormal
operation

Improvement and validation of algorithms

Initial Cal/Val

Review for the Ver.3
data release

Ver.2

Initial Cal.

Ver.3 Final review for the full
& extra success

Normal Operation

Cal. For the Ver.1

Cal. For the Ver.2

Post-normal
operation

Cal. For the Ver.3

Cal. Coef.
Determination
Vi-calobs. data

Ground system
Algo. Development& Improvement

Val.
In-situ obs.

Proc.test

Coef.
Algo. Improvements for Ver.1 fixing
Evaluation of
the accuracy

Ver. processing

Ver.1 processing
Proc.test

Re-processing of thepast data

Ver.3 processing
Proc.test

Algo. Improvements for Ver.2

Re-processingof the past
Algo.
Improvements for Ver.3
data

Val. For the Ver.2

Val. For the Ver.3

Re-processing of
the past data

Tuningcoef.

Val. For the Ver.1

Val. For the final review

地上データ

Field campaigns for the
Ver.1 data release

Field campaigns for the Ver.2-3 data release

Field campaigns forthe final review

6-5

2. Validation Results of Land Products
2.1 Evaluation Summary
Product

ReleasethresholdStandard
accuracy

Targetaccuracy

Status*1

Evaluation Methods◎

Evaluation of geolocation accuracies with GCPs prepared using
AVNIR-2 data.

○

Comparison with in-situ observed reflectance.

Grass:10%(scene),forest:10%(scene)○Comparison with in-situ observation and other satellite data.

Grass:10%,
forest:20%○

Comparison with in-situ observation (incl. the data from theliteratures).

○

Comparison with other satellite data.

○

Comparison with in-situ observations.

Precise<1 pixel<0.5 pixel<0.25 pixel
geometriccorrection
0.05
Atmospheric
0.3(<=443nm),
0.1(<=443nm),(<=443nm),
corrected
0.2 (>443nm) 0.05 (>443nm) 0.025
reflectance (incl. (scene)(scene)(>443nm)(scene)cloud detection)
Grass:25%(scene),Vegetation index forest:20%(scene)Grass:20%(scene),forest:15%(scene)Above-ground Grass:50%, Grass:30%,
forest: 100% forest:50%
biomass
Grass &
Vegetation
Grass & forest:
forest:20%
roughness index 40% (scene) (scene)
Shadow index

Grass &
Grass & forest:
forest:20%
30% (scene)(scene)Grass &
forest:10%(scene)Grass &
forest:10%(scene)fAPAR

Grass:50%,
forest: 50%

Grass:30%,
forest:20%

Grass:20%,
forest:10%○

Comparison with in-situ observation and other satellite data.

Leaf area index

Grass:50%,
forest: 50%

Grass:30%,
forest:30%

Grass:20%,
forest:20%○

Comparison with in-situ observation and other satellite data.

Surfacetemperature<3.0 K (scene) <2.5 K (scene) <1.5 K (scene)○

Comparison with in-situ observation and other satellite data.

*1 Symbols denote as follows; 〇: the release threshold achieved, ◎: the standard accuracy achieved, ☆: the target accuracy achieved.

別1 - 6

2. Validation Results of Land Products

2.2 (a) Precise geometrically corrected Top-of-Atmosphere (TOA) radiance（LTOA）

Validation Method:- The geometric accuracies were evaluated by automatic matching of SGLI VN11 for VNR and SW3 for
IRS at 250 m resolution with AVNIR-2 ortho-corrected mosaic data around Japan islands.
- The accuracies of POL bands were evaluated as registration errors relative to the VNR band thatwere resampled to 1 km resolution by averaging.
- Evaluation method is quadratic curve fitting of cross-correlation coefficients (considering pixel
locking correction)
Validation data and condition, period etc.
- Reference data: ortho-corrected mosaic of AVNIR-2 with less cloud covers as shown below*1
GC1SG1_20180625D01D_T0529_L2SG_LTOAQ_0006.h5- Dependence of geometric errors on altitude was evaluated for confirming the accuracies of theortho-corrected images*1) Overall geometric accuracies of LTOA depend also on those of L1B. Regarding the geometric accuracies of L1B, please refer to the “geometriccorrection” on the SGLI calibration pages.
Target Image example: GC1SG1_20180625D01D_T0529_L2SG_LTOAQ_0104.h5

-1.0

+/-0
error [pixel]+1.0

Distribution of geolocation error between
SGLI/Lt_VN11 and AVNIR-2/Band4
Horizontal (X)Vertical (Y)別1 - 7

2. Validation Results of Land Products

2.2 (a) Precise geometrically corrected Top-of-Atmosphere (TOA) radiance（LTOA）
Validation Results: Histograms (upper), altitude dependences (middle), statistics (lower) of estimated geometric errors

x
y

ave
-0.05
0.04

std
0.36
0.28

rms
0.36
0.28

VNR 183844 samples

x
y

ave
0.07
-0.06

std
0.46
0.32

rms
0.46
0.32

IRS 263228 samples

x
y

ave
-0.19
0.03

std
0.29
0.28

rms
0.34
0.28

POL (P1) 48525 samples

x
y

ave
-0.02
-0.04

std
0.26
0.19

rms
0.26
0.20

POL (P2) 41421 samples

Note: There is no systematic error depending on altitude, indicating that the ortho-correction works well.

Estimated errors

Release threshold

Standard accuracy

Target accuracy< 0.36 (VNR)< 0.46 (IRS)< 0.34 (POL)< 1.0 pixel< 0.5 pixel<0.25pixel

Release threshold & Standard accuracy are achieved

別1 - 8

2. Validation Results of Land Products

2.2 (b) Atmospherically corrected reflectance (RSRF)
Validation Method:--

Accuracy targets were defined as RMSE of the reflectances acquired at the ground surface with moderate
reflectance of around 0.2 at solar zenith angles SZA less than 30 degrees. In addition, the release threshold isdefined as the value acquired at the condition of aerosol optical depth AOT (at the wavelength of 500 nm) lessthan 0.25.
In-situ measured reflectances simultaneously acquired with the SGLI observations were used for evaluating
RMSE. (Relative errors for the reflectance of 0.2 were also evaluated for comparison).

Validation data and condition etc.:-

In-situ data measured within the time window of 1-1.5 hours at the sites shown in the figure below (for theperiod during Jan. 24 to Sep. 28, 2018)
All the SGLI channels except for VN07 and VN10 (saturated at land areas) and SW02 (water vapor absorption
channel) were evaluated.
The data of pixels at AOT>0.8 and/or with cloudy or cloud shadow flags were eliminated.
(There is no change at conditions of τa ≤0.25 and/or SZA ≤ 30deg. See the table shown on the next page）
AsiaFlux/PEN sites
PI’s sites

PI’s site

CEOS/RadCALNET

別1 - 9

2. Validation Results of Land Products

2.2 (b) Atmospherically corrected reflectance (RSRF)
Validation Results:
RMS differences due to QC types

0.015
36%

0.013
26%

0.014
23%

0.017
23%

0.021
20%

0.027
27%

0.026
19%

0.076
27%

0.062
20%

0.032
9%

0.036
9%

0.034
11%

0.036
31%

0.083
27%

band left fig. sza<30 aot<0 Both.25
N= 52-116 21-65 44-92 16-43
VN01 0.015 0.016 0.014 0.014
VN02 0.013 0.013 0.013 0.011
VN03 0.014 0.014 0.014 0.012
VN04 0.017 0.014 0.018 0.013
VN05 0.021 0.019 0.021 0.018
VN06 0.027 0.031 0.029 0.034
VN08 0.026 0.019 0.027 0.017
VN09 0.076 0.085 0.078 0.086
VN11 0.062 0.065 0.056 0.060
SW01 0.032 0.031 0.030 0.029
SW03 0.036 0.040 0.033 0.036
SW04 0.034 0.038 0.032 0.034
PI01
0.036 0.026 0.040 0.026
PI02
0.083 0.068 0.087 0.067

Evaluated with insitu measured flux
reflectances because
in-situ BRDF
observations are
difficult on the
ground within 1 km x
1km field of view.

Estimated errors

Release threshold

Standard accuracy

Target accuracy

0.019(<=443nm)
0.084 (>443nm)

0.3 (<=443nm) →150%
0.2 (>443nm) →100%

0.1 (<=443nm) →50%
0.05 (>443nm) →25%

0.05 (<=443nm) →25%
0.025 (>443nm) →13%

Release threshold is achieved

Relative errors estimatedfor the reflectance of 0.2

別1 -2.2 (b) Atmospherically corrected reflectance (RSRF)
Comparison with BRDF models of POLDER

RMS=
0.018

0.028

0.055





0.021

0.059

0.074

0.022

0.026

0.054

0.055

Maignan, F., et al.,Polarized reflectances ofnatural surfaces: Spaceborne
measurements and analyticalmodeling, Remote Sensing
of Environment (2009)

BRDF models of POLDER (observation years are different)
were used for simulating SGLI slant observations

BRDF models of POLDER are derived for land cover classes with relatively homogeneous surface.
The differences in center wavelengths of SGLI and POLDER were corrected by interpolation.
SGLI-derived reflectances are consistent well with those of POLDER except at bare land.

別1 - 11

2.2 (b) Atmospherically corrected reflectance (RSRF)
Supplemental evaluations for slant observations
0.024

0.028

0.026

0.029

0.036

0.054

0.046
0.091

0.049






0.051
0.089

0.055
BRDF models of MODIS (observation years are the same)
were used for simulating SGLI slant observations

Comparison with MODIS-derived global BRDF products.
The differences in center wavelengths of SGLI and MODIS were corrected by interpolation.
SGLI-derived reflectances are consistent well with that of MODIS within the same orders of RMS for in-situ observation.
Peak and frequency were consistent well with those of MODIS with relatively large variances of slant observation bands (*possibly due tothe difference in the direction of slant observation path. That is, the line of sight of SGLI is along track whereas that of MODIS is cross-track.）

別1 - 12

2. Validation Results of Land Products
2.2 (c) Vegetation indices (VGI: NDVI, EVI)
Validation Method:--

Comparisons of SGLI-derived VGIs with those derived from in-situ observed spectralreflectances*1 were made for forest and grass areas.

*1： Comparisons were made only for the sites with a homogeneous land cover class (LCC) within one pixel (250mx250m) of SGLI after
checking the homogeneity of LCC with high resolution satellite imagery

As a supplemental evaluation, comparison with other satellite products (MODIS Terra 16-dayscomposites [MOD13Q1]） was also made.

Validation data and condition etc.:-

Sky-camera data were used to eliminate cloud contaminated SGLI data.
For the in-situ sites with less observation data within the validation periods (Baganuul,
BayanUnjuul, Watarase, Teshio, Lambir) 10-day composite of SGLI data was compared with insitu data assuming that there is no change in VGIs during the composite period.
Because there are few in-situ data for grass land, the data at Mase (LCC: Paddy) acquired during
July 1st to August 30th were used for the ground truth of grass land.
Comparisons with other satellite products were made for a date within the composite period ofeach products.

Validation period:-

August 22nd to October 30th 2018 for all the sites.
April 21st to July 31st 2018 for Takayama (TKY), Fuhihokuroku (FHK) Watarase (WTR), Mase (MSE).
The in-situ data during the period with solar zenith angle larger than 70 degree for Poker Flat
Research Range (PFRR) were eliminated.
The data on August 29, 30, and 31 were used for the comparison with MODIS products.
別1 - 13

2. Validation Results of Land Products
2.2 (c) Vegetation indices (VGI: NDVI)

Location of in-situ sites

Validation Results (vs. in-situ observation):

PFRR
BayanUnjuul

All cases

Only for clear weather cases

BaganuulLambirTSE

Forest: 8.45%

Forest: 11.45%, Grass: 10.62%: Forest (num. of plots=17)
× : Grass (num. of plots=0)

TKY
MSE, WTR: Forest (num. of plots=80)
× : Grass (num. of plots=27)

FHK

Estimated errors

Release threshold

Standard accuracy

Target accuracy

8 (11*1) %11*1 %

20% (Forest) scene,
25% (Grass) scene

15% (Forest) scene,
20% (Grass) scene

10% (Forest) scene,
10% (Grass) scene*1 Evaluated errors using all the data including potentially cloud contaminated ones

Release threshold & Standard accuracy are achieved(Remarks: The standard accuracy are achieved even using possibly cloud contaminated data.
Currently there are few in-situ data for grass land. )6 - 14

2. Validation Results of Land Products
2.2 (c) Vegetation indices (VGI: NDVI)Validation Results (vs. other satellite product of NDVI):

ForestMOD13Q1

Grass
T2A（ndvi_MVC）[2018/8/29-9/13]

MOD13Q1 [2018/8/29-9/13]

num. of plots=9997

num. of plots=10225

MOD13Q1: Aug.29-Sep.12 [16-day composites] vs. SGLI: Aug. 29, 30,31
Forest: GlobCover’s forest class
Copernicus/GIOGL1_NDVI300_V1.0.1 [9/1-9/10]
Grass: GlobCover’s grass, sparse vegetation, farm classes
NDVI

0

1 others

Estimated errors

Release threshold

Standard accuracy

Target accuracy

19 %
24 %

20% (Forest) scene,
25% (Grass) scene

15% (Forest) scene,
20% (Grass) scene

10% (Forest) scene,
10% (Grass) scene

Release threshold is achieved (vs. other satellite products)
6 - 15

2. Validation Results of Land Products
2.2 (c) Vegetation indices (VGI: EVI)

Location of in-situ sites

Validation Results (vs. in-situ observation):

PFRR
BayanUnjuul

Only for clear weather cases

All cases

BaganuulLambir

TSE

TKY
森林: 19.34%: 森林(num. of plots=17)
× : 草原(num. of plots=0)

MSE, WTR

森林: 26.46%, 草原: 23.96%: 森林(num. of plots=80)
× : 草原(num. of plots=27)

FHK

Estimated errors

Release threshold

Standard accuracy

Target accuracy

19(26*1) %24*1 %

20% (Forest) scene,
25% (Grass) scene

15% (Forest) scene,
20% (Grass) scene

10% (Forest) scene,
10% (Grass) scene*1 Evaluated errors using all the data including potentially cloud contaminated ones

Release threshold & Standard accuracy are achieved(Remarks: The standard accuracy are achieved even using possibly cloud contaminated data.
Currently there are few in-situ data for grass land. )6 - 16

2. Validation Results of Land Products
2.2 (c) Vegetation indices (VGI: EVI)

Validation Results*1 (vs. other satellite product of EVI):

ForestMean：0.37
RMSE: 0.10
num. of plots=9994

MOD13Q1

Grass
Mean：0.25
RMSE: 0.08
num. of plots=10222

T2A（ndvi_MVC）[2018/8/29-9/13]

MOD13Q1: Aug.29-Sep.12 [16-day composites] vs. SGLI: Aug. 29, 30,31
Forest: GlobCover’s forest class
EVI
Grass: GlobCover’s grass, sparse vegetation, farm classes

MOD13Q1 [2018/8/29-9/13]

0

1 others*1 These are supplemental results because EVI depends on satellite zenith angle and weather condition etc.

6 - 17

2. Validation Results of Land Products
2.2 (d) Above-ground biomass (AGB)
Validation Method:-

Comparisons of SGLI-derived AGBs with those derived from in-situ observations were made for forest andgrass areas.
As supplemental data for the in-situ reference, AGB obtained from FOS data (http://forest-observationsystem.net/) were used.
As a supplemental evaluation, comparison with other satellite products (Global Forest Biomass Map by WUR,
GlobalBiomassCarbon2000, GlobBiomass) was also made.

Validation data and condition etc.:-

One-month averages of SGLI AGB data were compared with in-situ data assuming that there is no change in
AGBs during one-month.
The pixels with bit-flags of low quality and probably cloudy were eliminated.
Before the comparison with SGLI-derived AGBs, the quality of AGB data from FOS were checked and filtered inorder to ensure that the value of AGB does not change even in the SGLI’s spatial resolution.
Comparison with other satellite products was made based on image appearance.

Validation period:-

August 23nd to September 25th 2018.

Location of in-situ sites
Spasskaya Pad
URY
PFRR
MGL(２サイト)
LambirWTR
ボリビア４サイト

FHK

FOSサイト

別1 - 18

2. Validation Results of Land Products
2.2 (d) Above-ground biomass (AGB)

Comparison with other satellite products

Validation Results:

SGLI [2018/9/1-9/12]
Grass

Forest: 62.20%(excl. .FOS), 47.82% (all)Grass: 42.59%: In-situ data
× : FOS data
Forest (num. of plots=23)
Grass (num. of plots=2)

Global Forest Biomass Map by WUR

GlobalBiomassCarbon2000
AGB [t/ha] 0

400 others

Estimated errors

Release threshold

Standard accuracy

Target accuracy

48 (62*1)%
43 %100% (Forest),
50% (Grass)

50% (Forest),
30% (Grass)

20% (Forest),
10% (Grass)*1 Results excluding FOS data

Release threshold is achieved

別1 - 19

2. Validation Results of Land Products
2.2 (d) Above-ground biomass (AGB)
Validation Results (cont.):

Comparison with other satellite-derived AGB products
A）

C）

B）

A）

B）

C）

D）

D）

AGB [t/ha] 0

400 others

A): SGLI （averaging [9/1-12]）
B): GlobalForestBiomassMap by WUR [GEOCARBON] (forest area only)C): New IPCC Tier1 Global Biomass Carbon Map For the Year 2000
D): DUE GlobBiomass by ESA (forest area only)

別1 - 20

2. Validation Results of Land Products
2.2 (e) Vegetation roughness index (VRI)
Validation Method:-

Comparisons of SGLI-derived VRIs with those derived from in-situ observed directionalreflectances were made for forest and grass areas.
Due to the bad weather in 2018, there are no in-situ data obtained under clear sky conditions.
That is why the comparisons were made with in-situ data obtained under cloudy conditions
and other satellite products.

Validation data and condition etc.:-

In-situ VRIs were first derived from reflecnances observed at the same geometric conditions as
SGLI observations using the same equation defined in the SGLI algorithm, and then comparedwith SGLI-derived VRIs.
The pixels with bit-flags of low quality were eliminated.
Due to the bad weather in 2018, evaluations were made using only the data shown below;- Simulated VRIs derived from MODIS/BRDF product (MCD43A1) acquired on October 28,
2018 using only the reflectances at the same geometric conditions as those of SGLI.
- In-situ derived VRIs calculated from BRDF data acquired at Watarase on May 21, 2018
under cloudy conditions (Only the SGLI and in-situ data with the same sensor zenith
angle of within ±5 degree were used for comparison).

Validation period:-

October 28th, November 3rd 2018 (vs. MCD43A).
May 1st to June 10th 2018 (vs. Watarase).
別1 - 21

2. Validation Results of Land Products
2.2 (e) Vegetation roughness index (VRI)
Validation Results:
Comparison with VRIs derived from MCD43A1

SGLI/VRI [2018/10/28]
Sites for comparison

Comparison with in-situ derived VRIs at Watarase under cloudy condition
Cloud contaminatedwithin 1 pixel (1km): Release thoreshold*By eliminating the pixels withcloud contamination and/or
pixel location errors, theestimated errors become: Sensor zenith<±5°23.26% (below the release× : Sensor zenith>±5°
threshold) .

Pixel location
error

Estimated errors
21*1, 23*2%

Release threshold
40% (Forest, Grass) Scene

MCD43A1/VRI*The error pixels of SGLI data were eliminated in the comparison.
VRI

Standard accuracy01

Target accuracy

20% (Forest, Grass) Scene 10% (Forest, Grass) Scene*1 Results compared with MCD43A1 data, *2 Result compared with in-situ data at Watarase under cloudy condition.

Release threshold is achieved

別1 - 22

2. Validation Results of Land Products
2.2 (f) Shadow index (SDI)
Validation Method:-

Comparisons of SGLI-derived SDIs with those derived from in-situ observation data were made for forestand grass areas.

Validation data and condition etc.:-

First, direct solar radiation for each SGLI scene was simulated using the Numerical digital surface model(DSM)*1 (spatial resolution of approx. 50 cm) provided from USGS 3 Dimensional Elevation Programme(3DEP). Second, the areas with zero solar radiation were identified as shadow and integrated to calculate
the areal fraction of shadow within one pixel of SGLI. Then, the areal fraction was used as ground truth.
*1: The DSM was derived from lidar observation data obtained from 2015 to 2018.

-

Only the pixels meeting the following conditions were used for validation;- NDVI > 0.65
- The pixel is not adjacent to cloudy pixels- Satellite zenith angle < 8 deg.
Data for validation

Validation period:- June to October 2018Name

SGLI TILE

Rows x cols

Date of SGLI obs. (# of scenes)

WalnutGulch, AZ

V05H0827 x 76

2018/08/25 – 09/24 (2)Mesa, COV05H0912 x 10

2018/06/18 – 09/24 (10)Olgalake, MI

V04H1118 x 32

2018/06/02 – 10/16 (18)Glacier NP., MT

V04H1035 x 60

2018/06/05 – 09/20 (17)Zion NP., UT

V05H0917 x 142018/06/02 – 09/27 (6)Zion NP. 2, UT

V05H0926 x 35

2018/06/02 – 09/27 (6)別1 - 23

2. Validation Results of Land Products
2.2 (f) Shadow index (SDI)

Direct solar radiation simulated from
DSM around Zion NP. site↓
The area with 0 W/m2 is identified as
shadow.

Validation Results:

Simulated direct solar radiation (W/m2)

Location of validation sites

RE:29.7％
DSM (left), NDVI (mid), and SDI (right) at Zion NP. site

Frequency distribution of the differences
between in-situ and SGLI data

Comparison results

Estimated errors

Release threshold

Standard accuracy

Target accuracy

30%

Grass, Forest: 30%

Grass, Forest: 20%

Grass, Forest: 10%

Release threshold is achieved
別1 - 24

2. Validation Results of Land Products
2.2 (g) Fraction of absorbed PAR (FAPAR)
Validation Method:-

Comparisons of SGLI-derived FAPARs with those derived from in-situ observation data (PAR meter andspectroradiometer) were made for forest and grass areas.

-

As supplemental data for the in-situ reference, FAPARs obtained from other satellite products(Copernicus/GIOGL1_FAPAR) and those obtained from the literatures published in the past were used.

Validation data and condition etc.:-

Ten-day averages of SGLI FAPAR data were compared with in-situ data assuming that there is no change in
FAPARs during ten days.
Comparisons of SGLI-FAPARs with other satellite products were made for same composite periods and withthe same definition of FAPAR that is the sum of the green FAPARs derived for the upper and lower layers.
Discrimination of forest and grass was done using an existed land cover map (GlobCover).
When comparing SGLI-FAPARS with in-situ derived ones which include the effects of stems and branches,
SGLI-FAPARs were converted to the ones with the same definition as the in-situ data and then compared.
When the temporal period of data acquisition were different between SGLI-FAPARs and in-situ derived ones
including those from the past literatures, the temporal consistency of FAPAR was confirmed using SGLI-NDVI
and other satellite products.

Validation period:-

Sep. 1st to 12th 2018 (vs. GIOGL1_FAPAR).

-

Sep. 1st to 10th*1 2018 (vs. in-situ data and literatures).

-

Apr. 21st to Jul. 31st 2018 (vs. in-situ data obtained at Fujihokuroku (FHK), Watarase (WTR), Takayama (TKY),
Fujiyoshida (FJY)).

*1 When there is no SGLI-derived FAPARs during the period, SGLI data of 10-day before and after the period were used for comparison. Temporal consistencyof FAPAR during the comparison period was confirmed using NDVI and other satellite-derived LAIs.

別1 - 25

2. Validation Results of Land Products
2.2 (g) Fraction of absorbed PAR (FAPAR)

Location of in-situ sites and literatures’ sites
PFRR

Validation Results:
Comparison results for green FAPAR of Upper + Lower layer
Grass

ForestMean：0.67
RMSE: 0.13

Comparison results for total
FAPAR (incl. the effects ofstems and branches)

Literature data

Mean：0.36
RMSE: 0.11

URY

TKY

WTR
FHK
FJY

Other satellite: 19.42%:GEOV (num. of plots=9196)

In-situ: 8.16%, Other sat.: 29.19%:GEOV (num. of plots=8883)
× :In-situ (num. of plots=1)

Forest: GlobCover’s forest class
Grass: GlobCover’s grass, sparse vegetation, crop land classes

Forest: 16.79%, Grass: 41.17%※PFRR: Total FAPAR at canopy level: In-situ data
× : Literatures
Forest (num. of plots=8)
Grass (num. of plots=4)

Estimated errors

Release threshold

Standard accuracy

19 (17*1)%
41% [in-situ + literature], 29%[other satellite]

50% (Forest),
50% (Grass)

20% (Forest),
30% (Grass)

Target accuracy
10% (Forest),
20% (Grass)*1 As total FAPAR

Release threshold is achieved
別1 - 26

2. Validation Results of Land Products
2.2 (g) Fraction of absorbed PAR (FAPAR)

FAPAR retrieved results (Comparison with other satellite products

FAPAR 01

othersT2A（fapar_MVC）[2018/11/1-11/8]

Copernicus/GIOGL1_LAI300_V1.0.1 [10/20]
MCD15A2H [2018/11/1-11/8]


MCD15A2H: Nov. 1st-8th [8-days composite with maximum FAPAR, 500m]
GIOGL1: Oct. 11th-20th 2018 [10-day composite with MV (vza/sza), 300m]

Spatial distribution of SGLI (T2A) is consistent with other satellite products.

別1 - 27

2. Validation Results of Land Products
2.2 (h) Leaf area index (LAI)
Validation Method:-

Comparisons of SGLI-derived LAIs with those derived from in-situ observation data (LAI-2000 andspectroradiometer) were made for forest and grass areas.
As supplemental data for the in-situ reference, LAIs obtained from other satellite products(Copernicus/GIOGL1_LAI) and those obtained from the literatures published in the past were used.

Validation data and condition etc.:--

Ten-day averages of SGLI LAI data were compared with in-situ data assuming that there is no change in LAIs during ten days.
Comparisons of SGLI-LAIs with in-situ data and other satellite products for the confirmation of the release thresholdachievement were made for the total LAI (the sum of LAIs of upper layer and that of lower layers), and also for the upper layer
LAI as a supplemental data at the present. In future, the achievement of the accuracies for the upper layer LAI is a goal of the
SGLI LAI products.
Discrimination of forest and grass was done using an existed land cover map (GlobCover).
When comparing SGLI-FAPARS with in-situ derived ones which include the effects of stems and branches, SGLI-FAPARs wereconverted to the ones with the same definition as the in-situ data and then compared.
When the temporal period of data acquisition were different between SGLI-FAPARs and in-situ derived ones including those fromthe past literatures, the temporal consistency of FAPAR was confirmed using SGLI-NDVI and other satellite products.
In-situ data and other satellite products were used for the total LAI evaluation, and in-situ data and literature data were used forthat of upper layer LAI.
The comparisons with other satellite products were done for the same composition period. When the temporal period of dataacquisition were different between SGLI-LAIs and in-situ derived ones including those from the past literatures, the temporalconsistency of LAI was confirmed using SGLI-NDVI and other satellite products.

Validation period:-

Sep. 1st to 12th 2018 (vs. GIOGL1_LAI).
Sep. 1st to 10th*1 2018 (vs. in-situ data and literatures).
Apr. 21st to Jul. 31st 2018 (vs. in-situ data obtained at Fujihokuroku (FHK), Watarase (WTR).

*1 When there is no SGLI-derived FAPARs during the period, SGLI data of 10-day before and after the period were used for comparison. Temporal consistencyof FAPAR during the comparison period was confirmed using NDVI and other satellite-derived LAIs.

別1 - 28

2. Validation Results of Land Products
2.2 (h) Leaf area index (LAI)
Validation Results:

Location of in-situ sites and literatures’ sites
PFRR
BaganuulComparison results for LAI of upper and lower layers
ForestGrass

Other sat.
Mean：3.06 m2/m2
RMSE: 1.52 m2/m2

Comparison results for
LAI f upper layer
Lambir (2 sites)

Other sat.
Mean：1.18 m2/m2
RMSE: 0.74 m2/m2

Literature data

URY

TKY

WTR
FHK

In-situ: 23.57%

In-situ: 15.53%:GEOV (num. of plots=9199)
× :In-situ (num. of plots=3):GEOV (num. of plots=8889)
× : In-situ (num. of plots=3)

Forest: GlobCover’s forest class
Grass: GlobCover’s grass, sparse vegetation, crop land classes

Estimated errors

Release threshold24%(69%*1) [in-situ]
39%[in-situ + literature]

50% (Forest),
50% (Grass)

Forest: 68.52%, Grass: 38.59%: In-situ
× : Literature
Forest (num. of plots=19)
Grass (num. of plots=8)

Standard accuracy

Target accuracy

30% (Forest),
30% (Grass)

20% (Forest),
20% (Grass)*1 As LAI of upper layer (canopy_LAI)

Release threshold is achieved

別1 - 29

2. Validation Results of Land Products
2.2 (h) Leaf area index (LAI)

LAI retrieved results (Comparison with other satellite products

LAI [m2/m2] 08othersT2A（fapar_MVC）[2018/11/1-11/8]

Copernicus/GIOGL1_LAI300_V1.0.1 [10/20]
MCD15A2H [2018/11/1-11/8]


MCD15A2H: Nov. 1st-8th [8-days composite with maximum FAPAR, 500m]
GIOGL1: Oct. 11th-20th 2018 [10-day composite with MV (vza/sza), 300m]

Spatial distribution of SGLI (T2A) is consistent with other satellite products.

別1 - 30

2. Validation Results of Land Products
2.2 (i) Land surface temperature (LST)
Validation Method:-

Comparisons of SGLI-derived LSTs with other satellite products (MOD11C1: Daily global product of MODIS)
were made using the equation (1) shown below.
Comparisons of SGLI-derived LSTs with those derived from in-situ observation data (brigntness temperature
estimated from the data of thermal radiometer at ground sites taking into account the emissivity of thesurface) were made using the equation (1).

Evaluation variable: 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝐾𝐾 =∑ 𝑆𝑆 𝑖𝑖 −𝑇𝑇 𝑖𝑖

Validation data and condition etc.:
-

-

𝑁𝑁

2

(1)

N: the number of observation data
S 𝑖𝑖 : SGLI-derived LST
T 𝑖𝑖 : LST derived from in-situ data

When comparing with MOD11C1 (pixel size is approx. 5 km), SGLI LST data of 250 m resolution were averaged to have the same
pixel size. Other conditions for the comparison are the following;
Observation time difference between SGLI and MODIS is less than 10 min.
Valid MODIS LST data: the lowest two bits of the MODIS QC flag are ‘00’.
Valid SGLI LST data (see QA flag and Mask_for_statistics of SGLI products)
In addition, SGLI-derived LST data were compared with in-situ data at Mase and Fujihokuroku (emissivity is assumed to be 0.98
for both sites) which were acquired within the time difference of 15 minitues from the SGLI observations. Other QC conditions
for in-situ data are the following;
Conversion residuals of SGLI are less than 1 Kelvin.
In-situ data are also qualified with the difference of upper andlower radiation fluxes and the variations of the low fluxes within
15 min.

Validation period:-

Aug. 22nd to Sep. 17th 2018 (vs. MOD11C1).
Mar. 14th to Sep. 28th 208 (vs. in-situ data).

別1 - 31

2. Validation Results of Land Products
2.2 (i) Land surface temperature (LST)

Validation Results:
Comparison results with MODIS products (Aug. 27, 2018)

Comparison results with in-situ data
Night

Day

Night

Day

Day + Night

Summary (Aug.22 to Sep.17 2018)
RMSE Ave. [K]
Day
Night
Day + Night

2.95
2.09
2.52

Estimated errors

Release threshold

Standard accuracy

Target accuracy

2.5 [K]@MODIS
2.7 [K]@in-situ< 3.0K< 2.5K< 1.5K

Release threshold is achieved

別1 - 32

3. Validation Results of Atmosphere Products
3.1 Evaluation Summary
Product

ReleasethresholdStandard
accuracy

Targetaccuracy

Status*1

10% (with
Cloud
whole-skyflag/Classification camera)

Incl. below cloud Incl. below cloudamountamount☆

Classified cloud
fraction

20% (on solar
irradiance)

15% (on solar
irradiance)

10% (on solar
irradiance)☆

Cloud top
temp/height

1K

3 K/2 km (toptemp/height)

1.5 K/1 km(temp/height)◎

Water cloudOT/effective
radiusIce cloud optical
thickness
Aerosol over theocean
Land aerosol bynear ultra violet
Aerosol by
Polarization

Evaluation Methods

Comparison with in-situ observation (sky-camera images)
for release threshold. Evaluations for standard and target
accuracies were performed as the Classified cloud fraction
products.
Comparison of SGLI-derived solar irradiance using cloud
products including cloud flag, cloud fraction etc. withground-measured solar irradiance.
Evaluation was made as vi-cal. of SGLI TIR bands for the
release threshold. In addition, comparison with othersatellite data for evaluating the achievement of thestandard accuracy.

10%/30%100% (as cloud(CloudOT/radius
50% / 20%liquid water))○

Comparison with other satellite (MODIS) data.

30%

70%

20%

○

Comparison with other satellite (MODIS) data.

0.1 (Monthly
τa_670,865)

0.1 (sceneτa_670,865)

0.05 (sceneτa_670,865)○

Comparison with other satellite (MODIS) data.

0.15 (Monthly
τa_380)0.15 (sceneτa_380)0.1 (sceneτa_380 )○Comparison with in-situ observation and other satellite(MODIS) data.

0.1 (sceneτa_670,865)◎

Comparison with in-situ observation and other satellite(MODIS) data.

0.15
0.15 (scene(Monthlyτa_670,
τa_670,865)
865)*1 Symbols denote as follows; 〇: the release threshold achieved, ◎: the standard accuracy achieved, ☆: the target accuracy achieved.

別1 - 33

3. Validation Results of Atmosphere Products
3.2 (a) Cloud flag/Classification (CLFG)
Validation Method:-

Release Threshold: Overall classification errors are evaluated comparing SGLI derived CLFG with thosederived from sky-camera images (by matching the field of view of SGLI and sky-camera).
Standard and target accuracies: Evaluated as the classified cloud fraction product.

Validation data and condition etc.:-

In-situ data: Binary classification of clear/cloudy was applied to sky-camera images using red, green,
and blue band digital data of the images. Sky-area within the field of view of 120 degree circle wasused for the analysis of cloud fraction.
SGLI data: SGLI-derived cloud flag was binary classified into clear and cloudy pixels using the data ofclear probability. The areas within the circle of 6 km from the in-situ camera sites are extracted fromSGLI CLFG images and analyzed to derive cloud fraction to be compared with in-situ data.

Validation period:-

Daytime: Apr. 1st to Jul. 7th 2018 for seven sites (Ny-Alesund, Sapporo, Tsukuba (JAXA), Tsukuba(Meteorological Research Institute), Kumamoto, Miyako-jima, Syowa Station at Antarctica).
Nighttime: Apr. 1st to Sep. 1st 2018 for three sites (Sapporo, Tsukuba (JAXA), and Kitami)

別1 - 34

3. Validation Results of Atmosphere Products
3.2 (a) Cloud flag/Classification (CLFG)
Validation Results:
DaytimeBinary classification of sky-camera images
DaytimeNighttime

Estimated errors

Release threshold

9.5 % (Day)
8.6 % (Night)

10 %Standard accuracy

Target accuracy

Evaluated as the classified cloud fraction
product.

Release threshold is achieved*（*Standard and Target accuracies are also achieved evaluated as the cloud fraction product）

別1 - 35

3. Validation Results of Atmosphere Products
3.2 (a) Cloud flag/Classification (CLFG)
Validation Results:

Supplemental slides

Results of individual sites
札幌

つくば

つくば

熊本

宮古島 昭和基地

Accuracies*1

NyAlesund(Sapporo)

TKSC

Tsukuba

Kumamoto

Miyako-jima

Syowa St.

All

N

53

25

58

25

53

47

33

294

UAcloud

100.0

95.0

91.7

100.0

100.0

82.9

86.7

92.9

PAcloud

92.1

90.5

100.0

100.0

82.9

93.5

96.3

92.2

OA

94.3

88.0

94.8

100.0

88.7

83.0

84.8

90.5

精度

全体

*1 In the case of cloud height at 6 km

UA: User’s Accuracy
PA: Producer’s Accuracy

別1 - 36

3. Validation Results of Atmosphere Products
3.2 (a) Cloud flag/Classification (CLFG)

Supplemental slides

Evaluation method: BI-SI method for cloud classificationa) Training datafor clear caseb) Training datafor cloudy case

d)

c)

Clear
CloudyFig X1 Example of analysis method of the Logistic regression approach. a) 2D-histogram for clear training data, b) 2Dhistogram for cloudy training data, c) example of the Logistic regression curve, and d) calculated clear probability on the BISI space.

a)

b)

c)

Fig X2 Examples of raw sky-camera images (upper images) and analyzed sky-camera images (lower images) for a)completely clear sky, b) completely cloudy, c) mixture of clear and cloudy.

別1 - 37

3. Validation Results of Atmosphere Products
3.2 (b) Classified cloud fraction (CLFR)

Validation Method:- Overall classification errors are evaluated by comparing SGLI-derived solar
radiation, which is monthly average for every 0.1 degree global grids, within-situ measured solar radiation (monthly average).
Validation data and condition etc.:- Solar radiation was derived using SGLI cloud related products, i.e., cloud flag
(CLFG), cloud properties (CLPR), atmospherically corrected land surface
reflectance (RSRF) , and ancillary data (meteorological data, elevation etc.).
- When comparing with in-situ data, only the in-situ data meeting thefollowing conditions were used in order to eliminate variable in-situ data
due to the horizontal heterogeneity of clouds;- The time difference between SGLI and in-situ observation was less than
5 minutes.
- Standard deviation of the in-situ data was less than 10 % of the in-situ
data average.
Validation period:- BSRN： Jul. 1st to Oct. 31st 2018 for 22 sites- SKYNET ： Jul. 1st to Oct. 31st 2018 for 3 domestic sites
別1 - 38

3. Validation Results of Atmosphere Products
3.2 (b) Classified cloud fraction (CLFR)
Validation Results:
Monthly average

Estimated errors

Release threshold

10 % (as solar radiation)

20% (as solar radiation)

Supplemental: Non-monthly average

SGLI: 0.1 deg. Grid average vs. In-situ instantaneous values

Standard accuracy

Target accuracy

15% (as solar radiation) 10% （as solar radiation)

Release threshold, Standard and Target accuracies are achieved*（*Standard and Target accuracies of cloud flag/classification product are also achieved）

別1 - 39

3. Validation Results of Atmosphere Products
3.2 (c) Cloud top temperature/Cloud top height (CLTT/CLTH)

Validation Method:- Release threshold: Evaluated as vicarious calibration of SGLI TIR bands.
- Standard and target accuracies: Relative errors are evaluated comparing
SGLI-derived cloud top temperature and height with those derived from insitu (ground and airborne) and/or other satellite products (Terra/MODIS:
MOD06 C6) for uniform liquid clouds with moderate optical thickness.
Validation data and condition etc.:- Only the data of water clouds with MOD06 cloud optical depth larger than
5 and cloud top temperature higher than 270 K were used for comparison.
Validation period:- MOD06：Aug. 22nd to Sep. 14th 2018

別1 - 40

3. Validation Results of Atmosphere Products

3.2 (c) Cloud top temperature /Cloud top height (CLTT/CLTH)
Validation Results:
Cloud top temperature(Land: daytime)

Cloud top height(Land: daytime)

Estimated errors (Ocean, Land)

Release threshold

Standard accuracy

Target accuracy

TIR band Vi. Cal.： 0.55 K
Cloud top temp.: 2.1 K, 2.6 K
Cloud top height: 1.2 km, 0.6 km

1K
-

3K
2 km

3K
2 km

Release threshold and Standard accuracy are achieved
別1 - 41

3. Validation Results of Atmosphere Products

3.2 (d) Water cloud optical thickness/Water cloud effective radius (CLOT_W/CLER_W)
Validation Method:- Release threshold: Relative errors are evaluated comparing SGLI derived
cloud optical thickness and effective radius with those from other satellite
products (MODIS: MOD06, C6) for clouds of mid- to low latitude regions(monthly average).
- Standard accuracy: Relative errors are evaluated comparing cloud liquidwater converted from SGLI derived cloud optical thickness and effective
radius products with those measured with microwave radiometer on the
ground.
Validation data and condition etc.:- Only the data of MOD06 data acquired within 30 minutes from SGLI
observations were used for comparison.
Validation period:- MOD06：Aug. 22nd to Sep. 14th 2018

別1 - 42

3. Validation Results of Atmosphere Products

3.2 (d) Water cloud optical thickness/Water cloud effective radius (CLOT_W/CLER_W)
Validation Results:
Water cloud optical thickness

Water cloud effective radius(Left: One-deg. grid average over ocean, Right: zonal average) (Left: One-deg. grid average over ocean, Right: zonal average)

Estimated errors (Ocean, Land)
Optical thickness: 8, 9 %Effective radius: 2, 5 %Cloud liquid water: -, -Release threshold

Standard accuracy

Target accuracy

10 %* (vs. MODIS)
30 %* (vs. MODIS)-

100 % (vs. in-situ obs.)

20% (vs. in-situ obs.)
50% (vs. in-situ obs.)*As monthly average of mid- to low latitude regions

Release threshold is achieved

別1 - 43

3. Validation Results of Atmosphere Products

3.2 (d) Water cloud optical thickness/Water cloud effective radius (CLOT_W/CLER_W)
Validation Results: Global distribution (Monthly average)
SGLI-CLPR

Supplemental slides

MOD06

Water
cloud
opticalthickness

Water
cloud
effective
radius

別1 - 44

3. Validation Results of Atmosphere Products
3.2 (e) Ice cloud optical thickness (CLOT_I)

Validation Method:- Release threshold: Relative errors are evaluated comparing SGLI derived
ice cloud optical thickness with those from other satellite products(MODIS: MOD06, C6) for clouds of mid- to low latitude regions (monthly
average).
- Standard accuracy: Relative errors are evaluated comparing SGLI derived
ice cloud optical thickness with those measured with sky-radiometers on
the ground.
Validation data and condition etc.:- Only the data of MOD06 data acquired within 30 minutes from SGLI
observations were used for comparison.
Validation period:- MOD06：Aug. 22nd to Sep. 14th 2018

別1 - 45

3. Validation Results of Atmosphere Products
3.2 (e) Ice cloud optical thickness (CLOT_I)
Validation Results:
Over Ocean

Over Land(Left: One-deg. grid average over ocean, Right: zonal average) (Left: One-deg. grid average over ocean, Right: zonal average)

Estimated errors(Ocean, Land)27, 29 %(vs. Other satellite)

Release threshold

Standard accuracy

Target accuracy

30 %(vs. Other satellite)

70 %(Sky-radiometer)

20 %(Sky-radiometer)

Release threshold is achieved
別1 - 46

3. Validation Results of Atmosphere Products
3.2 (e) Ice cloud optical thickness (CLOT_I)

Validation Results: Global distribution (Monthly average)
SGLI-CLPR

Supplemental slides

MOD06

Ice cloudopticalthickness

別1 - 47

3. Validation Results of Atmosphere Products

3.2 (f) Aerosol over ocean and land (Non-polarization/Polarization) (ARNP-O, ARNP-L, ANPL)
Validation Method:

Aerosol over ocean:-Release threshold: Overall RMS errors are evaluated comparing SGLI derived aerosol optical thickness (AOT)with those from other satellite sensors (monthly average).
- Standard accuracy: RMS errors are evaluated comparing SGLI derived AOT with those from other satellite
sensors and shipborne in-situ observations (AERONET/Maritime Aerosol Network) (scene by scene).
Aerosol over land:- Release threshold: RMS errors are evaluated comparing SGLI derived AOT with those from sky-radiometers at
ground observation network (Skynet and AERONET) and other satellite sensors. (monthly average).
- Standard accuracy: RMS errors are evaluated comparing SGLI derived AOT with those from other satellite
sensors and sky-radiometer at ground observation network (Skynet and AERONET) (scene by scene).

Validation data and condition etc.:•

vs. Sky-radiometer: the SGLI data within 10 km from the sky-radiometer sites were used andaveraged for comparison with the data of sky-radiometers.

Validation period:••

MODIS: Sep. 1st to 30th 2018
In-situ (sky-radiometer) data for land products:• Data sources: SKYNET (Chiba Univ., Toyama Univ.), Japan Meteorological Agency, AERONET• Period: Aug. 1st to Oct. 22nd 2018 (for non-polarization AOT products); Aug. 5th to Sep. 30th
208 (for Polarization AOT product).
別1 - 48

3. Validation Results of Atmosphere Products

3.2 (f) Aerosol over ocean and land (Non-polarization) (ARNP-O, ARNP-L)
Validation Results: Non-polarization AOTs over ocean and land
AOT over LandAOT over Ocean(Monthly average)
vs. MODIS (DT method)(Monthly average)
vs. MODIS (DT method)

AOT over Land
SGLI 0.1 deg. Grid average
vs. In-situ instantaneous values

Estimated errors

Release threshold

Standard accuracy

Target accuracy

0.09 （ocean-other sat., monthly ave.）0.10（monthly ave.）0.10 （scene）

0.05 （scene）

0.15 （land-other sat., monthly ave.）0.15（land-in-situ, scene）

0.15 （monthly ave.）0.15 （scene）

0.10 （scene）

Release threshold is achieved
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3. Validation Results of Atmosphere Products

3.2 (f) Aerosol over ocean and land (Non-polarization) (ARNP-O, ARNP-L)
Validation Results: Global distribution (Monthly average)＊Upper and lower images indicate different results of MODIS land algorithms
SGLI-ARNP
SGLI-ARNP
vs. MODIS
Ocean: DT
Land: DT

SGLI-ARNP
vs. MODIS
Ocean: DT
Land: DB

MODIS
vs. MODIS
DT-landvs. MODIS DB

Note:• DT：Dark Target algorithm• DB：Deep Blue algorithm

別1 - 50

3. Validation Results of Atmosphere Products
3.2 (f) Aerosol over land (Polarization) (ANPL)

Validation Results: Polarization AOTs over land
Vs. in-situ data (sky-radiometer)（Scene）

Vs. MODIS (monthly ave.)

Estimated errors

Release threshold

Standard accuracy

Target accuracy

0.14 (in-situ, scene)
0.15 (other sat., monthly ave.)0.15 （monthly ave.）0.15 （scene）

0.10 （scene）

Release threshold and Standard accuracy are achieved
別1 - 51

3. Validation Results of Atmosphere Products
3.2 (f) Aerosol over land (Polarization) (ANPL)

Validation Results: Global distribution (Monthly average)
SGLI vs. MODIS：AOT September 2018 (Descending)

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4. Validation Results of Ocean Products
4.1 Evaluation Summary
Product

ReleasethresholdStandard
accuracy

Target accuracy

Normalized water
50% (<600nm)
30% (<600nm)
2
leaving radiance (incl. 60% (443~565nm) 0.5W/m /str/um 0.25W/m2/str/um(>600nm)(>600nm)cloud detection)
Atmospheric
80%
50%
30%
correction(AOT@865nm)(AOT@865nm)(AOT@865nm)
parameters
Photosynthetically20% (10km/month) 15% (10km/month) 10% (10km/month)available radiation−35~+50%
Chlorophyll-a−60~+150%(offshore),−60~+150%(offshore)concentration−50~+100% (coast)
Total suspended−60~+150%
matter concentration (offshore)
Colored dissolved
organic matterSea surface
temperature

Status*1

Evaluation Methods◎

Comparison with in-situ observation data.

○

Comparison with in-situ observation data.

◎

Comparison with in-situ observation data.

○

Comparison with in-situ observation data.
Comparison with other satellite data
(GOCI).

−60~+150%−50~+100%○−60~+150%(offshore)−60~+150%−50~+100%○Comparison with in-situ observation andother satellite data (MODIS).

0.8 K (daytime)

0.8 K (day & night 0.6 K (day & night
time)
time)

☆

Comparison with in-situ observation data.

*1 Symbols denote as follows; 〇: the release threshold achieved, ◎: the standard accuracy achieved, ☆: the target accuracy achieved.

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4. Validation Results of Ocean Products
4.2 (a) Normalized water leaving radiance (NWLR)

Validation Method:-

RMS errors are evaluated comparing SGLI-derived NWLR with in-situ optical measurements conducted during
simultaneous buoy (MOBY*1), tower (AERONET-OC: sky- and ocean-radiometer installed on oceanic towers)
and the campaigns of ship observations and also comparing with other satellite products.

Validation data and condition etc.:-

In-situ data acquired within 3 hours from SGLI observations were used for comparison.
SGLI data were extracted from 5 by 5 pixels near the in-situ observation sites to have one averaged value andthen the data were selected by the following criteria (Bailey, 2006);
1. Aerosol optical thickness (AOT) ≤ 0.3, solar zenith angle ≤ 70 deg., the atmospheric correction scheme
passed successfully, the target pixel is neither near the cloudy pixel nor within the region of the sun-glint
correction, and the number of valid pixels ≥ 13.
2. A coefficient of variation (CV) is computed for pixels which passed the 1st test (1.) for bands between 412
and 565 nm and for the AOT 865 nm using the arithmetic mean and standard deviation of the 5x5 pixels,
and the median CV is less than 0.15.

Validation period:-

Yoko-Maru: Feb. 2nd to Oct. 16th 2018
Shinsei-Maru: May 21st to 28th 2018
Nagasaki-Maru: Jul. 19th to 27th 2018
MOBY*: Jan. 1st to Jul. 9th 2018
AERONET-OC: Jan. 1st to Oct. 26th 2018

*1: MOBY data are provided from NOAA through the agreement (a memorandum of understanding (MoU)) between JAXA and NOAA.
Reference: Bailey, S.W., and Werdell, P.J. (2006). A multi-sensor approach for the on-orbit validation of ocean color satellite data products. Rem.
Sens. Environ. 102, 12-23.

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4. Validation Results of Ocean Products
4.2 (a) Normalized water leaving radiance (NWLR)

Validation Results:

RE:

RE :

RE :

RE :

14%

41%

32%

19%

RE :

RE :

RE :

21%

25%

0.38 W/m2/str/um

Estimated errors

Release threshold

14 ~ 41% (<=600nm)
0.38W/m2/str/um(>600nm)

60% (443 ~ 565 nm)

Standard accuracy

Target accuracy

30% (<600 nm),
50% (<600 nm),2
0.5W/m /str/um (>600nm) 0.25W/m2/str/um (>600nm)

Release threshold and Standard accuracy are achieved
別1 - 55

4. Validation Results of Ocean Products
4.2 (b) Atmospheric correction parameters (ACP)

Validation Method:-

RMS errors are evaluated comparing SGLI-derived aerosol optical thickness (AOT) with in-situ measurementsof AOT at the wavelength of 865 nm conducted during simultaneous tower (AERONET-OC: sky- and oceanradiometer installed on oceanic towers).

Validation data and condition etc.:-

In-situ data acquired within 3 hours from SGLI observations were used for comparison.
SGLI data were extracted from 5 by 5 pixels near the in-situ observation sites to have one averaged value andthen the data were selected by the following criteria (Bailey, 2006);
1. Aerosol optical thickness (AOT) ≤ 0.4, solar zenith angle ≤ 70 deg., the atmospheric correction scheme
passed successfully, the target pixel is neither near the cloudy pixel nor within the region of the sun-glint
correction, and the number of valid pixels ≥ 13.
2. A coefficient of variation (CV) is computed for pixels which passed the 1st test (1.) for bands between 412
and 565 nm and for the AOT 865 nm using the arithmetic mean and standard deviation of the 5x5 pixels,
and the median CV is less than 0.15.

Validation period:-

AERONET-OC: Jan. 1st to Oct. 26th 2018

Reference: Bailey, S.W., and Werdell, P.J. (2006). A multi-sensor approach for the on-orbit validation of ocean color satellite data products. Rem. Sens.
Environ. 102, 12-23.

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4. Validation Results of Ocean Products
4.2 (b) Atmospheric correction parameters (ACP)

Validation Results:

精度: 67.9%

Estimated errors

Release threshold

Standard accuracy

Target accuracy

68%(AOT@865nm)

80% (AOT@865nm)

50% (AOT@865nm)

30% (AOT@865nm)

Release threshold is achieved

別1 - 57

4. Validation Results of Ocean Products
4.2 (c) Photosynthetically available radiation (PAR)

Validation Method:-

RMS errors are evaluated comparing SGLI-derived monthly averaged PAR with those derived
from mooring buoys such as TAO/TRITON, PIRATA, RAMA.

Validation data and condition etc.:-

In-situ data acquired within 3 hours from SGLI observations were converted to daily PARs andthen averaged to monthly PARs for comparison with SGLI- PARs.
Daily SGLI-PARs within 10 km box at the center of in-situ observation sites were extracted andthen averaged to monthly PARs.

Validation period:-

TAO/TRITON、PIRATA、 RAMA : Jan. 1st to Oct. 31th 2018

Reference: National Center for Atmospheric Research Staff (Eds). Last modified 01 Nov 2013. "The Climate Data Guide: Tropical Moored Buoy System: TAO,TRITON, PIRATA, RAMA (TOGA)." Retrieved from https://climatedataguide.ucar.edu/climate-data/tropical-moored-buoy-system-tao-triton-pirata-rama-toga.

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4. Validation Results of Ocean Products
4.2 (c) Photosynthetically available radiation (PAR)

Validation Results:

RE: 15.2%

Estimated errors

Release threshold

Standard accuracy

Target accuracy

15% (10km/monthly ave.)20% (10km/monthly ave.)

15% (10km/monthly ave.)

10% (10km/monthly ave.)

Release threshold and Standard accuracy are achieved
別1 - 59

4. Validation Results of Ocean Products
4.2 (d) Chlorophyll-a concentration (CHLA)

Validation Method:-

RMS errors are evaluated comparing SGLI derived CHLA with those derived from in-situ sampled sea water byfluorescence method or HPLC analysis and also with other satellite products.

Validation data and condition etc.:--

In-situ data acquired within 3 hours from SGLI observations were used for comparison.
SGLI data were extracted from 5 by 5 pixels near the in-situ observation sites to have one averaged value andthen the SGLI data were selected by the following criteria (Bailey, 2006);
1. Aerosol optical thickness (AOT) ≤ 0.3, solar zenith angle ≤ 70 deg., the atmospheric correction scheme
passed successfully, the target pixel is neither near the cloudy pixel nor within the region of the sun-glint
correction, and the number of valid pixels ≥ 13.
2. A coefficient of variation (CV) is computed for pixels which passed the 1st test (1.) for bands between 412
and 565 nm and for the AOT 865 nm using the arithmetic mean and standard deviation of the 5x5 pixels,
and the median CV is less than 0.15.
Comparisons between SGLI and other satellite CHLA products were conducted for monthly averaged global
data projected on grids with 1/24 deg. Interval.

Validation period:-

Yoko-Maru: Feb. 2nd to Oct. 16th 2018
Shinsei-Maru: May 21st to 28th 2018
Nagasaki-Maru: Jul. 19th to 27th 2018
Hokko-Maru: Jun. 1st to 8th 2018
Aqua/MODIS: Oct. 1st to 31st 2018

Reference: Bailey, S.W., and Werdell, P.J. (2006). A multi-sensor approach for the on-orbit validation of ocean color satellite data products. Rem. Sens.
Environ. 102, 12-23.

別1 - 60

4. Validation Results of Ocean Products
4.2 (d) Chlorophyll-a concentration (CHLA)

Validation Results:
VS. In-situ data (open sea)

VS. Aqua/MODIS (open sea)

RE:

RE:

-58.0%

147.3%

Monthly (Oct.) ave. Chl-a

Estimated errors

Release threshold

Standard accuracy

Target accuracy-58% (in-situ, open sea)
147% (Aqua/MODIS, open sea)

−60~+150% (open sea)

−60~+150%−35~+50% (open sea),−50~+100% (coastal)

Release threshold is achieved
別1 - 61

4. Validation Results of Ocean Products
4.2 (e) Total suspended matter concentration (TSM)

Validation Method:-

RMS errors are evaluated comparing SGLI derived TSM with those derived from in-situ sampled
sea water by filtration method (weighting the dried filters before and after the filtration toestimate the mass of suspended matter) and also with other satellite products.

Validation data and condition etc.:-

Comparisons only with other satellite products were conducted because there are no in-situ
data available at the moment of evaluation 1-year after the GCOM-C launch.
Korean’s geostationary satellite “GOCI”-derived TSM was used for the comparison with SGLI for
the TSM range of 0.1 to 65 g/m3 (*1). The comparison was made on the spatial grids of 1 km.

Validation period:-

GOCI: Oct. 31, 2018.

*1: The definition of GOCI’s TSM is different from that of SGLI. That is, GOCI’s TSM is the amount of floating inorganic matte in seawater, whereas
SGLI’s TSM is the sum of floating inorganic and organic matter in seawater. Thus, SGLI’s TSM is considered to be larger than that of GOCI.

別1 - 62

4. Validation Results of Ocean Products
4.2 (e) Total suspended matter concentration (TSM)

Validation Results:

Comparison with GOCI(> 1g/m3)

RE:

47 %

RE::

126 %

※The definition of GOCI’s TSM: ”The amount of floating inorganic matte in seawater”*1)*1) http://kosc.kiost.ac.kr/eng/p30/kosc_p33.html

Estimated errors

Release threshold

126% (vs. GOCI)−60~+150% (open sea)
-53% (vs. GOCI, > 1g/m3)

Standard accuracy

Target accuracy−60~+150%−50~+100%

Release threshold is achieved
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4. Validation Results of Ocean Products
4.2 (e) Total suspended matter concentration (TSM)

Validation Results (Cont.):--

SGLI-derived TSMs tend to be higher than those of GOCI for the TSM range higher than 1 g/m3
which is considered due to the difference of the TSM definition between SGLI and GOCI as
described before.
In addition, SGLI-derived TSMs become significantly higher than those of GOCI at the lower TSM
range less than 1 g/m3 which can be considered due to an overestimation of NWLR at 670 nm asshown in the figure below. The overestimation of TSM could be reduced after the improvementof the SGLI NWLR product by next update.
• NWLR(670) error of 0.4 W/m2/sr/μm is theestimated accuracy in this evaluation (within
the standard accuracy).
• nLw(670) error of 0.2 W/m2/sr/μm is theestimate using in-situ data from MOBY*1(within the target accuracy).
*1: MOBY data are provided from NOAA through the agreement (amemorandum of understanding (MoU)) between JAXA and NOAA.

The effects of NWLR (670) errors on TSM

6 - 64

4. Validation Results of Ocean Products
4.2 (f) Colored dissolved organic matter (CDOM)

Validation Method:-

RMS error is evaluated comparing SGLI derived CDOM with those derived from in-situ sampled sea water by
optical measurements and also with other satellite products.

Validation data and condition etc.:--

In-situ data acquired within 3 hours from SGLI observations were used for comparison.
SGLI data were extracted from 5 by 5 pixels near the in-situ observation sites to have one averaged value andthen the SGLI data were selected by the following criteria (Bailey, 2006);
1. Aerosol optical thickness (AOT) ≤ 0.3, solar zenith angle ≤ 70 deg., the atmospheric correction scheme
passed successfully, the target pixel is neither near the cloudy pixel nor within the region of the sun-glint
correction, and the number of valid pixels ≥ 13.
2. A coefficient of variation (CV) is computed for pixels which passed the 1st test (1.) for bands between 412
and 565 nm and for the AOT 865 nm using the arithmetic mean and standard deviation of the 5x5 pixels,
and the median CV is less than 0.15.
Comparisons between SGLI and other satellite CDOM products were conducted for monthly averaged global
data projected on grids with 1/24 deg. Interval.

Validation period:-

Yoko-Maru: Feb. 2nd to Oct. 16th 2018
Shinsei-Maru: May 21st to 28th 2018
Nagasaki-Maru: Jul. 19th to 27th 2018
Hokko-Maru: Jun. 1st to 8th 2018
Aqua/MODIS: Oct. 1st to 31st 2018

Reference: Bailey, S.W., and Werdell, P.J. (2006). A multi-sensor approach for the on-orbit validation of ocean color satellite data products. Rem. Sens.
Environ. 102, 12-23.

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4. Validation Results of Ocean Products
4.2 (f) Colored dissolved organic matter (CDOM)

Validation Results:
VS. In-situ data (open sea)

VS. Aqua/MODIS (open sea)

RE:
49%

RE:
122.8%

Monthly (Oct.) ave. CDOM

Estimated errors

Release threshold

Standard accuracy

Target accuracy-51% (in-situ, open sea)
123% (Aqua/MODIS, open sea)

−60~+150% (open sea)

−60~+150%−50~+100%

Release threshold is achieved
別1 - 66

4. Validation Results of Ocean Products
4.2 (g) Sea surface temperature (SST)

Validation Method:-

Overall RMS errors are evaluated comparing SGLI derived SST with those derived from buoymeasurements obtained from iQuam.

Validation data and condition etc.:--

In-situ buoy data acquired within the spatial difference of 10 km and time difference of 2 hours from SGLI
observations were used for comparison. In addition, before the comparison, the SGLI SSTs that meet thefollowing conditions were selected;
1. Standard deviation of SGLI SST within 5 x 5 pixels around the buoy location is less than 1.0 ℃.
2. The difference between maximum and minimum of SGLI SSTs within the 5x5 pixel box is less than 3.0 ℃.
3. The difference between SGLI SST and iQuam SST is less than 5 ℃.
SGLI SSTs at the spatial resolution of 1 km with the quality flag of “good” or “acceptable” were used forcomparison (same as the input for Level-3 processing).
The buoy data with the quality assurance flag of iquam_flag=0 and quality_level=5 were obtained from NOAA
iQuam site and used for the comparison.

Location of buoy data

Validation period:-

Oct. 1st to 31st 2018.

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4. Validation Results of Ocean Products
4.2 (g) Sea surface temperature (SST)

Validation Results:
DaytimeJapan

Nighttime

RMSE :

RMSE:

0.50℃

0.41℃

2018.10.02 01:01(UTC) SST
Spatial distribution of SGLI SST (thewestern North Pacific Ocean off Japan)

Estimated errors

Release threshold

Standard accuracy

Target accuracy

0.4℃ (day)0.5℃ (night)

0.8℃ (day)

0.8℃

0.6℃

Release threshold, Standard and Target accuracies are achieved
別1 - 68

5. Validation Results of Cryosphere Products
5.1 Evaluation Summary
Product

Snow and Ice
covered area (incl.
cloud detection)
Okhotsk sea-ice
distribution
Snow and ice
surfaceTemperature

Snow grain size ofshallow layer

ReleasethresholdStandard
accuracy

Targetaccuracy

10%

7%

10%

Status*1

Evaluation Methods

5%○Comparison with other satellite (MODIS)
data.

5%

3%

○

5K

2K

1K

◎

100%

50%

30%

○*

Comparison with other satellite (MODIS)
data.
Comparison with in-situ observation (AWS
thermal radiometer data) other satellite(MODIS) data.
Comparison with climatology (relation
between snow surface temperature andsnow grain size) for the release threshold.
In addition, comparison with in-situ
observation data at Greenland for the
standard accuracy. *After the quality
control of SGLI data, the snow grain size
product has a potential to achieve thestandard accuracy.

*1 Symbols denote as follows; 〇: the release threshold achieved, ◎: the standard accuracy achieved, ☆: the target accuracy achieved.

別1 - 69

5. Validation Results of Cryosphere Products
5.2 (a) Snow and Ice covered area (SICE)

Validation Method:-

Overall classification errors are evaluated comparing SGLI derived SICE with other satellite products. Relative
errors are calculated by using the following equation.
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 % =1∑ 𝑆𝑆 𝑖𝑖 −𝑇𝑇 𝑖𝑖
𝑁𝑁
1∑ 𝑇𝑇 𝑖𝑖
𝑁𝑁

2

∗ 100

(N: the number of data, S: SGLI obs., T: other satellite data.)

Validation data and condition etc.:-

Snow covered area: MOD10C2 Snow Cover Extent ProductSea-ice covered area: MOD29E1D Sea Ice ProductSun-lit regions in the Northern Hemisphere are the target area for the evaluation of SICE accuracy. Eight-day
composite data of SICE were generated for SGLI and MODIS and then used for the comparison.

Validation period:-

Mar. 14th to Aug. 20th 2018

別1 - 70

5. Validation Results of Cryosphere Products
5.2 (a) Snow and Ice covered area (SICE)*Snow Fraction > 10%

Validation Results: White: snow cover, Blue: sea-ice cover

SGLI

Relative Error = 9.39%
Bias = 744,064 km2

Jun.26th to Jul.3rd 2018

MODIS

Snow and sea-ice cover derived from SGLI and MODIS data

Scatter plot between MODIS and SGLI SICE

Estimated errors

Release threshold

Standard accuracy

Target accuracy

9.4%

10%

7%

5%

Release threshold is achieved

別1 - 71

5. Validation Results of Cryosphere Products
5.2 (b) Okhotsk sea-ice distribution (OKID)

Validation Method:-

Overall classification errors are evaluated comparing SGLI derived sea-ice distribution with other satellite
products. Relative errors are calculated by using the following equation.
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 % =1∑ 𝑆𝑆 𝑖𝑖 −𝑇𝑇 𝑖𝑖
𝑁𝑁
1∑ 𝑇𝑇 𝑖𝑖
𝑁𝑁

2

∗ 100

(N: the number of data, S: SGLI obs., T: other satellite data.)

Validation data and condition etc.:-

Sea-ice covered area: MOD29E1D Sea Ice ProductSun-lit regions within the Okhotsk sea (43-63 deg.N, 135-163 deg.E) are the target area for the evaluation of
OKID accuracy. Eight-day composite data of OKID were generated for SGLI and MODIS and then used for thecomparison.

Validation period:-

Mar. 14th to Aug. 20th 2018

MOD29E1D 1day composited
EASE grid data
Re-projection to Sinusoidal tile

8 days8day composite
Sea Ice Extent
別1 - 72

5. Validation Results of Cryosphere Products
5.2 (b) Okhotsk sea-ice distribution (OKID)*Snow Fraction > 10%

Validation Results:

Relative Error = 9.05%
Bias = 91,081km2

SGLI Reflectance

SGLI sea-ice (OKID)

Scatter plot between MODIS and SGLI SICE

Estimated errors

Release threshold

Standard accuracy

Target accuracy

9.1%

10%

5%

3%

Release threshold is achieved

別1 - 73

5. Validation Results of Cryosphere Products
5.2 (c) Snow and ice surface Temperature (SIST)

Validation Method:-

Release threshold: Overall RMS errors are evaluated comparing SGLI derived SIST with thosefrom other satellite products.
Standard accuracy: RMS errors are evaluated comparing SGLI SIST with those from in-situ
thermal radiometer measurements on the ground.

Validation data and condition etc.:-

Snow and ice surface temperature: MOD11A1 Land Surface Temperature Product (1 km tile)
Other satellite: Sun-lit regions in the Northern Hemisphere are the target area for theevaluation of SIST accuracy. Daily tile data of SGLI SIST were compared with that of MOD11A1
product.
In-situ data: In-situ measured SISTs calculated from thermal radiometer data installed at the
PROMICE Automatic Weather Stations (AWS) were used for the comparison with SGLI SIST. The
in-situ data acquired at within the time difference of 30 minutes from SGLI observations areused and compared with SGLI SISTs at the nearest neighbor of in-situ sites.

Validation period:-

Jul. 1st to Sep. 30th 2018

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5. Validation Results of Cryosphere Products
5.2 (c) Snow and ice surface Temperature (SIST)

Validation Results:

MOD11A1
RMSE = 2.6K
Bias = 0.25K[K]
C2AB_SIST

For the release thresholdevaluation (vs. MODIS product)

For the standard accuracy evaluation(vs. AWS measurements)

Estimated errors

Release threshold

Standard accuracy

Target accuracy

Other sat.: 2.6K
In-situ: 1.5K

5K （vs. other sat.）

2K （vs. in-situ）

1K （vs. in-situ）

Release threshold and Standard accuracy are achieved
別1 - 75

5. Validation Results of Cryosphere Products
5.2 (d) Snow grain size of shallow layer (SGSL)

Validation Method:-

Release threshold: Overall errors are evaluated comparing SGLI derived SGSL with climatological relationshipbetween snow grain size and snow surface temperature derived from the past observations.
Standard accuracy: RMS errors are evaluated comparing SGLI SGSL with those from in-situ data obtained bysnow pit works on the ground. Relative errors are calculated by using the following equation.
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 % =1∑ 𝑆𝑆 𝑖𝑖 −𝑇𝑇 𝑖𝑖
𝑁𝑁
1∑ 𝑇𝑇 𝑖𝑖
𝑁𝑁

2

∗ 100

(N: the number of data, S: SGLI obs., T: other satellite data.)

Validation data and condition etc.:-

Climatology: Surface temperature dependence of snow grain size observed in the past study using GLI (Hori etal., 2006) was confirmed. For example, steep increase of snow grain size at the melting point of ice, andgradual increase of snow grain size with surface temperature at the lower temperature range below 0 ℃.
In-situ data: A sun-lit snow field (E-GRIP site) over the Greenland ice sheet is the target area for the evaluationof SGSL accuracy. In-situ data were obtained with instruments (IceCube/ HISSGraS) that measures specificsurface area (SSA) of snow particles. The in-situ derived SSAs acquired within the time difference of 10
minutes from SGLI observations were converted to optically equivalent sphere grain sizes and then comparedwith SGLI SGSL (250 m resolution) at the nearest neighbor of the in-situ site.

Validation period:-

Jul. 2nd to 16th 2018

Reference: Hori, M., Aoki, Te., Stamnes, K., Li, W. (2007). ADEOS-II/GLI snow/ice products - Part III: Retrieved results, Remote Sensing of Environment,
111, 291-336.

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5. Validation Results of Cryosphere Products
5.2 (d) Snow grain size of shallow layer (SGSL)

Field experiments at EGRIP, Greenland in 2018

Grain size (μm)

Grain size ( μm)

Validation Results:

GLI

Hori et al. (2006)

EGRIP
Cloud contaminations
were confirmed on
sky-camera images

SGLI
Surface temp.(K)

SGLI-derived snow grain size on Jul. 13th 2018

SGLI-derived SGSLs are consistent with
Climatological relationship between those obtained at the Greenland ice
snow surface temperature and snow sheet (EGRIP) in July 2018.
grain size

RMSE = 85.97%(33.4% if the cloud effects are eliminated.)

Estimated errors

Release threshold

Standard accuracy

Target accuracy

86% (33%*)

100%

50%

30%

Release threshold is achieved(*if the cloud effects are eliminated by quality assurance process in next updates, the standard accuracy can be achieved.)

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