APPENDIX 1
OVERVIEW OF THE GLOBAL CHANGEOBSERVATION MISSION (GCOM)

1-1

1.

Introduction

Comprehensive observation, understanding, assessment, and prediction of global climate change arecommon and important issues for all mankind. This is also identified as one of the important socioeconomic benefits by the 10-year implementation plan for Earth Observation that was adopted by the Third
Earth Observation Summit to achieve the Global Earth Observation System of Systems (GEOSS).
International efforts to comprehensively monitor the Earth by integrating various satellites, in-situ
measurements, and models are gaining importance. As a contribution to this activity, the Japan Aerospace
Exploration Agency (JAXA) plans to develop the Global Change Observation Mission (GCOM). GCOM
will take over the mission of the Advanced Earth Observing Satellite-II (ADEOS-II) and develop into longterm monitoring of the Earth.
As mentioned in the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC),
warming of the climate system is unequivocal as is now evident from observations of increases in global
average air and ocean temperatures and widespread melting of snow and ice. However, climate change
signals are generally small and modulated by natural variability, and are not necessarily uniform over the
Earth. Therefore, the observing system of the climate variability should be stable, and should cover a longterm over the entire Earth.
To satisfy these needs, GCOM consists of two medium-size, polar-orbiting satellite series, GCOM-W(Water) and GCOM-C (Climate). Two instruments were selected to cover a wide range of geophysicalparameters: the Advanced Microwave Scanning Radiometer 2 (AMSR2) on GCOM-W and the Secondgeneration Global Imager (SGLI) on GCOM-C. The AMSR2 instrument performs observations related to
the global water and energy cycle, while the SGLI conducts surface and atmospheric measurements related
to the carbon cycle and radiation budget. This chapter presents an overview of the mission objectives,
observing systems, and data products of GCOM.
2.

Mission Objectives

The major objectives of GCOM can be summarized as follows.
- Establish and demonstrate a global, long-term Earth-observing system for understanding climate
variability and the water-energy cycle.
- Enhance the capability of climate prediction and provide information to policy makers throughprocess studies and model improvements in concert with climate model research institutions.
- Construct a comprehensive data system integrating GCOM products, other satellite data, and in-situ
measurements.
- Contribute to operational users including weather forecasting, fishery, and maritime agencies by
providing near-real-time data.
- Investigate and develop advanced products valuable for understanding of climate change and water
cycle studies.
Detailed explanations of the objectives are as follows.
(1) Understanding global environment changes
A) Establish and demonstrate a global, long-term Earth-observing system that is able to observe
valuable geophysical parameters for understanding global climate variability and water cycle
mechanisms.
B) Contribute to improving climate prediction models by providing accurate values of model
parameters.
1-2C) Clarify sinks and sources of greenhouse gases.
D) Contribute to validating and improving climate prediction models by forming a collaborative
framework with climate model institutions and providing long-term geophysical datasets tothem.
E) Detect trends of global environment changes (e.g., global warming, vegetation changes,
desertification, variation of atmospheric constituents, wide area air pollution, and depletionof ozone layers) from long-term variability of geophysical parameters by extracting shortterm (three- to six-year) natural variability.
F) Advance process studies of Earth environmental changes using observation data.
G) Estimate radiative forcing, energy and carbon fluxes, and albedo by combining satellite
geophysical parameters, ground in-situ measurements, and models.
H) Advance the understanding of the Earth’s system through the activities above.
I) Contribute to an international environmental strategy utilizing the results above.
(2) Direct contribution to improving people’s lives
A) Improvement of weather forecast accuracy (particularly typhoon track prediction, localized
severe rain, etc.).
B) Improvement of forecast accuracy for unusual weather and climate.
C) Improvement of water-route and maritime information.
D) Provision of fishery information.
E) Efficient coastal monitoring.
F) Improved yield prediction of agricultural products.
G) Monitoring and forecasting air pollution including yellow dust.
H) Observation of volcanic smoke and prediction of the extent of the impact.
I) Detection of forest fires.
3.

Observing Systems

3.1. Overall concept
As mentioned in the previous section, the entire GCOM will consist of two satellite series spanning three
generations. However, a budget will be approved for each satellite. Currently, only the GCOM-W and
GCOM-C satellites have been launched as the first satellite in the GCOM series, and successor of GCOMW, AMSR3, will be installed on the Global Observing SATellite for Greenhouse gases and Water cycle(GOSAT-GW), a joint mission with greenhouse gases observation mission, to be launched in JFY 2024
(see APPENDIX 7).
Both GCOM-W and GCOM-C satellites are medium-size platforms that are smaller than the ADEOSII satellite. This is to reduce the risk associated with large platforms having valuable and multiple observing
instruments. Also, since the ADEOS-II problem was related to the solar paddle, a dual solar-paddle design
was adopted for both satellites. To assure data continuity and consistent calibration, original idea was that
follow-on satellites will be launched so as to overlap the preceding satellite by one year. The concept issummarized in Fig. 1.
1-year
GCOM-W
GCOM-W2

LaunchGCOM-W3
GCOM-C
multi-band optical imager

Launchmulti-band optical imager

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Figure 1: GCOM Concept

3.2. GCOM-W and AMSR2 instrument
Figure 2 presents an overview of the GCOM-W satellite; its major characteristics are listed in Table
1. GCOM-W carries AMSR2 as the sole onboard mission instrument. The satellite will orbit at analtitude of about 700km and will have an ascending node local time of 13:30, to maintain consistency
with Aqua/AMSR-E observations.

Figure 2: Overview of GCOM-W Satellite

Instrument
Orbit
Size

Table 1: Major Characteristics of GCOM-W Satellite
Advanced Microwave Scanning Radiometer 2 (AMSR2)
Sun-synchronous orbit
Altitude: 700km (over the equator)
5.1m (X) * 17.5m (Y) * 3.4m (Z) (on-orbit)

Mass

1991kgPower

More than 3880W (EOL)

LaunchMay 18, 2012 by H-IIA Rocket

Design Life

5 years

StatusPost-Mission Phase since Nov. 2018

Figure 1 presents an overview of the AMSR2 instrument in two different conditions. Also, basic
characteristics including center frequency, bandwidth, polarization, instantaneous field of view(FOV), and sampling interval are indicated in Table 2. The basic concept is almost identical to that of
AMSR-E: a conical scanning system with a large offset parabolic antenna, feed horn cluster to realize
multi-frequency observation, external calibration with two temperature standards, and total-power
radiometer systems. The 2.0m diameter antenna, which is larger than that of AMSR-E, provides better
spatial resolution at the same orbit altitude of around 700km. The antenna will be developed basedon the experience gained from the 2.0m diameter antenna for ADEOS-II AMSR except the
deployment mechanism. For the C-band receiver, we adopted additional 7.3GHz channels forpossible mitigation of radio-frequency interference. An incidence angle of 55 degrees (over theequator) was selected to maintain consistency with AMSR-E. The swath width of 1450km and theselected satellite orbit will provide almost complete coverage of the entire Earth’s surface within twodays independently for ascending and descending observations.
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Figure 3: Sensor Unit of AMSR2 Instrument in Deployed (left) and Stowed (right) Conditions.
Table 2: Major Characteristics of AMSR2 Instrument
Parameter
Center Frequency (GHz)

Performance and characteristics
6.925/7.3

10.65

18.7

23.8

36.5

89.0

350

100

200

400

1000

3000

Bandwidth (MHz)Polarization
NEDT (K) 1

Vertical and Horizontal polarization< 0.34/0.43< 0.70< 0.70

Dynamic range (K)< 0.60< 0.70< 1.20/1.40 2

2.7 to 340

Nominal incidence angle (deg.)

55.0/54.5 2

55.0

Beam width (deg.)

1.8

1.2

0.65

0.75

0.35

0.15

IFOV (km) Cross-track x along-track

35x62

24x42

14x22

15x26

7x12

3x5

Approximate sampling interval (km)10

5Swath width (km)> 1450Digital quantization (bits)

12

Scan rate (rpm)40

3.3. GCOM-C and SGLI instrument
Figure 4 gives an overview of the GCOM-C satellite; its major characteristics are listed in Table 3.
GCOM-C will carry SGLI as the sole mission onboard instrument. The satellite will orbit at an altitude ofabout 800km; the descending node local time will be 10:30, to maintain a wide observation swath andreduce cloud interference over land.

1-5Figure 4: Overview of GCOM-C Satellite

Instrument
Orbit
Size

Table 3: Major Characteristics of GCOM-C Satellite
Second-generation Global Imager (SGLI)
Sun-synchronous orbit
Altitude: 798km (over the equator)
4.6m (X) * 16.3m (Y) * 2.8m (Z) (on orbit)

Mass

2093kgPower

More than 4000W (EOL)

LaunchDec. 23 2017 by H-IIA Rocket

Design Life

5 years

StatusPhase-DThe SGLI instrument has two major new features: 250m spatial resolution for most of the visible
channels and polarization/multidirectional observation capabilities. The 250m resolution will provide
enhanced observation capability over land and coastal areas where the influences of human activity
are most obvious. The polarization and multidirectional observations will enable us to retrieve aerosol
information over land. Precise observation of global aerosol distribution is a key for improving
climate prediction models.
SGLI consists of two major components: the Infrared Scanner (IRS) and the Visible and Nearinfrared Radiometer (VNR). An overview of the SGLI instrument is shown in Fig. 5 for the entireradiometer layout, IRS, and VNR components. Also, requirements for sensor performance are listed
in Tables 4 and 5. VNR can be further divided into two components: VNR-Non Polarized (VNR-NP)
and VNR-Polarized (VNR-P). VNR-NP and VNR-P are the 11-channel multi-band radiometer andthe polarimeter with three polarization angles (0, 60, and 120 degrees). VNR-P has a tilting function
to meet the scatter angle requirement from aerosol observation. The IRS is an infrared radiometercovering wavelengths from 1μm to 12μm. It consists of short infrared (SWI; 1.05 to 2.21μm) andthermal infrared (TIR 10.8 and 12.0μm) sensors. It employs a scanning mirror system with a 45degree tilted flat mirror rotating continuously to realize an 80-degree observation swath andcalibration measurement in every scan.
Through intensive discussions and optimizing studies, the number of SGLI channels was decreased
from the 36 channels of GLI aboard ADEOS-II to 19 channels, while the number of SGLI standard
products will increase compared to those of GLI.
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Figure 5: Overview of SGLI Radiometer Layout (upper), IRS Instrument (lower-left), and VNR Radiometers(lower-right).

Table 4: SGLI Major Performance Requirements
Item
Spectral Bands

Scan Angle
Swath width
Instantaneous field of view
(IFOV) at nadir
Observing direction
Quantization
Absolute Calibration Accuracy
Lifetime

Requirement
VNR-NP : 11CH 380-865nm
VNR-P: 2CH 673.5, 868.5nm / 0, 60, 120deg Polarization
IRS SWI : 4CH 1.05-2.21µm
IRS TIR : 2CH 10.8, 12.0µm
VNR-NP: 70deg (Push broom scanning)
VNR-P: 55deg (Push broom scanning)
IRS SWI/TIR : 80deg (45deg rotation mirror scanning)
1150km for VNR-NP/P
1400km for IRS SWI/TIR
VNR-NP: 250mVNR-P: 1000m
IRS SWI: 250m(SW3CH), 1000m(SW1,2,4CH)
IRS TIR: 250m±45 degrees in along track direction for VNR-P
Nadir for VNR-NP, IRS SWI, and IRS TIR
12bit
VNR : ≤3% IRS : ≤5% TIR : ≤0.5K
5 Years

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Table 5: SGLI Observation Requirement Details
CH
VNR-NPVNR-PIRS SWIIRS TIR

4.

VN1
VN2
VN3
VN4
VN5
VN6
VN7
VN8
VN9
VN10
VN11
P1
P2
SW1
SW2
SW3
SW4
T1
T2

λ
Δλ
nm: VNR, IRS SWI
μm: IRS TIR
380
10
412
10
443
10
490
10
530
20
565
20
673.5
20
673.5
20
763
12
868.5
20
868.5
20
673.5
20
868.5
20
1050
20
1380
20
1630
200
2210
50
10.8
0.74
12.0
0.74

IFOV
m
250
250
250
250
250
250
250
250
250
250
250
1000
1000
1000
1000
250
1000
1000/500/250
1000/500/250

SNR
SNR: VNR, IRS SWINEΔT(K): IRS TIR
250
400
300
400
250
400
400
250
1200 (@1km IFOV)
400
200
250
250
500
150
57
211
0.2 (@500m IFOV)
0.2 (@500m IFOV)

L (for SNR)
W/m2/sr/μm
60
75
64
53
41
33
23
25
40
8
30
25
30
57
8
3
1.9
300 (K)300 (K)

Products

Geophysical products made available by GCOM-W and GCOM-C are listed in Tables 6, 7, and 8.
There are two categories of data products: standard product and research product. A “standard”
product is defined as a product with proven accuracy that is to be operationally processed anddistributed. In contrast, a “research” product is a prototype for a standard product and is processed ona research basis. Both tables indicate standard products with shading.

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Table 6: Standard Geophysical Products of GCOM-W
Accuracy 1

Product

Areas

Resolution(km)

Integrated
water vapor

Global,over ocean

15±3.5 kg/m2±3.5 kg/m2±2.0 kg/m2

0-70 kg/m2

Vertically integrated (columnar) water vapor
amount. Except sea ice and precipitating areas.

Integrated
cloud liquid
water

Global,over ocean

15±0.10 kg/m2±0.05 kg/m2±0.02 kg/m2

0-1.0 kg/m2

Vertically integrated (columnar) cloud liquid water.
Except sea ice and precipitating areas.

Precipitation

Global, except
cold latitudes

15

Ocean ±50 % Ocean ±50% Ocean ±20%Land ±120 % Land ±120 % Land ±80 %0-20 mm/h

Surface precipitation rate. Accuracy is defined as
relative error (ratio of root-mean-square error toaverage precipitation rate) in 50km grid average.

Sea surface
temperature

Global,over ocean

50±0.8 °C±0.5 °C±0.2 °C-2-35 °C

Except sea ice and precipitating areas. Goal
accuracy is defined as monthly mean bias error in
10 degrees latitudes.

Sea surface
wind speed

Global,over ocean

15±1.5 m/s±1.0 m/s±1.0 m/s

0-30 m/s

Sea iceconcentration

Polar region,over ocean

15

±10 %

±10 %

±5 %

0-100 %Snow depth

Land

30

±20 cm±20 cm±10 cm0-100 cm

Except ice sheets and dense forest areas. Accuracy
is expressed in snow depth and defined as mean
absolute error of instantaneous observations.

0-40 %

Volumetric water content over global land areas
including arid and cold regions, except areas
covered by vegetation with 2kg/m2 waterequivalent. Accuracy is defined as mean absolute
error of instantaneous observations.

Soil moisture

Land

ReleasethresholdStandard

Goal

50

±10 %

±10 %

±5 %

Range

Except sea ice and precipitating areas.

Accuracy is expressed in absolute value of sea ice
concentration (%).

1: Accuracy is defined as root-mean-square error of instantaneous values unless otherwise stated. Assumed validation methodologies
are not explained here.

Table 7: Research Products of GCOM-W
Products
All-weather sea surface wind speed
High-resolution (10-GHz)
sea surface temperature
Multi-band SST
Soil moisture and vegetation water content
based on the land data assimilation
Land surface temperature
Vegetation water content

Area
Ocean

Resolution(km)
60± 7 m/s

0 - 70 m/s

Ocean

30

± 0.8 °C

-2 - 35 °C

Ocean
Global overland (snowfree area)

30-50± 0.8 °C

-2 - 35 °C

25soil moisture: ± 8%
vegetation water: ± 1 kg/m2

soil moisture: 0 - 100 %vegetation water: 0 - 2 kg/m2

Land

15

Land
Ocean in highHigh resolution sea ice concentration
latitude
Ocean in highThin ice detection
latitudes
Ocean in highSea ice motion vector
latitudeTotal precipitable water over land
Land
Polar region,
Thin Ice Thickness (Thermal Ice Thickness)over ocean
Polar region,
Sea Ice Thickness (>= 20 cm)
over ocean

Target accuracy

Range

10

forest area: ± 3 °C
nondense vegetation: ± 4 °C
± 1 kg/m2

0 - 4 kg/m2

5± 15 %

0 - 100 %15± 80 %

N/A

50

2 components: 6 cm/s

12.5
15

1-9

0 - 40 cm/s

± 6.5 kg/m
Thin solid ice: ± 10 cm
Active frazil ice: ± 3 cm

0 – 70 kg/m2± 20 cm

0.2 – 1.2 m

2

15

0 - 50 °C

0 – 20 cm

Table 8: Geophysical Products of GCOM-C (1/3)
Area Group

Product

common

TOA radiance(including
system Standard
geometric correction)

Radiance

Category Developer

Precisegeometric
Standard
correction
Surface
Atmospheric correctedreflectancereflectance (incl. cloudStandard
detection)
Vegetation index

Standard

fAPAR

Standard

Vegetation
Leaf area index
and carbon
cycle
Above-ground biomass

Day/night

Land

Temperature Surface temperatureLand
netproduction

primary

JAXA

Both

Tile, Global (mosaic
250m
1, 8 days, month)

JAXA

DaytimeTile , Global (1, 8days, month)

250m

JAXA

DaytimeTile , Global (1, 8days, month)

250m

PI

DaytimeTile , Global (1, 8250m
days, month)PI

DaytimeTile , Global (1, 8days, month)
Tile , Global (1, 8days, month)
Tile , Global (1, 8days, month)Standard

Standard

PI

DaytimeStandardPI

BothResearchPI

Daytime
N/A

Evapotranspiration

Research

PI/ JAXA

Fire detection index

Research

JAXA

Both*12

Research

PI/JAXA

DaytimeResearch

JAXA/PI

N/A

Application Land cover typeLand surface albedo

Photosynthetically Active
Research
Radiation*16
Vegetation phenology*16 Research

Atmosphere

Cloud

VNR,SWI Land/coast:
Radiometric 5%250m,
offshore: 1km,
(absolute)*3
polarimetory:1km
Geometric<1
TIR Land/coast: 500m, pixel
offshore: 1km

JAXA

Standard<1pixelStandard accuracy*2

Target accuracy*2

VNR,SWI: 5% (absolute),
VNR,SWI: 3% (absolute), 0.5% (relative) *3
1% (relative) *3
TIR: 0.5K (@300K)
TIR: 0.5K (@300K)
Geometric<0.3 pixel
Geometric<0.5 pixel<0.5pixel<0.25pixel

0.3 (<=443nm),
0.1 (<=443nm),
0.05 (<=443nm),
0.2(>443nm)0.05 (>443nm) (scene) *7 0.025 (>443nm) (scene)*7*7(scene)Grass:
25%,
Grass: 20%, forest: 15%
forest:20%
Grass: 10%, forest: 10% (scene)(scene)(scene)Grass:
50%,
Grass: 30%, forest:20% Grass: 20%, forest: 10%
forest: 50%
Grass:
50%,
Grass: 30%, forest:30% Grass: 20%, forest: 20%
forest: 50%
Grass:
50%,
Grass: 30%, forest: 50% Grass: 10%, forest: 20%
forest: 100%
Grass and forest: Grass and forest: 20%
Grass and forest: 10% (scene)
40% (scene)(scene)Grass and forest: Grass and forest: 20%
Grass and forest: 10% (scene)
30% (scene)(scene)1km
1km
250m, 1km
500m

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

Global (month, year) 1km

N/A

N/A

30% (yearly)

Tile , Global (8 days,
500m
half-month, month)
Scene or Tile
500m
Global (month,250m
season)Tile , Global (1, 8
1km
days, month)
250m (Japan),Tile, Global (1, 8days, month)(global)

N/A

N/A

10% *13 (error judgment rate)

N/A

N/A

20% *14 (error judgment rate)

N/A

N/A

30% (error judgment rate)

N/A

N/A

10%

N/A

N/A

10% (10 km/month)

JAXA

DaytimePI

DaytimeTile (1 day)

250m
1km

5km

8日

day, month）

N/A
N/A
10% (with wholeIncl. below cloud amountsky camera)
20% (on solar
15% (on solar
irradiance)*9
irradiance)*9
3K/2km (top
1K*4
temp/height)*5
10%/30% (Cloud
100% as CLW*7
OT/radius)*6

Tile , Global（1, 8day, month）

30%*6

20%*8

Cloud flag/Classification

Standard

Both

Tile , Global（1, 8day, month）

Classified cloud fraction

Standard

DaytimeGlobal （1, 8 day,month）

Cloud top temp/heightStandard

Both

Tile , Global （1, 8day, month）

Water cloud OT/effective
radiusStandard

DaytimeIce cloud optical thickness Standard

DaytimePI

Releasethreshold*2

Grid size

TIR and land SWI:
both,
Other VNR, SWI: Scene
daytime (+special
operation)

Vegetation roughness index Standard
Shadow index

Production unit

1km (Tile),
Tile , Global （1, 8 0.1deg (global)

1C-10

70%*8

Incl. below cloud amount
10% (on solar irradiance)*9
1.5K/1km (temp/height)*5
50%*7 / 20%*8

Water cloud geometrical
thickness

Aerosol

RadiationbudgetResearchPI

DaytimeAerosol properties (using
both NP and PL)

Standard

JAXA

DaytimeLong-wave radiation flux

ResearchPI

DaytimeShort-wave radiation flux

Research

JAXA/PI

DaytimeTile , Global （1, 8day, month）

N/A

Tile , Global （1, 8day, month）

Ocean: 0.1(Monthly ta_670,865)*10
Land: 0.15
(Monthly
ta_380)*10

Tile , Global （1, 8day, month）
Tile , Global （1, 8day, month）

1C-11

N/A

300m

Ocean: 0.1(scene
ta_670,865)*10
Land: 0.15 (scene
ta_380)*10

Ocean: 0.05 (scene ta_670,865)
Land: 0.1(scene ta_380 )

N/A

N/A

Downward 10W/m2, upward 15W/m2 (monthly)

N/A

N/A

Downward 13W/m2, upward 10W/m2

Table 8: Geophysical Products of GCOM-C (2/3)
Area Group

Product
Category Developer Day/night
Normalized water-leaving
radiance (incl. cloudStandard
detection)
PI
DaytimeAtmospheric correction
Standard
Ocean color parameter
Photosynthetically available
Standard JAXA/ PI Daytime
radiation
Euphotic zone depth

Research

Chlorophyll-a concentration Standard
In-water

Total suspended matter
concentration
Colored dissolved organic
matter

Ocean

Inherent optical properties
Temperature Sea-surface temperature
Ocean net primary
productivity

PI

Grid sizePI

Standard

PI

Research

PIStandard

JAXA
PI

Daytime80% (AOT@865nm)
Scene, Global (1, 8 days,
month)
Scene, Global (1, 8 days,
month)

Daytime

Scene, Global (1, 8 days,
month)

Both

Scene, Global (1, 8 days,
month)

Daytime

Scene, Global (1, 8 days,
month)PI

Daytime

Scene, Global (1, 8 days,
month)

Red tide

ResearchPI

Daytime

Scene, Global (1, 8 days,
month)

Application

Cryosphere

multi sensor merged ocean
Research JAXA/PI Daytime
color
multi sensor merged SST
Research JAXA Both
Floating algae index*16
Research JAXA Daytime
Snow and Ice covered area
Standard
Daytime(incl. cloud detection)
PI
Okhotsk sea-ice distribution Standard
DaytimeArea/
distribution Snow and ice classification ResearchPI
DaytimeSnow covered area in forests
ResearchPI
Daytimeand mountains
Snow and ice surface
Standard
DaytimeTemperature
Snow grain size of shallow
Standard
Daytimelayer
PI
SurfaceSnow grain size ofproperties
Research
Daytimesubsurface layer

Research

DaytimePI

N/A-60 to +150% (offshore)-60 to +150% (offshore)-60 to +150% (offshore)

Research

Snow and ice albedo

20% (10km/month)
Coast: 250m
Offshore: 1km
Global: 4-9km

Scene, Global (1, 8 days,
month)

Phytoplankton functional
type

Snow grain size of top layer Research

Release threshold*2
60% (443~565nm)

Scene, Global (1, 8 days,
month)JAXA

Standard

Research

Daytime

Production unit

DaytimeArea, Global (1, 8 days, month)

Coast: 500m
Others: Same as above
Coast: 500m
Others: Same as above

Coast: 250m
Others: Same as above

Coast: 250m
Offshore: 1km

250m (Japan)
250m (Tile), 1km
Tile, Global (1, 8 days, month)(global)Area (1day)
250m
Global (8 days, month)
1km
Area (1 day)

Area (1, 8 days)

250m

Standard accuracy*2
Target accuracy*2
50% (<600nm)
30% (<600nm)
0.5W/m2/str/um (>600nm) 0.25W/m2/str/um (>600nm)
50% (AOT@865nm)
15% (10km/month)

30% (AOT@865nm)
10% (10km/month)

N/A

30%

-60 to +150%-35 to +50% (offshore), -50
to +100% (coast)-60 to +150%-60 to +150%-50 to +100%-50 to +100%

N/A

N/A

a (440): RMSE<0.25, bbp(550): RMSE<0.25

0.8K (daytime)

0.8K (day & night time)

0.6K (day and night time)

N/A

N/A

70% (monthly)

N/A

N/A

error judgment rate of large/
small phytoplankton
dominance<20%; or error
judgment rate of the dominantphytoplankton functionalgroup <40%

N/A

N/A

error judgment rate <20%

N/A

N/A

N/A
N/A

N/A
N/A

10%
10%
N/A
N/A

(vicarious val
other sat. data)-35 to +50% (offshore), -50 to+100% (coast)
0.8K (day & night time)
TBD

with 7%

5%

5%
N/A

3%
10%

N/A

30%

500m (Tile), 1km
Tile, Global (1, 8 days, month)(global)250m (Tile), 1km
Tile, Global (1, 8 days, month)(global)

5K (vicarious val with other sat.
2K
data and climatology)
100% (vicarious val. with50%
climatology between temp-size)

Tile, Global (1, 8 days, month) 1km

N/A

N/A

50%

N/A

N/A

50%

N/A

N/A

7%

250m (Tile), 1km
Tile, Global (1, 8 days, month)(global)Global (1, 8 days, month)
1km

1C-12

1K
30%

Table 8: Geophysical Products of GCOM-C (3/3)
Area Group
Cryosphere

Surfaceproperties
Boundary

Product

Category Developer Day/night

Production unit

Snow impurity

ResearchPI

DaytimeIce sheet surface roughness Research
Ice sheet boundary
ResearchmonitoringPI

Daytime

Grid size
250m (Tile), 1km
Tile, Global (1, 8 days, month)(global)Area (Season)
1km

JAXA

DaytimeArea (Season)

250m

Release threshold*2Standard accuracy*2

Target accuracy*2

N/A

N/A

50%

N/A

N/A

0.05 *15

N/A

N/A

<500m

Common notes:*1. Heritage levels from ADEOS-II/GLI study are shown by A-C; A: high heritage, B: Remaining issues, C: new or many issues remaining to be resolved*2. The “release threshold” is minimum levels for the first data release at one year from launch. The "standard" and "research" accuracies correspond to full and extra success criteria of the mission. Accuracies
are basically shown by RMSE.
*16 Candidate for research products.
Radiance data notes:*3. Absolute error is defined as offset + noise; relative error is defined as relative errors among channels, FOV, and so on. Release threshold of radiance is defined as estimated errors from vicarious, onboard solar
diffuser, and onboard blackbody calibration because of lack of long-term moon samples
Atmosphere notes:*4. Vicarious val. on sea-surface temperature and comparison with objective analysis data
*5. Inter comparison with airplane remote sensing on water clouds of middle optical thickness*6. Release threshold is defined by vicarious val. with other satellite data (e.g., global monthly statistics in the mid-low latitudes)*7. Comparison with cloud liquid water by in-situ microwave radiometer*8. Comparison with optical thickness by sky-radiometer (the difference can be large due to time-space inconsistence and large error of the ground measurements)*9. Comparison with in-situ observation on monthly 0.1-degree*10. Estimated by experience of aerosol products by GLI and POLDER
Land data notes:*11. Defined with land reflectance~0.2, solar zenith<30deg, and flat surface. Release threshold is defined with AOT@500nm<0.25*12. Night time 250m product can be produced by special observation requests of 1.6µm channel*13. Evaluate in semiarid regions (steppe climate, etc.)*14. Fires >1000K occupying >1/1000 on 1km pixel at night (using 2.2um of 1 km and thermal infrared channels)
Cryosphere notes:*15. Defined as height/width of the surface structures

1C-13

APPENDIX 1-C
SUPPLEMENTAL TABLES FOR THE PRODUCTVALIDATIONS OF THE GLOBAL CHANGEOBSERVATION MISSION-CLIMATE (GCOM-C)

1C-0

Table C1 Definition and validation method of GCOM-C L1B and L2 products
Category

Product [Definition・Unit]

Accuracy*16

CommonReleaseSatellite-observed radiance(Data(Level-1B）
Def.:
Satellite-observaed releasethreshradianceswhich
are old)

radiometricallyandgeometrically corrected withinter-bandregistration. StanCalibration information is dard
added.
Unit: W/m2/str/µm

Land

Goal

Precise geometric correctedradiance (LTOA)
Def.: This product contains 1)
PGCP parameters whichindicate geometric biases
estimated using GCP, and 2)
radiance images which areprojected
tosinusoidal
projection plane with thecenter longitude of 0 degree
after the correction of thegeometric biases using the
PGCP.
Unit: W/m2/str/µm
Land atmospheric correctedreflectance (LSRF)
Def.: Land surface reflectancecorrected for the effects ofatmospheric scattering andabsorption. Correction of
directional anisotropic effects
are also made for 8-day andmonthly composite products.
Unit: none
Vegetation index (VGI)
Def.: Indices indicating
vegetation cover and activity
such as NDVI and EVI
Unit: none

Accuracy of radiance is evaluated as RMS error basedon vicarious calibration, on-board calibrations withsolar diffuser and blackbody and so on.
Geometrical accuracy is evaluated using GCP as RMS
error of pixel position after systematic geometriccorrection.
except TIR: 5%(abs.*11), Accuracy of radiance is evaluated as RMS error based
1% (relative)on vicarious calibration, on-board calibrations with
TIR: 0.5K (@300K)
solar diffuser and blackbody, and maneuver
geometric accr.<0.5pixel operations for moon calibration and inter-band
calibration (yaw-direction maneuver).
Except TIR: 3%(abs.*11),
Geometricalaccuracy is evaluated using GCP as RMS
0.5% (relative)
error of pixel position after systematic geometric
TIR: 0.5K (@300K)
geometric accr.<0.3pixel correction.

Release<1pixelStandard<0.5pixel

Goal<0.25pixel

Release0.3 (<=443nm), 0.2(>443nm) (scene)*8

Standard
Goal

0.1 (<=443nm), 0.05(>443nm) (scene)*8
0.05 (<=443nm), 0.025(>443nm) (scene)*8

ReleaseGrass land： 25%(scene),Forest： 20% (scene)

Standard
Goal

Above-ground biomass (AGB)
Def.: Dry weight of aboveground vegetation
Unit: t/ha

Cal/Val Method

5% (absolute*11)
geometric accr.<1pixel

ReleaseStandard
Goal

Accuracy of precise geometric correction is evaluatedas RMS error of pixel position using GCPs.

RMS error between satellite-derived reflectances andground truth measurements is estimated at a region
where aerosol optical thickness at 500nm is less than
0.25.
RMS error between satellite-derived reflectances andground truth measurements is estimated.

RMS error is evaluated comparing SGLI-derived VI
with in-situ measured VI derived fromspectroradiometer data at JaLTER, JapanFlux, PEN,
Yatsuga-take tower site etc. and also with othersatellite VI products.
Grass land: 20% (scene), RMS error is evaluated comparing SGLI-derived VI
with in-situ measured VI derived from
Forest： 15% (scene)
spectroradiometer data at JaLTER, JapanFlux, PEN,
Grass land： 10%
Yatsuga-take tower site etc.
(scene),Forest: 10% (scene)
RMS error is evaluated comparing SGLI-derived AGBIO
Grass land： 50%,
with in-situ measured AGBIO at JaLTER, JapanFlux,
Forest： 100%
PEN, Yatsuga-take tower site etc. (derived from direct
measurements of dry weight of grass at grass land,
indirect estimation with allometry equation asfunctions of tree diameter at brest height (DBH) andtree height, or 3-D laser scanner measurements atforest), and also with AGBIO derived from othersatellites and numerical ecosystem models.
RMS error is evaluated comparing SGLI-derived AGBIO
Grass land：30%,
with in-situ measured AGBIO at JaLTER, JapanFlux,
Forest：50%
PEN, Yatsuga-take tower site etc.
Grass land：10%,
Forest：20%

1C-1

Vegetation roughness index(VRI)
Def.: An index indicating plantvertical structure observed
from multi-angle directions.
Unit: none

ReleaseShadow index (SI)
Def.: An index indicating
shadow fraction ofvegetation area inferredfrom spectral reflectance.
Unit: none

ReleaseFraction of absorbed PAR(FAPAR)
Def.: Fraction ofphotosynthetically active
radiation absorbed byvegetation
Unit: none

Leaf area index (LAI)
Def.: The sum of the one sided
green leaf area per unit
ground area.
Unit: none

Grass land･Forest：40%(scene)Grass land・Forest：20%(scene)Grass land・Forest：10%(scene)RMS error is evaluated comparing SGLI-derived VRIwith in-situ measured VRI at JaLTER, JapanFlux, PEN,
Yatsuga-take tower site etc. (derived from spectoral
reflectance data acquired using tower and RC
helicopter and so on).

Grass land・Forest：
30% (scene)
Grass land・Forest：
20% (scene)
Grass land・Forest：
10% (scene)

RMS error is evaluated comparing SGLI-derived VRIwith in-situ measured SI at JaLTER, JapanFlux, PEN,
Yatsuga-take tower site etc. (derived from spectoral
reflectance data acquired using tower and RC
helicopter and so on), or comparing with SI inferredfrom data of high spatial resolution optical sensor.

ReleaseGrass land： 50%,
Forest： 50%

Standard
Goal

Grass land：30%,
Forest：20%
Grass land：20%,
Forest：10%

ReleaseGrass land： 50%,
Forest： 50%

Stan- dard

Grass land：30%,
Forest：30%
Grass land：20%,
Forest：20%

Standard
Goal

Standard
Goal

ReleaseLess than 3.0K (scene)

Stan- dardLess than 2.5K (scene)

Goal

Less than 1.5K (scene)

Land net primary production(LNPP)
Def.: Net primary productivity
which is how much carbon
dioxide vegetation takes induring photosynthesis (GPP)
minus how much carbon
dioxide the plants releaseduring respiration or decay.
Unit: gC/m2/year
Evapotranspiration index (ETI)
Def.: An index to understandthe droughty state ofvegetation.
Unit: none

ReleaseN/A

RMS error is evaluated comparing SGLI-derived FAPAR
with in-situ measured FAPAR at JaLTER, JapanFlux,
PEN, Yatsuga-take tower site etc. (derived from data
of PAR meter or spectroradiometer data measuring
upward and downward PAR at forest canopy andfloor.), and with other satellite FAPAR products.
RMS error is evaluated comparing SGLI-derived FAPAR
with in-situ measured FAPAR at JaLTER, JapanFlux,
PEN, Yatsuga-take tower site etc. (derived from data
of PAR meter or spectroradiometer data measuring
upward and downward PAR at forest canopy andfloor.).
RMS error is evaluated comparing SGLI-derived LAI
with in-situ measured LAI at JaLTER, JapanFlux, PEN,
Yatsuga-take tower site etc. (derived from data oflitter trap or LAI-2000 and spectroradiometer datameasuring downward radiant flux etc. at forest floor.),and with other satellite LAI products.
RMS error is evaluated comparing SGLI-derived LAI
with in-situ measured LAI at JaLTER, JapanFlux, PEN,
Yatsuga-take tower site etc. (derived from data oflitter trap or LAI-2000 and spectroradiometer datameasuring downward radiant flux etc. at forest floor.).
RMS error is evaluated comparing SGLI-derived LSTwith in-situ measured LST at the ground surface withuniform land cover and also comparing with othersatellite LST products.
RMS error is evaluated comparing SGLI-derived LSTwith in-situ measured LST at the ground surface withuniform land cover (TBD).
N/A

Stan- dard

N/A

N/A

Goal

30％(annual ave.)

RMS error is evaluated comparing SGLI-derived LNPP
with in-situ measured LNPP at JaLTER, JapanFlux, PEN
sites and also comparing with other satellite LNPP
products.

ReleaseStan- dard

N/A
N/A

N/A
N/A

Goal

10%(as classification
error)*13

Fire detection index (FDI)
Def.: Location of fire hot spots
detected using thermal andshortwave infrared bands.
Unit: none

ReleaseStan- dard
Goal

N/A
N/A
20% (as classification
error)*14

Land cover type (LCT)

ReleaseN/AClassification error is evaluated comparing SGLI
derived ETI with in-situ measured latent heattransport at flux sites (TBD).
N/A
N/AClassification error is evaluated comparing SGLI
derived FDI with that derived from high spatial
resolution optical sensors which has shortwave andthermal infrared bands.
N/A

Goal

Land

Land surface temperature (LST)
Def.: Temperature ofterrestrical land surface.
Unit: Kelvin

1C-2

Def.: Land cover type classified
using vegetation indices andland reflectance.
Unit: none

Stan- dard

N/A

N/A

Goal

30% (as classification
error)

Land surface albedo (LALB)
Def.: Ratio of upward reflectedenergy to downward solar
radiation energy.
Unit: none

ReleaseStan- dard

N/A
N/A

Classification error is evaluated comparing SGLI
derived LCT with the ground truth derived from
Degree Confluence Project data on a global scale, andalso comparing with regional LCT (such as Japan area)
derived from high spatial resolution sensors.
N/A
N/A

Goal

10%

Cloud flag (CLFG)
Def.: Cloud discrimination flagincluding the classification ofcloud type and phase(liquid/solid).
Unit: none

Release10% (comparison with
sky-camera binary
image)

Stan- dard

Release

Evaluated as the cloud
fraction products.
Evaluated as the cloud
fraction products.
20% (as solar
radiation)*615%( as solar
radiation)*6
10%（as solar
radiation)*6
1K *1

Stan- dard3K *2 /2km *2

Goal

1.5K *2 /1km*2

Goal

Atmosphere

AtmosphereClassified cloud fraction(CLFR)
Def.: Cloud fractions for 9 cloudtypes which are classified
based on the ISCCP
classification rule.
Unit: percent
Cloud top temp/height (CLTTH)
Def.: Temperature and height ofcloud top layer.
Unit: Kelvin for temperature,
km for height

ReleaseStan- dard
Goal

Water-cloud optical thickness & Release
effective radius (CLOTER_W)
Def.: Optical thickness andeffective radius of water
Stan- dard
cloud droplets
Unit: none for thickness, µm forradiusIce-cloud optical thickness(CLOT_I)
Def.: Optical thickness of ice
cloud.
Unit: none

Aerosol over the ocean andland (ARNP)
Def.: Optical thickness,Ångström exponent, and10%/30% (optial
thickess/radius) *3

100% (as cloud liquidwater*4)

Goal

50% *4 /20% *5

Release30% *3Stan- dard

70% *5

Goal
Release20 % *5
Ocean: 0.1(monthly
ave. of ta_670, 865)
Land: 0.15(monthly ave.
ofta_380)

1C-3

RMS error is evaluated comparing SGLI-derived LALB
with in-situ measured LALB derived fromspectroradiometer data at JaLTER, JapanFlux, PEN,
Yatsuga-take tower site etc. (derived from spectoral
reflectance data acquired using tower and RC
helicopter and so on) and also with other satellite
LALB products.
Overall classification error is evaluated comparing
SGLI derived CLFG with those derived from othersatellite sensors, cloud amounts collected through
GTS (The Global Telecommunication System), andskycamera images.
Same as the classified cloud fraction.
Same as the classified cloud fraction.
Overall classification error is evaluated comparing SGLI
derived solar radiation which is monthly average forevery 0.1 degree global grid with in-situ measured solar
radiation, skycamera images, and existing cloud
fraction climatology datasets such as ISCCP(theInternational Satellite Cloud Climatology Project).
The release criterion shown in the left column
indicates a threshold for SGLI TIR band brightness
temperature by which the ability to sense cloud top
temperature is evaluated indirectly. The accuracy of
TIR band is assessed through the product evaluation
process of sea surface temperature etc. Also
confirmed is the consistency of SGLI derived cloud top
temperature with object analysis data of air
temperature profile over ocean in daytime.
RMS error is evaluated comparing SGLI derived CLTTH
with those derived from airbone and satellite borne
lidar and radiometer etc. for uniform liquid clouds
with moderate optical thickness.
RMS error is evaluated comparing SGLI derived
CLOTER_W with those from other satellite sensors forclouds of mid- to low latitude regions (monthly
average).
RMS error is evaluated comparing cloud liquid water
converted from SGLI derived CLOTER_W with thosemeasured with microwave radiometer on the ground.
Overall RMS error is evaluated comparing SGLI
derived CLOTER_W with those derived frommicrowave radiometer and skyradiometer (for optical
thickness) and other satellite sensors (both param.).
RMS error is evaluated comparing SGLI derived
CLOT_I with those from other satellite sensors forclouds of mid- to low latitude regions (monthly
average). .
RMS error is evaluated comparing SGLI derived
CLOT_I with those from skyradiometers at groundobservation network and other satellite sensors.
Overall RMS error is evaluated comparing SGLI
derived AROT with those from other satellite sensors
and climatology based on the past satellite
observations (monthly average).

characterization of aerosols(light absorption coefficient ofaerosol over land) estimatedusing non-polarization andpolarization bands.
Unit: none

Stan- dard

Water cloud geometrical
thickness (CLGT_W)
Def.: Geometrical thickness ofwater cloud.
Unit: mReleaseOcean: 0.1(scene’s
ta_670, 865)*7
Land: 0.15(scene’s
ta_380) *7
Ocean: 0.05(scene’s
ta_670, 865)
Land: 0.1(scene’s
ta_380 )N/AStan- dard

N/A

Goal

300m

Long-wave radiation flux
(LWRF)
Def.: Longwave radiation flux at
the ground including
downward longwave
radiation flux and upward
longwave radiation flux.
Unit: W/m2
Short-wave radiation flux
(SWRF)
Def.: Shortwave radiation flux
at the ground including
downward shortwave
radiation flux and upward
shortwave radiation flux.
Unit: W/m2
Normalized water leaving
radiance (NWLR)
Def.: The upwelling radiancejust above the sea surface.
Unit: W/m2/str/um or 1/sr

ReleaseN/A

Stan- dard

N/A

Goal

Downward flux:
10W/m2, Upward flux:
15W/m2 (0.1 deg.,monthly ave.）
N/A
N/A

Goal

ReleaseStan- dard

Ocean

Photosynthetically Available
Radiation (PAR)Def.: Photon flux density within
the visible wavelength range(400 to 700 nm) over ocean
which is potencially available
to plant for photosynthesis.
Unit: Ein/m2/day or mol
photons/m2/day

N/A
N/A
RMS error is evaluated comparing SGLI derived
CLGT_W with those measured at the ground and fromspace (satellite) with cloud radar and lidar
instruments.
N/A
N/A
RMS error is evaluated comparing SGLI derived
monthly averaged LWRF with those from groundradiation observation network (ARM, BSRN), groundobservation network (JaLTER, JapanFLux, PEN, Fluxnetetc.), and other satellite sensors.
N/A
N/A

Goal

Downward: 13W/m2,
RMS error is evaluated comparing SGLI derived
Upward: 10W/m2
monthly averaged SWRF with those from ground(0.1deg. , monthly ave.） radiation observation network (ARM, BSRN), groundobservation network (JaLTER, JapanFLux, PEN, Fluxnetetc.), and other satellite sensors.

Release60% (443~565nm)

Stan- dard

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

Goal

Atmospheric correction
param.(ACP)
Def.: Aerosol optical properties
for the atmosphericcorrection over ocean.
Unit: none

RMS error is evaluated comparing SGLI derived AROTwith those from other satellite sensors and in-situ
observations (Skynet, AERONET and AERONET
Maritime Aerosol Network).

Release80% (ta_865)

Stan- dard

50% (ta_865)

Goal

30%

Release20% (10km/month)

Stan- dard

15% (10km/month)

Goal

10% (10km/month)

1C-4

RMS error is evaluated comparing SGLI derived NWLR
with in-situ optical measurements conducted during
simultaneous ship observations campaign and also
comparing with other satellite products.
RMS error is evaluated comparing SGLI derived NWLR
with in-situ optical measurements conducted during
simultaneous ship observations campaign.
RMS error is evaluated comparing SGLI derived
monthly averaged LWRF with those from groundradiation observation network (ARM, BSRN), groundobservation network (JaLTER, JapanFLux, PEN, Fluxnetetc.), and other satellite sensors.
RMS error is evaluated comparing SGLI derived
aerosol optical thickness with those from in-situ
measurements using radiometers during
simultaneous ship observations campaign and also
comparing with other satellite sensors.
RMS error is evaluated comparing SGLI derived
aerosol optical thickness with those from in-situ
measurements using radiometers during
simultaneous ship observations campaign.
RMS error is evaluated comparing SGLI derived
monthly averaged SWRF with those from groundradiation observation network (ARM, BSRN), groundobservation network (JaLTER, JapanFLux, PEN, Fluxnetetc.), and other satellite sensors.
RMS error is evaluated comparing SGLI derived
monthly averaged PAR with those derived frommooring buoy such as NDBC, TAO/TRITON etc. as solar
radiation or PAR.
RMS error is evaluated comparing SGLI derived NWLR
with in-situ optical measurements conducted during
simultaneous ship observations campaign.

OceanChlorophyll-a concentration(CHLA)
Def.: Concentration of thegreen pigment inphytoplankton in sea surface
layer.
Unit: mg/m3

Release-60~+150% (open sea)

Stan- dard

-60~+150%

Goal

Total Suspended Matter
concentration (TSM)
Def.: Dry weight of suspended
matter in a unit volume of
surface water which is thesum of organics such as
phytoplankton and inorganics
such as soil.
Unit: g/m3
Colored dissolved organic
matter (CDOM)
Def.: Light absoption coefficientof organics dissolved insurface water.
Unit: 1/m
Sea surface temperature (SST)
Def.: Temperature of sea
surface.
Unit: °C

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

Stan- dard

-60~+150%

Goal-50~+100%

Release-60~+150% (open sea)

Stan- dard

-60~+150%

Goal-50~+100%

Release

0.8K (daytime only)

Stan- dard

0.8K

Goal

0.6K

ReleaseStan- dard

N/A
N/A

Goal

30% (inferred fromextinction coefficient)ReleaseStan- dard

N/A
N/A

Goal

Absorption coefficient@440nm: RMSE<0.25
and backscattering
coefficient ofphytoplankton@550nm: RMSE<0.25

Release

N/A

N/A

Stan- dard

N/A

N/A

Goal

70% (monthly ave.)

RMS error is evaluated comparing SGLI derived
monthly averaged ONPP with those derived fromsimultaneous in-situ measurements.

Release

N/A

N/A

Stan- dard

N/A

N/A

Goal

Classification error of
dominant/nondominant spesies oflarge/small
phytoplankton: 20%, orclassification error ofClassification error is evaluated comparing with SGLI
derived PHFT with the dominant type ofphytoplankton group (such as Bacillariophyceae,
Chlorophyceae, and Haptophyta etc.) determinedfrom the plant pigment analysis of sea water samples
using HPLC.

Euphotic zone depth (EZD)
Def.: The sea depth where
photosynthetic available
radiation ( PAR) is 1% of its
surface value.
Unit: mInherent optical properties(IOP)
Def.: Optical properties of sea
water such as spectral
absorption, scattering, andbackscattering coefﬁcientsfor characterizing the marine
optical environment andremote-sensing applications.
Unit: 1/m
Ocean net primary productivity(ONPP)
Def.: Net primary productivity
which is gross photosynthetic
carbon fixation minus the
carbon respired to support
maintenance requirementsof the whole plant.
Unit: mgC/m2/day
Phytoplankton functional type
(PHFT)
Def.: Conceptual groupings ofphytoplankton species, whichhave a ecological
functionality in common suchas nitrogen fixation,
calciﬁcation, siliciﬁcation,
DMS production and so on.

1C-5

RMS error is evaluated comparing SGLI derived CHLA
with those derived from sea water samples byfluorescence method or HPLC analysis and also withother satellite products.
RMS error is evaluated comparing SGLI derived CHLA
with those derived from sea water samples byfluorescence method or HPLC analysis.
RMS error is evaluated comparing SGLI derived SSwith those derived from sea water samples byfiltration method and also with other satellite
products.
RMS error is evaluated comparing SGLI derived SSwith those derived from sea water samples byfiltration method.

RMS error is evaluated comparing SGLI derived CDOM
with those derived from sea water samples by opticalmeasurements and also with other satellite products.
RMS error is evaluated comparing SGLI derived CDOM
with those derived from sea water samples by opticalmeasurements.
Overall RMS error is evaluated comparing SGLI
derived SST with those derived from other satellite
sensors and also comparing with those from buoymeasurements (daytime only) obtained through GTS
and internet.
Overall RMS error is evaluated comparing SGLI
derived SST with those derived from other satellite
sensors and also comparing with those from buoymeasurements obtained through GTS and internet.
N/A
N/A
RMS error is evaluated comparing SGLI derived EZD
with those derived from simultaneous measurements
of in-water downward irradiance (in-situ EZD isdetermined from the slope of measured irradiance).
N/A
N/A
RMS error is evaluated comparing SGLI derived IOP
with those derived from simultaneous opticalmeasurements.

Unit: none

dominant functional
type in a phytoplankton
group: 40%

ReleaseRedtide (RTD)
Def.: Detection of a red tide Stan- dard
phenomenon known as an
Goalalgal bloom.
Unit: none

N/A

N/A

N/A

N/A

20％ (as classification
error)

ReleaseMulti sensor merged ocean
color parameters (MOC)
Stan- dard
Def.: Multi-sensor merged
Goalchrollophyl-a concentration
product with higher temporal
resolution than that of SGLI
original product.
Unit: mg/m3

N/A
N/A

Classification error is evaluated comparing SGLI
derived RTD with the occurrence of red tide events
determined by eye during simultaneous shipobservations campaign.
N/A
N/A

Multi sensor merged sea
surface temperature (MSST)
Def.: Multi-sensor merged
seasurface temperature
product with higher temporal
resolution than that of SGLI
original products.
Unit: °C
Snow and Ice covered area
(SICA)
Def.: The extent of global snow
and ice cover.
Unit: none

-35~+50% (Open sea),-50~+100% (Coastal)Same as the SGLI original product (CHLA).

Release

N/A

N/A

Stan- dard

N/A

N/A

Goal

0.8K

Same as the SGLI original product (SST).

Release10% (comparison with
Overall classification error is evaluated comparing
other satellite products) SGLI derived SICA with other satellites’ same products
and climatology of related geophysical parameters
derived from the past observations.
7%
Overall classification error is evaluated comparing
SGLI derived SICA with those derived from moderate
and high spatial resolution satellite sensors and alsowith snow and ice information obtained at groundstations etc.
5%
Same as the SGLI original product (CHLA).

Stan- dard

Goal

Okhotsk sea-ice distribution(OKID)
Def.: The extent of sea ice inOkhotsk Sea.
Unit: none

ReleaseStan- dard

Goal

Cryosphere

Snow and ice surface
Temperature (SIST)
Def.: Temperature of snow andice surface.
Unit: Kelvin

Release10% (comparison with
Overall classification error is evaluated comparing
other satellite products) SGLI derived OKID with other satellites’ same products
and climatology of related geophysical parameters
derived from the past observations.
5%
Overall classification error is evaluated comparing
SGLI derived OKID with those derived from moderate
and high spatial resolution satellite sensors and alsowith ice information obtained at ship etc.
3%
Same as the SGLI original product (SST).

Stan- dard

5K (comparison withother satellite products
and meteorologicalmeasurements)
2K

Goal

1K

Snow grain size of shallow layer(SNGSL)
Def.: Grain size of snow ice
particle in shallow layer
derived mainly from SGLI
865nm band reflectance.
Unit: µm

ReleaseStan- dard

100%(evaluated withclimatology oftemperature-snow
grain size relationship)
50%

Goal

30%

RMS error is evaluated comparing SGLI SNGSL withthose from in-situ radiometer measurements andsnow pit works.

Snow and ice classification (SIC)

Release

N/A

N/A

1C-6

Overall RMS error is evaluated comparing SGLI
derived SIST with those from other satellite sensors,
air temperatures from GTS and ice buoys, andclimatology derived from the past observations.
RMS error is evaluated comparing SGLI SIST withthose from in-situ radiometer measurements andsnow pit works, air temperatures from GTS and ice
buoys.
Overall error is evaluated comparing SGLI derived
SNGSL with other satellites’ products and climatology
derived from the past observations.

Def.: Classification of snow andice cover types derived using
spectral reflectance andtemperature.
Unit: none

Stan- dard

N/A

Goal

10%

Snow area in forest andmountain (SCAFM)
Def.: The extent of snow coverin forest and mountaneous
region.
Unit: none

ReleaseStan- dard

N/A
N/A

Goal

30%

Snow grain size of subsurface
layer (SNGSS)
Def.: Grain size of snow ice
particle in sub-surface layer
derived mainly from SGLI
1050nm band reflectance.
Unit: µm
Snow grain size of top layer(SNGST)
Def.: Grain size of snow ice
particle in top-surface layer
derived mainly from SGLI
1640nm band reflectance.
Unit: µm
Snow and ice albedo (SIALB)
Def.: Spectrally integrated
albedo of snow surface.
Unit: none

Release

N/A

N/A
Classification error is evaluated comparing SGLI
derived SIC with those derived from other moderate
and high spatial resolution satellite sensors and alsowith snow and ice information obtained at groundstation etc.
N/A
N/A
Classification error is evaluated comparing SGLI
derived SCAFM with those derived from othermoderate and high spatial resolution satellite sensors
and also with snow information obtained at groundstation etc.
N/A

Stan- dard

N/A

N/A

Goal

50%

RMS error is evaluated comparing SGLI SNGSS withthose from in-situ radiometer measurements andsnow pit works.

Release

N/A

N/A

Stan- dard

N/A

N/A

Goal

50%

RMS error is evaluated comparing SGLI SNGST withthose from in-situ radiometer measurements andsnow pit works.

Release

N/A

N/A

Stan- dard

N/A

N/A

Goal

7%

Snow impurity (SNIP)
Def.: Mass fraction of snow
impurity mixed in snow layer
which is optically equivalent
to soot.
Unit: ppmw
Ice sheet surface roughness(ISRGH)
Def.: Surface roughness of ice
sheets defined as the ratio ofheight to width of aroughness pattern.
Unit: none
Ice sheet boundary monitoring(ISBM)
Def.: Boundary line between ice
sheets and sea surface.
Unit: none

ReleaseN/A

RMS error is evaluated comparing SGLI SIALB withthose from in-situ radiometer measurements andsnow pit works.
N/A

Stan- dard

N/A

N/A

Goal

50%

ReleaseN/A

RMS error is evaluated comparing SGLI SNIP withthose from in-situ radiometer measurements andsnow pit works.
N/A

Stan- dard

N/A

N/A

Goal

0.05 *15

ReleaseN/A

RMS error is evaluated comparing SGLI derived ISRGH
with those derived from other moderate and highspatial resolution satellite sensors and with numericalsimulation results.
N/A

Stan- dard

N/A

N/A

Goal

500m 以下

Overall bias of ice sheet boundary line is evaluatedcomparing SGLI derived ISBM with those derived fromother moderate and high spatial resolution satellite
sensors.

Common notes:*1. Heritage levels from ADEOS-II/GLI study are shown by A-C; A: high heritage, B: Remaining issues, C: new ormany issues remaining to be resolved*2. The “release threshold” is minimum levels for the first data release at one year from launch. The "standard" and"research" accuracies correspond to full and extra success criteria of the mission. Accuracies are basically shown by
RMSE.
Radiance data notes:*3. Absolute error is defined as offset + noise; relative error is defined as relative errors among channels, FOV, and soon. Release threshold of radiance is defined as estimated errors from vicarious, onboard solar diffuser, and onboard
blackbody calibration because of lack of long-term moon samples

1C-7

Atmosphere notes:*4. Vicarious val. on sea-surface temperature and comparison with objective analysis data
*5. Inter comparison with airplane remote sensing on water clouds of middle optical thickness*6. Release threshold is defined by vicarious val. with other satellite data (e.g., global monthly statistics in the mid-low
latitudes)*7. Comparison with cloud liquid water by in-situ microwave radiometer*8. Comparison with optical thickness by sky-radiometer (the difference can be large due to time-space inconsistence
and large error of the ground measurements)*9. Comparison with in-situ observation on monthly 0.1-degree*10. Estimated by experience of aerosol products by GLI and POLDER
Land data notes:*11. Defined with land reflectance~0.2, solar zenith<30deg, and flat surface. Release threshold is defined with
AOT@500nm<0.25*12. Night time 250m product can be produced by special observation requests of 1.6µm channel*13. Evaluate in semiarid regions (steppe climate, etc.)*14. Fires >1000K occupying >1/1000 on 1km pixel at night (using 2.2um of 1 km and thermal infrared channels)
Cryosphere notes:*15. Defined as height/width of the surface structures

1C-8

TABLE C2 Expected reference data for the validation of GCOM-C/SGLI standard products
Cate
gory

Product [Unit]

Accuracy Targets

Satellite-observed
radiance (Level-1B)[W/m2/str/μm]

Release: 5％ (Abs.
*11)
Geometric: <1pixel

Val. Data Type
(Main/Auxiliary)
In-situ &variouscal.data(Main)

Algorithm PIs

Validation PIs

In-situ Data

Instruments

Observation Sites

Period,Frquency,Obs. Cycles

JAXA

JAXA

Ground reflectance data,
MOBY data etc.
(cooperation with NOAA)
Onboard calibration data

Spectrometer

CEOS cal sites

Year-round

MODIS(MOD02,M
YD02)
CAI(L1,L1B)
ASTER(L1B)

GlobalYear-round

Spectrometer

CEOS cal sites

Year-round

MODIS(MOD02,M
YD02)
CAI(L1,L1B)
ASTER(L1B)

GlobalYear-round

MODIS（MCD43C4)CAI
AVNIR-2
MODIS（MCD43C4)
CAI(Defined in GCP
library)

Spectral reflectance (incl.
BRDF) data measured
from UAV

FieldSpec, MS-720
Hyperspectral
CameraYatsugatake

Campaign

Spectral data measured
from Tower
Spectral data measured
from UAV (combined with

MS-700MS-720JaLTER, JapanFlux,
PEN sites

Year-round

Other satellite data (TBD)

CommonPrecise geometriccorrected
radiance[W/m2/str/μm]

Land

Land atmosphericcorrected
reflectance [―]Standard: VIS-SWIR:
5％ (Abs.*11), 1％(Relative)
TIR: 0.5K (@300K)
Geometric:<0.5pixel
Goal: VIS-SWIR : 3％
(Abs.*11), 0.5%
(Relative)
TIR: 0.5K (@300K)
Geometric:<0.3pixel
Release: <1pixel

In-situ &variouscal.data(Main)

Ground reflectance data,
MOBY data etc.
(cooperation with NOAA)
Onboard calibration data
Other satellite data (TBD)

Other satellites(Main)

Standard: <0.5pixel
Goal: <0.25pixel

Other satellites(Main)

Release :0.3 (<=443nm),
0.2 (>443nm)(scene)(*8)

In-situ(Main)JAXA(RESTEC,
Tokai U.)JAXA

GCP database derived
from AVNIR-2 etc.

GCP database derived
from AVNIR-2 etc.
JAXA

Honda-Kajiwara
Nasahara

1C-1

SGLI

SGLI

Year-roundVegetation index[―]

BiRS simulations foruniform surfaces)
L2 atmospheric correctedreflectance product(MOD09, MYD09)

Other satellites(Auxiliary)

JAXA

Standard: 0.1(<=443nm), 0.05(>443nm)(scene)(*8)
Goal: 0.05(<=443nm), 0.025(>443nm)(scene)(*8)

In-situ(Main)

Honda-Kajiwara

Release:grass： 25% (scene),
forest： 20% (scene)

In-situ(Main)

Standard:
grass： 20% (scene),
forest： 15% (scene)Goal:grass： 10% (scene),
forest： 10% (scene)

Nasahara

JAXA

Honda-Kajiwara
Nasahara

Other satellites(Main)JAXA

In-situ(Main)

Honda-Kajiwara
Nasahara

1C-2

Spectral data measured
from UAV
Spectral data measured
from Tower
Spectral data measured
from UAV

MODIS of Terra &Aqua

Global but every
typical LCC (TBD)

Year-round or
SeasonallyFieldSpec, MS-720
Hyperspectral
CameraYatsugatake

Campaign

JaLTER, JapanFlux,
PEN sites

Year-roundforest：Yatsugatake

Campaign

grass・forest：JaLTER,
JapanFlux, PEN sites

Year-round

GlobalYear-roundforest：Yatsugatake

Campaign

grass, forest：JaLTER,
JapanFlux, PEN sites

Year-roundMS-700MS-720Spectral data measured
from UAV

FieldSpec, MS-720
Hyperspectral
CameraSpectral data measured
from Tower
Spectral data measured
from UAV
L2 VI products(MOD13,MYD13)

MS-700MS-720Spectral data measured
from UAV
Spectral data measured
from Tower
Spectral data measured
from UAV

MODIS of Terra &Aqua
JASMESCAI
FieldSpec, MS-720
Hyperspectral
CameraMS-700MS-720Above-groundbiomass[t/ha]

Release:grass： 50%,
forest： 100%In-situ(Main)

Honda

Honda-KajiwaraNasahara

Honda-KajiwaraJAXA
NakajiStandard:
grass：30%, forest：
50%
Goal:
grass：10%, forest：
20%

Other satellites(Main)

Honda-Kajiwara

model(Main)

Nagai

In-situ(Main)

Honda-KajiwaraNasahara

Honda-KajiwaraJAXA
NakajiVegetation
roughness index[―]

Release: grass･
forest： 40% (scene)

In-situ(Main)

Honda

Honda-Kajiwara

1C-3

AGBIO estimated from
Every Tree Measurements(DBH, Tree Hight, Tree
Density etc.)

AGBIO estimated from
3D-Laser Scanner datameasured at ground

Tree (direct)
measurements

3D-Laser Scanner

L2-L3 AGBIO products
derived from satellite
borne lider and SAR
Output of eco-system
model

PALSAR-2,
ISS/MOLI (L+5yr),
ISS/GEDI (L+5yr)
BEAMS (Sasai)

AGBIO estimated from
Every Tree Measurements(DBH, Tree Hight, Tree
Density)

Tree (direct)
measurements

AGBIO estimated from
3D-Laser Scanner datameasured at ground

VRI derived from 3D-Laser
Scanner data measured
from UAV or near surface(Tower)3D-Laser Scanner

3D-Laser Scanner

forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites
Mine site (GOSAT2) ofAustralia、Fujihokuroku,
Tomakomai, Uryuu,
Mase, Alaska (boreal,
200m sq scale),
Pasoh/ Malaysia(Tropical-rain)
forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites

Campaign

Campaign

Year-round
Global but every
typical LCC (TBD)

Year-roundforest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites
Mine site (GOSAT2) ofAustralia、Fujihokuroku,
Tomakomai, Uryuu,
Mase, Alaska (boreal,
200m sq scale),
Pasoh/ Malaysia(Tropical-rain)
forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites

Campaign

forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites

Campaign

Campaign

Shadow index[―]

Standard: grass・
forest： 20% (scene)
Goal: grass・forest：
10% (scene)

In-situ(Main)

Release: grass･
forest： 30% (scene)

In-situ(Main)Moriyama

Honda-Kajiwara

VRI derived from 3D-Laser
Scanner data measured
from UAV or near surface(Tower)3D-Laser Scanner

forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites

Campaign

Honda-Kajiwara

Spectral reflectance from
UAV
3D-Laser Scanner data &images from UAV

FieldSpec, MS-720
3D-Laser Scanner
Digital camera
etc.

forest：Yatsugatake,
Gotograss・forest：JaLTER,
JapanFlux, PEN sites

Campaign

Campaign

MS-700MS-720forest：Yatsugatake,
Gotograss・forest：JaLTER,
JapanFlux, PEN sites

Landsat8

grass：
forest：Goto Is.

Year-round

FieldSpec, MS-720
3D-Laser Scanner
Digital camera
etc.

forest：Yatsugatake,
Gotograss・forest：JaLTER,
JapanFlux, PEN sites

Campaign

MS-700MS-720forest：Yatsugatake,
Gotograss・forest：JaLTER,
JapanFlux, PEN sites

Nasahara

Standard:
grass・forest： 20%(scene)Goal:
grass･forest： 10%(scene)Other satellites(Auxiliary)Moriyama

In-situ(Main)

Honda-Kajiwara

Nasahara

Other satellites(Auxiliary)
Fraction ofabsorbed
photosynthetically
active radiation(fPAR) [―]Release:grass： 50%, forest：50%

In-situ(Main)Moriyama

Kobayashi(Univ.
Tsukuba),
Kobayashi(JAM
STEC)

Honda,
Kajiwara,
Nasahara,
Nagai

1C-4

Spectral reflectance from
Tower
Spectral data measured
from UAVL1 radiance of high-rsol.
satellite imagers
Spectral reflectance from
UAV
3D-Laser Scanner data &images from UAV
Spectral reflectance from
Tower
Spectral data measured
from UAVL1 radiance of high-rsol.
satellite imagers

Campaign

Landsat8

grass：
forest：Goto Is.

Year-roundPAR derived with PAR
meter or spectrometer(incident, reflercted,
transmitted PAR)measured from Towers

PAR meters
MS700
Spectrometer

Year-round

Combine canopy model.
<=
Ground LIDER+
Heli DSM

3D-Laser Scanner
Digital camera
etc.

forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites,
Australia, Fujihokuroku,
Tomakomai, Uryuu,
Mase
500m square sites

Standard:grass：30%、forest：
20%
Goal:
grass：20%, forest：
10%

Leaf area index [―]Release:grass： 50%, forest：
50%

Standard:
grass：30%、forest：
30%
Goal:
grass：20%, forest：
20%

Other satellites(Main)JAXA

L2 FPAR products(MOD15, MYD15)

MODIS of Terra &Aqua

GlobalYear-roundIn-situ(Main)

Honda, Kajiwara,
Nasahara,
Nagai

PAR derived with PAR
meter or spectrometer(incident, reflercted,
transmitted PAR)measured from Towers

PAR meters
MS700
Spectrometer

Year-round

Combine canopy model.
<=
Ground LIDER+
Heli DSM
In-situ measured LAI(from instrument(indirect) or grass cutting(direct) method)

3D-Laser Scanner
Digital camera
etc.

forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites
Australia, Fujihokuroku,
Tomakomai, Uryuu,
Mase

L2 LAI products (MODIS)MODIS of Terra &Aqua

In-situ(Main)

Kobayashi(Univ.
Tsukuba),
Kobayashi(JAMSTEC)

Honda, Kajiwara,
Nasahara,
Nagai

Other satellites(Main)JAXA

In-situ(Main)

Honda, Kajiwara,
Nasahara,
Nagai

1C-5

In-situ measured LAI(from instrument(indirect) or grass cutting(direct) method)

LAI-2000
Litter trap etc.

LAI-2000
Litter trap etc.

500m square sites
forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites
Australia, Fujihokuroku,
Tomakomai, Uryuu,
Mase Alaska (boreal,
200m sq scale),
Pasoh/ Malaysia(Tropical-rain)(500m square sites)
Global but every
typical LCC (TBD)

Campaign

forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites
Australia, Fujihokuroku,
Tomakomai, Uryuu,
Mase Alaska (boreal,
200m sq scale),
Pasoh/ Malaysia(Tropical-rain)(500m square sites)

Campaign

Year-roundLand surface
temperature [K]Release:
3.0K 以下 (scene)

In-situ(Main)MoriyamaMoriyama

in situ BT measured fromgroundIR thermometer

Railroad Valley, ND &Ivanpah playa, CA
Yatsugatake

Campaign

Honda-Kajiwara

In-situ BT measured fromUAV

IR thermometer

In-situ BT measured fromTower

IR thermometer

JaLTER, JapanFlux,
PEN sites

Year-round

LST converted from Tairobtained at Fluxsite, GTS,
GSOD or other sites
L2 LST products (MOD11,
MYD11)
L2 LST products from
Sentinel-3
in situ BT measured fromgroundThermometer

Fluxnet, GTS sites

Year-round

MODIS of Terra &Aqua
Sentinel-3

Global but every
typical LCC (TBD)

Year-roundIR thermometer

Campaign

In-situ BT measured fromUAV

IR thermometer

Railroad Valley, ND &Ivanpah playa, CA
Yatsugatake

In-situ BT measured fromTower

IR thermometer

Year-round

Tair obtained from
Fluxsite, GTS, GSOD orother sites
Cloud amount derived
from skycamera

Thermometer

JaLTER, JapanFlux,
PEN sites
GTS sites

Year-round

GTS cloudiness

Human-eyeOther satellites(Main)

L2 cloud flag product(MOD35, MYD35)MODIS
VIIRS etc.

Kumamoto,
Greenland, Abashiri,
Tsukuba, Shirase,
Noto, Yoyogi,
Iriomote, Osaka,
Tomakomai, Polarregion (Sbalvard,
Syowa St.)
GlobalIn-situ(Main)

same as CLFR

same as CLFR

Nasahara
JAXA

Standard:
2.5K 以下 (scene)
Goal:
1.5K 以下 (scene)

Other satellites(Main)JAXA

In-situ(Main)Moriyama
Honda-Kajiwara
Nasahara
JAXA

Cloud flag [―]Release: 10%(comparisonwith
sky-camera binary
image)

AtmosphereStandard&Goal:
Eavaluated as theIn-situ(Main)

Nakajima(main),
Ishimoto, Riedi,
Stamnes,
JAXA

Irie
Nakajima
Kuji
JAXA

1C-6

Sky-Camera

Campaign

Campaign

Year-roundYear-roundcloud fraction
products
Classified cloud
fraction [%]Cloud top temp &height[K], [km]Release: 20% (assolar radiation)(*6)

In-situ(Main)

Nakajima(main),
Ishimoto, Riedi,
IwabuchiNakajima,
Yamazaki,
Irie,
Kuji,
KhatriBSRN solar radiation data
Whole sky image data

Solar radiation
base
Sky-Camera(supplemental)

Climatology(Main)

ISCCP climatologicaldatasetVarious satellites

Standard: 15%( assolar radiation )(*6)
Goal: 10%（ as solar
radiation )(*6)

In-situ(Main)

BSRN solar radiation data

Solar radiation
base

Release: 1K(*1)

Climatology(Main)

Standard:
3K(*2)/2km(*2)
Goal:
1.5K(*2)/1km(*2)

In-situ(Main)

Other satellites(Main)

Whole sky image data

Nakajima(main),
Ishimoto, Riedi,
Iwabuchi

Sky-Camera(supplemental)

BRSR etc.

Year-roundKumamoto,
Greenland, Abashiri,
Tsukuba, Shirase,
Noto, Yoyogi,
Iriomote, Osaka,
Tomakomai, Polarregion (Sbalvard,
Syowa St.)
GlobalYear-round

BRSR etc.

Year-roundKumamoto,
Greenland, Abashiri,
Tsukuba, Shirase,
Noto, Yoyogi,
Iriomote, Osaka,
Tomakomai, Polarregion (Sbalvard,
Syowa St.)
GlobalYear-roundYear-round

JAXA

ISCCP climatologicaldatasetVarious satellites

Irie,
Nakajima,Yamaza
ki,Kuji, Khratri

Data measured withground-based radar

FALCON(radar)

Chiba, etc., Nieolson(Contact to Shiobarasan (Irie))

Year-round

Data measured withairborne lidar

NASA Airborne
lidar

Flight courses (TBD,
Shinozuka-san (CI ofSano PI) has info.)

Campaigns

Data measured withsatellite-borne lidar

Satellite borne
lidar

GlobalYear-round

JAXA

1C-7

Year-roundWater-cloud optical
thickness &effective radius[―], [μm]Release: 10%/30%( optial
thickess/radius )(*3)
Standard: 100% ( ascloud liquid water:*4)

Goal: 50% (*4) /20%(*5)

Other satellites(Main)

Nakajima(main),
Ishimoto, Riedi,
IwabuchiIrie, Nakajima,
Yamazaki, Kuji,
KhatriIn-situ(Main)

In-situ(Main)

Other satellites(Main)
Ice-cloud optical
thickness[―]

Release: 30%(*3)
Standard: 70%(*5)
Goal: 20 %(*5)

Other satellites(Main)
In-situ(Main)

Nakajima(main),
Ishimoto, Riedi,
IwabuchiIrie, Nakajima,
Yamazaki, Kuji,
KhatriOther satellites(Main)
Aerosol over the
ocean
[―]

Release:0.1( monthly ave. ofτa_670, 865)

In-situ(Auxiliary)

JAXA, Mukai,
Sekiguchi,
Ishimoto, Riedi

Irie, Yamazaki,
Aoki, K.,
Kobayashi,
Mukai, Sano,

L2 Cloud effective radius
prd. (MOD06, MYD06)

MODIS of Terra &Aqua

Mid- to Low latitude
area

Year-round

Cloud liquid water datafrom Ground based
passive microwave
radiometer (PMR)

Microwave
radiometer

Fukue, Hedo, Chiba(Skynet supersites)

Year-round

Cloud liquid water datafrom ground based
passive microwave
radiometer (PMR)
Cloud optical thickness
data from skyradiometer
L2 Cloud effective radius
prd. (MOD06, MYD06)

Microwave
radiometer

L2 Cloud optical thickness
prd. (MOD06, MYD06)
SKYNET data

MODIS of Terra &Aqua
Skyradiometer

L2 Cloud optical thickness
prd. (MOD06, MYD06)

MODIS of Terra &Aqua

Skyradiometer data on
Mirai, Shirase etc.

Skyradiometer

Microtops data from
Maritime Aerosol
Network

Microtops

Airborne Sunphoto databy NASA Ames
Other satellites(Main)JAXA

L2 Aersosol products(MOD04, MYD04)

1C-8

PMR by NICT＠Okinawa (TBD)

Skyradiometer
MODIS of Terra &Aqua

Airbone Sunphoto

MODIS of Terra &
Aqua
CAI
VIIRS

Fukue, Hedo, Chiba(Skynet supersites)
Thai, Gouhi, Chiba,
Fukue, Hedo

Year-round

GlobalYear-roundMid- to Low latitudearea
Thai, Gouhi, Chiba,
Fukue, Hedo (Skynet
super sites)
GlobalYear-round

Cruise route of Mirai,
Shirase etc.
Various sites

Campaign

Flight courses (TBD,
Shinozuka-san (CI ofSano PI) has info.)

Campaigns

GlobalYear-roundYear-roundYear-roundYear-roundCampaign

Standard:
0.1(scene’s τa_670,
865)(*7)
Goal: 0.05(scene’sτa_670, 865)

In-situ(Main)

Irie, Yamazaki,
Aoki, K.,
Kobayashi,
Mukai, Sano,NASA

Other satellites(Main)

Aerosol over theland [―]

Release:0.15( monthly ave.
of τa_380)

Standard:
0.15(scene’sτa_380) (*7)
Goal: 0.1(scene’sτa_380 )In-situ(Main)(JAXA)

JAXA, Mukai,
Sekiguchi,
Ishimoto, Riedi

Skyradiometer data on
Mirai, Shirase etc.

Skyradiometer

Microtops data from
Maritime Aerosol
Network

Microtops

Airborne Sunphoto databy NASA Ames
L2 Aersosol products(MOD04, MYD04)

Irie,
Aoki K., Mukai,
SanoYamazaki,Kobayashi,Various PI/CI

SKYNET (Aoki),
AERONET (Sano),Skyradiometer (Yamazaki,
etc.)
Microtops data
Airborne Sunphoto databy NASA Ames

Other satellites(Main)JAXA

L2 Aersosol products(MOD04, MYD04)

In-situ(Main)

Irie,
Aoki K.,
Mukai,Sano,
Yamazaki,Kobayashi,Various PI/CI

SKYNET (Aoki),
AERONET (Sano),Skyradiometer (Yamazaki,
etc.)
Microtops data
Airborne Sunphoto databy NASA Ames

Other satellites(Main)JAXA

L2 Aersosol products(MOD04, MYD04)

1C-9

Airbone Sunphoto
MODIS of Terra &
Aqua
CAI
VIIRS
Skyradiometer
AeronetSkyradiometer
Microtops
Airbone Sunphoto

MODIS of Terra &
Aqua
CAI
VIIRS
Skyradiometer
AeronetSkyradiometer
Microtops
Airbone Sunphoto

MODIS of Terra &
Aqua
CAI
VIIRS

Cruise route of Mirai,
Shirase etc.
Various sites

Campaign

Flight courses (TBD,
Shinozuka-san (CI ofSano PI) has info.)

Campaigns

GlobalYear-round

Many Skynet sites(<100)
Many Aeronet sites(<100)
MRI sites
Various sites
Flight courses (TBD,
Shinozuka-san (CI ofSano PI) has info.)
GlobalYear-roundYear-roundYear-roundCampaigns
Campaigns

Many Skynet sites(<100)
Many Aeronet sites(<100)
MRI sites
Various sites
Flight courses (TBD,
Shinozuka-san (CI ofSano PI) has info.)
GlobalYear-roundYear-roundYear-roundCampaigns
Campaigns

Campaign

Year-roundYear-roundNormalized waterleaving radiance[W/m2/str/μm or
1/sr]

Ocean
Atmosphericcorrection param.
[―]

Photosynthetically
Available Radiation[Ein/m2/day or mol
photons/m2/day]Release: 60%(443~565nm)

In-situ(Main)Toratani,
Frouin, JAXA,
StamnesToratani, Frouin,
Hirawake,
Ishizaka,
Suzuki,
Kobayashi,
Khahru, Antoine,
Kuwahara, Isada,
Higa,
HirataIn-situ measured opticaldata

PRR (Hirawake,etc.)
TRIOS (Ishizaka,etc.)
C-OPS (Suzuki)

ECS, A-line, O-line,
Funka-bay, Tokyobay,Seto Inland sea,
Chukchi Sea, Bering
Sea, North Pacific, Isebay, Akkeshi-bay,
Toyama-Bay

Campaign

Other satellites(Main)

JAXA

MOD18

AQUA/MODIS,NPP/VIIRS

GlobalYear-round

Standard: 50%(<600nm)
0.5W/m2/str/um(>600nm)
Goal: 30% (<600nm)
0.25W/m2/str/um(>600nm)

In-situ(Main)

In-situ measured opticaldata

PRR (Hirawake,etc.)
TRIOS (Ishizaka,etc.)
C-OPS (Suzuki)
Aeronet-OC

ECS, A-line, O-line,
Funka-bay, Tokyobay,Seto Inland sea,
Chukchi Sea, Bering
Sea, North Pacific, Isebay, Akkeshi-bay,
Toyama-Bay

Campaign

Release: 80%(τa_865)

In-situ(Main)Toratani, Frouin,
Hirawake,
Ishizaka,
Suzuki,
Kobayashi,
Khahru, Antoine,
Kuwahara, Isada,
Higa,
HirataKobayashi
TorataniNASA

Aerosol optical thickness
data
Aerosol optical thickness
data
Aerosol optical thickness
data

Skyradiometer
AERONET/maritime(NASA)

Cruise track of Shirase
etc.
Many Aeronet sites(<100)
GlobalCampaign

Aerosol optical thickness
data

Skyradiometer
AERONET/maritime(NASA), SKYNET

Cruise track of Shirase
etc.
Many Aeronet sites(<100)

Campaign

Buoy: NDBC, TAO/TRITON
etc.
Ship: PRR data

PRR

Buoy sites
ECS, A-line, O-line,
Funka-bay, Tokyobay, Coast of Oita,
Chukchi Sea, Bering
Sea, North PacificYear-roundCampaign

Toratani,
Frouin,JAXA,
Stamnes

Other satellites(Main)JAXA

Standard: 50%(τa_865)
Goal: 30%

In-situ(Main)

Release: 20%(10km/month)In-situ(Main)

Kobayashi,
Toratani, etc.
NASA，
Cooperation with
Atmos. Gr.
Hirawake,
Ishizaka,
Suzuki,
Hirata,Saikaiku,

JAXA & Frouin

1C-10

AQUA/MODIS、
NPP/VIIRS

Year-roundChlorophyll-aconcentration[mg/m3]Standard: 15%(10km/month)
Goal: 10%(10km/month)In-situ(Main)

Release: -60~+150%(open sea)In-situ(Main)

JAXA, Toratani,
HirataOther satellites(Main)

Total suspended
matterconcentration[g/m3]

Colored dissolved
organic matter [m1]Standard: 60~+150%
Goal: -35~+50%(open sea),-50~+100% (coastal)In-situ(Main)

Release: -60~+150%(open sea)In-situ(Main)

Standard: 60~+150%
Goal: -50~+100%
Release: -60~+150%(open sea)

Other satellites(Main)
In-situ(Main)
In-situ(Main)

Other satellites(Main)
Standard: 60~+150%
Goal: -50~+100%

JAXA, Toratani,
HirataIn-situ(Main)

JAXA, Toratani,
HirataTohoku,SEABASS

Buoy: NDBC, TAO/TRITON
etc.
Ship: PRR data

PRR

Hirawake,
Ishizaka,
Suzuki,
Kobayashi,
Saikaiku,
Tohoku,SEABASS
JAXA

Pigment concentration
data measured withfluorescense method and
HPLC at Ship

Fluorescense
method, HPLC

MOD20, MOD21

AQUA/MODIS、
NPP/VIIRS

Hirawake,
Ishizaka, Suzuki,
Kobayashi,
Saikaiku,
Tohoku,SEABASS

Pigment concentration
data measured withfluorescense method and
HPLC at Ship

Fluorescense
method, HPLC

Ishizaka,
Kobayashi,
SeaBASSJAXA

Dry weight of filtered SS
sampled at Ship

Sampling andfiltering

MOD23

Ishizaka,
Kobayashi,
SeaBASS
Hirawake,
Ishizaka,
Kobayashi,
Saikaiku,
SeaBASSJAXA

Dry weight of filtered SS
sampled at Ship

Hirawake,
Ishizaka,
Kobayashi,

1C-11

Buoy sites
ECS, A-line, O-line,
Funka-bay, Tokyobay, Coast of Oita,
Chukchi Sea, Bering
Sea, North Pacific
ECS, A-line, O-line,
Funka-bay, Tokyobay,Seto Inland sea,
Chukchi Sea, Bering
Sea, North Pacific, Isebay, Akkeshi-bay,
Toyama-Bay
GlobalYear-roundCampaign

ECS, A-line, O-line,
Funka-bay, Tokyobay,Seto Inland sea,
Chukchi Sea, Bering
Sea, North Pacific, Isebay, Akkeshi-bay,
Toyama-Bay
ECS, Tokyo-bay

Campaign

AQUA/MODIS、
NPP/VIIRS
Sampling andfiltering

GlobalYear-round

ECS, Ariake, Tokyobay

Campaign

Ship: Absorption data ofsampling water

Absorption meter

ECS, Ariake, Tokyobay, Ise-bay, Chukchi
Sea, Bering Sea,
Akkeshi-bay

Campaign

MOD24

AQUA/MODIS

GlobalYear-round

Ship: Absorption data ofsampling water

Absorption meter

ECS, Tokyo-bay, Isebay, Chukchi Sea,
Bering Sea, Akkeshibay

Campaign

Campaign

Year-roundCampaign

Saikaiku,
SeaBASSSea surface
temperature[℃]

Release: 0.8K
(daytime only)

In-situ(Main)JAXA

JAXA

Hirawake,
Ishizaka,
Kobayashi,
Saikaiku, Tohoku,
SEABASS

Standard: 0.8K
Goal: 0.6K

Release: 10%(comparison withother satellites
products)

CryosphereStandard：7%
Goal：5%

Bucket,thermometer

GTS sites

Year-round

ECS, A-line, O-line,
Funka-bay, Tokyobay,Seto Inland sea,
Chukchi Sea, Bering
Sea, North Pacific, Isebay, Akkeshi-bay,
Toyama-Bay
GlobalCampaign

Other satellites(Main)JAXA

MOD28
SST of AMSR2

MODIS
AMSR2

In-situ(Main)JAXA

GTS
iQuam (buoy data for
AMSR2 val)
In-situ measured SST
Bucket SST, Nautical SST,
Argo float SST, etc.

thermometer
onboard buoy

GTS sites

Year-round

Bucket,thermometer

Campaign

MOD28
SST of AMSR2
In-situ snow depth from
WMO(GSOD),
In-situ snow depth fromNOAA(GHCND)
L2 snow cover prd.
(MOD10、MYD10)
L2 snow cover productL1 radiance

MODIS
AMSR2
supersonic or
laser
supersonic or
laser
MODIS
VIIRS
Landsat8 etc.

ECS, A-line, O-line,
Funka-bay, Tokyobay,Seto Inland sea,
Chukchi Sea, Bering
Sea, North Pacific, Isebay, Akkeshi-bay,
Toyama-Bay
Global
GTS sites
GTS sites

Year-round

GlobalYear-roundIn-situ snow depth from
WMO(GSOD),
In-situ snow depth fromNOAA(GHCND)

supersonic or
laser
supersonic or
laser

GTS sites
GTS sites

Year-round

Hirawake,
Ishizaka,
Kobayashi,
Saikaiku, Tohoku,
SEABASS

Snow and Ice
covered area[―]

GTS
iQuam (buoy data for
AMSR2 val)
In-situ measured SST
Bucket SST, Nautical SST,
Argo float SST, etc.

Other satellites(Main)
In-situ(Auxiliary)

JAXA
Stamnes

JAXA

Other satellites
Climatology(Main)JAXA

In-situ(Auxiliary)

JAXA

1C-12

Year-roundYear-roundOther satellites
Climatology(Main)
Okhotsk sea-ice
distribution[―]

Snow and ice
surfaceTemperature[K]

Release: 10%(comparison withother satellite
products)

Other satellites(Main)

Standard：5%
Goal：3%In-situ(Auxiliary)
Other satellites
Climatology(Main)

Release: 5K( comparison withother satellite
products andmeteorologicalmeasurements )In-situ(Main)

Other satellites(Main)JAXA

Stamnes

JAXA

JAXA
JAXA

StamnesAoki, JAXAJAXAClimatology(Main)

Standard：2K
Goal：1K

In-situ(Main)

Aoki, JAXA

1C-13

L2 snow cover prd.
(MOD10、MYD10)
L2 snow cover productL1 radiance

MODIS
VIIRS
Landsat8 etc.

Global

L2 sea-ice cover product(MOD10、MYD10)
L2 sea-ice cover productL1 radiance
Sea ice conc. measured
from ground, airplane etc.
L2 sea-ice cover product(MOD10、MYD10)
L2 sea-ice cover productL1 radiance

MODIS
VIIRS
Landsat8 etc.

Sea of Okhotsk

Dec.-May

Human-eye,
CameraMODIS
VIIRS
Landsat8 etc.

Sea of Okhotsk

Dec.-May

Sea of Okhotsk

Dec.-May

In-situ Tair obtained from
GTS, GSOD, GC-Net etc.
Longwave radiation
observation fromPROMICE AWSs.

Thermometer at
GTS
ArCS II-SIGMA,
GC-Net and
PROMICE AWSs or
ocean bouys
GLI
MODIS
VIIRS
Landsat8 etc.

GTS sites etc.

Year-round

Global, Greenland,
Antarctica etc.

Year-round

Thermometer at
GTS sites or oceanbouys

GTS sites etc.

Year-round

Thermometer at
GTS
ArCS II-SIGMA,
GC-Net and
PROMICE AWSs or
ocean bouys
IR thermoeter, FTIR, Thermometeretc.

GTS sites etc.

Year-round

ArCS II-SIGMA, GCNet and PROMICEAWSs on Greenland

Campaign

GLI snow surface temp.
(Climatology)
MODIS snow surf. temp.
(Climatology)
VIIRS snow surface temp.
Landsat8 snow surface
temp. (High resol.)
Climatology of Tair etc.
In-situ Tair obtained from
GTS, GSOD, GC-Net etc.
In-situ Tsnow, Tair andLongwave radiation data

Year-round

ArCS II-SIGMA, GCNet and PROMICEAWSs on Greenland

Hokkaido, Finland,
Greenland, Antarcticaetc.

Snow grain size ofshallow layer[μm]

Release: 100%
(evaluated withclimatology oftemperature‐snow
grain size
relationship)Standard：50%
Goal：30%

Other satellites
Climatology(Main)

Stamnes

JAXA

In-situ(Main)

Aoki, JAXA

Other satellites
Climatology(Auxiliary)

JAXA

GLI snow grain size
(Climatology)
MODIS snow grain size
(Climatology)
VIIRS snow grain size
Landsat8 snow grain size
(High resol.)
SGLI SIST product

GLI
MODIS
VIIRS
Landsat8 etc.
SGLI

Global, Greenland,
Antarctica etc.

In-situ Tair obtained from
GTS etc
Snow grain size derived
from in-situ snow pit dataand opticalmeasurements(reflectance, SSA etc.)
GLI snow grain size
(Climatology)
MODIS snow grain size
(Climatology)
VIIRS snow grain size
Landsat8 snow grain size
(High resol.)

Thermometer at
GTS
Snow Pit Work
Tools,
FieldSpecFR, NIR
Camera, IceCube,HISSGraS etc.
GLI
MODIS
VIIRS
Landsat8 etc.

GTS sites etc.

Year-round

Hokkaido, Finland,
Greenland, Antarctica
etc.

Campaign

Global, Greenland,
Antarctica etc.

Year-round

Common notes:*1. Heritage levels from ADEOS-II/GLI study are shown by A-C; A: high heritage, B: Remaining issues, C: new or many issues remaining to be resolved*2. The “release threshold” is minimum levels for the first data release at one year from launch. The "standard" and "research" accuracies correspond to full and extra success criteria of the mission. Accuracies arebasically shown by RMSE.
Radiance data notes:*3. Absolute error is defined as offset + noise; relative error is defined as relative errors among channels, FOV, and so on. Release threshold of radiance is defined as estimated errors from vicarious, onboard solar
diffuser, and onboard blackbody calibration because of lack of long-term moon samples
Atmosphere notes:*4. Vicarious val. on sea-surface temperature and comparison with objective analysis data
*5. Inter comparison with airplane remote sensing on water clouds of middle optical thickness*6. Release threshold is defined by vicarious val. with other satellite data (e.g., global monthly statistics in the mid-low latitudes)*7. Comparison with cloud liquid water by in-situ microwave radiometer*8. Comparison with optical thickness by sky-radiometer (the difference can be large due to time-space inconsistence and large error of the ground measurements)*9. Comparison with in-situ observation on monthly 0.1-degree*10. Estimated by experience of aerosol products by GLI and POLDER
Land data notes:*11. Defined with land reflectance~0.2, solar zenith<30deg, and flat surface. Release threshold is defined with AOT@500nm<0.25

1C-14*12. Night time 250m product can be produced by special observation requests of 1.6µm channel*13. Evaluate in semiarid regions (steppe climate, etc.)*14. Fires >1000K occupying >1/1000 on 1km pixel at night (using 2.2um of 1 km and thermal infrared channels)
Cryosphere notes:*15. Defined as height/width of the surface structures

1C-15

TABLE C3 Expected reference data for the validation of GCOM-C/SGLI research products
Categor
Product [Unit]yLand net
primary
production[gC/m2/year]

Accuracy Targets
Goal: 30％(annual
ave.)

Land

ET index [―]Goal: 10% (asclassification
error)(*13)

Fire detection
index [―]

Goal: 20% (asclassification
error)(*14)

Val. Data Type
Algorithm PIs(Main/Auxiliary)In-situYang(Main)
Tachiiri

Other satellites(Main)
In-situ(Main)

Other satellites(Main)

Land cover type Goal: 30% (asIn-situ[―]classification error) (Main)
Other satellites(Main)

Land surface
albedo [―]Goal: 10%In-situ(Main)

Atmosphere

Water cloud
geometrical
thickness[m]

Goal: 300m

In-situ(Main)

Other satellites(Main)

Instruments

Observation Sites

Nasahara
Nagai

LNPP data derived fromvarious variables
measured at flux tower
sites
LNPP products derived
from other satellites
Latent heat flux measured
at flux tower sites

Thermometer,
spectrometer,pyranometer etc.

forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites

MODIS
VIIRS etc.
Eddy Correlation Flux
Measurement System

Year-round

MODIS
Landsat8

Global covering every
typical LCT
forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites
AmeriFlux, AsiaFlux
Global covering every
typical vegetation type
Global covering every
typical LCT

Every year (TBD)

Landsat8
AVNIR-2
etc.

Global covering every
typical LCT

Seasonally (TBD)

Spectometer

forest：Yatsugatake,grass・forest：JaLTER,
JapanFlux, PEN sites

Campaign/Year-round

MODIS
VIIRS
etc.
Falcon radar

Global covering every
typical LCT

Year-round

Falcon sites

Year-round

Ceilometer

Cruise course of Shirase
between Japan and theAntarctica

Campaign

GlobalYear-round

TasumiNasahara
JAXA

JAXA

JAXA

Hotspots data derived
from other satellites

JAXA
SoyamaTakagiNasahara

SoyamaNasahara

Degree Confluence Project(DCP) data

JAXA
SoyamaNasahara

L1 radiance data of highresolution satellite

JAXA, Susaki

HondaKajiwara
Nasahara
JAXA

Other satellites(Main)Kuji,
Nagao

Period, Frquency,
Obs. Cycles
Year-round

Validation PIs In-situ Data

Irie,
Kuji

Google Earth
Spectral reflectance datameasured at flux tower,
RC helocopter etc
LALB products derived
from other satellites
Cloud profile data
Cloud bottom heightobtained with ceilometer
onboard Shirase

Cloud top height data
Calipso etc.
etc. measured from space

1C-16

Campaign/Year-roundYear-roundLong-wave
radiation flux
[W/m2]

Goal: Downward
flux: 10W/m2,
Upward: 15W/m2(0.1deg., monthly
ave)

In-situ(Main)

Kuji,
Nagao

Khatri,Yamazaki

Other satellites
Climatology(Main)
Short-wave
radiation flux
[W/m2]

Goal: Downward:
13W/m2,
Upward: 10W/m2(0.1deg., monthly
ave)

In-situ(Main)

JAXA,
Nagao

Khatri,Yamazaki

Other satellites
Climatology(Main)
Euphotic zone
depth
[m]

Ocean

Goal: 30% (inferred In-situ
from extinction(Main)
coefficient)

HirataInherent optical Goal: Absorption
In-situproperties
coefficient(Main)[1/m]@440nm:RMSE<0.25 andbackscattering
coefficient ofphytoplankton@55
0nm: RMSE<0.25

HirataToratani
FrouinHirawake,
Ishizaka,
Suzuki,
Kobayashi,
Khahru,Antoine,Kuwahara,
Isada,
Higa,
HirataToratani,
Hirawake,
Ishizaka,
Suzuki,
Kobayashi,
Khahru,Antoine,Kuwahara,
Isada,
Higa,

Longwave radiation datafrom radiation network
Longwave radiation datafrom from flux network

Net radiometer etc.

Clouds and aerosol data
Global radiative flux data
(ISCCP-FD)
Surface Radiation Budget(GEWEX-SRB)
Longwave radiation datafrom radiation network
Longwave radiation datafrom from flux network

MODIS
ISCCP
GEWEX

Clouds and aerosol data
Global radiative flux data
(ISCCP-FD)
Surface Radiation Budget(GEWEX-SRB)
In-situ measured optical
data

MODIS
ISCCP
GEWEX
PRR (Hirawake, etc.)
TRIOS (Ishizaka, etc.)
C-OPS (Suzuki)

ECS, A-line, O-line,
Campaigns
Funka-bay, Tokyobay,Seto Inland sea,
Chukchi Sea, Bering Sea,
North Pacific, Ise-bay,
Akkeshi-bay, Toyama-Bay

Pigment concentration
data measured withfluorescense method and
HPLC at Ship

Fluorescense method,
HPLC

ECS, A-line, O-line,
Campaigns
Funka-bay, Tokyobay,Seto Inland sea,
Chukchi Sea, Bering Sea,
North Pacific, Ise-bay,
Akkeshi-bay, Toyama-Bay

1C-17

Net radiometer etc.

BSRN, Skynet, JMA etc
sites
JaLTER, JapanFLux, PEN,
Fluxnet sites
Global

BSRN, Skynet, JMA etc
sites
JaLTER, JapanFLux, PEN,
Fluxnet sites
GlobalYear-roundYear-roundYear-roundYear-roundHirata
FrouinOcean net
primary
productivity[mgC/m2/day]

Goal: 70%
(monthly ave.)

In-situ(Main)

Hirawake,
Ishizaka,
Tachiiri

Hirawake,
Ishizaka,
Tachiiri

ONPP derived from in-situ FRRF
measurements

Phytoplankton Goal: Classification
functional type error of[―]
dominant/non‐dominan t spesies
of large/small
phytoplankton:
20%, orclassification errorof dominantfunctional type in aphytoplankton
group: 40%
Redtide [―]Goal: 20% (asclassification
Error)

In-situ(Main)

Hirawake,
HirataHirawake,
HirataPigment concentration
data measured withfluorescense method and
HPLC at Ship

Fluorescense method,
HPLC

In-situ(Main)

Ishizaka,
Kobayashi,
Higa

Ishizaka,
Kobayashi,
Higa

Existence of red tide
observed by human eyes

Human eye

Multi sensor
merged oceancolor
parameters[mg/m3]

Goal:-35~+50%(open sea),-50~+100%(coastal)

In-situ(Main)JAXA,
Wang

JAXA, Wang

Pigment concentration
data measured withfluorescense method and
HPLC at Ship

Fluorescense method,
HPLC

Multi sensor
merged sea
surfacetemperature[℃]

Goal: 0.8K

Other satellites(Main)JAXA

JAXA

L2 SST products

JAXA

GTS
iQuam (buoy data for
AMSR2 val)

In-situ(Main)

1C-18

ECS, A-line, O-line,
Campaigns
Funka-bay, Tokyo-bay,
Coast of Oita, Chukchi
Sea, Bering Sea, North
Pacific
ECS, A-line, O-line,
Campaigns
Funka-bay, Tokyo-bay,
Coast of Oita, Chukchi
Sea, Bering Sea, North
Pacific, Okhotsk, East andwest of tohoku, east
setonai-kai, Ise-bay

Campaigns

MODIS, VIIRSFunka-bay, Tokyo-bay,
Coast of Oita, East andwest of tohoku, east
setonai-kai, Ise-bay
ECS, Ariake, A-line, Oline, Funka-bay, Tokyobay, Coast of Oita,
Chukchi Sea, Bering Sea,
North Pacific, Okhotsk,
East and west of tohoku,
east setonai-kai, Ise-bay
GlobalThermometer

GTS sites

Year-roundCampaigns

Year-roundSnow and iceclassification[―]

Goal：10%

Other satellites(Main)

Stamnes, Aoki

In-situ(Main)Snow area inforest andmountain[―]

Goal：30%

Other satellites(Main)

JAXA

JAXA

JAXA
(Stamnes)

In-situ(Auxiliary)

JAXA

JAXA

Aoki

Cryosphere

L2 snow cover prd.
(MOD10、MYD10)
L2 snow cover productL1 radiance
In-situ photograph taken
at Buoy, Ship, etc.
Photograph taken from
Airplane
L2 snow cover prd.
(MOD10、MYD10)
L2 snow cover productL1 radiance

MODIS
VIIRS
Landsat8 etc.

GlobalYear-roundWeb camera etc.

Buoys, Ships, etc.

Year-round

MODIS
VIIRS
Landsat8 etc.

GlobalYear-roundIn-situ photograph taken
at ground sites etc.
Photograph taken from
Airplane
Snow grain size derived
from in-situ snow pit dataand optical measurements

Web camera etc.

Mountain and forestsites, etc.

Year-round

Snow Pit Work Tools,
FieldSpecFR, NIR
Camera, IceCube,HISSGraS etc.

Hokkaido, Greenland,
Antarctica etc.

Campaign

Hokkaido, Greenland,
Antarctica etc.

Campaign

Spectrometer
Hokkaido, Greenland,(FieldSpecFR etc.),
Antarctica etc.
Snow Pit Work Tools,
NIR Camera, IceCube,HISSGraS etc.
Spectrometer
Hokkaido, Greenland,(FieldSpecFR etc.),
Antarctica etc.
Snow Pit Work Tools,
Snow filteration system

Campaign

Greenland, Antarctica

Annually

Snow grain size Goal：50%
of subsurface
layer [μm]In-situ(Main)

Stamnes, Aoki

Snow grain size Goal：50%
of top layer[μm]

In-situ(Main)

Stamnes, Aoki, Aoki
Kokhanovsky

Snow grain size derived
Snow Pit Work Tools,
from in-situ snow pit data FieldSpecFR, NIR
and optical measurements Camera, IceCube,HISSGraS etc.

Snow and ice
albedo [―]Goal：7%In-situ(Main)

Stamnes, Aoki, Aoki
Kokhanovsky

Albedo calculated basedon in-situ measured
optical data and snow pit
work data

Snow impurity[ppmw]

Goal：50%In-situ(Main)

Stamnes, Aoki, Aoki
Kokhanovsky

Ice sheetsurfaceroughness [―]Goal：0.05 (*15)

Other satellites(Main)Aoki

Snow impurity
concentration estimatedfrom in-situ measured
optical data and also
directly measured byfiltering method
Roughness estimated from MODIS, MISR, VIIRS
other satellite data
Landsat8 etc.

Aoki

1C-19

Campaign

Model(Main)
Ice sheet
Goal：<500m
boundarymonitoring [―]Other satellites
Climatology(Auxiliary)

JAXA

JAXA

Roughness estimatedRadiative transfer code Greenland, Antarctica
through simulations of(ARTMASS)
etc.
snow BRDF using radiativetransfer code
L1 radiance data
MODIS
Antarctica etc.
VIIRS
Landsat8 etc.

AnnuallyMonthlyCommon notes:*1. Heritage levels from ADEOS-II/GLI study are shown by A-C; A: high heritage, B: Remaining issues, C: new or many issues remaining to be resolved*2. The “release threshold” is minimum levels for the first data release at one year from launch. The "standard" and "research" accuracies correspond to full and extra success criteria of the mission. Accuracies arebasically shown by RMSE.
Radiance data notes:*3. Absolute error is defined as offset + noise; relative error is defined as relative errors among channels, FOV, and so on. Release threshold of radiance is defined as estimated errors from vicarious, onboard solar
diffuser, and onboard blackbody calibration because of lack of long-term moon samples
Atmosphere notes:*4. Vicarious val. on sea-surface temperature and comparison with objective analysis data
*5. Inter comparison with airplane remote sensing on water clouds of middle optical thickness*6. Release threshold is defined by vicarious val. with other satellite data (e.g., global monthly statistics in the mid-low latitudes)*7. Comparison with cloud liquid water by in-situ microwave radiometer*8. Comparison with optical thickness by sky-radiometer (the difference can be large due to time-space inconsistence and large error of the ground measurements)*9. Comparison with in-situ observation on monthly 0.1-degree*10. Estimated by experience of aerosol products by GLI and POLDER
Land data notes:*11. Defined with land reflectance~0.2, solar zenith<30deg, and flat surface. Release threshold is defined with AOT@500nm<0.25*12. Night time 250m product can be produced by special observation requests of 1.6µm channel*13. Evaluate in semiarid regions (steppe climate, etc.)*14. Fires >1000K occupying >1/1000 on 1km pixel at night (using 2.2um of 1 km and thermal infrared channels)
Cryosphere notes:*15. Defined as height/width of the surface structures

1C-20

Table C4 Definition of the disclosure level (DL)General users

Registered users

EarthCARE PI

GCOM PI

EORC researchers

Disclosure level(A-D) to be set bydata provider(A)
EORC Internal use
only

OK

-

-

-

-

(B1)
GCOM related PIs
only

OK

OK

-

-

-

Usage

1) Cal & Val of SGLI products and/or applications for Earth sciences (such as
scatter plots, statistics from which raw data cannot be reproduced) are
possible to be published. It is necessary to describe the use of JAXA’s
database and the organization of data acquisition in theacknowledgement *1
2) Redistribution of the raw data is prohibited.
1) Cal & Val of GCOM products and/or applications for Earth sciences are
possible to be published. It is necessary to agree with data provider about
how to acknowledge the favor (e.g., including data provider as a co-author
or in the acknowledgement) and to describe the use of JAXA’s database
and the organization of data acquisition in the acknowledgement*1.
2) Data use beyond the objectives of the GCOM mission is prohibited.
3) Redistribution of the raw data is prohibited.
1) Cal & Val of EarthCARE products and/or applications for Earth sciences are
possible to be published. It is necessary to agree with data provider about
how to acknowledge the favor (e.g., including data provider as a co-author
or in the acknowledgement) and to describe the use of JAXA’s database
and the organization of data acquisition in the acknowledgement *1.
2) Data use beyond the objectives of the EarthCARE & GCOM mission isprohibited.
3) Redistribution of the raw data is prohibited.
1) User registration is required.
2) Applications for Earth sciences are possible to be published. It is necessary
to submit an application form to JAXA prior to the publication. Also, it isnecessary to to describe the use of JAXA’s database and the organizationof data acquisition in the acknowledgement*1.
3) Redistribution of the raw data is prohibited.

(B2)
GCOM &
EarthCARE PIs
only

OK

OK OK

-

-

(C)
Registered users

OK

OK OK OK-

OK OK OK

1) It is necessary to describe the use of JAXA’s database when using the dataand publishing results. It is also necessary to report the results ofOKpublication to JAXA*1.
2) Redistribution of the raw data is prohibited.

(D)
Open to the public OK(no limitation)*1 follow the JAXA’s policy on data use

1C-21

Land

Table C5 GCOM-C PIs in the previous RA
PI_Name
Yoshiaki HONDA

Affiliation
Chiba Univ.

Research title
Upgrading AGB estimation using BRDF based on SGLI observation data.

Kenlo Nasahara

Tsukuba Univ.

Development of LAI/FAPAR product and global land cover maps

Hideki
KOBAYASHI
Tatsuro Nakaji

JAMSTECWei Yang

Chiba Univ.

Noriko SOYAMA

Tenri Univ.

Development of the voxel-based plant canopy radiative transfer and estimation andvalidation of large-scale ecosystem parameters from SGLI
Development of multiscale forest AGB validation sites equipping tree census and
3D forest volume data set
Generation of global land surface phenology and carbon flux products using GCOMC/SGLI data
Development and improvement of GCOM-C/SGLI LST estimation algorithm,
Development and improvement of GCOM-C/SGLI Shadow index estimation
algorithm
Development of global land cover classification algorithms and validation methods

Masahiro Tasumi

Miyazaki Univ.

Development of GCOM-C Global ETindex Estimation Algorithm

Hokkaido Univ.

Masao MORIYAMA Nagasaki Univ.

Takayuki KANEKO Tokyo Univ. ERI
Masataka TAKAGI Kochi Univ. of Technology
Takashi Nakajima

Tokai Univ.

Kentaroh Suzuki

Tokyo Univ. AORI

Hiroshi Ishimoto

JMA MRI

Global observations of cloud from the GCOM-C SGLI for improving cloud sciences
and contributing climate change studies, -Algorithms and validationA study of cloud microphysical structures and processes with a combined use of
GCOM-C/SGLI multi-wavelength measurements
Development of an algorithm for three-dimensional cloud from multispectral andmultidirectional measurement by SGLI and validation of cloud products
Advanced volcanic ash algorithm using multiple satellites observation

Sonoyo Mukai

Makoto KUJI

The Kyoto College ofGraduate Studies for
Informatics
Tokyo Univ. of Marine
Science and Technology
Nara Women's Univ.

Elucidation of the characteristics of atmospheric particulates through the
integrated use of "polarization and simultaneous multi-wavelength (including nearultraviolet) observation data" by SGLI
Improvement of an advanced remote sensing algorithm for atmospheric aerosols
using SGLIRetrieval and validation of cloud geometrical properties

Hitoshi Irie

Chiba Univ.

Akihiro Yamazaki

JMA MRI

Kazuma Aoki

Toyama Univ.

Promotion of applied researches with GCOM-C atmosphere products by precise
validation utilizing SKYNET and A-SKY international ground-based remotesensing observation networks
Acquisition of validation data by ground-based radiation observation andevaluation of GCOM-C atmospheric products
Aerosol optical properties of atmosphere and their effects of earth climate change

Pradeep Khatri

Soka University

Quality assessment of cloud properties observed by SGLI/GCOM-C

Hiroshi Kobayashi

Yamanashi Univ.

Jérôme RIEDI

Université de Lille

Validation of GCOM-C products related to marine aerosols by shipboard observationand development of mineral dust index
Investigation of the cloud top thermodynamic phase from the synergistic use ofpolarimetric, multi-directional, and high temporal resolution observations

Hiroto Higa

Yokohama National Univ.

Taka Hirata

Hokkaido Univ.

Joji Ishizaka

Nagoya Univ.

Shintaro Takao

NIES

Toru Hirawake

NIPR

Robert Frouin

Scripps Institution of
Oceanography

David Antoine

Curtin Univ.

Atmosphere

Hironobu Iwabuchi Tohoku Univ.

Ocean

Advanced volcano observation using GCOM-C SGLI images: elucidation of theeruptive process and examinations towards operational monitoring
Improvement of Mapping Tender Green and Autumn Color using GCOM-C

Miho Sekiguchi

Victor S. Kuwahara Soka Univ.
Eko Siswanto

JAMSTEC

Joaquim I. Goes

Columbia Univ.

Development of high accuracy GCOM-C ocean color products and water quality data
assimilation system for coastal areas and lakes
Validating and updating SGLI ocean colour products for marine ecosystemapplications
Validation of GCOM-C coastal products and the application
Effects of phytoplankton community composition and new production on nitrogenand carbon dynamics: A GCOM-C/SGLI perspective
Practical use of the GCOM-C/SGLI 250 m resolution data in the Antarctic sea icezone and its implication for estimations of phytoplankton biomass and primary
production
Estimating the fraction of PAR absorbed by live phytoplankton from SGLI data (Aglobal time series of the fraction of photosynthetically available radiation absorbed
by live phytoplankton from GCOM-C SGLI data)
Validation of GCOM-C/SGLI geophysical products over varied oceanographic
regimes
Characterization and Application of GCOM-C Bio-optical Products in Oceanic,
Coastal and Inland Waters
GCOM-C SGLI-based near-real-time observing system for monitoring ocean color in
Asian waters(A) Sea Surface Nitrate and Nitrate Based New Production - two innovative research
products from SGLI on board GCOM-C, and (B) Exploiting multi-platform, multisensor data for improved measurements of Net Primary Production from GCOM-C
SGLI for climate change studies

1C-22

Cryosphere
Multidisciplinary

Fumihiro
Takahashi
Menghua Wang

Green & Life Innovation,
Inc
NOAA/NESDIS/STAR

Lachlan McKinna

Go2Q Pty Ltd

Application examination research on the use of GCOM-C data for predicting andpreventing biofouling on fixed nets in coastal areas
NOAA-JAXA Collaborations: Evaluation and Applications of SGLI/GCOM-C Ocean
Color Products
Advanced NASA inherent optical properties algorithm support for SGLI

Teruo Aoki

NIPR

Algorithm improvement and validation for GCOM-C/SGLI snow and ice products

Knut Stamnes

Stevens Institute ofTechnology

GCOM-C/SGLI snow/ice products: Improvements and continued validation with
post-launch data

Masahiro Hori

Toyama Univ.

Keiya Yumimoto

Kyusyu Univ.

Daisuke Goto

NIES

Sei-Ichi Saitoh

Digital Hokkaido

Tomonori Isada

Hokkaido Univ.

Atsushi Matsuoka

Univ. New Hampshire

Takemasa Miyoshi

RIKEN

Kaoru Tachiiri

JAMSTEC

Naohiko Hirasawa

NIPR

Development of an advanced method for monitoring the Arctic environments using
GCOM-C/SGLI and the in-situ data collection and the collaboration with anumerical climate model for enhancing the value of the SGLI cryosphere products
Development of aerosol assimilation and forecasting system with data from multiple
space-borne observation platforms
Research on air pollution prediction by assimilating aerosol products retrieved fromsatellites
Sustainable use of salmon resource under changing climate using multiple satellite
datasets
Validation for ocean color products and development of marine spatial information
using multiple satellite applications in the coastal waters of Hokkaido: towardsustainable management of fisheries resources
Decadal trends in organic carbon stocks in a changing Arctic Ocean: multi-sensor
approach
Advances and applications of satellite data assimilation of clouds, precipitation, andthe oceanContribution to satellite products development by sharing needs and results of aclimate change research project
The current state of snowfall and surface melting on the Antarctic ice sheet andunderstanding the relationship with global warming using ground-based andsatellite observations

Table C6
Success level
Assessment condition

Minimum success

Full success

Extra successAchievestandard
accuracies of all standard
products, within 5 years
after launch,

Achieve the target accuracy of
one or more products within 5
years after launch.

data production

Complete calibration andvalidation phase and start data
distribution of more than 20
products*3 achieving therelease threshold accuracy*2
about 1 year after launch.

Standard
product*1(Set
releasethreshold/ standard/target accuracies)

Research
product*1(Set only
accuracy)

Real-time
availability

targetNA

NA

When the products achieve therelease threshold accuracy,
confirm ability to distributethe data within the requiredtime.

Continue required-timedata distribution during
the operation period from
confirmation of the releasethreshold accuracy to 5
years after launch.
Continueobservation*4and data distribution from
confirmation of releasethreshold accuracy to 5
years after launch.

data distribution
Continuity
*1
*2
*3
*4

When the products achieve therelease threshold accuracy,
confirm
abilitytocontinuously observe anddistribute products.

Achieve the target accuracy of
one or more products within 5
years after launch or add newimportant products for climatechange research.

NA

NAStandard products are defined as products that are especially important for achieving the mission goal, sufficiently confirm the application reality fromADEOS-II results etc. and are suitable for operational data distribution. Research products are defined as products still in the research phase ofdevelopment and application or are unsuitable for operational data distribution.
Release threshold accuracy: Minimum accuracy for release as available for climate research
The threshold number of products, 20, corresponds to the number of ADEOS-II GLI standard products in the GCOM-C standard products.
This means to obtain observation data continuously during the planned Earth-observation operation period

1C-23