Global Change Observation Mission 2nd
Research Announcement (GCOM-C1 First RA)
As the second Global Change Observation Mission (GCOM) research announcements (RA), the Japan Aerospace Exploration Agency (JAXA)
announces the opportunity to conduct "development of retrieval algorithms for geophysical products", "fundamental data acquisition andvalidation preparation", and "application research directly connecting to the GCOM-C1 data".
Infrared Scanner
GCOM1. Outline of the RA
GCOM-C1 Satellite(SGLI-IRS)
GCOM-C1 satellite is planned to be launched in the winter period ofStar tracker
Visible and Near Infrared Radiometer(SGLI-VNR)
Japanese Fiscal Year (JFY) 2013. Second generation Global Imager(SGLI) will be carried by the GCOM-C1 and have special features ofSolar paddle
wide spectral coverage from 380nm to 12um, high spatial resolutionof 250m, field of view more than 1000km, two direction simultaneous
Orbit direction
observation, and polarization observation. GCOM-C1 mission aims to
InfraRed Scanner
contribute of our knowledge improvement and prediction of global(SGLI-IRS)
Earth direction
carbon cycle and radiation budget through the high accuracy
Polarization (along-track
Visible & Near infrared pushobservation about global vegetation, ocean color, temperature, cloud,slant) radiometer (P)broom Radiometer (VNR)
aerosol, and polar regions by the SGLI.
Visible and Near-infrared
This RA covers a four-year research period from JFY 2009 to JFYRadiometer (SGLI-VNR)
2012. This RA emphasizes product development and acquisition of
GCOM is a long-term global change observation mission which
fundamental data for the algorithms (especially for new products, or
consists of two satellite types and three consecutive generations withsignificant improvement of existing products by new ideas), because
a one-year overlap, resulting in over a 13-year observation period.
the period corresponds to preparation period until 1-year of the
The two satellites are GCOM-W (Water) and GCOM-C (Climate). The
GCOM-C1 launch.
GCOM-W1 satellite (to be launched in JFY2011) will carry theParticipation in this RA is open to all categories of domestic andAdvanced Microwave Scanning Radiometer-2 (AMSR2) to contributeforeign organizations including educational institutions (except forto understanding the water and energy cycle. The GCOM-C1 satellite
students), industries, non-profit institutions and Japanese(planned to be launched in JFY2013) will be equipped with theGovernment agencies. (The funding to the foreign organization is
Second-generation Global Imager (SGLI) to observe the Earth’s
basically limited to the case of special needs for the GCOM-C1
atmosphere and surface for contributing to the understanding of themission success.) After this RA, i.e. before one-year of the GCOMcarbon cycle and radiation budget.
C1 launch, we are planning to restart the RA to conduct researches
more weighted to the operation and product validation during three
years before and after the launch.
2. Proposal Preparation Instructions and Deadline
Proposal RA details and forms for proposals can be downloaded
from the following URL. Proposers without access to the Web or who
experience difficulty in using this site may contact GCOM RA office(see below) for assistance. The deadline for submitting proposals is
March 31, 2009.
RA details and forms for proposals
http://suzaku.eorc.jaxa.jp/GCOM/ra/2ndra_info_e.html
3. GCOM RA Office
Mr. Hiroshi Sasaki (GCOM RA Office)Earth Observation Research Center (EORC), Tsukuba Space Center
Japan Aerospace Exploration Agency
2-1-1, Sengen, Tsukuba, Ibaraki, 305-8505, Japan
TEL : +81-29-868-2729 / FAX : +81-29-868-2961
E-mail: GCOM_RA@jaxa.jp
4. GCOMGCOM-C1 Satellite and SGLI Sensor
Outline of the GCOM-C1 satellite and SGLI sensor are described
below. Also, you can find the table listing the geophysical parameters
to be retrieved from SGLI’s data in the backside.
GCOMGCOM-C1 Specification
GCOM-C SGLI characteristics (baseline of GCOM-C1 BBM design)
Sun-synchronous (descending local time: 10:30)
Orbit (TBD)
Altitude: 798km, Inclination: 98.6deg
Launch Date

Jan. 2014 (HII-A)

Mission Life

5 years (3 satellites; total 13 years)

Scan
Scan width
Digitalization
Polarization
Along track
direction

Push-broom electric scan (VNR: VN & P)
Wisk-broom mechanical scan (IRS: SW & T)
1150km cross track (VNR: VN & P)
1400km cross track (IRS: SW & T)
12bit
3 polarization angles for P
Nadir for VN, SW and T,+45 deg and -45 deg for P

VN: Solar diffuser, Internal lamp (PD), Lunar by pitch
maneuvers, and dark current by masked pixels andnighttime obs.
On-board
SW: Solar diffuser, Internal lamp, Lunar, and dark current bycalibration
deep space window
T: Black body and dark current by deep space window
All: Electric calibration
VN: Visible and Near infrared, P: Polarimetry, SW: Shortwave infrared, T: Thermal infrared

SGLI Function

Nadir multi-channel observation (17channels in the visible, NIR, tothermal infrared wavelength regions)(250m resol.: 11 chs,
500m resol.: 2 chs,
1km resol.: 4 chs)

SGLI can observe the whole
globe at least once per two days.
Forward or backward polarization
along-track slant view (1km resol.: 2 chs)

Orbit direction
Swath： 1150km（VNR, Polarization）
1400km（SWIR, TIR）

SGLI will have functions of traditional nadir non-polarization
observation with 17 spectral channels ranging from near-UV tothermal infrared region, two directional observation with twopolarization channels at red and near-infrared wavelengths. With its
wide swath over 1000km, SGLI can observe the earth’s surface athigh temporal and spatial resolution (observation frequency: once per
two days, primary spatial resolution: 250m). These functions enable
us to observe global vegetation parameters, cloud and aerosol
properties, ocean color and temperature in coastal to outsea regions,snow and ice in the cryosphere with high accuracy.
SGLI SpecificationλSGLI channels
Δλ
Lstd
Lmax SNR at Lstd IFOVCH

VN, P, SW: nm
T: μm

VN, P: W/m2/sr/μm
T: Kelvin

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

380
412
443
490
530
565
670
670
763
865
865
670
865
1050
1380
1630
2210
10.8
12.0

60
75
64
53
41
33
23
25
40
8
30
25
30
57
8
3
1.9
300
300

10
10
10
10
20
20
10
20
8
20
20
20
20
20
20
200
50
0.7
0.7

210
250
400
120
350
90
62
210
350
30
300
250
300
248
103
50
20
340
340

VN, P, SW: T: NEΔT

m

250
400
300
400
250
400
400
250
400
400
200
250
250
500
150
57
211
0.2
0.2

250
250
250
250
250
250
250
250
1000
250
250
1000
1000
1000
1000
250
1000
500
500

GCOM-C1 Product※light blue: standard products, and white: research products

Area Group

Product※

L-1 Precise Geometric Corr. Precise geometric correction
Atmospheric corrected reflectanceL-2 Atmospheric Corrected
Reflectance

Vegetation index
Land surface albedo

L. LandL-3 Land Primary
Production

Fraction of Absorbed
Photosynthetically Active Radiation
Leaf area index
Water stress trend
Land net primary production
Above-ground biomass

L-4 Above-ground Biomass Vegetation roughness index
Shadow index

L-5 Temperature
L-6 Land Cover Type

A-1 CloudA. Atmosphere

A-2 Aerosol

A-3 Radiation Flux

Surface temperature
Fire detection index
Land cover type
Cloud flag/Classification
Classified cloud fraction
Cloud top temp/height
Water cloud OT/effective radius
Ice cloud optical thickness
Aerosol over the oceanLand aerosol by near ultra violet
Aerosol by Polarization
Short-wave radiation flux
Long-wave radiation flux
Water cloud geometrical thickness
Normalized water leaving radiance

O-1 Atmospheric Correction Atmospheric correction param.
over Ocean
Photosynthetically available
radiation
Chlorophyll-a concentration

Suspended solid concentration

O. Ocean

O-2 Ocean Color

Colored dissolved organic matter
Inherent optical properties
Phytoplankton functional type

Description※
Radiance after the geometric correction with ground control point also taking into account the altitude of the pixel.
Ground surface reflectance after the correction of the atmospheric effects such as scattering and absorption by molecules
Index parameter as a measure of density and activity of green vegetation. NDVI (calculated from red and near-infrared
channel reflectances) and EVI (an extended vegetation index using visible channel reflectance) are expected.
The ratio of upward reflected radiation energy divided by downward solar radiation energy estimated from the type of land
cover and the surface reflectances at each channel.
Fraction of photosynthetically active radiation (wavelength: 400-700nm) absorbed by vegetation.
The ratio of total upper leaf surface of vegetation divided by the surface area of the land on which the vegetation grows.
A trend of water stress on vegetation estimated from diurnal variation of the surface temperature.
The net absorbed carbon amount by land vegetation which is the difference between photosynthetically absorbed amountand emitted amount by the respiration.
Dry weight of above-ground biomass.
A roughness index expressing 3-dimensional structure vegetation derived by multi-angle observation.
Fraction of vegetation shadow which resulted from its 3-dimensional structure. This parameter is estimated using the
wavelength dependence of the surface reflectances.
Surface temperature of the land surface
Position of fire detected using the radiation data at the thermal- and shortwave- infrared channels.
Land cover type classified using vegetation indices and the surface reflectances at each channels.
Cloud/Clear discrimination and the type of cloud cover.
Cloud fraction statistically derived for each cloud type.
Cloud top temperature and height derived from brightness temperature data at the thermal infrared channels.
Optical thickness of water cloud and the size of cloud droplet.
Optical thickness of ice cloud.
Aerosol properties including optical thickness, size distribution (Angstrom Exponent), and the type of component.
Optical thickness and an coefficient indicating the absorptivity of visible light by land aerosols.
Optical thickness and Angstrom Exponent derived from the polarization observations.
Downward and upward shortwave radiation flux at the ground surface (Radiation budget of shortwave radiation).
Downward and upward longwave radiation flux at the ground surface (Radiation budget of longwave radiation). Upward
flux under cloudy weather condition will be estimated using the surface temperature derived by AMSR2 etc.
Geometrical thickness of water cloud derived using the radiance data at the oxygen band (763nm). Combined use of thisparameter with cloud top height enable us to estimate cloud bottom height, which will then contributes to the improvementof the retrieval accuracy of the longwave radiation budget at the ground surface.
Water leaving radiances at each channels at the ocean surface after the correction of the atmospheric effects.
Aerosol properties including optical thickness and Angstrom exponent necessary for the atmospheric correction.
Downward radiation at the wavelength of 400-700nm at the ocean surface which is available for phytoplankton.
Concentration of a primal photosynthetical pigment in phytoplankton in the ocean surface layer.
The amount of suspended solid (SS) in the ocean surface layer expressed in a unit of dry weight per volume of the ocean
water. SS is defined as a combined material of organic matter such as plankton and inorganic matter such as soil particles.
Absorption coefficient of colored dissolved organic matter (CDOM) in the ocean surface layer.
Optical properties of ocean water such as absorption coefficients of plankton pigment, SS, CDOM, and scattering
coefficients of SS, which are estimated using the normalized water leaving radiances.
Fraction of individual phytoplankton groups characterized by the fixation type such as nitrogen fixation, silicate fixation,and carbon dioxide fixation, which are estimated using the normalized water leaving radiances.
Discrimination of redtide using the characteristic of ocean color.
Sea surface temperature (SST) of bulk water.
Carbon fixation ability of oceanic phytoplankton by photosynthesis (carbon emission by respiration is subtracted).
The depth of ocean layer in which a substantial amount of light for the organism growth is available.
Ocean color data merged with multiple ocean color sensors' data such as NPOESS/VIIRS.
SST data merged with multiple sensors' SST data derived from AMSR-2 and NPOESS/VIIRS etc.
Snow and ice discrimination.
Sea ice distribution in Okhotsk Sea processed in near real-time
Snow and ice cover type (such as new snow/old snow, or first year ice/multi-year ice etc.)

RedtideSea surface temperature
Ocean net primary productivity
O-4 Primary Productivity
Euphotic zone depth
multi sensor merged ocean color
O-5 Multi Sensor Merged
Product
multi sensor merged SST
Snow and Ice covered area
Okhotsk sea-ice distribution
Snow and ice classification
S-1 Area/Distribution
Snow covered area in forest andSnow covered area in forest and mountain regions where vegetation cover is likely mixed with snow.
mountainIce sheet boundary monitoring
Position of major Ice sheet boundary.
Snow and ice surface Temperature Surface temperature of snow and ice surface
Snow grain size retrieved with the reflectance at 865nm channel. Retrieved sizes represent the snow property at a shallow
Snow grain size of shallow layer
layer of 0-30cm.
grain size retrieved with the reflectance at 1050nm channel. Retrieved sizes represent the snow property at the
S-2 Surface Properties
Snow grain size of subsurface layer Snowsubsurface layer which is upper than that with 865nm channel.
Snowgrain size retrieved with the reflectance at 1640nm channel. Retrieved sizes represent the property of the top snow
Snow grain size of top layer
layer.
Snow impurity
Ratio of impurity in snow such as soot and dust.
The ratio of upward reflected radiation energy divided by downward solar radiation energy estimated using the snow
Snow and ice albedo
surface reflectances at each channel taking into account the atmospheric effect.
S-3 Albedo
Roughness of the ice sheet (defined as the ratio of the height divided by the width of the roughness) derived by multiIce sheet surface roughness
angle observation.
Itisacommontask
formakingmostof
SGLI products to discriminate between clear, cloud, snow/ice surfaces. However, it is also the fact that there is a
C-1 Clear/Cloud/Cryosphere necessity to develop a proper discrimination
scheme specific for each algorithm. JAXA will promote sharing the knowledge of the spectral features of eachdiscrimination
observation target and the way to the discrimination as far as possible for further improving the performance of the individual algorithms.
It is necessary to separate the component of the reflected light at a ground target from the light component of the atmospheric scattering (especially related tothe aerosol properties A-2) in satellite observed radiances in order to estimate the surface reflectance (land, ocean, and snow). For this purpose, JAXA will
C-2 Aerosol Correction
promote sharing the knowledge of and exchange the processing technique of the radiative transfer process in the atmosphere-surface system.
Observing polarized radiances is an unique function of SGLI. Besides the aerosol product by polarization (A-2), we will explore the development of new
products to be derived with the polarization observation and their application. Because the polarization observation is a new function also from the point of view
C-3 Polarization Analysisof hardware development, JAXA will promote the close cooperation with the calibration activities primarily conducted by JAXA.
It is necessary not only to cooperate with researches on the monitoring and prediction of the carbon cycle and radiative forcing, but also to improve the
C-4 Combined Global
development scheme of our satellite products based on the needs requested by those researches and the knowledge obtained through the cooperation. JAXA
Environmental Change
will promote combined analysis with the results of numerical models and also promote the sharing of the knowledge and technique of individual research groups
Analysisfor future assimilation of satellite data in the model.
Accuracy of satellite product is affected by both the sensor performance and the algorithm performance. It is necessary, therefore, to develop algorithms
C-5 Consideration of SGLI appropriate for actual SGLI performance to be achieved. For example, JAXA will promote close cooperation between the team evaluating the radiative transfer
process in the algorithms and the teams conducting ground truth observations and vi-carious calibration. Also, JAXA will bridge the gap between system
Calibration Performancegeometric correction and precise geometric correction teams to be conducted as a calibration activity.

O-3 Temperature

S. Cryosphere
C. Common