GOSAT Satellite Mission Summary

CEOS EO HANDBOOK – MISSION SUMMARY - GOSAT -

Full Name

Greenhouse gases Observing SATellite
aka Ibuki

Status

Operational (extended)

Mission Agencies

JAXA , MOE (Japan), NIES (Japan)

Launch Date

23 Jan 2009

Mission Links

mission site | data access portal

EOL Date

Dec 2023

EO Portal Info

NORAD Catalog #

33492 (TLE)

International Designator

2009-002A

Orbit Type

Sun-synchronous

Orbit Period

98.18 minutes

Orbit Sense

Descending

Orbit Inclination

98.06 deg

Orbit Altitude

666 km

Orbit Longitude

Orbit LST

13:00

Repeat Cycle

3 days

Objectives and Applications

Observation of greenhouse gases (CO2, CH4) and solar-induced chlorophyll fluorescence (SIF).

Mission Measurements

Category	Parameter	Instrument(s)
Atmosphere	Aerosols	TANSO-CAI
	Cloud type, amount and cloud top temperature	TANSO-CAI
	Ozone	TANSO-FTS
	Trace gases (excluding ozone)	TANSO-FTS
	Atmospheric Temperature Fields	TANSO-FTS
Land	Vegetation	TANSO-CAI, TANSO-FTS

Mission Instruments

TANSO-CAI - Thermal And Near infrared Sensor for carbon Observation - Cloud and Aerosol Imager

TANSO-FTS - Thermal And Near infrared Sensor for carbon Observation - Fourier Transform Spectrometer

Featured Datasets
More Datasets

GOSAT Full Archive and Tasking
Jan-2009

GOSAT is a Japanese climate change EO mission, developed by JAXA. The mission carries two thermal and near infrared sensors for carbon observation – a Fourier Transform Spectrometer (TANSO-FTS) and a Cloud and Aerosol Imager (TANSO-CAI). The objective of the mission is to provide monitoring of the sources and sinks of CO2 on a sub-continental scale in support of the Kyoto protocol. ESA offers access to worldwide GOSAT data (both archived and new acquisitions) via the TPM scheme. Read more

OpenSearch Datasets

Selected IDN OpenSearch Results (search all 22 )
ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retri ...

ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retri ...

ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V7.3 (ACOS_L2S) at GES DISC

ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V9r (ACOS_L2S) at GES DISC

CarbonTracker-Lagrange North America GOSAT Vertical Profile of Footprints V1 (CMS_CTL_NA_GOSAT_FOOTP ...

CARVE: Monthly Atmospheric CO2 Concentrations (2009-2013) and Modeled Fluxes, Alaska

CMS (Carbon Monitoring System) Methane (CH4) Flux for North America 0.5 degree x 0.667 degree V1 (CM ...

CMS GOSAT and ObsPack L4 Top-down yearly methane emissions for individual sectors at 0.5x0.625 degre ...

ESA Greenhouse Gases Climate Change Initiative (GHG CCI): Column-averaged CO2 from GOSAT generated w ... $The CO2_GOS_OCFP dataset comprises level 2, column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2) from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). It has been produced using the University of Leicester Full-Physics Retrieval Algorithm, which is based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra. A second product, generated using the alternative SRFP algorithm, is also available. The OCFP product is considered the GHG_cci baseline product and it is advised that users who aren't sure which of the two products to use, use this product. For more information regarding the differences between baseline and alternative algorithms please see the Greenhouse Gases CCI data products webpage.The XCO2 product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further information, including details of the OCFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG).$
ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged CO2 Merged Product generat ... $The CO2_EMMA dataset comprises of level 2, column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2). It has been produced using the ensample median algorithm EMMA to produce a merged SCIAMACHY and GOSAT XCO2 Level 2 product, as part of the ESA Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the product is v2.2, and forms part of the Climate Research Data Package 4.The EMMA algorithm has been applied to level 2 data from multiple XCO2 retrievals from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. This merged SCIAMACHY and GOSAT XCO2 Level 2 product is primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). For further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR).$

Selected FedEO OpenSearch Results (view all 30 results: browser , table )
GOSAT-2 TANSO FTS-2 and CAI-2 full archive and new products

GOSAT-2 TANSO FTS-2 and CAI-2 ESA archive

GOSAT TANSO FTS and CAI ESA archive

ESA Greenhouse Gases Climate Change Initiative (GHG CCI): Column-averaged CO2 from GOSAT generated w...

ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged CO2 Merged Product generat...

ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 Merged Product generat...

ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 from GOSAT generated w...

CLIMATE APPLICATIONS: Primarily to obtain information on the natural and anthropogenic sources and s...

CH4_GOS_SRPR, version v2.3.7. CLIMATE APPLICATIONS: Primarily to obtain information on the natural a...

CLIMATE APPLICATIONS: Comparison with climate models and to obtain information on CO2 sources and si...

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