GOSAT carries the Thermal and Near-infrared Sensor for carbon Observation (TANSO), which is composed of two subunits: the Fourier Transform Spectrometer (FTS) and the Cloud and Aerosol Imager (CAI). The data from FTS and CAI are processed and used together to calculate column abundances of CO2 and CH4 and to estimate sources and sinks as well as the three-dimensional distributions of CO2 and CH4 concentrations using a global atmospheric tracer transport model.
GOSAT observational data are processed at the GOSAT Data Handling Facility (DHF) of NIES and the data products are distributed to general users through the GOSAT data product distribution website (GOSAT User Interface Gateway, GUIG). The GOSAT DHF collects the specific point observation requests from qualified researchers and the observation requests of NIES and transfers them to JAXA. JAXA coordinates all observation requests to prepare the satellite operation plan.
The FTS and CAI data are received and processed into Level 1B (L1B) data at JAXA Tsukuba Space Center. These data are then transferred to the GOSAT DHF. The GOSAT DHF also collects the reference data (e.g., meteorological information) necessary for higher level processing. Using the reference data, the FTS observations are processed into column abundances (Level 2, L2), spatially interpolated monthly global distributions of column abundance (Level 3, L3), sources and sinks (Level 4A, L4A), and three-dimensional distributions of CO2 and CH4 (Level 4B, L4B). Reference data used for validating the products are also stored in the DHF.
GOSAT products are distributed through the GUIG. L1B data contain radiance spectra converted from raw data acquired by the satellite. The higher level products from L2–L4 store retrieved physical quantities such as the atmospheric columnar concentrations of CO2 and CH4. Users will be able to search and order these products using the GUIG (https://data.gosat.nies.go.jp/) by the end of 2016 or using the GOSAT Data Archive Service (GDAS, http://data2.gosat.nies.go.jp/) after January 2017.
To improve data quality, we updated the algorithm used for the estimation of XCO2 and XCH4 [column-averaged dry-air mole fractions (the ratio of the total amount of targeted gas molecules to the total amount of dry air molecules contained in a vertical column from the ground surface to the top of the atmosphere) for CO2 and CH4] and validated the retrieved values by comparing them to high-precision ground-based measurements. Using these L2 values, higher level data products such as monthly estimates of CO2 and CH4 regional fluxes were obtained. Based on these flux estimates, concentrations of CO2 and CH4 in three-dimensional space were simulated. These data have been made available to the public as GOSAT L4A (flux estimates) and L4B (three-dimensional concentration distributions). GOSAT data collected and archived for more than 6 years, can be used to map the seasonal variations and annual trends of XCO2 and XCH4 on regional and global scales.
The top images in Fig. 9.1 show the monthly mean GOSAT XCO2 data gridded to a 5-degree by 5-degree mesh. The circles show GLOBALVIEW data (ground observation, 212 sites). With this input, the middle images are generated (monthly flux estimates) and the bottom images show flux uncertainties (GOSAT L4A).
Figure 9.2 shows the L4B data product, which is the result of an atmospheric tracer transport model simulation based on the flux distribution (L4A) estimated from the ground-based and GOSAT-based concentration data. L4B products store global concentrations using a 2.5-degree mesh in intervals of 6 h at 17 vertical levels, ranging from near the surface to the top of the atmosphere.
MOE, NIES, and JAXA issued a press-release on December 4, 2014 stating that GOSAT archive data has the potential to detect the origin of increased CO2 concentrations. These analyses have progressed and have been performed for the Tokyo metropolitan area and other major cities around the world. The results, announced on September 1, 2016, demonstrated for the first time the possibility of using satellite observations to monitor and verify the emissions reported by countries, even at relatively small scales.
Figure 9.3a shows areas where high concentrations of anthropogenic CO2 emissions were observed (average from June 2009 to December 2014). The color represents concentration. Figure 9.3b shows the correlation between the satellite data and inventory estimates for Japan.
These results demonstrate that satellite measurements have the potential to be used for Measurement, Reporting, and Verification (MRV)—especially verification for multilateral agreements—in combination with ground-based, airborne, and other measurements. For such purposes, it is critical that data are free and open.