5:15 PM - 6:30 PM
[HTT18-P02] Data quality of GOSAT-2/TANSO-FTS-2 GHG profile data retrieved from the V102.102 radiance spectra
Keywords:satellite remote sensing, GHG, retrieval algorithm
Greenhouse Gases Observing Satellite-2 (GOSAT-2), the successor of GOSAT launched in 2009, was successfully launched on 29th October, 2018 and started its regular operation on 1st February, 2019. Thermal infrared (TIR) bands of Thermal and Near Infrared Sensor for Carbon Observation-Fourier Transform Spectrometer-2 (TANSO-FTS-2) on board the GOSAT-2 can provide information on vertical structures of GHG concentrations and temperature in the atmosphere [Saitoh et al., 2009, 2016].
We have retrieved GHG concentrations and temperature in several atmospheric layers (up to 30 layers) from the TIR bands of GOSAT-2/TANSO-FTS-2 by adopting a non-linear maximum a posteriori (MAP) method with linear mapping. In the retrieval processing, we used the Level 1B V102.102 radiance spectra of TANSO-FTS-2. We have used 9, 10, and 15 μm bands for CO2, O3, and temperature retrieval and 7 and 8 μm bands for CH4, N2O, and H2O retrieval, basically following the GOSAT/FTS TIR algorithm [Saitoh et al., 2009, 2016]. We have taken into account the EOF components of spectral residuals and simultaneously retrieved surface parameters. As the signal-to-noise ratio (SNR) values of the TIR bands of TANSO-FTS-2 are significantly larger than those of TANSO-FTS, we can expect TANSO-FTS-2 to observe greenhouse gases concentrations with higher accuracy and precision.
Retrieved CO2, CH4, and N2O concentrations showed reasonable latitudinal gradients over the ocean. Over the land, the retrieved CH4 and N2O concentrations had larger variabilities than expected; they clearly had positive biases over the Sahara, which could be attributable to the inappropriate setting of surface emissivity there in the retrieval processing.
We have retrieved GHG concentrations and temperature in several atmospheric layers (up to 30 layers) from the TIR bands of GOSAT-2/TANSO-FTS-2 by adopting a non-linear maximum a posteriori (MAP) method with linear mapping. In the retrieval processing, we used the Level 1B V102.102 radiance spectra of TANSO-FTS-2. We have used 9, 10, and 15 μm bands for CO2, O3, and temperature retrieval and 7 and 8 μm bands for CH4, N2O, and H2O retrieval, basically following the GOSAT/FTS TIR algorithm [Saitoh et al., 2009, 2016]. We have taken into account the EOF components of spectral residuals and simultaneously retrieved surface parameters. As the signal-to-noise ratio (SNR) values of the TIR bands of TANSO-FTS-2 are significantly larger than those of TANSO-FTS, we can expect TANSO-FTS-2 to observe greenhouse gases concentrations with higher accuracy and precision.
Retrieved CO2, CH4, and N2O concentrations showed reasonable latitudinal gradients over the ocean. Over the land, the retrieved CH4 and N2O concentrations had larger variabilities than expected; they clearly had positive biases over the Sahara, which could be attributable to the inappropriate setting of surface emissivity there in the retrieval processing.