JpGU-AGU Joint Meeting 2017

Presentation information

[JJ] Poster

A (Atmospheric and Hydrospheric Sciences) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS11] [JJ] Atmospheric Chemistry

Wed. May 24, 2017 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall HALL7)

convener:Hitoshi Irie(Center for Environmental Remote Sensing, Chiba University), Toshinobu Machida(National Institute for Environmental Studies), Hiroshi Tanimoto(National Institute for Environmental Studies), Yoko Iwamoto(Graduate School of Biosphere Science, Hiroshima University)

[AAS11-P14] Comparisons of column-averaged dry-air mole fractions of greenhouse gases among GOSAT/TANSO-FTS SWIR, TIR, and NICAM-TM data

*Hiromichi Hatta1, Naoko Saitoh2, Yosuke Niwa3, Ryoichi Imasu4, Kei Shiomi5, Yukio Yoshida6 (1.Chiba university Graduate School of Advanced Integration Science, 2.Center for Environmental Remote Sensing, Chiba University, 3.Meteorologocal Research Institute, 4.Atmosphere and Ocean research Institute, 5.Japan Aerospace Exploration Agency, 6.National Institute for Environmental Studies)

Keywords:GOSAT, XCO2, XCH4

Greenhouse gases Observing SATellite (GOSAT) was launched on 23 January, 2009. Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) on board the GOSAT has SWIR and TIR bands and can observe column-averaged dry-air mole fractions of CO2 and CH4 (XCO2 and XCH4) in the SWIR bands [Yoshida et al., 2011] and CO2 and CH4 vertical profiles in the TIR band [Saitoh et al., 2009]. In this study, we calculated XCO2 and XCH4 values from the TIR CO2 and CH4 profiles, and then compared them with XCO2 and XCH4 data of the SWIR bands and Nonhydrostatic ICosahedral Atmospheric Model-based Transport Model (NICAM-TM) [Niwa et al., 2011]. Before calculating the TIR XCO2 values, we applied bias-correction values evaluated based on the comparisons of aircraft CO2 data.
We compared latitudinal distributions of XCO2 among TANSO-FTS TIR, SWIR, NICAM-TM, and a priori (NIES-TM05) data [Saeki et al., 2013]. TIR XCO2 data over the land in the Northern Hemisphere except the Sahara desert were slightly smaller than SWIR XCO2 data and, in contrast, slightly larger over the land in the Southern Hemisphere. Over the Sahara desert, TIR XCO2 data in the daytime were considerably smaller than SWIR and NICAM-TM XCO2 data, which suggests that surface parameters used in the TIR retrieval had some problems. Over Hawaii where there is no strong CO2 source, TIR XCO2 data agreed with SWIR XCO2 data to within 1% on average.