Articles | Volume 9, issue 5
https://doi.org/10.5194/amt-9-2119-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-2119-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Algorithm update of the GOSAT/TANSO-FTS thermal infrared CO2 product (version 1) and validation of the UTLS CO2 data using CONTRAIL measurements
Naoko Saitoh
CORRESPONDING AUTHOR
Center for Environmental Remote Sensing, Chiba University,
Chiba, Japan
Shuhei Kimoto
Center for Environmental Remote Sensing, Chiba University,
Chiba, Japan
Ryo Sugimura
Center for Environmental Remote Sensing, Chiba University,
Chiba, Japan
Ryoichi Imasu
Atmosphere and Ocean Research Institute, University of
Tokyo, Kashiwa, Japan
Shuji Kawakami
Japan Aerospace Exploration Agency, Tsukuba,
Japan
Kei Shiomi
Japan Aerospace Exploration Agency, Tsukuba,
Japan
Akihiko Kuze
Japan Aerospace Exploration Agency, Tsukuba,
Japan
Toshinobu Machida
National Institute for Environmental Studies, Tsukuba,
Japan
Yousuke Sawa
Meteorological Research Institute, Tsukuba,
Japan
Hidekazu Matsueda
Meteorological Research Institute, Tsukuba,
Japan
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Cited
15 citations as recorded by crossref.
- Bias assessment of lower and middle tropospheric CO<sub>2</sub> concentrations of GOSAT/TANSO-FTS TIR version 1 product N. Saitoh et al. 10.5194/amt-10-3877-2017
- An Analysis of Interhemispheric Transport Pathways Based on Three‐Dimensional Methane Data by GOSAT Observations and Model Simulations D. Belikov et al. 10.1029/2021JD035688
- Gradients of column CO<sub>2</sub> across North America from the NOAA Global Greenhouse Gas Reference Network X. Lan et al. 10.5194/acp-17-15151-2017
- Detection of Methane Emission from a Local Source Using GOSAT Target Observations A. Kuze et al. 10.3390/rs12020267
- Calibration, Level 1 Processing, and Radiometric Validation for TANSO-FTS TIR on GOSAT F. Kataoka et al. 10.1109/TGRS.2018.2885162
- A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 2: Optimization scheme and identical twin experiment of atmospheric CO<sub>2</sub> inversion Y. Niwa et al. 10.5194/gmd-10-2201-2017
- Atmospheric ammonia retrieval from the TANSO-FTS/GOSAT thermal infrared sounder Y. Someya et al. 10.5194/amt-13-309-2020
- Comparison of the GOSAT TANSO-FTS TIR CH<sub>4</sub> volume mixing ratio vertical profiles with those measured by ACE-FTS, ESA MIPAS, IMK-IAA MIPAS, and 16 NDACC stations K. Olsen et al. 10.5194/amt-10-3697-2017
- Update on the GOSAT TANSO–FTS SWIR Level 2 retrieval algorithm Y. Someya et al. 10.5194/amt-16-1477-2023
- Satellite observation of atmospheric methane: intercomparison between AIRS and GOSAT TANSO-FTS retrievals M. Zou et al. 10.5194/amt-9-3567-2016
- GOSAT CH4 Vertical Profiles over the Indian Subcontinent: Effect of a Priori and Averaging Kernels for Climate Applications D. Belikov et al. 10.3390/rs13091677
- Optimization of the Photon Path Length Probability Density Function-Simultaneous (PPDF-S) Method and Evaluation of CO2 Retrieval Performance Under Dense Aerosol Conditions C. Iwasaki et al. 10.3390/s19051262
- Spatio-Temporal Validation of AIRS CO2 Observations Using GAW, HIPPO and TCCON H. Yang et al. 10.3390/rs12213583
- Greenhouse gases Observing SATellite 2 (GOSAT-2): mission overview R. Imasu et al. 10.1186/s40645-023-00562-2
- Comparison of Retrieved L2 Products from Four Successive Versions of L1B Spectra in the Thermal Infrared Band of TANSO-FTS over the Arctic Ocean S. Payan et al. 10.3390/rs9111167
14 citations as recorded by crossref.
- Bias assessment of lower and middle tropospheric CO<sub>2</sub> concentrations of GOSAT/TANSO-FTS TIR version 1 product N. Saitoh et al. 10.5194/amt-10-3877-2017
- An Analysis of Interhemispheric Transport Pathways Based on Three‐Dimensional Methane Data by GOSAT Observations and Model Simulations D. Belikov et al. 10.1029/2021JD035688
- Gradients of column CO<sub>2</sub> across North America from the NOAA Global Greenhouse Gas Reference Network X. Lan et al. 10.5194/acp-17-15151-2017
- Detection of Methane Emission from a Local Source Using GOSAT Target Observations A. Kuze et al. 10.3390/rs12020267
- Calibration, Level 1 Processing, and Radiometric Validation for TANSO-FTS TIR on GOSAT F. Kataoka et al. 10.1109/TGRS.2018.2885162
- A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 2: Optimization scheme and identical twin experiment of atmospheric CO<sub>2</sub> inversion Y. Niwa et al. 10.5194/gmd-10-2201-2017
- Atmospheric ammonia retrieval from the TANSO-FTS/GOSAT thermal infrared sounder Y. Someya et al. 10.5194/amt-13-309-2020
- Comparison of the GOSAT TANSO-FTS TIR CH<sub>4</sub> volume mixing ratio vertical profiles with those measured by ACE-FTS, ESA MIPAS, IMK-IAA MIPAS, and 16 NDACC stations K. Olsen et al. 10.5194/amt-10-3697-2017
- Update on the GOSAT TANSO–FTS SWIR Level 2 retrieval algorithm Y. Someya et al. 10.5194/amt-16-1477-2023
- Satellite observation of atmospheric methane: intercomparison between AIRS and GOSAT TANSO-FTS retrievals M. Zou et al. 10.5194/amt-9-3567-2016
- GOSAT CH4 Vertical Profiles over the Indian Subcontinent: Effect of a Priori and Averaging Kernels for Climate Applications D. Belikov et al. 10.3390/rs13091677
- Optimization of the Photon Path Length Probability Density Function-Simultaneous (PPDF-S) Method and Evaluation of CO2 Retrieval Performance Under Dense Aerosol Conditions C. Iwasaki et al. 10.3390/s19051262
- Spatio-Temporal Validation of AIRS CO2 Observations Using GAW, HIPPO and TCCON H. Yang et al. 10.3390/rs12213583
- Greenhouse gases Observing SATellite 2 (GOSAT-2): mission overview R. Imasu et al. 10.1186/s40645-023-00562-2
Saved (preprint)
Latest update: 02 Nov 2024
Short summary
This study compared GOSAT/TANSO-FTS thermal infrared (TIR) V1 and CONTRAIL CME CO2 data in the upper troposphere and lower stratosphere. The TIR CO2 averages agreed with the CME CO2 averages within 0.1 and 0.5 % in the Southern and Northern Hemisphere. At northern low and middle latitudes, their agreements were worse in spring and summer. The negative bias there made the maximum of TIR data being lower than that of CME data, which leads to underestimating the amplitude of CO2 seasonal variation.
This study compared GOSAT/TANSO-FTS thermal infrared (TIR) V1 and CONTRAIL CME CO2 data in the...