Articles | Volume 7, issue 9
https://doi.org/10.5194/amt-7-2987-2014
© Author(s) 2014. 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-7-2987-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
17 Sep 2014
Research article |
| 17 Sep 2014
Validation of XCH4 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data
National Institute for Environmental Studies (NIES), Tsukuba, Japan
I. Morino
National Institute for Environmental Studies (NIES), Tsukuba, Japan
O. Uchino
National Institute for Environmental Studies (NIES), Tsukuba, Japan
Y. Miyamoto
Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan
National Institute for Environmental Studies (NIES), Tsukuba, Japan
now at: Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
Y. Yoshida
National Institute for Environmental Studies (NIES), Tsukuba, Japan
T. Yokota
National Institute for Environmental Studies (NIES), Tsukuba, Japan
C. Sweeney
National Oceanic and Atmospheric Administration (NOAA), Boulder, CO, USA
P. P. Tans
National Oceanic and Atmospheric Administration (NOAA), Boulder, CO, USA
S. C. Biraud
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA, USA
T. Machida
National Institute for Environmental Studies (NIES), Tsukuba, Japan
J. V. Pittman
Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
E. A. Kort
Jet Propulsion Laboratory/California Institute of Technology, Pasadena, CA, USA
now at: Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI, USA
T. Tanaka
National Institute for Environmental Studies (NIES), Tsukuba, Japan
now at: NASA Ames Research Center, Moffett Field, CA, USA
S. Kawakami
Japan Aerospace Exploration Agency (JAXA), Tsukuba, Japan
Y. Sawa
Meteorological Research Institute (MRI), Tsukuba, Japan
K. Tsuboi
Meteorological Research Institute (MRI), Tsukuba, Japan
H. Matsueda
Meteorological Research Institute (MRI), Tsukuba, Japan
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30 citations as recorded by crossref.
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- Two-Year Comparison of Airborne Measurements of CO2 and CH4 With GOSAT at Railroad Valley, Nevada T. Tanaka et al. https://doi.org/10.1109/TGRS.2016.2539973
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- Comparison of XH2O Retrieved from GOSAT Short-Wavelength Infrared Spectra with Observations from the TCCON Network E. Dupuy et al. https://doi.org/10.3390/rs8050414
- An Approach to Estimate Atmospheric Greenhouse Gas Total Columns Mole Fraction from Partial Column Sampling J. Tadić & S. Biraud https://doi.org/10.3390/atmos9070247
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- Observations of XCO2 and XCH4 with ground-based high-resolution FTS at Saga, Japan, and comparisons with GOSAT products H. Ohyama et al. https://doi.org/10.5194/amt-8-5263-2015
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- Extending methane profiles from aircraft into the stratosphere for satellite total column validation using the ECMWF C-IFS and TOMCAT/SLIMCAT 3-D model S. Verma et al. https://doi.org/10.5194/acp-17-6663-2017
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- Estimation and analysis of CO2 column concentrations (XCO2) in the Yangtze River Delta of China based on multi-source data and machine learning C. Chen et al. https://doi.org/10.1016/j.apr.2025.102528
- Development of satellite-based surface methane flux model for major agro-ecosystems using energy balance diagnostics S. Thakur et al. https://doi.org/10.1007/s10333-020-00808-5
30 citations as recorded by crossref.
- In situ measurement of CO2 and CH4 from aircraft over northeast China and comparison with OCO-2 data X. Sun et al. https://doi.org/10.5194/amt-13-3595-2020
- Methane profiles from GOSAT thermal infrared spectra A. de Lange & J. Landgraf https://doi.org/10.5194/amt-11-3815-2018
- Impact of equatorial and continental airflow on primary greenhouse gases in the northern South China Sea C. Ou-Yang et al. https://doi.org/10.1088/1748-9326/10/6/065005
- Assessment of seasonal variations of carbon dioxide concentration in Iran using GOSAT data S. Mousavi et al. https://doi.org/10.1111/1477-8947.12121
- Long-term and interannual variations of atmospheric methane observed by the NIES and collaborative observation networks T. Umezawa et al. https://doi.org/10.1186/s40645-025-00711-9
- Two-Year Comparison of Airborne Measurements of CO2 and CH4 With GOSAT at Railroad Valley, Nevada T. Tanaka et al. https://doi.org/10.1109/TGRS.2016.2539973
- Bias corrections of GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> with TCCON data and their evaluation using aircraft measurement data M. Inoue et al. https://doi.org/10.5194/amt-9-3491-2016
- Spatiotemporal distribution patterns of atmospheric methane using GOSAT data in Iran S. Mousavi & S. Falahatkar https://doi.org/10.1007/s10668-019-00378-5
- Evaluation of Bias Correction Methods for GOSAT SWIR XH2O Using TCCON data T. Trieu et al. https://doi.org/10.3390/rs11030290
- Comparison of XH2O Retrieved from GOSAT Short-Wavelength Infrared Spectra with Observations from the TCCON Network E. Dupuy et al. https://doi.org/10.3390/rs8050414
- An Approach to Estimate Atmospheric Greenhouse Gas Total Columns Mole Fraction from Partial Column Sampling J. Tadić & S. Biraud https://doi.org/10.3390/atmos9070247
- Spatial and temporal distribution of carbon dioxide gas using GOSAT data over IRAN S. Falahatkar et al. https://doi.org/10.1007/s10661-017-6285-8
- Spatiotemporal Variations of XCH4 across China during 2003–2021 Based on Observations from Multiple Satellites J. Qin et al. https://doi.org/10.3390/atmos13091362
- High-performance and wavelength-transplantable on-chip Fourier transform spectrometer using MEMS in-plane reconfiguration H. Chen et al. https://doi.org/10.1364/PRJ.521439
- Comparison of Distributions of Atmospheric Gas Admixture Concentrations Measured by Remote and In Situ Instruments over the Russian Sector of the Arctic O. Antokhina et al. https://doi.org/10.1134/S1024856018060027
- Methane cross-validation between three Fourier transform spectrometers: SCISAT ACE-FTS, GOSAT TANSO-FTS, and ground-based FTS measurements in the Canadian high Arctic G. Holl et al. https://doi.org/10.5194/amt-9-1961-2016
- Analyzing spatio-temporal patterns in atmospheric carbon dioxide concentration across Iran from 2003 to 2020 S. Mousavi et al. https://doi.org/10.1016/j.aeaoa.2022.100163
- Research Progress on On‐Chip Fourier Transform Spectrometer L. Zhang et al. https://doi.org/10.1002/lpor.202100016
- Comparison of GOSAT SWIR and Aircraft Measurements of XCH<sub>4</sub> over West Siberia A. Ono et al. https://doi.org/10.2151/sola.2015-036
- A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm J. Laughner et al. https://doi.org/10.5194/amt-16-1121-2023
- Comparison of XCH4 Derived from g-b FTS and GOSAT and Evaluation Using Aircraft In-Situ Observations over TCCON Site S. Kenea et al. https://doi.org/10.1007/s13143-019-00105-0
- Influences of aerosols and thin cirrus clouds on GOSAT XCO2 and XCH4 using Total Carbon Column Observing Network, sky radiometer, and lidar data T. Trieu et al. https://doi.org/10.1080/01431161.2022.2038395
- Observations of XCO2 and XCH4 with ground-based high-resolution FTS at Saga, Japan, and comparisons with GOSAT products H. Ohyama et al. https://doi.org/10.5194/amt-8-5263-2015
- Validation of TANSO-FTS/GOSAT XCO2 and XCH4 glint mode retrievals using TCCON data from near-ocean sites M. Zhou et al. https://doi.org/10.5194/amt-9-1415-2016
- Extending methane profiles from aircraft into the stratosphere for satellite total column validation using the ECMWF C-IFS and TOMCAT/SLIMCAT 3-D model S. Verma et al. https://doi.org/10.5194/acp-17-6663-2017
- Visible (400- to 700-nm) chirped-grating-coupled waveguide spectrometer X. Wang et al. https://doi.org/10.1364/OE.462781
- 大气甲烷卫星传感器和遥感算法研究综述 何. He Zhuo et al. https://doi.org/10.3788/AOS230429
- CH4 concentrations over the Amazon from GOSAT consistent with in situ vertical profile data A. Webb et al. https://doi.org/10.1002/2016JD025263
- Estimation and analysis of CO2 column concentrations (XCO2) in the Yangtze River Delta of China based on multi-source data and machine learning C. Chen et al. https://doi.org/10.1016/j.apr.2025.102528
- Development of satellite-based surface methane flux model for major agro-ecosystems using energy balance diagnostics S. Thakur et al. https://doi.org/10.1007/s10333-020-00808-5
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