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DOI: 10.14569/IJACSA.2018.090909
PDF

Quality Flag of GOSAT/FTS Products Taking into Account Estimation Reliability

Author 1: Kohei Arai
Author 2: Takashi Higuchi
Author 3: Hiroshi Okumura
Author 4: Hirofumi Ohyama
Author 5: Shuji Kawakami
Author 6: Kei Shiomi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 9, 2018.

  • Abstract and Keywords
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Abstract: Quality and cloud flags of GOSAT/FTS: Fourier Transform Spectrometer onboard Greenhouse gasses Observation Satellite products taking into account cirrus clouds and thick aerosols are considered and proposed. Influence due to cirrus and thick aerosol on estimation of column CO2 and CH4 with GOSAT/FTS data is clarified. Relatively large estimation errors are observed in column CO2 and CH4 retrievals with FTS data in some atmospheric conditions. In order to find such cases, retrieval results and quality/cloud flags in the GOSAT/FTS data products are checked. Through the investigation, it is found that relatively large error is caused by convergence problem due to cirrus clouds and thick aerosols. In the proposed paper, some of the cases of which relatively large estimation error is occurred at the Saga TCCON (The Total Carbon Column Observing Network) site are investigated. Also, a comparative study is conducted between standard products provided by NASA/JPL and the Levenberg-Marquardt based least square method of column CO2 and CH4 retrieval. It is suggested that some improvements of estimation accuracy of column CO2 and CH4 retrieval with GOSAT/FTS data can be expected.

Keywords: Levenberg-Marquardt; FTS; GOSAT; aerosol; cirrus cloud

Kohei Arai, Takashi Higuchi, Hiroshi Okumura, Hirofumi Ohyama, Shuji Kawakami and Kei Shiomi, “Quality Flag of GOSAT/FTS Products Taking into Account Estimation Reliability” International Journal of Advanced Computer Science and Applications(IJACSA), 9(9), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090909

@article{Arai2018,
title = {Quality Flag of GOSAT/FTS Products Taking into Account Estimation Reliability},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090909},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090909},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {9},
author = {Kohei Arai and Takashi Higuchi and Hiroshi Okumura and Hirofumi Ohyama and Shuji Kawakami and Kei Shiomi}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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