Articles | Volume 21, issue 3
https://doi.org/10.5194/acp-21-1797-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-1797-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Feb 2021
Research article |
| 10 Feb 2021
| 10 Feb 2021
Satellite retrieval of aerosol combined with assimilated forecast
Mayumi Yoshida
CORRESPONDING AUTHOR
Japan Aerospace Exploration Agency, Tsukuba, 305-8505, Japan
present
address: Remote Sensing Technology Center of Japan, Tsukuba, 305-8505,
Japan
Keiya Yumimoto
Research Institute for Applied Mechanics, Kyushu University, Fukuoka,
816-8580, Japan
Takashi M. Nagao
Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba,
277-8568, Japan
Taichu Y. Tanaka
Meteorological Research Institute, Tsukuba, 305-0052, Japan
Maki Kikuchi
Japan Aerospace Exploration Agency, Tsukuba, 305-8505, Japan
Hiroshi Murakami
Japan Aerospace Exploration Agency, Tsukuba, 305-8505, Japan
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- Fengyun 4A Land Aerosol Retrieval: Algorithm Development, Validation, and Comparison With Other Datasets X. Su et al. 10.1109/TGRS.2023.3330544
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Latest update: 21 Nov 2024
Short summary
We developed a new aerosol satellite retrieval algorithm combining a numerical aerosol forecast. This is the first study that utilizes the assimilated model forecast of aerosol as an a priori estimate of the retrieval. Aerosol retrievals were improved by effectively incorporating both model and satellite information. By using the assimilated forecast as an a priori estimate, information from previous observations can be propagated to future retrievals, thus leading to better retrieval accuracy.
We developed a new aerosol satellite retrieval algorithm combining a numerical aerosol forecast....
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