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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Cited
19 citations as recorded by crossref.
- An aerosol odyssey: Navigating nutrient flux changes to marine ecosystems D. Hamilton et al. 10.1525/elementa.2023.00037
- Enhanced Simulation of an Asian Dust Storm by Assimilating GCOM-C Observations Y. Cheng et al. 10.3390/rs13153020
- Air quality impacts on rooftop photovoltaic energy production during the 2019–2020 Australian bushfires season A. Isaza et al. 10.1016/j.solener.2023.04.014
- A New Algorithm for Himawari-8 Aerosol Optical Depth Retrieval by Integrating Regional PM₂.₅ Concentrations W. Xu et al. 10.1109/TGRS.2022.3155503
- Retrieval of hourly aerosol single scattering albedo over land using geostationary satellite data X. Jiang et al. 10.1038/s41612-024-00690-6
- Himawari-8 High Temporal Resolution AOD Products Recovery: Nested Bayesian Maximum Entropy Fusion Blending GEO With SSO Satellite Observations T. Zhang et al. 10.1109/TGRS.2023.3262785
- Analysis and validation of ocean color and aerosol properties over coastal regions from SGLI based on a simultaneous method M. Sekiguchi et al. 10.1007/s10872-021-00627-0
- A Geometry-Discrete Minimum Reflectance Aerosol Retrieval Algorithm (GeoMRA) for Geostationary Meteorological Satellite Over Heterogeneous Surfaces T. Zhang et al. 10.1109/TGRS.2022.3200425
- Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and Oceania Z. Yang et al. 10.1016/j.rse.2023.113878
- Validation, inter-comparison, and usage recommendation of six latest VIIRS and MODIS aerosol products over the ocean and land on the global and regional scales X. Su et al. 10.1016/j.scitotenv.2023.163794
- Improved hourly estimate of aerosol optical thickness over Asian land by fusing geostationary satellites Fengyun-4B and Himawari-9 Y. Cheng et al. 10.1016/j.scitotenv.2024.171541
- Precipitable water vapor estimation from Himawari-8/AHI observations using a stacking machine learning model Z. Du et al. 10.1016/j.atmosres.2024.107281
- System vicarious calibration of GCOM-C/SGLI visible and near-infrared channels H. Murakami et al. 10.1007/s10872-022-00632-x
- Accuracy and error cause analysis, and recommendations for usage of Himawari-8 aerosol products over Asia and Oceania L. Feng et al. 10.1016/j.scitotenv.2021.148958
- Evaluation and uncertainty analysis of Himawari-8 hourly aerosol product version 3.1 and its influence on surface solar radiation before and during the COVID-19 outbreak C. Tang et al. 10.1016/j.scitotenv.2023.164456
- Fengyun 4A Land Aerosol Retrieval: Algorithm Development, Validation, and Comparison With Other Datasets X. Su et al. 10.1109/TGRS.2023.3330544
- Geographical coverage analysis and usage suggestions of temporal averaged aerosol optical depth product from GOES-R satellite data X. Jiang et al. 10.1080/01431161.2024.2331978
- Evaluation of LaSRC aerosol optical depth from Landsat-8 and Sentinel-2 in Guangdong-Hong Kong-Macao greater bay area, China Y. Jin et al. 10.1016/j.atmosenv.2022.119128
- Improvement in Dust Storm Simulation by Considering Stone Coverage Effects for Stony Deserts in East Asia T. Sekiyama et al. 10.1029/2022JD037295
19 citations as recorded by crossref.
- An aerosol odyssey: Navigating nutrient flux changes to marine ecosystems D. Hamilton et al. 10.1525/elementa.2023.00037
- Enhanced Simulation of an Asian Dust Storm by Assimilating GCOM-C Observations Y. Cheng et al. 10.3390/rs13153020
- Air quality impacts on rooftop photovoltaic energy production during the 2019–2020 Australian bushfires season A. Isaza et al. 10.1016/j.solener.2023.04.014
- A New Algorithm for Himawari-8 Aerosol Optical Depth Retrieval by Integrating Regional PM₂.₅ Concentrations W. Xu et al. 10.1109/TGRS.2022.3155503
- Retrieval of hourly aerosol single scattering albedo over land using geostationary satellite data X. Jiang et al. 10.1038/s41612-024-00690-6
- Himawari-8 High Temporal Resolution AOD Products Recovery: Nested Bayesian Maximum Entropy Fusion Blending GEO With SSO Satellite Observations T. Zhang et al. 10.1109/TGRS.2023.3262785
- Analysis and validation of ocean color and aerosol properties over coastal regions from SGLI based on a simultaneous method M. Sekiguchi et al. 10.1007/s10872-021-00627-0
- A Geometry-Discrete Minimum Reflectance Aerosol Retrieval Algorithm (GeoMRA) for Geostationary Meteorological Satellite Over Heterogeneous Surfaces T. Zhang et al. 10.1109/TGRS.2022.3200425
- Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and Oceania Z. Yang et al. 10.1016/j.rse.2023.113878
- Validation, inter-comparison, and usage recommendation of six latest VIIRS and MODIS aerosol products over the ocean and land on the global and regional scales X. Su et al. 10.1016/j.scitotenv.2023.163794
- Improved hourly estimate of aerosol optical thickness over Asian land by fusing geostationary satellites Fengyun-4B and Himawari-9 Y. Cheng et al. 10.1016/j.scitotenv.2024.171541
- Precipitable water vapor estimation from Himawari-8/AHI observations using a stacking machine learning model Z. Du et al. 10.1016/j.atmosres.2024.107281
- System vicarious calibration of GCOM-C/SGLI visible and near-infrared channels H. Murakami et al. 10.1007/s10872-022-00632-x
- Accuracy and error cause analysis, and recommendations for usage of Himawari-8 aerosol products over Asia and Oceania L. Feng et al. 10.1016/j.scitotenv.2021.148958
- Evaluation and uncertainty analysis of Himawari-8 hourly aerosol product version 3.1 and its influence on surface solar radiation before and during the COVID-19 outbreak C. Tang et al. 10.1016/j.scitotenv.2023.164456
- Fengyun 4A Land Aerosol Retrieval: Algorithm Development, Validation, and Comparison With Other Datasets X. Su et al. 10.1109/TGRS.2023.3330544
- Geographical coverage analysis and usage suggestions of temporal averaged aerosol optical depth product from GOES-R satellite data X. Jiang et al. 10.1080/01431161.2024.2331978
- Evaluation of LaSRC aerosol optical depth from Landsat-8 and Sentinel-2 in Guangdong-Hong Kong-Macao greater bay area, China Y. Jin et al. 10.1016/j.atmosenv.2022.119128
- Improvement in Dust Storm Simulation by Considering Stone Coverage Effects for Stony Deserts in East Asia T. Sekiyama et al. 10.1029/2022JD037295
Latest update: 17 Jul 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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