Aerosol data assimilation using data from Fengyun-4A, a next-generation geostationary meteorological satellite. (15th September 2020)
- Record Type:
- Journal Article
- Title:
- Aerosol data assimilation using data from Fengyun-4A, a next-generation geostationary meteorological satellite. (15th September 2020)
- Main Title:
- Aerosol data assimilation using data from Fengyun-4A, a next-generation geostationary meteorological satellite
- Authors:
- Xia, Xiaoli
Min, Jinzhong
Shen, Feifei
Wang, Yuanbing
Xu, Dongmei
Yang, Chun
Zhang, Peng - Abstract:
- Abstract: The Fengyun-4A (FY-4A) meteorological satellite, a next-generation geostationary meteorological satellite, was launched on December 11, 2016. For instance, the Advanced Geosynchronous Radiation Imager (AGRI) aboard FY-4A (AGRI/FY-4A) takes full-disk images at a 15-min interval in 14 spectral bands with the 0.5–4-km resolution. Here we developed data assimilation system based on the Gridpoint Statistical Interpolation (GSI) system in which the Aerosol Optical Depth (AOD) derived from FY-4A data were successfully assimilated for the first time. The capability to assimilate FY-4A Aerosol optical depth (AOD) with an hourly cycling configuration was then evaluated by a dust storm over East Asia during 12–14 May 2019. The analyses initialized Weather Research and Forecasting-Chemistry (WRF-Chem) model forecasts. The system is tested with FY-4 AOD, Himawari-8 AOD in experiments and then the results are compared to the Aerosol Robotic Network (AERONET) AOD observations, which serving as the independent observations. The results indicated that assimilating FY-4 AOD substantially showed much better agreement with observations than those from the control. Furthermore, the Bias and RMSE generally reduced about 20% with forecast range. This study indicates that the aerosol data assimilation using data from FY-4A can be used to improve the performance of forecast model. Highlights: It is the first attempt to assimilate FY-4A AOD with a rapid-update DA system. It was investigatedAbstract: The Fengyun-4A (FY-4A) meteorological satellite, a next-generation geostationary meteorological satellite, was launched on December 11, 2016. For instance, the Advanced Geosynchronous Radiation Imager (AGRI) aboard FY-4A (AGRI/FY-4A) takes full-disk images at a 15-min interval in 14 spectral bands with the 0.5–4-km resolution. Here we developed data assimilation system based on the Gridpoint Statistical Interpolation (GSI) system in which the Aerosol Optical Depth (AOD) derived from FY-4A data were successfully assimilated for the first time. The capability to assimilate FY-4A Aerosol optical depth (AOD) with an hourly cycling configuration was then evaluated by a dust storm over East Asia during 12–14 May 2019. The analyses initialized Weather Research and Forecasting-Chemistry (WRF-Chem) model forecasts. The system is tested with FY-4 AOD, Himawari-8 AOD in experiments and then the results are compared to the Aerosol Robotic Network (AERONET) AOD observations, which serving as the independent observations. The results indicated that assimilating FY-4 AOD substantially showed much better agreement with observations than those from the control. Furthermore, the Bias and RMSE generally reduced about 20% with forecast range. This study indicates that the aerosol data assimilation using data from FY-4A can be used to improve the performance of forecast model. Highlights: It is the first attempt to assimilate FY-4A AOD with a rapid-update DA system. It was investigated for the dust storm occurred over East Asia on 12–14 May 2019. General positive impacts were achieved from assimilating high-frequency data. … (more)
- Is Part Of:
- Atmospheric environment. Volume 237(2020)
- Journal:
- Atmospheric environment
- Issue:
- Volume 237(2020)
- Issue Display:
- Volume 237, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 237
- Issue:
- 2020
- Issue Sort Value:
- 2020-0237-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09-15
- Subjects:
- Fengyun-4 satellite -- Aerosol optical depth -- Data assimilation -- Dust storm
Air -- Pollution -- Periodicals
Air -- Pollution -- Meteorological aspects -- Periodicals
551.51 - Journal URLs:
- http://www.sciencedirect.com/web-editions/journal/13522310 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.atmosenv.2020.117695 ↗
- Languages:
- English
- ISSNs:
- 1352-2310
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1767.120000
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