期刊
REMOTE SENSING
卷 13, 期 15, 页码 -出版社
MDPI
DOI: 10.3390/rs13153020
关键词
aerosol data assimilation; GCOM-C; SGLI satellite; aerosol optical depths
类别
资金
- National Key Research and Development Program of China [2016YFC0202001, 2017YFC0209803]
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDA2006010302]
- National Natural Science Funds of China [41875133, 41590875, 41605083]
- Youth Innovation Promotion Association CAS [2020078]
- International Partnership Program of Chinese Academy of Sciences [134111KYSB20200006]
- Postgraduate Research and Practice Innovation Program of Jiangsu Province [KYCX20_0921]
- JAXA collaborative research project [ER2GCF214]
The Japanese SHIKISAI satellite, equipped with the SGLI instrument, allows for more precise global aerosol observations. By assimilating these observations using advanced models, such as 4D-LETKF and SPRINTARS coupled with NICAM, the study demonstrates significant improvements in Asian dust storm simulations.
Dust aerosols have great effects on global and regional climate systems. The Global Change Observation Mission-Climate (GCOM-C), also known as SHIKISAI, which was launched on 23 December 2017 by the Japan Aerospace Exploration Agency (JAXA), is a next-generation Earth observation satellite that is used for climate studies. The Second-Generation Global Imager (SGLI) aboard GCOM-C enables the retrieval of more precious global aerosols. Here, the first assimilation study of the aerosol optical thicknesses (AOTs) at 500 nm observed by this new satellite is performed to investigate a severe dust storm in spring over East Asia during 28-31 March 2018. The aerosol observation assimilation system is an integration of the four-dimensional local ensemble transform Kalman filter (4D-LETKF) and the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) coupled with the Non-Hydrostatic Icosahedral Atmospheric Model (NICAM). Through verification with the independent observations from the Aerosol Robotic Network (AERONET) and the Asian Dust and Aerosol Lidar Observation Network (AD-Net), the results demonstrate that the assimilation of the GCOM-C aerosol observations can significantly enhance Asian dust storm simulations. The dust characteristics over the regions without GCOM-C observations are better revealed from assimilating the adjacent observations within the localization length, suggesting the importance of the technical advances in observation and assimilation, which are helpful in clarifying the temporal-spatial structure of Asian dust and which could also improve the forecasting of dust storms, climate prediction models, and aerosol reanalysis.
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