Enhanced Simulation of an Asian Dust Storm by Assimilating GCOM-C Observations

• Published in: Remote Sensing
• Main Authors: Yueming Cheng, Tie Dai, Daisuke Goto, Hiroshi Murakami, Mayumi Yoshida, Guangyu Shi, Teruyuki Nakajima
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2021
• Subjects: aerosol data assimilation; GCOM-C/SGLI satellite; aerosol optical depths; Science; Q; Aerosol Robotic Network
• Online Access: https://doi.org/10.3390/rs13153020; https://doaj.org/article/f9d96e79198446aeab517ba415a76344

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.