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Taklimakan Desert, located in southwest Xinjiang Uyghur Autonomous Region, is one of the predominant dust origin in China. Dust is one of the main types of atmospheric aerosol in this region. Emerging remote sensing imagery from geostationary meteorological satellite undeniably becomes an ideal mean for monitoring large regional distribution and intensity of dust storms. Among them, Indian National Satellite (INSAT 3A) is suitable for dust aerosol retrieval and dust storm detection for Xinjiang region as it can provide high spatiotemporal earth observation with a Charge Couple Device (CCD) camera. The camera contains three bands with a spatial resolution of 1km, which are very applicable for AOD retrieval. However, there is still no mature algorithm for the retrieval of AOD over land using INSAT 3A data, though some work have been done with other geostationary satellites [1-4].

The purpose of this paper is to study the optical properties of dust aerosol and its relationship with dust events in Xinjiang area based on INSAT 3A data. Firstly, AOD in the desert area is derived utilizing an improved algorithm transplanted from a previous study using Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the geostationary satellite Meteosat Second Generation (MSG) [2]. This algorithm takes advantage of INSAT 3A three-band data and six predefined aerosol types. Besides, the algorithm was improved by considering the impact of the dust aerosol on short wave infrared band (1.6 mu m).

The retrieved AOD is then validated using MODIS AOD product, which shows a squared correlation coefficient of 0.83. Thereafter, a good exponential correlation is established between situ visibility obtained from an atmospheric station in Karshgar, and satellite-retrieved AOD (MODIS). The result shows a squared correlation coefficient of 0.67, which demonstrates the rationality of identifying and quantifying dust storm intensity with satellite retrieved AOD. A case study of a dust storm occurred on April 23, 2014 shows a good performance of dust identification using the retrieved AOD.