Abstract

Asian dust storm outbreaks significantly influence air quality, weather, and climate. Therefore, it is desirable to have qualitative and quantitative information on the time, location, and coverage of these outbreaks at high spatial and temporal resolution. The imager on board the Indian metrological geostationary satellite INSAT-3D observes Asia at a temporal resolution of 30 min and a spatial resolution of 1, 4, 8, and 4 km in the visible, middle infrared (MIR), water vapour (WV), and thermal infrared (TIR) bands, respectively. In this article, an algorithm is described for detecting desert dust storms from INSAT-3D imager data. The algorithm described here is a combination of various pre-existing methods such as infrared split-window, MIR and TIR brightness temperature difference, and visible to MIR reflectance ratio, which are based on the fact that dust exhibits features of spectral dependence and contrast over the visible, MIR, and TIR spectrum that are different from clouds, surface, and clear-sky atmosphere. Using the Atmospheric Infrared Sounder (Aqua/AIRS) dust score as proxy, INSAT-3D dust storm products were tested under different scenarios such as dust storms and dust transport in Asia. TIR observations from the geostationary platform of INSAT-3D allows computation of the infrared difference dust index (IDDI), which gives a quantitative measure of dust loading relative to clear atmosphere. Moreover, due to the high temporal resolution (30 min) of INSAT-3D observations, INSAT-3D-derived dust products allow more precise monitoring of dust transportation as compared with dust products derived from polar satellite observations.

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