Detection of dust storms from multi-channel satellite imagers

Aerosols, especially those with large spatial and temporal variability, such as dust, exert large influences on climate, weather, air quality, hydrological cycles, and ecosystems. Detection of these highly variable aerosols is challenging because of their episodic features, such as short lifetime, multi-scales, and strong interactions with local and regional surface and meteorological conditions. Since dust particles can directly alter solar and earth radiation in both visible and infrared (IR) spectral regions through scattering and absorption processes, both visible and IR remote sensing techniques can be used for detection of dust in the atmosphere. In this paper, we introduce an algorithm for detecting episodic dust storms from satellite imagers considering dust particles display some spectral variations in visible and IR spectral regions different from those of cloud or clear-sky condition. The detection is based on the analysis of reflectance (or radiance) in visible bands or brightness temperature (BT) in IR bands. The magnitude of the difference in reflectance and/or BTs in selected bands (or channels) is used to infer the signature of dust. Detailed description of the algorithm and the examples of dust storm detection will be provided.