Dust Detection Over East Asia From Multispectral and Multi‐Temporal Himawari‐8/AHI Thermal Infrared Observations

Abstract

Dust storms are extremely destructive weather events that commonly occur over deserts worldwide and are transported to surrounding areas by strong winds (Park et al., 2014). The mineral dust aerosols affect the radiative energy budget and thermodynamic structure of the Earth and Atmosphere system through extinction and emission of radiation and play an essential role in processes governing the weather and climate system (Miller et al., 2017;Painter et al., 2010;Zheng et al., 2022). Dust storms are frequent in northwestern China and Mongolia every spring (Park et al., 2014;She et al., 2018). The dust can sweep most of northern and eastern China, South Korea, and Japan and cause severe air pollution and economic losses before settling in the ocean (Han et al., 2022). Surface observations are sparse, and difficult to locate and track dust transport. Satellite remote sensing may be the only means of large-scale and all-day monitoring of dust events (Hu et al., 2008). While the duration of dust storms is from hours to days, and the coverage is substantial (Li et al., 2021), the ultra-high temporal sampling frequency of geostationary weather satellites makes them a better choice for dust detection.In the last decades, various detection methods have been developed based on the spectral properties of dust (Zhou et al., 2020). In the solar shortwave wavelengths, an important feature of dust is strong ultraviolet absorption. The Absorption Aerosol Index (AAI) has been used to detect dust for more than 40 years based on the relatively small reflectance variation between the two ultraviolet channels in the presence of dust aerosols (Stein Zweers, 2021). Similar to AAI, the Dust Aerosol Index calculated from the reflectance of deep blue and blue channels is an effective metric for the preliminary separation of dust aerosols (Ciren & Kondragunta, 2014;Hsu et al., 2004;Zhou et al., 2020). The absorption of dust gradually decreases with increasing wavelength in the visible and near-infrared (VIR) wavelengths, leading it to appear generally as yellow on the true color image (Miller, 2003). Therefore, the reflectance, the reflectance ratio, and the reflectance normalized difference index of VIR bands can be used as a basic test for dust detection (