Abstract
All-weather, all-season microwave remote sensing is one of the most powerful technologies for monitoring natural disasters. Multichannel brightness temperature (T b) measurements from satellite-borne passive microwave remote sensing has played an important role in retrieving quantitative physical information regarding global and regional weather and climate, atmospheric precipitation, land hydrology, and oceanic surface winds. However, in January 2008, during severe weather conditions with heavy snow and frost in the usually warm south of China, the operational algorithm for snow detection using multichannel T b data failed to detect snow. In this article, based on the simulation of vector radiative transfer of a snowpack model of dense and sticky Mie ice particles, characteristic indexes of scattering and polarization differences, average indexes in the previous year under normal situation, and changes in antecedent indexes are newly defined and analysed. A new detection flowchart is designed to effectively detect the regional snow and frost disaster in 2008 in southern China.
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