Improvement of the dust retrieval algorithm using GK-2A Geostationary satellite by updating Asian dust chemical composition

Abstract

Dust storms often occur in the spring season and influence large areas of Korean peninsula. During a dust storm event, the concentration of dust particles in the atmosphere increases significantly. Satellite monitoring is a powerful tool for studying the properties of large-scale dust storms. however, amidst all uncertainties associated with aerosol properties, the inadequate information about the chemical composition of the dust also greatly affects the radiation field at the top of atmosphere (TOA). GEO-KOMPSAT-2A is a South Korean geostationary meteorological satellite for the meteorological mission and the space weather monitoring mission. It has been equipped with AMI (Advanced Meteorological Imager) and KSEM (Korean Space Environment Monitor) payloads. In this study, an algorithm will be investigated that uses four infrared channels: 8.6 μm, 10.4 μm, 11.2 μm and 12.4 μm, on the AMI. updating Asian dust components according to 25 samples collected during 14 Asian dust events occurring between 2005 and 2018 on the Korean Peninsula and compared them to 34 soil samples (<20 µm) obtained from the Mongolian Gobi Desert, which is a major source of Asian dust will be presented. We used the libRadtran radiative transfer model for simulation of the atmospheric condition, presence of the aerosols and radiance reaching TOA. according to the refractive index and size distribution dataset of new components and strong dependency of TIR wavelength bands to the optical properties of the dust we expect this method will increase the accuracy of the algorithm.