Abstract
Abstract Himawari-8, a new generation geostationary satellite, with the Advanced Himawari Imager (AHI) providing Full Disk observation with high temporal resolution (10 min) exhibits prominent advantage in monitoring aerosols over East Asia region. The AHI has 16 channels from 0.46 to 13.3 to capture visible and infrared spectral data. In this paper, we developed a regional algorithm to retrieve the Aerosol Optical Depth (AOD) over Beijing area based on the AHI visible and short-wave infrared (SWIR) data from June to August 2016. The AHI surface reflectance at 0.46, 0.64, 0.86 and 2.3 μm channel was obtained using the lowest gas-corrected reflectance based on the three-month top of the atmosphere (TOA) data. The algorithm employed superposing technique and linear regression to iteratively train the AHI surface reflectance, and built optimal surface reflectance relationships between visible and SWIR bands with three Normalized Difference Vegetation Index (NDVI) classifications over Beijing area. Based on these surface reflectance relationships, the AHI AOD data were retrieved through the radiation transmission function. The AOD products from the AErosol RObotic NETwork (AERONET) ground measurement, the MODerate resolution Imaging Spectroradiometer (MODIS) and the Japan Aerospace Exploration Agency (JAXA) official AHI were used to evaluate the performance of our AOD retrievals. At diurnal scale, more than 66% of AHI AOD retrievals fell within the EE in the afternoon, which indicated that these retrievals could capture the regional aerosol variability over Beijing area. In contrast, the AHI JAXA AOD product significantly overestimated aerosol loadings. The low AOD biases (13:00–16:00) under low aerosol conditions from our retrieval algorithm demonstrated that the AHI surface reflectance assumptions are available. However, AHI retrievals in XiangHe overestimated AOD under high aerosol conditions, which indicated that the urban aerosol model is inappropriate over this site. In addition, our AHI AOD algorithm was only applied over Beijing area in the summer of 2016. The retrieval time-independence in this algorithm has not been estimated in fall and winter when NDVI is lower. Future study will investigate this surface algorithm at larger temporal and spatial scales.
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