Fast and operational gap filling in satellite-derived aerosol optical depths using statistical techniques

作者：Kyunghwa Lee, Mijeong Kim, Myungje Choi, Jhoon Kim, Yunsoo Choi, Jaehoon Jeong, Kyung‐Jung Moon, Sojin Lee · 发表于：Journal of Applied Remote Sensing · 年份：2022 · DOI：10.1117/1.jrs.16.044507 · 被引用次数：13 · 研究领域：Atmospheric aerosols and clouds、Atmospheric and Environmental Gas Dynamics、Atmospheric chemistry and aerosols

Satellite observations, used worldwide in the atmospheric sciences, are extremely useful for providing aerosol information within a wide spatial range. However, the coverage of aerosol data by satellite observations is sometimes of inferior quality because of the effects of surface reflectivity and clouds. To fill the gaps in aerosol optical depths (AODs) retrieved from geostationary ocean color imager observations, this study applies operational statistical techniques, including radial basis functions (RBFs) with four different weightings (i.e., linear, multiquadric, thin-plate, and inverse), Poisson, and ordinary Kriging. Based on computation time and accuracy of the individual gap-filling techniques, Poisson and the liner RBF are selected as the two best methods and then averaged with weights using one-dimensional weighted average (1D-WAVG) and two-dimensional weighted average (2D-WAVG) root mean square errors. All methods produce reliable results, yielding a correlation coefficient between 0.74 and 0.87 over the entire research domain. Out of the individual techniques, the Poisson, with an initial estimation from a zonal mean of AODs, is the most accurate with the lowest computational costs, even for a large number of missing pixels and most regions, excluding East China (EC). The Poisson’s high bias over EC is compensated in 1D- and 2D-WAVGs by taking more accurate estimations of the linear RBF than those of the Poisson over the region. If we consider 1D- and 2D-WAVGs in...