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Study of Aerosol Influence on Nighttime Land Surface Temperature Retrieval Based on Two Methods

机译:基于两种方法的气溶胶对夜间地表温度反演的影响

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The aim of this study is to evaluate the aerosol influence on LST retrieval with two algorithms (split-window (SW) method and a four-channel based method) using simulated data under typical conditions. The results show that the root mean square error (RMSE) decreases to approximately 2.3 K for SW method and 1.5 K for four channel based method when VZA = 60° and visibility = 3 km; an RMSE would be increased by approximately 1.0 K when visibility varies from 3 km to 23 km. Moreover, a detailed sensitivity analysis under a visibility of 3 km and 23 km is performed in terms of uncertainties of land surface emissivity (LSE), water vapor content (WVC), and instrument noise, respectively. It is noted that the four-channel based method is more sensitive to LSE than SW method, especially for dry atmosphere; LST error caused by a WVC uncertainty of 20% is within 1.5 K for SW method and within 0.8 K for four-channel based method; the instrument noise would introduce LST error with a maximum standard deviation of 0.5 K and 0.04 K for the four-channel based method and SW method, respectively.
机译:这项研究的目的是使用典型条件下的模拟数据,通过两种算法(分割窗口(SW)方法和基于四通道的方法)评估气溶胶对LST检索的影响。结果表明,当VZA = 60°且能见度= 3 km时,SW法的均方根误差(RMSE)降低至约2.3 K,四通道法的均方根误差降低至1.5K。当能见度从3公里到23公里不等时,RMSE大约增加1.0K。此外,分别在地表发射率(LSE),水汽含量(WVC)和仪器噪声的不确定性方面进行了在3?km和23?km可见度下的详细灵敏度分析。值得注意的是,基于四通道的方法对LSE的敏感性比对SW方法的敏感性高,尤其是对于干燥的大气环境。 WVC不确定性由20%引起的LST误差,对于SW方法而言,在1.5 K之内,对于基于四通道方法的LST误差在0.8 K之内;对于基于四通道的方法和基于SW的方法,仪器噪声会导致LST误差,最大标准偏差分别为0.5 K和0.04K。

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