中文摘要：

在对地表温度（land surface temperature,LST）进行反演时,通常由于缺乏详细大气剖面数据使得大气透射率难以获取。基于实地大气模式,借助近地面气温、相对湿度和大气压3个基本参量,改进了大气透射率反演方法;在大气水分含量超出0.4~3.0 g·cm-2的极端情况下,建立了相应的大气透射率估计方程;并在此基础上,对全国范围大气透射率的变化进行了监测。研究结果表明,在大气水分含量较低的情况下,该方法精度较高,其相对误差在1.33%~4.07%之间,仅会对LST产生0.2℃~0.6℃的反演误差,比改进前的反演精度提高了25%~71%。

英文摘要：

When the land surface temperature（LST） is inverted by using mono -window algorithm, it is difficult to obtain atmospheric transmissivity when detailed atmospheric profile data are absent. In this study, an atmospheric transmissivity inversion method was improved using three basic parameters comprising near - surface temperature, relative humidity and atmospheric pressure based on the field atmospheric modes. The authors established the corresponding equations to estimate atmospheric transmittance when the atmospheric moisture content exceeds 0.4-3.0 g·cm^-2. On such a basis, the authors monitored the atmospheric transmissivity changes on nationwide scale. The resuhs of the study show that the method proposed in this paper has very high precision under the condition of lower atmospheric moisture content. The precision of LST is improved by about 25% to 71%, and only when the relative error is between 1.33% and 4.07%, the LST produces error between 0.2℃ and 0.6%.