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GMS 5资料反演地表温度的一个修正算法
引用本文:王旻燕,吕达仁.GMS 5资料反演地表温度的一个修正算法[J].地球物理学报,2005,48(5):1034-1044.
作者姓名:王旻燕  吕达仁
作者单位:中国科学院大气物理研究所LAGEO,北京,100029;中国科学院大气物理研究所LAGEO,北京,100029
基金项目:国家自然科学基金(49790020,40027002),科技部基础预研专项基金(2001CCA02200)联合资助.
摘    要:本文研究发展利用GMS 5/VISSR每小时卫星观测资料反演地表温度的方法,首先利用时空判断法进行云检测寻找晴空像元,然后从辐射传输方程出发,由实时探空资料求取大气上行、下行辐射率及大气透过率,根据由AVHRR NDVI导出的地表比辐射率,用单时相双光谱分裂窗法反演得到地表温度.比较反演结果与54511站及其他中国基准站2000年地面0cm地表温度实测值,相对于国际上其他经验公式而言,本文算法在精度上有所提高.敏感性分析试验着重于大气衰减的影响.基于本文算法,给出了内蒙中东部地区地表温度连续4天的变化实例以及东亚部分陆地“纯晴天”地表温度图.

关 键 词:GMS  地表温度LST  分裂窗算法  云检测  地表比辐射率
文章编号:0001-5733(2005)05-1034-11
收稿时间:2004-03-22
修稿时间:2004-03-222005-05-17

An improved algorithm to retrieve land surface temperature by GMS 5 data
WANG Min-yan,LU Da-Ren.An improved algorithm to retrieve land surface temperature by GMS 5 data[J].Chinese Journal of Geophysics,2005,48(5):1034-1044.
Authors:WANG Min-yan  LU Da-Ren
Institution:LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Abstract:An algorithm to retrieve land surface temperature by GMS 5/VISSR thermal infrared data is improved, which is called the single time/dual channel split-window algorithm. It adopts the spatial-temporal threshold criterion for cloud detection. From real-time radiosonde data the atmospheric upward and downward radiation and transmissivity are calculated, and the involved emissivity is derived from AVHRR-NDVI. Thus, LST in two thermal infrared channels is retrieved from the RTE (Radiation Transport Equation). Compared with the observed surface temperature (0 cm) at station 54511 and other 43 stations in 2000, LST solutions from RTE are more accurate, with respect to other international algorithms. Sensitivity analysis focuses on the effect of atmospheric attenuation. Based on this algorithm, land surface diurnal cycle in 4 continuous days in the middle and east of Inner Mongolia and the yearly average land surface temperature distribution in pure clear days in East Asia are presented.
Keywords:GMS  Land surface temperature  Split-window algorithm  Cloud detection  Emissivity
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