程洁等:Effects of Thermal-Infrared Emissivity Directionality on Surface Broadband Emissivity and Longwave Net Radiation Estimation
被阅读 1923 次
2014-04-04

Effects of Thermal-Infrared Emissivity Directionality on Surface Broadband Emissivity and Longwave Net Radiation Estimation
作者:Cheng, J (Cheng, Jie)[ 1 ] ; Liang, SL (Liang, Shunlin)[ 1,2 ]
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷: 11  期: 2  页: 499-503
DOI: 10.1109/LGRS.2013.2270293
出版年: FEB 2014

摘要
Directionality is ignored in the satellite retrieval of surface thermal-infrared emissivity, which will unavoidably affect the estimates of surface broadband emissivity and surface longwave net radiation. The purpose of this work is to quantify the effects of emissivity directionality. First, three types of emissivity data are used to calculate hemispherical emissivity and the difference between directional broadband emissivity and hemispherical broadband emissivity. The emissivity directionality is highly significant, and the directional emissivity decreases with increasing view angles. A view angle within 45 degrees-60 degrees can be found whose directional emissivity is highly close to the hemispherical emissivity, and the difference between the calculated directional and hemispherical broadband emissivity is zero. The difference between the atmospheric downward radiation and blackbody radiation at surface temperature is then determined by extensive simulations. Finally, the error ranges of surface longwave net radiation are presented. If the sensor scan angle is within +/- 55 degrees, the error can reach as high as 17.48 and 14.05 W/m(2) for water and bare ice, respectively; the error is less than 2.74 W/m(2) for snow with different radii; the error can reach 4.11 W/m(2) for sun crust; the error is less than 5.14 W/m(2) for minerals, sand, slime and gravel; and clay has the smallest error at 1.02 W/m(2).

通讯作者地址: Cheng, J (通讯作者)
Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.
地址:
[ 1 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[ 2 ] Univ Maryland, Dept Geog, College Pk, MD 20742 USA