Estimation of Land Surface Temperature under Cloudy Skies Using Combined Diurnal Solar Radiation and Surface Temperature Evolution
Estimation of Land Surface Temperature under Cloudy Skies Using Combined Diurnal Solar Radiation and Surface Temperature Evolution
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DOI：
10.3390/rs70100905
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发表时间：
2015-01
期刊：
影响因子：
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通讯作者：
Xiaoyu Zhang;Jing Pang;Lingling Li
中科院分区：
文献类型：
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作者：
Xiaoyu Zhang;Jing Pang;Lingling Li
地表温度是陆地-大气系统相互作用的关键参数。然而，云会影响热红外遥感资料中地表温度数据的检索。因此，确定一种在天空阴天时估算地表温度的方法是很重要的。基于一维传热方程，结合日温度和净短波太阳辐射（NSSR）的演变，提出了一种利用日NSSR和地表温度估算多云天气下地表温度的新方法。根据中国长武生态系统实验站的原位测量结果进行了验证。结果表明，对于阴天数据，实际和估计的lst之间的均方根误差（RMSE）高达1.23 K。对晴空（Tclear）下估计的地表温度和估计的NSSR误差的敏感性分析表明，在实际Tclear上加上0.5 K的偏差，在实际NSSR上加上10%的NSSR误差，得到的Tcloud的RMSE小于1.5 K。利用MSG-SEVIRI的Tclear和NSSR产品估算南欧地区的Tcloud。结果表明，该算法对于阴天条件下的地表温度反演是可行的，但存在一定的不确定性。值得注意的是，由于假定日照变化引起地表温度变化，该方法只能在白天使用。此外，如果任何一天的清晰观测少于6次，则不能使用该方法。
Land surface temperature (LST) is a key parameter in the interaction of the land-atmosphere system. However, clouds affect the retrieval of LST data from thermal-infrared remote sensing data. Thus, it is important to determine a method for estimating LSTs at times when the sky is overcast. Based on a one-dimensional heat transfer equation and on the evolution of daily temperatures and net shortwave solar radiation (NSSR), a new method for estimating LSTs under cloudy skies (Tcloud) from diurnal NSSR and surface temperatures is proposed. Validation is performed against in situ measurements that were obtained at the ChangWu ecosystem experimental station in China. The results show that the root-mean-square error (RMSE) between the actual and estimated LSTs is as large as 1.23 K for cloudy data. A sensitivity analysis to the errors in the estimated LST under clear skies (Tclear) and in the estimated NSSR reveals that the RMSE of the obtained Tcloud is less than 1.5 K after adding a 0.5 K bias to the actual Tclear and 10 percent NSSR errors to the actual NSSR. Tcloud is estimated by the proposed method using Tclear and NSSR products of MSG-SEVIRI for southern Europe. The results indicate that the new algorithm is practical for retrieving the LST under cloudy sky conditions, although some uncertainty exists. Notably, the approach can only be used during the daytime due to the assumption of the variation in LST caused by variations in insolation. Further, if there are less than six Tclear observations on any given day, the method cannot be used.