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	Sensitivity study of soil moisture on the temporal evolution of surface temperature over bare surfaces
	Zhao W. ; Li Z. L.
	2013
关键词	mesoscale eta-model thermal inertia water content infrared data retrieval index implementation simulations calibration evaporation
英文摘要	Land surface soil moisture (SSM) is a fundamental variable in the hydrological cycle and is an important parameter in investigations on water and energy balances at the Earth's surface. Many efforts have been made to derive SSM from remotely sensed thermal infrared data. Using the Noah land surface model (LSM) and the Gaussian emulation machine for sensitivity analysis (GEM-SA) software, a sensitivity study was conducted for bare soil to investigate the interrelationship between the evolution of land surface temperature (LST) and SSM. Based on the diurnal cycles of LST and net surface shortwave radiation, eight parameters intuitively related to SSM were defined, and a sensitivity analysis (SA) was performed in the presence and absence of atmospheric variation. The results provided insight into the relationships between the eight parameters and various environmental factors such as soil physical parameters, soil moisture, albedo, and atmospheric parameters. For instance, the results suggested that the surface air temperature had a significant effect on the LST, especially the maximum, minimum, and average daytime temperatures. For a given atmospheric forcing data set, the LST rising rate normalized by the difference in the net surface shortwave radiation during the mid-morning (T-N) was the parameter most sensitive to the SSM, contributing 80.72% to the total variance. In addition, the time at which the daily maximum temperature occurred (t(d)), the daily minimum temperature, and the LST nocturnal decay coefficient were strongly related to the soil type. Using a linear combination of T-N and t(d), a method was proposed to retrieve the SSM, and the coefficients of the linear model were found to be independent of the soil type for a given atmospheric condition. Compared with the actual SSM values used in the Noah LSM simulation, the root mean square error (RMSE) of the SSM retrieved from our proposed method was within 0.04 m(3) m(-3) for all the 20 clear days evaluated in the present study.
出处	International Journal of Remote Sensing
卷	34
期	9-10
页	3314-3331
收录类别	SCI
语种	英语
ISSN号	0143-1161
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/30003]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Zhao W.,Li Z. L.. Sensitivity study of soil moisture on the temporal evolution of surface temperature over bare surfaces. 2013.

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