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	Variational Estimation of Land-Atmosphere Heat Fluxes and Land Surface Parameters Using MODIS Remote Sensing Data
	Meng C. L. ; Zhang C. L. ; Tang R. L.
	2013
关键词	data assimilation system soil-moisture lai product multiscale analysis temperature validation model fraction
英文摘要	A variational data assimilation algorithm for assimilating the land surface temperature (LST) into the Common Land Model (CLM) was implemented using the land surface energy balance equation as the adjoint physical constraint. In this data assimilation algorithm, the evaporative fractions of the soil and canopy were adjusted according to the remotely sensed surface temperature observations. This paper developed a very simple analytical algorithm to characterize the errors' weighting matrices in the cost function. The leaf area index (LAI) retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) was also assimilated into CLM using the direct insertion method. The analysis results from the CLM with the LST assimilation algorithm compare well with MODIS and field observations for the Yucheng site, especially in daytime. On the basis of the histogram of the error of the LST, it can be concluded that after assimilation, the LST was greatly improved in comparison with the MODIS observations, especially in daytime. These results indicate that this surface temperature assimilation method is efficient and effective, even when only one time observational LST data point is available for each day, especially in daytime. The regional spatial patterns of evapotranspiration and soil surface moisture were also compared before assimilation on the basis of LAI data calculated using the empirical formula, before assimilation on the basis of MODIS LAI data, and after assimilation on the basis of MODIS LAI data.
出处	Journal of Hydrometeorology
卷	14
期	2
页	608-621
收录类别	SCI
语种	英语
ISSN号	1525-755X
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/30342]
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	Meng C. L.,Zhang C. L.,Tang R. L.. Variational Estimation of Land-Atmosphere Heat Fluxes and Land Surface Parameters Using MODIS Remote Sensing Data. 2013.

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