干旱区生态环境知识资源中心(Arid): A numerical analysis of aggregation error in evapotranspiration estimates due to heterogeneity of soil moisture and leaf area index

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DOI	10.1016/j.agrformet.2019.02.017
	A numerical analysis of aggregation error in evapotranspiration estimates due to heterogeneity of soil moisture and leaf area index
	Chen, Qiting 1,2; Jia, Li 1; Menenti, Massimo 1,3; Hutjes, Ronald 2; Hu, Guangcheng 1; Zheng, Chaolei 1; Wang, Kun 1
通讯作者	Jia, Li
来源期刊	AGRICULTURAL AND FOREST METEOROLOGY
ISSN	0168-1923
EISSN	1873-2240
出版年	2019
卷号	269 页码:335-350
英文摘要	Land Surface Models which determine evapotranspiration (ET) by neglecting the sub-grid heterogeneity of land-atmosphere parameters will cause aggregation biases in spatially-averaged ET estimates, considering the non-linear dependences of ET on the heterogeneous land-atmosphere parameters. One frequently adopted strategy clusters the heterogeneous surface within a model grid into several tiles, assumed to be homogeneous, usually based on high-resolution land cover data. While the differences in bulk-averaged parameters between different tiles are considered, the heterogeneity within each tile is neglected. This study evaluated in detail the aggregation biases in the tile mean ET estimates due to applying bulk-averages of the Saturation degree of surface Soil Moisture (SSM) and Leaf Area Index (LAI) for each tile through numerical experiments. Four types of Probability Distribution Function (PDF) were used to simulate different scenarios on the heterogeneity (within a tile) of SSM and LAI, i.e., from water scarcity to wet, and from sparse to dense vegetation covered surfaces. Aggregation bias was calculated by comparing ET estimates based on bulk-averaged SSM and LAI with the one obtained by aggregation of the flux estimates based on the PDFs, which complies with energy conservation. In addition, a wide range of meteorological conditions was applied in our numerical experiments and the impacts were evaluated by binning results according to the reference ET (ET0). We found that potentially significant bias can be found in semi-arid areas. Neglecting the actual spatial variability of both SSM and LAI within tiles can lead to both large relative error (> 20%) and absolute error (> 1 mm/day) in the estimated ET. A negative bias is expected at low ET / ET0 and a positive bias is expected at large ET / ET0, regardless of climate conditions (i.e., ET0).
英文关键词	Evapotranspiration Heterogeneity Aggregation bias
类型	Article
语种	英语
国家	Peoples R China ; Netherlands
收录类别	SCI-E
WOS记录号	WOS:000463120900030
WOS关键词	SURFACE-ENERGY-BALANCE ; BIOSPHERE MODEL ; ECMWF MODEL ; RIVER-BASIN ; LAND ; PARAMETERIZATION ; SCALE ; WATER ; VEGETATION ; CLIMATE
WOS类目	Agronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS研究方向	Agriculture ; Forestry ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/213947
作者单位	1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China; 2.Wageningen Univ, NL-6700 AA Wageningen, Netherlands; 3.Delft Univ Technol, NL-2600 AA Delft, Netherlands
推荐引用方式 GB/T 7714	Chen, Qiting,Jia, Li,Menenti, Massimo,et al. A numerical analysis of aggregation error in evapotranspiration estimates due to heterogeneity of soil moisture and leaf area index[J],2019,269:335-350.
APA	Chen, Qiting.,Jia, Li.,Menenti, Massimo.,Hutjes, Ronald.,Hu, Guangcheng.,...&Wang, Kun.(2019).A numerical analysis of aggregation error in evapotranspiration estimates due to heterogeneity of soil moisture and leaf area index.AGRICULTURAL AND FOREST METEOROLOGY,269,335-350.
MLA	Chen, Qiting,et al."A numerical analysis of aggregation error in evapotranspiration estimates due to heterogeneity of soil moisture and leaf area index".AGRICULTURAL AND FOREST METEOROLOGY 269(2019):335-350.