GSTDTAP  > 气候变化
DOI10.1111/gcb.16002
A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems
Vicente Burchard-Levine; ; ctor Nieto; David Riañ; o; Wiliam P. Kustas; Mirco Migliavacca; Tarek S. El-Madany; Jacob A. Nelson; Ana Andreu; Arnaud Carrara; Jason Beringer; Dennis Baldocchi; M. Pilar Martí; n
2021-12-02
发表期刊Global Change Biology
出版年2021
英文摘要

It is well documented that energy balance and other remote sensing-based evapotranspiration (ET) models face greater uncertainty over water-limited tree-grass ecosystems (TGEs), representing nearly 1/6th of the global land surface. Their dual vegetation strata, the grass-dominated understory and tree-dominated overstory, make for distinct structural, physiological and phenological characteristics, which challenge models compared to more homogeneous and energy-limited ecosystems. Along with this, the contribution of grasses and trees to total transpiration (T), along with their different climatic drivers, is still largely unknown nor quantified in TGEs. This study proposes a thermal-based three-source energy balance (3SEB) model, accommodating an additional vegetation source within the well-known two-source energy balance (TSEB) model. The model was implemented at both tower and continental scales using eddy-covariance (EC) TGE sites, with variable tree canopy cover and rainfall (P) regimes and Meteosat Second Generation (MSG) images. 3SEB robustly simulated latent heat (LE) and related energy fluxes in all sites (Tower: LE RMSD ~60 W/m2; MSG: LE RMSD ~90 W/m2), improving over both TSEB and seasonally changing TSEB (TSEB-2S) models. In addition, 3SEB inherently partitions water fluxes between the tree, grass and soil sources. The modelled T correlated well with EC T estimates (r > .76), derived from a machine learning ET partitioning method. The T/ET was found positively related to both P and leaf area index, especially compared to the decomposed grass understory T/ET. However, trees and grasses had contrasting relations with respect to monthly P. These results demonstrate the importance in decomposing total ET into the different vegetation sources, as they have distinct climatic drivers, and hence, different relations to seasonal water availability. These promising results improved ET and energy flux estimations over complex TGEs, which may contribute to enhance global drought monitoring and understanding, and their responses to climate change feedbacks.

领域气候变化 ; 资源环境
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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/343059
专题气候变化
资源环境科学
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GB/T 7714
Vicente Burchard-Levine,Hé,ctor Nieto,et al. A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems[J]. Global Change Biology,2021.
APA Vicente Burchard-Levine.,Hé.,ctor Nieto.,David Riañ.,o.,...&n.(2021).A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems.Global Change Biology.
MLA Vicente Burchard-Levine,et al."A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems".Global Change Biology (2021).
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