气候变化领域集成服务门户(CCPortal): Averaging over spatiotemporal heterogeneity substantially biases evapotranspiration rates in a mechanistic large-scale land evaporation model

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DOI	10.5194/hess-24-5015-2020
	Averaging over spatiotemporal heterogeneity substantially biases evapotranspiration rates in a mechanistic large-scale land evaporation model
	Freund E.R.; Zappa M.; Kirchner J.W.
发表日期	2020
ISSN	1027-5606
起始页码	5015
结束页码	5025
卷号	24 期号:10
英文摘要	Evapotranspiration (ET) influences land-climate interactions, regulates the hydrological cycle, and contributes to the Earth's energy balance. Due to its feedback to large-scale hydrological processes and its impact on atmospheric dynamics, ET is one of the drivers of droughts and heatwaves. Existing land surface models differ substantially, both in their estimates of current ET fluxes and in their projections of how ET will evolve in the future. Any bias in estimated ET fluxes will affect the partitioning between sensible and latent heat and thus alter model predictions of temperature and precipitation. One potential source of bias is the so-called "aggregation bias"that arises whenever nonlinear processes, such as those that regulate ET fluxes, are modeled using averages of heterogeneous inputs. Here we demonstrate a general mathematical approach to quantifying and correcting for this aggregation bias, using the GLEAM land evaporation model as a relatively simple example. We demonstrate that this aggregation bias can lead to substantial overestimates in ET fluxes in a typical large-scale land surface model when sub-grid heterogeneities in land surface properties are averaged out. Using Switzerland as a test case, we examine the scale dependence of this aggregation bias and show that it can lead to an average overestimation of daily ET fluxes by as much as 10% across the whole country (calculated as the median of the daily bias over the growing season). We show how our approach can be used to identify the dominant drivers of aggregation bias and to estimate sub-grid closure relationships that can correct for aggregation biases in ET estimates, without explicitly representing sub-grid heterogeneities in large-scale land surface models. © 2020 Author(s).
语种	英语
scopus关键词	Earth (planet); Estimation; Evaporation; Evapotranspiration; Surface measurement; Atmospheric dynamics; Hydrological cycles; Hydrological process; Land surface modeling; Land surface models; Land surface properties; Mathematical approach; Spatiotemporal heterogeneities; Agglomeration; evapotranspiration; heterogeneity; numerical model; simulation; spatiotemporal analysis
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159278
作者单位	Freund, E.R., Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium, Department of Hydrology, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany, Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland; Zappa, M., Swiss Federal Research Institute WSL, Birmensdorf, 8903, Switzerland; Kirchner, J.W., Department of Environmental Systems Science, ETH Zurich, Zurich, 8092, Switzerland, Swiss Federal Research Institute WSL, Birmensdorf, 8903, Switzerland, Department of Earth and Planetary Science, University of California, Berkeley, CA 94720, United States
推荐引用方式 GB/T 7714	Freund E.R.,Zappa M.,Kirchner J.W.. Averaging over spatiotemporal heterogeneity substantially biases evapotranspiration rates in a mechanistic large-scale land evaporation model[J],2020,24(10).
APA	Freund E.R.,Zappa M.,&Kirchner J.W..(2020).Averaging over spatiotemporal heterogeneity substantially biases evapotranspiration rates in a mechanistic large-scale land evaporation model.Hydrology and Earth System Sciences,24(10).
MLA	Freund E.R.,et al."Averaging over spatiotemporal heterogeneity substantially biases evapotranspiration rates in a mechanistic large-scale land evaporation model".Hydrology and Earth System Sciences 24.10(2020).