Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets

doi:10.1088/1748-9326/aac4bb

	Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets
	Wartenburger,Richard 1,37; Seneviratne,Sonia I 1; Hirschi,Martin 1; Chang,Jinfeng 24,30; Ciais,Philippe 24; Deryng,Delphine 2,3; Elliott,Joshua 26; Folberth,Christian 9; Gosling,Simon N 20; Gudmundsson,Lukas 1
刊名	Environmental Research Letters
	2018-06-21
卷号	13 期号:7
关键词	ISIMIP2a evapotranspiration uncertainty cluster analysis hydrological extreme events
ISSN号	1748-9326
DOI	10.1088/1748-9326/aac4bb
英文摘要	Abstract Actual land evapotranspiration (ET) is a key component of the global hydrological cycle and an essential variable determining the evolution of hydrological extreme events under different climate change scenarios. However, recently available ET products show persistent uncertainties that are impeding a precise attribution of human-induced climate change. Here, we aim at comparing a range of independent global monthly land ET estimates with historical model simulations from the global water, agriculture, and biomes sectors participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Among the independent estimates, we use the EartH2Observe Tier-1 dataset (E2O), two commonly used reanalyses, a pre-compiled ensemble product (LandFlux-EVAL), and an updated collection of recently published datasets that algorithmically derive ET from observations or observations-based estimates (diagnostic datasets). A cluster analysis is applied in order to identify spatio-temporal differences among all datasets and to thus identify factors that dominate overall uncertainties. The clustering is controlled by several factors including the model choice, the meteorological forcing used to drive the assessed models, the data category (models participating in the different sectors of ISIMIP2a, E2O models, diagnostic estimates, reanalysis-based estimates or composite products), the ET scheme, and the number of soil layers in the models. By using these factors to explain spatial and spatio-temporal variabilities in ET, we find that the model choice mostly dominates (24%–40% of variance explained), except for spatio-temporal patterns of total ET, where the forcing explains the largest fraction of the variance (29%). The most dominant clusters of datasets are further compared with individual diagnostic and reanalysis-based estimates to assess their representation of selected heat waves and droughts in the Great Plains, Central Europe and western Russia. Although most of the ET estimates capture these extreme events, the generally large spread among the entire ensemble indicates substantial uncertainties.
语种	英语
出版者	IOP Publishing
WOS记录号	IOP:1748-9326-13-7-AAC4BB
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/67774]
专题	中国科学院地理科学与资源研究所
作者单位	1.Institute for Atmospheric and Climate Science, ETH Zurich, Universitaetstrasse 16, CH-8092 Zurich, Switzerland 2.Climate Analytics, 10969 Berlin, Germany 3.Columbia University Center for Climate Systems Research, New York, NY 10025, United States of America 4.International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria 5.Institute of Physical Geography, Goethe-University Frankfurt, Frankfurt, Germany 6.Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Frankfurt, Germany 7.Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, People’s Republic of China 8.Atmospheric Sciences & Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States of America 9.Ecosystem Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria 10.School of Geography, Earth & Environmental Sciences and Birmingham Institute of Forest Research, University of Birmingham, Birmingham, United Kingdom
推荐引用方式 GB/T 7714	Wartenburger,Richard,Seneviratne,Sonia I,Hirschi,Martin,et al. Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets[J]. Environmental Research Letters,2018,13(7).
APA	Wartenburger,Richard.,Seneviratne,Sonia I.,Hirschi,Martin.,Chang,Jinfeng.,Ciais,Philippe.,...&Zhou,Tian.(2018).Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets.Environmental Research Letters,13(7).
MLA	Wartenburger,Richard,et al."Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets".Environmental Research Letters 13.7(2018).