| 题名 | Evapotranspiration simulations in ISIMIP2a-Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets |
| 作者 | Wartenburger, Richard1  ; Seneviratne, Sonia, I1; Hirschi, Martin1; Chang, Jinfeng24,31; Ciais, Philippe24; Deryng, Delphine2,3; Elliott, Joshua26; Folberth, Christian9; Gosling, Simon N.21; Gudmundsson, Lukas1; Henrot, Alexandra-Jane15; Hickler, Thomas25,29,30; Ito, Akihiko17; Khabarov, Nikolay4; Kim, Hyungjun23; Leng, Guoyong8; Liu, Junguo4,13 ; Liu, Xingcai7; Masaki, Yoshimitsu19; Morfopoulos, Catherine28; Mueller, Christoph18; Schmied, Hannes Mueller5,6; Nishina, Kazuya17; Orth, Rene32,35; Pokhrel, Yadu14; Pugh, Thomas A. M.10,11,12; Satoh, Yusuke4; Schaphoff, Sibyll18; Schmid, Erwin20; Sheffield, Justin33,34; Stacke, Tobias16; Steinkamp, Joerg37; Tang, Qiuhong7; Thiery, Wim1,36; Wada, Yoshihide4; Wang, Xuhui24; Weedon, Graham P.22; Yang, Hong27; Zhou, Tian8
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| 通讯作者 | Wartenburger, Richard |
| 发表日期 | 2018-07
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| DOI | |
| 发表期刊 | |
| ISSN | 1748-9326
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| 卷号 | 13期号:7 |
| 摘要 | 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. |
| 关键词 | |
| 相关链接 | [来源记录] |
| 收录类别 | |
| 语种 | 英语
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| 学校署名 | 其他
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| 资助项目 | Defra Integrated Climate Program - DECC/Defra[GA01101]
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| WOS研究方向 | Environmental Sciences & Ecology
; Meteorology & Atmospheric Sciences
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| WOS类目 | Environmental Sciences
; Meteorology & Atmospheric Sciences
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| WOS记录号 | WOS:000436020600001
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| 出版者 | |
| EI入藏号 | 20184706084862
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| EI主题词 | Climate Change
; Cluster Analysis
; Diagnostic Products
; Digital Storage
; Evapotranspiration
; Soils
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| EI分类号 | Atmospheric Properties:443.1
; Health Care:461.7
; Soils And Soil Mechanics:483.1
; Data Storage, Equipment And Techniques:722.1
; Computer Software, Data HAndling And Applications:723
; Probability Theory:922.1
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| 来源库 | Web of Science
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| 引用统计 |
被引频次[WOS]：40
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| 成果类型 | 期刊论文 |
| 条目标识符 | //www.snoollab.com/handle/2SGJ60CL/27579 |
| 专题 | 工学院_环境科学与工程学院 |
| 作者单位 | 1.Swiss Fed Inst Technol, Inst Atmospher & Climate Sci, Univ Str 16, CH-8092 Zurich, Switzerland 2.Climate Analyt, D-10969 Berlin, Germany 3.Columbia Univ, Ctr Climate Syst Res, New York, NY 10025 USA 4.IIASA, Laxenburg, Austria 5.Goethe Univ Frankfurt, Inst Phys Geog, Frankfurt, Germany 6.Senckenberg Biodivers & Climate Res Ctr SBiK, Frankfurt, Germany 7.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China 8.Pacific Northwest Natl Lab, Atmospher Sci & Global Change Div, Richland, WA 99352 USA 9.IIASA, Ecosyst Serv & Management Program, Laxenburg, Austria 10.Univ Birmingham, Sch Geog Earth & Environm Sci, Birmingham, W Midlands, England 11.Univ Birmingham, Birmingham Inst Forest Res, Birmingham, W Midlands, England 12.Karlsruhe Inst Technol, Inst Meteorol & Climate Res Atmospher Environm Re, Garmisch Partenkirchen, Germany 13.South Univ Sci & Technol China, Sch Environm Sci & Engn, Shenzhen, Peoples R China 14.Michigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA 15.Univ Liege, Unite Modelisat Climat Cycles Biogeochim, UR SPHERES, Liege, Belgium 16.Max Planck Inst Meteorol, Hamburg, Germany 17.Natl Inst Environm Studies, Tsukuba, Ibaraki, Japan 18.Potsdam Inst Climate Impact Res PIK, Telegraphenberg A31, D-14473 Potsdam, Germany 19.Hirosaki Univ, Aomori, Japan 20.Univ Nat Resources & Life Sci, Dept Econ & Social Sci, Feistmantelstr 4, A-1180 Vienna, Austria 21.Univ Nottingham, Sch Geog, Nottingham NG7 2RD, England 22.Met Off JCHMR, Maclean Bldg,Benson Lane, Wallingford OX10 8BB, Oxon, England 23.Univ Tokyo, Inst Ind Sci, Tokyo, Japan 24.UVSQ, CEA, CNRS, Lab Sci Climat & Environm,UMR8212, Gif Sur Yvette, France 25.Goehte Univ, Inst Phys Geog, Geosci, Frankfurt, Germany 26.Univ Chicago, 5757 S Univ Ave, Chicago, IL 60637 USA 27.Eawag, Dept Syst Anal Integrated Assessment & Modelling, CH-8600 Dubendorf, Switzerland 28.Univ Exeter, Coll Life & Environm Sci, Exeter, Devon, England 29.Senckenberg Biodivers & Climate Res Ctr BiK F, Senckenberganlage 25, D-60325 Frankfurt, Germany 30.Goethe Univ Frankfurt, Senckenberganlage 25, D-60325 Frankfurt, Germany 31.Univ Paris 06, UPMC, Sorbonne Univ, LOCEAN IPSL,CNRS,IRD,MNHN, Paris, France 32.Stockholm Univ, Bolin Ctr Climate Res, Dept Phys Geog, SE-10691 Stockholm, Sweden 33.Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08544 USA 34.Univ Southampton, Geog & Environm, Southampton, Hants, England 35.Max Planck Inst Biogeochem, Dept Biogeochem Integrat, D-07745 Jena, Germany 36.Vrije Univ Brussel, Dept Hydrol & Hydraul Engn, Pl Laan 2,1050, B-1050 Brussels, Belgium 37.Johannes Gutenberg Univ Mainz, Zentrum Datenverarbeitung, Mainz, Germany |
| 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).
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| 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).
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| 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).
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