Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1088/1748-9326/aac4bb |
Evapotranspiration simulations in ISIMIP2a-Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets | |
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 | |
2018-07-01 | |
发表期刊 | ENVIRONMENTAL RESEARCH LETTERS
![]() |
ISSN | 1748-9326 |
出版年 | 2018 |
卷号 | 13期号:7 |
文章类型 | Article |
语种 | 英语 |
国家 | Switzerland; Germany; USA; Austria; Peoples R China; England; Belgium; Japan; France; Sweden |
英文摘要 | 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. |
英文关键词 | ISIMIP2a evapotranspiration uncertainty cluster analysis hydrological extreme events |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000436020600001 |
WOS关键词 | GLOBAL TERRESTRIAL EVAPOTRANSPIRATION ; LAND-SURFACE MODEL ; SOIL-MOISTURE ; POTENTIAL EVAPOTRANSPIRATION ; HYDROLOGICAL MODELS ; REANALYSIS DATA ; HIGH-RESOLUTION ; WATER ; PROJECT ; PARAMETERIZATION |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/34343 |
专题 | 气候变化 |
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). |
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). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论