Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.5194/gmd-9-2809-2016 |
LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project - aims, setup and expected outcome | |
van den Hurk, Bart1; Kim, Hyungjun2; Krinner, Gerhard3; Seneviratne, Sonia I.4; Derksen, Chris5; Oki, Taikan2; Douville, Herve6; Colin, Jeanne6; Ducharne, Agnes26; Cheruy, Frederique7; Viovy, Nicholas8; Puma, Michael J.9,10; Wada, Yoshihide11; Li, Weiping12; Jia, Binghao13; Alessandri, Andrea14; Lawrence, Dave M.15; Weedon, Graham P.16; Ellis, Richard17; Hagemann, Stefan18; Mao, Jiafu19,20; Flanner, Mark G.21; Zampieri, Matteo22; Materia, Stefano22; Law, Rachel M.23; Sheffield, Justin24,25 | |
通讯作者 | van den Hurk, Bart |
来源期刊 | GEOSCIENTIFIC MODEL DEVELOPMENT
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ISSN | 1991-959X |
EISSN | 1991-9603 |
出版年 | 2016 |
卷号 | 9期号:8页码:2809-2832 |
英文摘要 | The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode ("LMIP", building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework ("LFMIP", building upon the GLACE-CMIP blueprint). |
类型 | Article |
语种 | 英语 |
国家 | Netherlands ; Japan ; France ; Switzerland ; Canada ; USA ; Austria ; Peoples R China ; Italy ; England ; Germany ; Australia |
收录类别 | SCI-E |
WOS记录号 | WOS:000383800400002 |
WOS关键词 | CLIMATE-CHANGE ; INTERANNUAL VARIABILITY ; CARBON-DIOXIDE ; BIASES ; WATER ; PREDICTABILITY ; CRYOSPHERE ; DISCHARGE ; TRENDS ; IMPACT |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
来源机构 | 中国科学院大气物理研究所 ; Commonwealth Scientific and Industrial Research Organisation |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/193288 |
作者单位 | 1.KNMI, De Bilt, Netherlands; 2.Univ Tokyo, Inst Ind Sci, Tokyo, Japan; 3.CNRS, LGGE, Grenoble, France; 4.Swiss Fed Inst Technol, Inst Atmospher & Climate Sci, Zurich, Switzerland; 5.Environm & Climate Change, Div Climate Res, Toronto, ON, Canada; 6.Meteo France, CNRM, Toulouse, France; 7.Univ Paris 06, Ecole Polytech, Ecole Normale Super, LMD IPSL,CNRS, Paris, France; 8.LSCE IPSL CEA CNRS UVSQ, Gif Sur Yvette, France; 9.NASA, Goddard Inst Space Studies, New York, NY 10025 USA; 10.Columbia Univ, Ctr Climate Syst Res, New York, NY USA; 11.Int Inst Appl Syst Anal, Laxenburg, Austria; 12.China Meteorol Adm, Natl Climate Ctr, Lab Climate Studies, Beijing, Peoples R China; 13.Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China; 14.Agenzia Nazl Nuove Tecnol Energia & Sviluppo Econ, Rome, Italy; 15.Natl Ctr Atmospher Res, Climate & Global Dynam Lab, POB 3000, Boulder, CO 80307 USA; 16.Met Off JCHMR, Maclean Bldg, Wallingford, Oxon, England; 17.Ctr Ecol & Hydrol, Maclean Bldg, Wallingford, Oxon, England; 18.Max Planck Inst Meteorol, Hamburg, Germany; 19.Oak Ridge Natl Lab, Div Environm Sci, POB 2008, Oak Ridge, TN 37831 USA; 20.Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN USA; 21.Univ Michigan, Dept Climate & Space Sci & Engn, Ann Arbor, MI 48109 USA; 22.Euromediterranean Ctr Climate Change CMCC, Climate Simulat & Predict Div, Bologna, Italy; 23.CSIRO Oceans & Atmosphere, Aspendale, Vic, Australia; 24.Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08544 USA; 25.Univ Southampton, Geog & Environm, Southampton, Hants, England; 26.UPMC CNRS EPHE, Sorbonne Univ, UMR METIS 7619, Paris, France |
推荐引用方式 GB/T 7714 | van den Hurk, Bart,Kim, Hyungjun,Krinner, Gerhard,et al. LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project - aims, setup and expected outcome[J]. 中国科学院大气物理研究所, Commonwealth Scientific and Industrial Research Organisation,2016,9(8):2809-2832. |
APA | van den Hurk, Bart.,Kim, Hyungjun.,Krinner, Gerhard.,Seneviratne, Sonia I..,Derksen, Chris.,...&Sheffield, Justin.(2016).LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project - aims, setup and expected outcome.GEOSCIENTIFIC MODEL DEVELOPMENT,9(8),2809-2832. |
MLA | van den Hurk, Bart,et al."LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project - aims, setup and expected outcome".GEOSCIENTIFIC MODEL DEVELOPMENT 9.8(2016):2809-2832. |
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