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LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.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).
Document ID
20160011267
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Van Den Hurk, Bart
(Royal Netherlands Meteorological Inst. De Bilt, Netherlands)
Kim, Hyungjun
(Tokyo Univ. Japan)
Krinner, Gerhard
(Centre National de la Recherche Scientifique Annecy-le-Vieux, France)
Seneviratne, Sonia I.
(Institute for Atmospheric and Climate Science Zurich, Switzerland)
Derksen, Chris
(Environment Canada Toronto, Ontario, Canada)
Oki, Taikan
(Tokyo Univ. Japan)
Douville, Herve
(Centre National de Recherches Meteorologiques Toulouse, France)
Colin, Jeanne
(Centre National de Recherches Meteorologiques Toulouse, France)
Ducharne, Agnes
(Paris Univ. France)
Cheruy, Frederique
(Paris VI Univ. France)
Viovy, Nicholas
(Centre National de la Recherche Scientifique Gif-sur-Yvette, France)
Puma, Michael J.
(Columbia Univ. New York, NY, United States)
Wada, Yoshide
(International Inst. for Applied Systems Analysis Laxenburg, Austria)
Li, Weiping
(Central Meteorological Service Beijing, China)
Jia, Binghao
(Academia Sinica Beijing, China)
Alessandri, Andrea
(Agenzia Nazionale per le Nuove Tecnologie, l'Energia e lo Sviluppo Economico Sostenibile Bologna, Italy)
Lawrence, Dave M.
(National Center for Atmospheric Research Boulder, CO, United States)
Weedon, Graham P.
(Meteorological Office London, United Kingdom)
Ellis, Richard
(Centre for Ecology and Hydrology Wallingford, United Kingdom)
Hagemann, Stefan
(Max-Planck-Inst. fuer Meteorologie Hamburg, Germany)
Date Acquired
September 15, 2016
Publication Date
August 24, 2016
Publication Information
Publication: Geoscientific Model Development
Publisher: Copernicus
Volume: 9
e-ISSN: 1991-9603
Subject Category
Meteorology And Climatology
Report/Patent Number
GSFC-E-DAA-TN35358
Funding Number(s)
CONTRACT_GRANT: NNX14AB99A
Distribution Limits
Public
Copyright
Other
Keywords
atmospheric temperature
Earth surface
water
feedback
soil moisture
bias
variability
climate change

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