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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

  • Bart Van Den Hurk
  • , Hyungjun Kim
  • , Gerhard Krinner
  • , Sonia I. Seneviratne
  • , Chris Derksen
  • , Taikan Oki
  • , Hervé Douville
  • , Jeanne Colin
  • , Agnès Ducharne
  • , Frederique Cheruy
  • , Nicholas Viovy
  • , Michael J. Puma
  • , Yoshihide Wada
  • , Weiping Li
  • , Binghao Jia
  • , Andrea Alessandri
  • , Dave M. Lawrence
  • , Graham P. Weedon
  • , Richard Ellis
  • , Stefan Hagemann
  • Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, Justin Sheffield
  • Royal Netherlands Meteorological I.
  • Institute of Industrial Science
  • CNRS
  • ETH Zurich
  • Meteorological Research Branch
  • Météo-France/CNRS
  • Sorbonne Université
  • CEA/UVSQ/CNRS
  • Center for Climate Systems Research
  • International Institute for Applied Systems Analysis (IIASA)
  • China Meteorological Administration
  • Institute of Atmospheric Physics Chinese Academy of Sciences
  • Agenzia Nazionale per le Nuove Tecnologie
  • National Center for Atmospheric Research
  • Now at Met Office Hadley Centre
  • Centre for Ecology and Hydrology
  • Max Planck Institute for Meteorology
  • Oak Ridge National Laboratory
  • University of Michigan, Ann Arbor
  • Euro Mediterranean Center on Climage Change
  • Commonwealth Scientific and Industrial Research Organization
  • Princeton University
  • University of Southampton

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

Résumé

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).

langue originaleAnglais
Pages (de - à)2809-2832
Nombre de pages24
journalGeoscientific Model Development
Volume9
Numéro de publication8
Les DOIs
étatPublié - 24 août 2016

SDG des Nations Unies

Ce résultat contribue à ou aux Objectifs de développement durable suivants

  1. SDG 13 - Action climatique
    SDG 13 Action climatique
  2. SDG 15 - Vie sur terre
    SDG 15 Vie sur terre

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