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Peer-reviewed

ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks

Gerhard Krinner, Chris Derksen, Richard Essery, M. Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad W. Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Cheruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy M. Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, R. M. Law, David M. Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, О. Н. Насонова, Tomoko Nitta, Masashi Niwano, John W. Pomeroy, Mark S. Raleigh, Gerd Schaedler, В. А. Семенов, Tatiana G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, D. V. Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, Dan Zhu

Geoscientific model development · 2018

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Summary

Abstract. This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).

Source type
Peer-reviewed study
DOI
10.5194/gmd-11-5027-2018
Catalogue ID
BFmoef2us1-yhz1kl
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