Gerd Schaedler


2020

DOI bib
Snow cover duration trends observed at sites and predicted bymultiple models
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy M. Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cécile B. Ménard, О. Н. Насонова, Tomoko Nitta, John W. Pomeroy, Gerd Schaedler, В. А. Семенов, Tatiana G. Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, Hua Yuan

Abstract. Thirty-year simulations of seasonal snow cover in 22 physically based models driven with bias-corrected meteorological reanalyses are examined at four sites with long records of snow observations. Annual snow cover durations differ widely between models but interannual variations are strongly correlated because of the common driving data. No significant trends are observed in starting dates for seasonal snow cover, but there are significant trends towards snow cover ending earlier at two of the sites in observations and most of the models. A simplified model with just two parameters controlling solar radiation and sensible heat contributions to snowmelt spans the ranges of snow cover durations and trends. This model predicts that sites where snow persists beyond annual peaks in solar radiation and air temperature will experience rapid decreases in snow cover duration with warming as snow begins to melt earlier and at times of year with more energy available for melting.

2018

DOI bib
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, F. Chéruy, 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, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, Dan Zhu
Geoscientific Model Development, Volume 11, Issue 12

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).