Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 9, 2809-2832, 2016
http://www.geosci-model-dev.net/9/2809/2016/
doi:10.5194/gmd-9-2809-2016
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Model experiment description paper
24 Aug 2016
LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project – aims, setup and expected outcome
Bart van den Hurk1, Hyungjun Kim2, Gerhard Krinner3, Sonia I. Seneviratne4, Chris Derksen5, Taikan Oki2, Hervé Douville6, Jeanne Colin6, Agnès Ducharne24, Frederique Cheruy7, Nicholas Viovy8, Michael J. Puma9, Yoshihide Wada10, Weiping Li11, Binghao Jia12, Andrea Alessandri13, Dave M. Lawrence14, Graham P. Weedon15, Richard Ellis16, Stefan Hagemann17, Jiafu Mao18, Mark G. Flanner19, Matteo Zampieri20, Stefano Materia20, Rachel M. Law21, and Justin Sheffield22,23 1KNMI, De Bilt, the Netherlands
2Institute of Industrial Science, the University of Tokyo, Tokyo, Japan
3LGGE, CNRS, Grenoble, France
4Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
5Climate Research Division, Environment and Climate Change, Toronto, Canada
6CNRM, Centre National de Recherches Météorologiques, Météo-France, Toulouse, France
7LMD-IPSL, Centre National de la Recherche Scientifique, Université Pierre et Marie-Curie, Ecole Normale Supérieure, Ecole Polytechnique, Paris, France
8LSCE-IPSL: CEA-CNRS-UVSQ, Gif-sur-Yvette, France
9NASA Goddard Institute for Space Studies and Center for Climate Systems Research, Columbia University, New York, USA
10International Institute for Applied Systems Analysis, Laxenburg, Austria
11Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China
12State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
13Agenzia Nazionale per le nuove Tecnologie, l'energia e lo sviluppo economico sostenibile, Rome, Italy
14Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, USA
15Met Office (JCHMR) Maclean Building Crowmarsh Gifford Wallingford, Oxfordshire, UK
16Centre for Ecology and Hydrology, Maclean Building Crowmarsh Gifford Wallingford, Oxfordshire, UK
17Max-Planck-Institut für Meteorologie, Hamburg, Germany
18Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
19Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, USA
20Euro-Mediterranean Center for Climate Change (CMCC), Climate Simulation and Prediction Division, Bologna, Italy
21CSIRO Oceans and Atmosphere, Aspendale, Australia
22Department of Civil and Environmental Engineering Princeton University, Princeton, USA
23Geography and Environment, University of Southampton, Southampton, UK
24Sorbonne Universités, UMR 7619 METIS, UPMC/CNRS/EPHE, Paris, France
Abstract. 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).

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Citation: van den Hurk, B., Kim, H., Krinner, G., Seneviratne, S. I., Derksen, C., Oki, T., Douville, H., Colin, J., Ducharne, A., Cheruy, F., Viovy, N., Puma, M. J., Wada, Y., Li, W., Jia, B., Alessandri, A., Lawrence, D. M., Weedon, G. P., Ellis, R., Hagemann, S., Mao, J., Flanner, M. G., Zampieri, M., Materia, S., Law, R. M., and Sheffield, J.: LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soil moisture Model Intercomparison Project – aims, setup and expected outcome, Geosci. Model Dev., 9, 2809-2832, doi:10.5194/gmd-9-2809-2016, 2016.
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Short summary
This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture...
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