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Title: LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

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). Furthermore, 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. But, 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)more » and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [2];  [6];  [6];  [7];  [8];  [9];  [10];  [11];  [12];  [13];  [14];  [15];  [16];  [17];  [18] more »; ORCiD logo [19];  [20];  [21];  [21]; ORCiD logo [22];  [23] « less
+ Show Author Affiliations
  1. Royal Netherlands Meteorological Institute (KNMI), De Bilt (Netherlands)
  2. Univ. of Tokyo (Japan)
  3. Centre National de la Recherche Scientifique (CNRS), Grenoble (France)
  4. ETH Zurich (Switzerland)
  5. Environment and Climate Change, Toronto ON (Canada)
  6. National Center for Meteorological Research, Toulous (France)
  7. Sorbonne Univ., Paris (France)
  8. Univ. Pierre et Marie Curie, Paris (France)
  9. French Alternative Energies and Atomic Energy Commission (CEA-Saclay), Gif-sur-Yvette (France)
  10. Columbia Univ., New York, NY (United States). NASA Goddard Inst. for Space Studies and Center for Climate Systems Research
  11. International Inst. for Applied Systems Analysis, Laxenburg (Austria)
  12. China Meterological Administration, Beijing (China)
  13. Chinese Academy of Sciences (CAS), Beijing (China)
  14. National Agency for New Technologies, Rome (Italy)
  15. National Center for Atmospheric Research, Boulder, CO (United States)
  16. Joint Centre for Hydro-Meteorological Research (JCHMR), Oxfordshire (United Kingdom)
  17. Centre for Ecology and Hydrology, Oxfordshire (United Kingdom)
  18. Max Planck Inst. for Meteorology, Hamburg (Germany)
  19. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  20. Univ. of Michigan, Ann Arbor, MI (United States)
  21. Euro-Mediterranean Center for Climate Change (CMCC), Bologna (Italy)
  22. Commonwealth Scientific and Industrial Research Organization (CSIRO) Oceans and Atmosphere, Aspendale VIC (Australia)
  23. Univ. of Southampton (United Kingdom); Sorbonne Univ., Paris (France)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1376656
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Geoscientific Model Development (Online)
Additional Journal Information:
Journal Name: Geoscientific Model Development (Online); Journal Volume: 9; Journal Issue: 8; Journal ID: ISSN 1991-9603
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES

Citation Formats

van den Hurk, Bart, Kim, Hyungjun, Krinner, Gerhard, Seneviratne, Sonia I., Derksen, Chris, Oki, Taikan, Douville, Hervé, Colin, Jeanne, Ducharne, Agnès, Cheruy, Frederique, Viovy, Nicholas, Puma, Michael J., Wada, Yoshihide, Li, Weiping, Jia, Binghao, Alessandri, Andrea, Lawrence, Dave M., Weedon, Graham P., Ellis, Richard, Hagemann, Stefan, Mao, Jiafu, Flanner, Mark G., Zampieri, Matteo, Materia, Stefano, Law, Rachel M., and Sheffield, Justin. LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome. United States: N. p., 2016. Web. doi:10.5194/gmd-9-2809-2016.
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van den Hurk, Bart, Kim, Hyungjun, Krinner, Gerhard, Seneviratne, Sonia I., Derksen, Chris, Oki, Taikan, Douville, Hervé, Colin, Jeanne, Ducharne, Agnès, Cheruy, Frederique, Viovy, Nicholas, Puma, Michael J., Wada, Yoshihide, Li, Weiping, Jia, Binghao, Alessandri, Andrea, Lawrence, Dave M., Weedon, Graham P., Ellis, Richard, Hagemann, Stefan, Mao, Jiafu, Flanner, Mark G., Zampieri, Matteo, Materia, Stefano, Law, Rachel M., & Sheffield, Justin. LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome. United States. https://doi.org/10.5194/gmd-9-2809-2016
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van den Hurk, Bart, Kim, Hyungjun, Krinner, Gerhard, Seneviratne, Sonia I., Derksen, Chris, Oki, Taikan, Douville, Hervé, Colin, Jeanne, Ducharne, Agnès, Cheruy, Frederique, Viovy, Nicholas, Puma, Michael J., Wada, Yoshihide, Li, Weiping, Jia, Binghao, Alessandri, Andrea, Lawrence, Dave M., Weedon, Graham P., Ellis, Richard, Hagemann, Stefan, Mao, Jiafu, Flanner, Mark G., Zampieri, Matteo, Materia, Stefano, Law, Rachel M., and Sheffield, Justin. Wed . "LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome". United States. https://doi.org/10.5194/gmd-9-2809-2016. https://www.osti.gov/servlets/purl/1376656.
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@article{osti_1376656,
title = {LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome},
author = {van den Hurk, Bart and Kim, Hyungjun and Krinner, Gerhard and Seneviratne, Sonia I. and Derksen, Chris and Oki, Taikan and Douville, Hervé and Colin, Jeanne and Ducharne, Agnès and Cheruy, Frederique and Viovy, Nicholas and Puma, Michael J. and Wada, Yoshihide and Li, Weiping and Jia, Binghao and Alessandri, Andrea and Lawrence, Dave M. and Weedon, Graham P. and Ellis, Richard and Hagemann, Stefan and Mao, Jiafu and Flanner, Mark G. and Zampieri, Matteo and Materia, Stefano and Law, Rachel M. and Sheffield, Justin},
abstractNote = {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). Furthermore, 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. But, 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).},
doi = {10.5194/gmd-9-2809-2016},
journal = {Geoscientific Model Development (Online)},
number = 8,
volume = 9,
place = {United States},
year = {Wed Aug 24 00:00:00 EDT 2016},
month = {Wed Aug 24 00:00:00 EDT 2016}
}
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