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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

TitleLS3MIP (v1.0) contribution to CMIP6: The Land Surface, Snow and Soil moisture Model Intercomparison Project - Aims, setup and expected outcome
Publication TypeArticolo su Rivista peer-reviewed
Year of Publication2016
Authorsvan 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 Andrea, 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.
JournalGeoscientific Model Development
Volume9
Pagination2809-2832
ISSN1991959X
Keywordsair temperature, Arctic, Atmospheric circulation, Climate change, climate modeling, experimental study, land surface, precipitation (climatology), Regional climate, Soil moisture, Uncertainty analysis
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). © Author(s) 2016.

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URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84984832799&doi=10.5194%2fgmd-9-2809-2016&partnerID=40&md5=5ea2ae2cfa21cf32bc251aa50ad236e7
DOI10.5194/gmd-9-2809-2016
Citation KeyVanDenHurk20162809