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License: CC BY
Data sources: Datacite
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Smithsonian figshare
Software . 2021
License: CC BY
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LARS-WG stochastic weather generator

Authors: orcid Semenov, Mikhail;
Semenov, Mikhail
ORCID
Harvested from ORCID Public Data File

Semenov, Mikhail in OpenAIRE

LARS-WG stochastic weather generator

Abstract

{"references": ["Racsko P, Szeidl L & Semenov MA (1991) A serial approach to local stochastic weather models. Ecological Modelling, 57:27-41, https://doi.org/10.1016/0304-3800(91)90053-4 2.\tSemenov MA & Barrow EM (1997) Use of a stochastic weather generator in the development of climate change scenarios Climatic Change, 35:397-414 https://doi.org/10.1023/A:1005342632279", "Semenov MA & Barrow EM (1997) Use of a stochastic weather generator in the development of climate change scenarios Climatic Change, 35:397-414 https://doi.org/10.1023/A:1005342632279", "Semenov MA & Brooks RJ (1999) Spatial interpolation of the LARS-WG stochastic weather generator in Great Britain. Climate Research 11:137-148 https://doi.org/10.3354/cr011137", "Semenov MA (2008) Simulation of weather extreme events by a stochastic weather generator, Climate Research 35:203-212 https://doi.org/10.3354/cr00731", "Semenov MA, Donatelli M, Stratonovitch P, Chatzidaki E, and Baruth B. (2010) ELPIS: a dataset of local-scale daily climate scenarios for Europe. Climate Research 44:3-15 https://doi.org/10.3354/cr00865", "Semenov MA & Stratonovitch P (2010) The use of multi-model ensembles from global climate models for impact assessments of climate change. Climate Research 41:1-14 https://doi.org/10.3354/cr00836", "Semenov MA, Stratonovitch P (2015) Adapting wheat ideotypes for climate change: accounting for uncertainties in CMIP5 climate projections. Clim Res 65: 123\u2013139 https://doi.org/10.3354/cr01297"]}

LARS-WG 6.0, a stochastic weather generator, is a computationally inexpensive downscaling tool to generate local scale climate scenarios based on global or regional climate models for impact assessments of climate change. LARS-WG has been used in more than 75 countries for research and education. The current version of LARS-WG incorporates climate projections from the CMIP5 ensemble used in the IPCC Fifth Assessment Report. LARS-WG has been well validated in diverse climates around the world.

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Keywords

impact assessment, Ecology, Physiology, global climate model, downscaling, Plant Biology, Climate scenarios, climate change, Environmental Sciences not elsewhere classified, CMIP5, Climate scenarios, climate change, downscaling, CMIP5, weather generator, global climate model, impact assessment, weather generator, Developmental Biology, Biological Sciences not elsewhere classified

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