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State‐of‐the‐art with regional climate models

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  • Markku Rummukainen

Abstract

Regional climate models are used by a large number of groups, for more or less all regions of the world. Regional climate models are complementary to global climate models. A typical use of regional climate models is to add further detail to global climate analyses or simulations, or to study climate processes in more detail than global models allow. The relationship between global and regional climate models is much akin to that of global and regional weather forecasting models. Over the past 20 years, the development of regional climate models has led to increased resolution, longer model runs, and steps towards regional climate system models. During recent years, community efforts have started to emerge in earnest, which can be expected to further advance the state‐of‐the‐art in regional climate modeling. Applications of regional climate models span both the past and possible future climates, facilitating climate impact studies, information and support to climate policy, and adaptation. Copyright © 2010 John Wiley & Sons, Inc. This article is categorized under: Climate Models and Modeling > Earth System Models

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  • Markku Rummukainen, 2010. "State‐of‐the‐art with regional climate models," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 1(1), pages 82-96, January.
    • Handle: RePEc:wly:wirecc:v:1:y:2010:i:1:p:82-96
    DOI: 10.1002/wcc.8
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    Cited by:

    1. D A Sachindra & B J C Perera, 2016. "Statistical Downscaling of General Circulation Model Outputs to Precipitation Accounting for Non-Stationarities in Predictor-Predictand Relationships," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-21, December.
    2. Hoa X. Pham & Asaad Y. Shamseldin & Bruce W. Melville, 2021. "Projection of future extreme precipitation: a robust assessment of downscaled daily precipitation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(1), pages 311-329, May.
    3. Gino D. Marinucci & George Luber & Christopher K. Uejio & Shubhayu Saha & Jeremy J. Hess, 2014. "Building Resilience against Climate Effects—A Novel Framework to Facilitate Climate Readiness in Public Health Agencies," IJERPH, MDPI, vol. 11(6), pages 1-26, June.
    4. Ulazia, Alain & Sáenz, Jon & Ibarra-Berastegui, Gabriel & González-Rojí, Santos J. & Carreno-Madinabeitia, Sheila, 2017. "Using 3DVAR data assimilation to measure offshore wind energy potential at different turbine heights in the West Mediterranean," Applied Energy, Elsevier, vol. 208(C), pages 1232-1245.
    5. Zhang, Shuangyi & Li, Xichen, 2021. "Future projections of offshore wind energy resources in China using CMIP6 simulations and a deep learning-based downscaling method," Energy, Elsevier, vol. 217(C).

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