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WIREs Clim Change
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Added value in regional climate modeling

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Regional climate modeling is a dynamical downscaling technique applied to the results of global climate models (GCMs) in order to acquire more information on climate simulations and climate change projections. GCMs and regional climate models (RCMs) have undergone considerable development over the past few decades, and both have increased in resolution. The higher‐resolution edge of RCMs compared to GCMs still remains, however. This has been demonstrated in a number of specific studies. As GCMs operate on relatively coarse resolutions, they do not resolve more variable land forms and similar features that shape regional‐scale climates. RCMs operate on higher resolutions than GCMs, by a factor of 2–10. Some RCMs now explore resolutions down to 1–5 km. This adds value in regions with variable orography, land–sea and other contrasts, as well as in capturing sharp, short‐duration and extreme events. In contrast, large‐scale and time‐averaged fields, not least over smooth terrain and on scales that have been already skillfully resolved in GCMs, are not much affected. RCMs also generate additional detail compared to GCMs when in climate projection mode. Compared to the present‐day climate for which observations exist, here the added value aspect is more complex to evaluate. Nevertheless, added value is meaningfully underlined when there is a clear physical context for it to appear in. In addition to climate modeling and model evaluation‐related added value considerations, a significant relevant aspect of added value is the provision of regional scale information, including climate change projections, for climate impact, adaptation, and vulnerability research. WIREs Clim Change 2016, 7:145–159. doi: 10.1002/wcc.378 This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models
A number of regional climate modeling domains in The Coordinated Regional Climate Downscaling Experiment, CORDEX.
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Global climate model (GCM) (a) and regional climate model (RCM) (b) simulated changes (%) in annual mean snowfall over the North American Great Lakes region. (Reprinted with permission from Ref . Copyright 2012 American Meteorological Society)
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Topography in a global climate model (GCM) (CSIRO) and in a regional climate model (RCM) (WRF) at 50 and 10 km, respectively (a). Simulated change in precipitation from the last 25 years of the 20th century to the last 25 years of the 21st century, for Austral autumn (March–April–May) in the same models. Note the two‐dimensional legend. The hue indicates the simulated change in mm/month and the saturation the change in percent (b). Projected changes in seasonal precipitation in three regions of southeast Australia for the same models and the same period as above. The changes are shown in absolute and in relative units (c). (Reprinted with permission from Ref . Copyright 2015 John Wiley and Sons)
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Daily precipitation intensity PDFs for a nominal 1976–2005 period from global climate models (GCMs) (black), regional climate models (RCMs) at 0.44° (blue) and at 0.11° resolutions (red), and observations (green), European Alps. (a) All data have been interpolated to the GCMs' grid (i.e., upscaling of RCM results), (b) all the data have been interpolated to 0.44° (interpolation of GCM data, upscaling of 0.11°), and (c) all the data have been interpolated to to 0.11° (interpolation of both GCM and 0.44° RCM data). (Reprinted with permission from Ref . Copyright 2015 John Wiley and Sons)
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Skill in a 10 km regional climate model (RCM) (CaRD10) (a) and the NCEP/NCAR reanalysis (b) with respect to gridded observations, for January mean precipitation over the 1950–1997 period. (Reprinted with permission from Ref . Copyright 2011 John Wiley and Sons)
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Horizontal resolutions considered in today's higher‐resolution global climate models (GCMs) and in the very high resolution GCM models now being tested: (a) Illustration of the European topography at a resolution of 87.5 × 87.5 km; (b) same as (a) but for a resolution of 30.0 × 30.0 km. (Reprinted with permission from Ref . Copyright 2013 Cambridge University Press)
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