4.1 Article Proceedings Paper

Regional climate modeling: Progress, challenges, and prospects

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JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN
卷 82, 期 6, 页码 1599-1628

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METEOROLOGICAL SOC JAPAN
DOI: 10.2151/jmsj.82.1599

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Regional climate modeling using regional climate models (RCMs) has matured over the past decade to enable meaningful utilization in a broad spectrum of applications. In this paper, the latest progress in regional climate modeling studies is reviewed, including RCM development, applications of RCMs to dynamical downscaling for climate change assessment and seasonal climate predictions, climate process studies, and the study of regional climate predictability. Challenges and potential directions of future research in this important area are discussed, with focus on those that have received less attention previously, such as the importance of ensemble simulations, further development and improvement of the regional climate modeling approach, modeling extreme climate events and sub-daily variation of clouds and precipitation, model evaluation and diagnostics, applications of RCMs to climate process studies and seasonal predictions, and development of regional earth system models. It is believed that with the demonstrated credibility of RCMs in reproducing not only monthly to seasonal mean climate and interannual variability, but also the extreme climate events when driven by good quality reanalysis and continuous improvements in the skill of global general circulation models (GCMs) in simulating large-scale atmospheric circulation, regional climate modeling will remain an important dynamical downscaling tool for providing the needed information for assessing climate change impacts, and seasonal climate predictions, and a powerful tool for improving our understanding of regional climate processes. Internationally coordinated efforts can be developed to further advance regional climate modeling studies. It is also recognized that since the final quality of the results from nested RCMs depends in part on the realism of the large-scale forcing provided by GCMs, the reduction of errors and improvement in physics parameterizations in both GCMs and RCMs remain a priority for the climate modeling community.

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