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Title: Regional Climate Modeling: Progress, Challenges, and Prospects

Abstract

Regional climate modeling with regional climate models (RCMs) has matured over the past decade and allows for meaningful utilization in a broad spectrum of applications. In this paper, latest progresses in regional climate modeling studies are reviewed, including RCM development, applications of RCMs to dynamical downscaling for climate change assessment, seasonal climate predictions and climate process studies, and the study of regional climate predictability. Challenges and potential directions of future research in this important area are discussed, with the focus on those to which less attention has been given previously, such as the importance of ensemble simulations, further development and improvement of 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 both the demonstrated credibility of RCMs’ capability 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 the continuous improvements in the skill of global general circulation models (GCMs) in simulating large-scale atmospheric circulation, regional climate modeling will remain an important dynamicalmore » 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. An internationally coordinated effort can be developed with different focuses by different groups to 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 climate modeling community.« less

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
15016318
Report Number(s):
PNNL-SA-41328
Journal ID: ISSN 0026-1165; JMSJAU; KP1205030; TRN: US200512%%336
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of the Meteorological Society of Japan, 82(6):1599-1628; Journal Volume: 82; Journal Issue: 6
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; ATMOSPHERIC CIRCULATION; CLIMATE MODELS; CLIMATES; CLOUDS; EVALUATION; GENERAL CIRCULATION MODELS; PHYSICS; PRECIPITATION; SIMULATION

Citation Formats

Wang, Yuqing, Leung, Lai R., McGregor, John L., Lee, Dong-Kyou, Wang, Wei-Chyung, Ding, Yihui, and Kimura, Fujio. Regional Climate Modeling: Progress, Challenges, and Prospects. United States: N. p., 2004. Web. doi:10.2151/jmsj.82.1599.
Wang, Yuqing, Leung, Lai R., McGregor, John L., Lee, Dong-Kyou, Wang, Wei-Chyung, Ding, Yihui, & Kimura, Fujio. Regional Climate Modeling: Progress, Challenges, and Prospects. United States. doi:10.2151/jmsj.82.1599.
Wang, Yuqing, Leung, Lai R., McGregor, John L., Lee, Dong-Kyou, Wang, Wei-Chyung, Ding, Yihui, and Kimura, Fujio. Wed . "Regional Climate Modeling: Progress, Challenges, and Prospects". United States. doi:10.2151/jmsj.82.1599.
@article{osti_15016318,
title = {Regional Climate Modeling: Progress, Challenges, and Prospects},
author = {Wang, Yuqing and Leung, Lai R. and McGregor, John L. and Lee, Dong-Kyou and Wang, Wei-Chyung and Ding, Yihui and Kimura, Fujio},
abstractNote = {Regional climate modeling with regional climate models (RCMs) has matured over the past decade and allows for meaningful utilization in a broad spectrum of applications. In this paper, latest progresses in regional climate modeling studies are reviewed, including RCM development, applications of RCMs to dynamical downscaling for climate change assessment, seasonal climate predictions and climate process studies, and the study of regional climate predictability. Challenges and potential directions of future research in this important area are discussed, with the focus on those to which less attention has been given previously, such as the importance of ensemble simulations, further development and improvement of 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 both the demonstrated credibility of RCMs’ capability 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 the 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. An internationally coordinated effort can be developed with different focuses by different groups to 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 climate modeling community.},
doi = {10.2151/jmsj.82.1599},
journal = {Journal of the Meteorological Society of Japan, 82(6):1599-1628},
number = 6,
volume = 82,
place = {United States},
year = {Wed Dec 01 00:00:00 EST 2004},
month = {Wed Dec 01 00:00:00 EST 2004}
}
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