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Collaborative Research: Developing a Next-Generation Approach to Regional Climate Prediction at High Resolution

Collaborative Research: Developing a Next-Generation Approach to Regional Climate Prediction at High Resolution
合作研究:开发下一代高分辨率区域气候预测方法
批准号:
1048834
负责人:
Gregory Hakim
金额:
$38.1万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-05-15 至 2016-04-30

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中文摘要
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英文摘要
The need for more accurate and detailed regional climate predictions is widely recognized; industry, local government and society increasingly require sufficient understanding and warning to enable proper planning and adaptation to mitigate future costs and disruptions arising from climate variability and change. This project is addressing critical research and model development issues aimed at improving such regional predictions in a three-phase approach. The Nested Regional Climate Model from the National Center for Atmospheric Research is being further developed with the inclusion of ocean and land coupling, atmospheric chemistry, and decision support tools for societal and industry users. This model also forms a test bed for the next generation Model for Prediction Across Scales (MPAS), a next-generation regional weather-climate-ocean prediction system with sophisticated atmospheric chemistry components. A number of statistical and related downscaling techniques will also be developed to enable improved assessment of extreme weather systems and their impacts.Broader Impacts. A feature of the program is the wide, cross-disciplinary community approach and novel collaboration amongst experts in regional climate, severe weather, numerical modeling, data assimilation, atmospheric chemistry, industry, and societal applications. Coordinating the development of the new prediction systems and downscaling approaches directly with societal applications and development of decision tools will enable each to influence the other to their mutual benefit. Thus, the program entails both substantial intellectual merit and societal and scientific benefit. For example, it will enable earlier societal and industry use of the developing predictive capacity and lead to an improved, tightly-coupled predictive and decision system. This will feature novel societal approaches, such as the role that long-term contracts like multi-year insurance policies coupled with long-term loans can play in encouraging investments in cost-effective adaptation measures in the presence of climate change.
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