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

人们普遍认识到需要更准确和详细的区域气候预测；工业、地方政府和社会越来越需要充分的了解和预警，以便进行适当的规划和适应，以减轻气候变率和变化带来的未来成本和破坏。该项目正在处理关键的研究和模型开发问题，旨在以三阶段方法改进这种区域预测。国家大气研究中心的嵌套区域气候模式正在进一步发展，包括海洋和陆地耦合、大气化学以及为社会和工业用户提供决策支持工具。该模型还为下一代跨尺度预测模型（MPAS）提供了一个试验台，该模型是下一代区域天气-气候-海洋预测系统，具有复杂的大气化学成分。还将开发一些统计和相关的降尺度技术，以便改进对极端天气系统及其影响的评估。更广泛的影响。该计划的一个特点是广泛的，跨学科的社区方法和区域气候，恶劣天气，数值模拟，数据同化，大气化学，工业和社会应用领域专家之间的新颖合作。将新预测系统的发展和缩小规模的方法直接与社会应用和决策工具的发展协调起来，将使每一个都能够影响对方，从而实现互利。因此，该计划既需要大量的智力价值，也需要社会和科学效益。例如，它将使社会和工业更早地使用发展中的预测能力，并导致改进的、紧密耦合的预测和决策系统。这将以新颖的社会方法为特色，例如，多年保险政策等长期合同与长期贷款相结合，可以在鼓励投资于具有成本效益的气候变化适应措施方面发挥作用。

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.