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

人们广泛认识到需要更准确和详细的区域气候预测；工业界、地方政府和社会越来越需要充分的了解和预警，以便能够进行适当的规划和适应，以减轻气候变化和变化带来的未来成本和破坏。该项目正在解决关键研究和模型开发问题，旨在通过三阶段方法改进此类区域预测。国家大气研究中心的嵌套区域气候模型正在进一步开发，其中包括海洋和陆地耦合、大气化学以及面向社会和行业用户的决策支持工具。该模型还构成了下一代跨尺度预测模型（MPAS）的测试平台，该模型是具有复杂大气化学成分的下一代区域天气-气候-海洋预测系统。 还将开发一些统计和相关的降尺度技术，以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、跨学科的社区方法以及区域气候、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的专家之间的新颖合作。将新预测系统的开发和降尺度方法的开发直接与社会应用和决策工具的开发相协调，将使双方能够影响对方，从而实现互惠互利。因此，该计划既具有巨大的智力价值，又具有社会和科学效益。例如，它将使得社会和行业能够更早地使用正在发展的预测能力，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，例如多年期保单等长期合同与长期贷款相结合，可以在鼓励投资于气候变化时具有成本效益的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.