The Role of the Mean-State Atmospheric Circulation in Future Projections of Regional Hydroclimate and Cloud Feedbacks

平均状态大气环流在未来区域水文气候和云反馈预测中的作用

• 批准号: 2330009
• 负责人: Kevin Grise
• 金额: $ 46.68万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2330009&HistoricalAwards=false
• 关键词: Role; Mean; State; Atmospheric; Circulation

Efforts to mitigate climate risk rely on model simulations to determine how climate will change on a regional basis, for instance whether it will rain more or less in a given region as the world warms. But in many regions climate models do not produce consistent answers, for instance in the US Southwest some models project more summer rainfall while others project less. The lack of consensus could mean that either outcome is in fact equally likely, and the range of projections across the ensemble of available climate models is an accurate representation of the range of likely outcomes. Alternatively, perhaps some portion of the range should be discounted because the projections in that range are influenced by specific model biases which have a clear dynamical connection to the projected changes. For instance a recent study by the Principal Investigator (PI) connects projections of future precipitation over the Southwest to the moisture flow around a mid-tropospheric ridge over the central US in present-day simulations from the same models. The models which produce the strongest precipitation increases show excessive ridging which is not consistent with present-day observations, thus casting doubt on their projections of rainier summers in the Southwest.Research under this award continues the PI's effort to identify present-day atmospheric circulation features which affect future projections of regional precipitation change, as well as projections of regional cloud cover change which can amplify or reduce the warming effect of greenhouse gas emissions. The work uses statistical analysis of model simulations to identify relationships between future projections and present-day circulation features, followed by specialized simulations using the Community Atmosphere Model (CAM), the atmospheric component model of CESM, the Community Earth System Model. The simulations use "nudging" to produce present-day simulations which mimic several climate models, paired with simulations in which a uniform warming is applied to the ocean surface so that the effects of the differing present-day circulations can be assessed.The project is of societal as well as scientific interest given the need for better information to guide efforts to assess and respond to climate risk. The project provides support and training to a postdoctoral associate and a graduate student, thereby promoting the future workforce in this research area. In addition, the project hosts a summer undergraduate student through the Virginia-North Carolina Alliance for Minority Participation's summer research program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

减轻气候风险的努力依赖于模型模拟，以确定气候将如何在区域基础上变化，例如，随着世界变暖，某一地区的降雨会增加还是减少。但在许多地区，气候模型并不能得出一致的答案，例如，在美国西南部，一些模型预测的夏季降雨量更多，而另一些模型预测的降雨量更少。缺乏共识可能意味着任何一种结果实际上都是同样可能的，而现有气候模式集合的预估范围是可能结果范围的准确表示。或者，也许该范围的某些部分应不予考虑，因为该范围内的预估受到特定模式偏差的影响，而这种偏差与预估变化具有明显的动态联系。例如，首席研究员（PI）最近的一项研究将西南地区未来降水的预测与美国中部对流层中脊周围的水分流动联系起来，这些模拟来自相同的模式。产生最强降水增加的模式显示出过度隆起，这与目前的观测结果不一致，因此对其对西南夏季多雨的预测产生了怀疑。该奖项下的研究继续了PI的努力，以确定影响未来区域降水变化预测的当前大气环流特征，以及可以放大或减少温室气体排放的变暖效应的区域云量变化预测。这项工作使用模式模拟的统计分析来确定未来预测和当前环流特征之间的关系，然后使用社区大气模式（CAM）， CESM的大气成分模式，社区地球系统模式进行专门的模拟。这些模拟使用“轻推”的方法来模拟当前的几种气候模式，并与对海洋表面施加均匀变暖的模拟相结合，以便评估不同的当前环流的影响。鉴于需要更好的信息来指导评估和应对气候风险的工作，该项目具有社会和科学意义。该项目为一名博士后和一名研究生提供支持和培训，从而促进该研究领域的未来劳动力。此外，该项目还通过维吉尼亚-北卡罗来纳少数民族参与联盟的暑期研究项目招收了一名暑期本科生。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。