Sensitivity of Persistence Characteristics of Atmospheric Weather Regimes

大气天气状况持续特征的敏感性

• 批准号: 0233853
• 负责人: Samar Khatiwala
• 金额: $ 45.95万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-01 至 2007-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0233853&HistoricalAwards=false
• 关键词: Sensitivity; Persistence; Characteristics; Atmospheric; Weather

This project will quantify and interpret the dependence of the spatial and temporal characteristics of atmospheric flow regimes, focusing on events bearing non-gaussian distributions. The work is expected to contribute to the understanding of low-frequency atmospheric variability and changes in weather extrema, and the sensitivity of such events to small variations in climate forcing. A hierarchy of numerical models will be employed, ranging from a baroclinic, quasi-geostrophic scheme to a simplified global climate model. This novel strategy will be applied to investigate the anthropogenic forcing (such as the doubling of carbon dioxide) on regime persistence time via probability density functions. This project addresses a topic likely to provide useful information on extreme weather conditions, and how they impact the climate system. It is anticipated that the results will be of interest to forecasting the breakdown of persistent regimes, and be relevant to society at large for mitigating the effects of unusual weather conditions. Statistical and diagnostic tools developed as part of this study will be made available to the scientific community.

该项目将量化和解释大气流动制度的空间和时间特征的依赖性，重点是带有非高斯分布的事件。预计这项工作将有助于理解低频大气变异性和天气极端变化，以及此类事件对气候强迫较小变化的敏感性。将采用数值模型的层次结构，范围从斜压，准地斑方案到简化的全球气候模型。这种新型策略将用于研究通过概率密度函数在制度持续时间上对人为强迫（例如二氧化碳倍增）。该项目介绍了一个可能提供有关极端天气条件的有用信息以及它们如何影响气候系统的主题。可以预料，结果可以预测持续政权的细分，并与整个社会有关，以减轻异常天气状况的影响。作为本研究的一部分开发的统计和诊断工具将提供给科学界。