SGER: Stochastic Characteristics of Drought and Surface-Atmosphere Drought Forcing in Coupled General Circulation Models (GCMs)

SGER：耦合大气环流模型 (GCM) 中干旱和地表大气干旱强迫的随机特征

• 批准号: 0740021
• 负责人: John Dracup
• 金额: --
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2009-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0740021&HistoricalAwards=false
• 关键词: SGER; Stochastic; Characteristics; Drought; Surface

This is a grant under a Climate Variability and Predictability (CLIVAR) Program pilot project called DRICOMP, for the Drought in Coupled Models Project, which focuses on making initial explorations into the mechanisms of drought as they are represented in the output of global climate models and on attempting to assess the reliability of these models in simulating drought.Droughts are the nation's costliest natural disasters, with average annual impacts of $6-8 billion in the United States alone. The physical and dynamical mechanisms that lead to drought and the potential impacts of climate change on drought characteristics are, however, only poorly understood. This study represents an initial attempt to answer two research questions: . To what degree do surface-atmosphere interactions drive the stochastic characteristics of drought, including drought duration, magnitude, and recurrence, over selected regions? . How will anthropogenic climate change affect the physical and dynamical mechanisms that lead to drought, and subsequently the stochastic characteristics of drought? Stochastic characteristics of drought will be evaluated globally based on observed climate data and all 19 transient twentieth-century coupled climate simulations in the World Climate Research Program Coupled Model Intercomparison Project (WCRP CMIP3) data archive. A combined composite and multiple regression analysis will be used in an effort to objectively identify statistically significant patterns of antecedent and contemporaneous sea surface temperature (SST) and soil moisture (simulations only) associated with drought events. The role of surface-atmosphere forcing in the onset, persistence, and recession of drought events will then be assessed based on the amplitude and robustness of surface anomaly composites and multiple regression coefficients. Results will be compared between observations and simulations, and between models. Finally, the analysis will be repeated for all paired pre-industrial control and forced stabilization simulations in the CMIP3 data archive; potential impacts of climate change will be evaluated by comparing the drought characteristic and surface-atmosphere drought forcing between the control and forced stabilization simulations for all models. Broader impacts will be to improve our understanding of the stochastic nature of drought and the physical mechanisms that lead to drought events; the analyses will help to improve drought planning and management.

这是气候变化和可预测性（CLIVAR）计划试点项目DRICOMP的一笔赠款，用于耦合模式项目中的干旱，该项目的重点是对全球气候模式输出中所代表的干旱机制进行初步探索，并试图评估这些模式在模拟干旱方面的可靠性。干旱是美国损失最大的自然灾害，仅在美国，平均每年的影响就达60 - 80亿美元。 然而，人们对导致干旱的物理和动力机制以及气候变化对干旱特征的潜在影响知之甚少。 这项研究是回答两个研究问题的初步尝试：地面-大气相互作用在多大程度上驱动了选定区域的干旱随机特征，包括干旱持续时间、程度和重现性？.人为气候变化将如何影响导致干旱的物理和动力机制以及随后的干旱随机特征？将根据观测到的气候数据和世界气候研究方案耦合模式相互比较项目（WCRP CMIP 3）数据档案中的所有19个二十世纪瞬态耦合气候模拟，对干旱的随机特征进行全球评估。 将使用综合和多元回归分析，努力客观地确定与干旱事件有关的前期和同期海表温度和土壤湿度（仅模拟）的统计学显著模式。 然后，将根据地面异常复合物和多元回归系数的幅度和稳健性，评估地面-大气强迫在干旱事件发生、持续和衰退中的作用。 结果将在观测和模拟之间以及模型之间进行比较。 最后，将对CMIP 3数据档案中所有成对的工业化前控制和强制稳定模拟重复分析;将通过比较所有模型的控制和强制稳定模拟之间的干旱特征和地表-大气干旱强迫来评估气候变化的潜在影响。更广泛的影响将是提高我们对干旱的随机性和导致干旱事件的物理机制的理解;分析将有助于改进干旱规划和管理。