Predictability of Monthly and Seasonal Average Circulation of the Atmosphere

大气月平均环流和季节平均环流的可预测性

• 批准号: 9019296
• 负责人: Jagadish Shukla
• 金额: $ 120.06万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-02-15 至 1994-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9019296&HistoricalAwards=false
• 关键词: Predictability; Monthly; Seasonal; Average; Circulation

The PI will carry out modeling and diagnostic studies to investigate the interannual variability and predictability of the monthly and seasonal average circulation of the atmosphere. The long term goal is to investigate the predictability of the coupled ocean-atmosphere-land system. To accomplish this objective, the strategy is to utilize realistic models of the individual components (atmosphere, ocean, and land surface processes) to carry out sensitivity and predictability studies, first to examine the predictability of each component separately, and ultimately to examine the predictability of the coupled interactive system. The PI and his group will continue their ongoing research on the predictability of space-time averaged atmospheric circulation to establish a physical basis for, and demonstrate the feasibility of dynamic extended range forecasting. To accomplish the above objective the PI will continue to improve the NMC-derived atmospheric general circulation model so that its ability to simulate the annual cycle and interannual variability including space-time fluctuations is further improved. He will also use this model in conjunction with real observed states of the global atmosphere and global boundary conditions at the earth's surface to investigate the predictability of the regional space-time averaged circulation of the atmosphere. This research is important because it will provide a readily applied basis for improvements in operational weather and climate prediction models.

PI将进行建模和诊断研究， 调查的年际变化和可预测性 大气的月平均和季平均环流。 的 长期目标是研究 海气陆耦合系统 为了实现这一 目标，战略是利用现实的模型， 单个组件（大气、海洋和陆地表面 进行敏感性和可预测性研究， 首先分别检查每个组件的可预测性， 并最终检查耦合的可预测性， 互动系统 PI和他的团队将继续他们的 正在进行的关于时空平均的可预测性的研究 大气环流建立物理基础， 论证动态增程的可行性 预测。 为实现上述目标，PI将继续 改进NMC导出的大气环流模式， 它模拟年周期和年际变化的能力 包括时空波动在内的可变性 提高 他还将把这个模型与真实的 观测到的全球大气和全球边界状况 在地球表面的条件，以调查 区域时空平均环流的可预报性 大气层中。 这项研究很重要，因为它将提供一个容易的 改善作战天气的应用基础， 气候预测模型