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: 8713567
• 负责人: Jagadish Shukla
• 金额: $ 151.26万
• 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: 1987
• 资助国家: 美国
• 起止时间: 1987-07-15 至 1991-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8713567&HistoricalAwards=false
• 关键词: Predictability; Monthly; Seasonal; Average; Circulation

One of the very exciting frontiers of research in atmospheric sciences is understanding and extending the limits of dynamic predictibility on monthly and seasonal time scales. The potential societal impact of successful extended range forecasting is enormous. The main objective of this proposal is to carry out numerical modeling and diagnostic studies to investigate the predictibility of the monthly and seasonally averaged circulation of the atmosphere. The longer term goal of the research is to investigate the predictibility of the coupled land-ocean-atmosphere system. The focus of the work is practical, seeking to put together a numerical model, adapted from the operational version used by the National Meteorological Center(NMC), that should be able to produce extended range forecasts, and to put such a model to test. To accomplish this, the strategy is to utilize realistic models of individual components (atmosphere, ocean, and land surface processes) and to carry out sensitivity and predictibility studies, first to examine the predictibility of each component separately, and ultimately to examine the predictibility of the fully coupled interactive system. This is important because it will not only provide a crucial interface between the university research community and the NMC, but also allow development of better data sets as well as improve NMC's forecast capabilities beyond the current limit of around two weeks.

大气科学研究中非常令人兴奋的前沿之一是理解和扩展月度和季节时间尺度上动态可预测性的限制。 成功的扩展范围预测的潜在社会影响是巨大的。 该提案的主要目标是进行数值模拟和诊断研究，以调查大气月平均和季节平均环流的可预测性。 该研究的长期目标是调查陆地-海洋-大气耦合系统的可预测性。 这项工作的重点是实用性，寻求建立一个改编自国家气象中心（NMC）使用的业务版本的数值模型，该模型应该能够产生扩展范围的预报，并对这样的模型进行测试。 为了实现这一目标，该策略是利用各个组成部分（大气、海洋和陆地表面过程）的现实模型，并进行敏感性和可预测性研究，首先分别检查每个组成部分的可预测性，最后检查完全耦合的交互系统的可预测性。 这很重要，因为它不仅将在大学研究界和 NMC 之间提供一个重要的接口，而且还可以开发更好的数据集，并将 NMC 的预测能力提高到超出当前两周左右的限制。