Storm-Scale Predictability

风暴规模的可预测性

• 批准号: 0432232
• 负责人: Steven Mullen
• 金额: $ 28.71万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-11-15 至 2008-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0432232&HistoricalAwards=false
• 关键词: Storm; Scale; Predictability

As computer power continues to increase, the grid spacing of numerical weather prediction models correspondingly will decrease to the point that cloud-resolving models will be run on a real-time basis. However, whereas large-scale predictability issues have been studied extensively, very little work has explored the nature of storm-scale predictability. The main objective of this research is to ascertain the length of time for which useful forecasts of various features of the atmosphere at these scales can be expected. These features range from the exact timing, location, mode, and intensity of storms to the nature of the environment (instability, shear, etc.) in which storms may form. The predictability limits for these features will be estimated from large ensemble runs. As a preliminary step the ensembles will be launched from an idealized, horizontally homogeneous control run so that storms may be isolated and the storm environment closely controlled to determine the impact of environmental characteristics on storm predictability. Following that, horizontally nonhomogeneous numerical simulations will also be performed as the interaction between storms and inhomogeneities in the storm environment are likely to affect predictability. All experiments will be performed using the perfect model assumption so that the results will not be limited by the current skill of high-resolution numerical models. These experiments will provide an upper bound on storm-scale predictability. Knowledge of the inherent predictability limits at these storms is important for directing future research toward physically tractable problems and for instructing forecasters on how to interpret the output of high-resolution numerical models.

随着计算机能力的不断提高，数值天气预报模式的网格间距将相应地减少到云解析模式将实时运行的程度。 然而，虽然大规模的可预测性问题已经得到了广泛的研究，很少有工作探讨风暴规模的可预测性的性质。 这项研究的主要目的是确定在这些尺度上对大气的各种特征进行有用预报的时间长度。 这些特征包括风暴的确切时间、位置、模式和强度，以及环境的性质（不稳定性、切变等）。风暴可能形成的地方。 这些功能的可预测性限制将估计从大型合奏运行。 作为初步步骤，将从理想化的、水平均匀的控制运行中发射集合，以便可以隔离风暴并密切控制风暴环境，以确定环境特征对风暴可预测性的影响。 在此之后，水平非均匀的数值模拟也将进行风暴和风暴环境中的不均匀性之间的相互作用可能会影响可预测性。 所有的实验都将使用完美的模型假设进行，这样结果就不会受到当前高分辨率数值模型技能的限制。 这些实验将提供风暴规模可预测性的上限。 这些风暴的固有可预测性限制的知识是非常重要的，指导未来的研究对物理上容易处理的问题，并指导预报员如何解释高分辨率数值模式的输出。