Predictability Characteristics of Global and Limited Area Models

9408047 Paegle“全球和有限区域模型的可预报性特征” 根据该奖项，Paegle博士将继续研究大气的可预测性，特别是初始条件的不确定性对数值预测的影响，包括本地和远程。 将对全球和有限区域模型进行研究。 具体而言，他将： 1)用可变分辨率全球模型进行实验，使用分辨率 跨越三个数量级，以确定理论和实际限制， 可预测性以及限制如何取决于本地、远程和全球的不确定性。 的 结果应该对数值模型的设计有实际意义， 观察系统。 2)用高分辨率局部模型进行实验，该模型被设计成评估“价值- 增加了”通过相对于与不完美相关的不确定性的分辨率增强 由用于初始化模型的业务预报提供的边界条件。 目标是量化相对预测改进， 内部（局部）模型域来自外部预测技能的改进 （区域或全球）模型，提供边界条件。 这项研究的结果有明显的潜力，改善数值天气预报的短期和长期的时间尺度。 中尺度动力气象学和大尺度动力气象学项目将共同支持这一奖项。 ***

9408047 Paegle "Predictability Characteristics of Global and Limited Area Models" Under this award, Dr. Paegle will continue his investigations of atmospheric predictability, and in particular, the effects of uncertainties in the initial conditions, both local and remote, on numerical predictions. Studies will be carried out for global and limited-area models. Specifically, he will: 1) conduct experiments with a variable resolution global model, using resolutions spanning three orders of magnitude, to ascertain theoretical and ppactical limits of predictability and how the limits depend on local, remote, and global uncertainties. The results should have practical implications for the design of numerical models and observing systems. 2) perform experiments with a high resolution local model designed to assess the "value- added" by resolution enhancement relative to the uncertainty associated with imperfect boundary conditions provided from operational forecasts used to initialize the model. The goal is to quantify the relative forecast improvement which can be realized within the inner (local) model domain from improvements in the forecast skill of the outer (regional or global) model that supplies the boundary conditions. The results of this research have obvious potential for improving numerical weather prediction on both short and longer time scales. The Mesoscale Dynamic Meteorology and Large-scale Dynamic Meteorology Programs will share in the support of this award. ***