Convective Modeling and Predictabilty Studies

对可预测性的固有限制 大气数值模式 主要原因是 极限通常被认为是非线性相互作用 波谱的不同分量之间的不确定性 以及模型可分辨的波谱中的误差， 由于忽略未分辨波而引入的误差随着 在时间上的积分，在整个频谱中扩展，以及 最终会破坏预测。 气象学家现在有一些 了解用于以下目的的大规模模型的可预测性： 天气预报;空间分辨率约为数百 公里 对流和中尺度数值模式 近年来，气象事件变得越来越复杂， 多年来，可预测性的问题现在可以研究。 对流尺度模式的空间分辨率大致为1-2 中尺度模式为20-100公里。 在这个奖项下，Droegemeier教授将研究 一个对流尺度模型的可预测性，已被使用 研究雷暴外流和微暴流的动力学， 在模拟这些对流尺度上取得了一些成功， 事件 除了检查模型的敏感性 对初始条件的不同方面进行预测， Droegemeier教授将寻找初始化模型的方法 直接多普勒雷达观测;他还将继续他的 分段抛物线法在气象学中的应用 问题

There is an inherent limit to the predictability of atmospheric numerical models. The principal reason for this limit is generally considered to be the nonlinear interactions between different components of the wave spectrum; uncertainties and errors in the wave spectrum resolvable by the model and errors introduced by the neglect of unresolved waves grow with integration in time, spreading throughout the spectrum, and eventually destroy the forecast. Meteorologists now have some understanding of predictability of large scale models used for weather forecast; the spatial resolution is roughly hundreds of kilometers. Numerical models for convective- and meso- scale meteorological events have grown in sophistication in recent years, the question of predictability can now be investigated. The spatial resolution of convective-scale models is roughly 1-2 km, and 20-100 km for mesoscale models. Under this award, Professor Droegemeier will investigate the predictability of a convective-scale model, which has been used to study the dynamics of thunderstorm outflow and microbursts and demonstrated some success in simulating these convective-scale events. Besides examining the sensitivity of the model prediction to different aspects of the initial conditions, Professor Droegemeier will look for ways to initialize the model with direct Doppler radar observations; he will also continue his work on adapting the Piecewise Parabolic Method to meteorological problems.