Statistical-dynamical methods for scale dependent model evaluation and short term precipitation forecasting (STAMPF)

该项目的目的是对DWD天气预报模式链（LM/GME）在动力参数和云特性方面的降水预报进行依赖尺度的评估。动态状态指数（DSI）、湿度加权地转散度和云类型、覆盖和顶高是评价参数。DSI是最近从大气动力学第一原理发展而来的。它描述了由于非平稳性和非绝热过程引起的对广义动力平衡的偏离。评估的重点是天气尺度和对流尺度之间的相互作用，这往往是极端降水事件的原因。该方法旨在探讨天气尺度过程与模式中对流参数化之间的关系。评估的前提是在LM和GME的网格分辨率下对日降水和云参数进行独立于模式的现场表示（分析）。气象组织现有的天气观测分析方案将通过卫星数据进一步改进和扩展。它们将提供连续的云数据和降水率。将用现代统计方法估计所分析场的准确性。在进一步的步骤中，测试的动态参数将用于准预测降水预报或作为模型输出统计的预测因子。

The aim of the project is a scale dependent evaluation of precipitation forecast of the DWD weather prediction model chain (LM/GME) in relation to dynamical parameters and cloud properties. A Dynamic State Index (DSI), the humidity weighted ageostrophic divergence and cloud type, coverage and top height are the evaluation parameters. The DSI was recently developed from first principles of atmospheric dynamics. It describes the deviation from a generalised dynamical equilibrium due to nonstationarity and diabatic processes. The evalution focuses on interactions between synoptic and convective scales, which are often the reason for extreme precipitation events. This approach intends to explore the relation between synoptic scale processes and the convective parameterisation in the model. The prerequisite for the evaluation is a model independent field representation (analysis) of daily precipitation and cloud parameters in the grid resolution of LM and GME. An already existing analysis scheme of WMO-synoptical observations will be improved further and extended by satellite data. They will supply continuous cloud data and precipitation rates. The accuracy of the analysed fields will be estimated by means of modern statistical methods. In a further step the tested dynamic parameters will be used for a quasi-prognostic precipitation forecast or as predictors for model output statistics.