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

用于尺度相关模型评估和短期降水预报的统计动力学方法（STAMPF）

• 批准号: 5426405
• 负责人: Professor Dr. Ulrich Cubasch
• 金额: --
• 依托单位: Institut für Meteorologie
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2004
• 资助国家: 德国
• 起止时间: 2003-12-31 至 2010-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5426405?language=en
• 关键词: Statistical; dynamical; methods; scale; dependent

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.

该项目的目标是对 DWD 天气预报模型链 (LM/GME) 的降水预报与动力学参数和云特性进行尺度相关评估。动态状态指数（DSI）、湿度加权地转散度和云类型、覆盖范围和顶部高度是评估参数。 DSI 最近根据大气动力学的第一原理发展而来。它描述了由于非平稳性和非绝热过程而导致的广义动态平衡的偏差。评估重点关注天气尺度和对流尺度之间的相互作用，这通常是极端降水事件的原因。该方法旨在探索天气尺度过程与模型中对流参数化之间的关系。评估的先决条件是 LM 和 GME 网格分辨率中日降水量和云参数的模型独立场表示（分析）。现有的 WMO 天气观测分析方案将通过卫星数据得到进一步改进和扩展。他们将提供连续的云数据和降水率。分析字段的准确性将通过现代统计方法进行估计。下一步，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。