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

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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.