Quantitative precipitation forecasting (QPF) in low-mountain regions is a great challenge for the atmospheric sciences community. On the one hand, orographic enhancement of precipitation in these regions can result in severe flash-flood events. On the other hand, the relative importance of forcing mechanisms leading to convection initiation (CI) is neither well understood nor adequately reproduced by weather forecast models. This results in poor QPF skill, both in terms of the spatial distribution of precipitation and its temporal evolution.Two prominent systematic errors of state-of-theart mesoscale models are identified. Figure 1 shows the difference between a 1-month average of 24-h integrated precipitation forecasted with the Consortium for Small-Scale Modeling (COSMO)-EU Model (formerly known as Lokalmodell) of the German Meteorological Service (DWD) and the corresponding observational data. Shown on this figure is the Black Forest low-mountain region in southwestern Germany. Strong systematic errors are found on both the windward and the lee sides. On the windward side, the model strongly overestimates precipitation, whereas on the lee side it is underestimated, which we call the "windward/lee effect." To our knowledge, this error is found in all mesoscale models for both weather prediction and climate simulations, which require convection parameterization, such as in COSMOCH7 of Meteo Swiss, ARPEGE and ALADIN of Meteo France, as well as in the mesoscale models MM5 and ETA. Although we show a summertime example here, Baldauf and Schulz previously demonstrated that this error structure exists during all seasons.Another key problem is the inadequate simulation research campaign AffiliAtions:

International audienceDemonstration of probabilistic hydrological and atmospheric simulation of flood events in the Alpine region (D-PHASE) is made by the Forecast Demonstration Project in connection with the Mesoscale Alpine Programme (MAP). Its focus lies in the end-to-end flood forecasting in a mountainous region such as the Alps and surrounding lower ranges. Its scope ranges from radar observations and atmospheric and hydrological modeling to the decision making by the civil protection agents. More than 30 atmospheric high-resolution deterministic and probabilistic models coupled to some seven hydrological models in various combinations provided real-time online information. This information was available for many different catchments across the Alps over a demonstration period of 6 months in summer/ fall 2007. The Web-based exchange platform additionally contained nowcasting information from various operational services and feedback channels for the forecasters and end users. D-PHASE applications include objective model verification and intercomparison, the assessment of (subjective) end user feedback, and evaluation of the overall gain from the coupling of the various components in the end-to-end forecasting system

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The present study investigates the initiation of precipitating deep convection in an ensemble of convection-resolving mesoscale models. Results of eight different model runs from five non-hydrostatic models are compared for a case of the Convective and Orographically-induced Precipitation Study (COPS). An isolated convective cell initiated east of the Black Forest crest in southwest Germany, although convective available potential energy was only moderate and convective inhibition was high. Measurements revealed that, due to the absence of synoptic forcing, convection was initiated by local processes related to the orography. In particular, the lifting by low-level convergence in the planetary boundary layer is assumed to be the dominant process on that day. The models used different configurations as well as different initial and boundary conditions. By comparing the different model performance with each other and with measurements, the processes which need to be well represented to initiate convection at the right place and time are discussed. Besides an accurate specification of the thermodynamic and kinematic fields, the results highlight the role of boundary-layer convergence features for quantitative precipitation forecasts in mountainous terrain.