International audienceThe Mediterranean region is frequently affected by heavy precipitation events associated with flash floods, landslides, and mudslides that cause hundreds of millions of euros in damages per year and often, casualties. A major field campaign was devoted to heavy precipitation and flash floods from 5 September to 6 November 2012 within the framework of the 10-year international HyMeX (Hydrological cycle in the Mediterranean Experiment) dedicated to the hydrological cycle and related high-impact events. The 2- month field campaign took place over the Northwestern Mediterranean Sea and its surrounding coastal regions in France, Italy, and Spain. The observation strategy of the field experiment was devised to improve our knowledge on the following key components leading to heavy precipitation and flash flooding in the region: i) the marine atmospheric flows that transport moist and conditionally unstable air towards the coasts; ii) the Mediterranean Sea acting as a moisture and energy source; iii) the dynamics and microphysics of the convective systems producing heavy precipitation; iv) the hydrological processes during flash floods. This article provides the rationale for developing this first HyMeX field experiment and an overview of its design and execution. Highlights of some Intense Observation Periods illustrate the potential of the unique datasets collected for process understanding, model improvement and data assimilation

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Abstract. The limited-area ensemble prediction system COSMO-LEPS has been running every day at ECMWF since November 2002. A number of runs of the non-hydrostatic limited-area model Lokal Modell (LM) are available every day, nested on members of the ECMWF global ensemble. The limited-area ensemble forecasts range up to 120 h and LM-based probabilistic products are disseminated to several national and regional weather services. Some changes of the operational suite have recently been made, on the basis of the results of a statistical analysis of the methodology. The analysis is presented in this paper, showing the benefit of increasing the number of ensemble members. The system has been designed to have a probabilistic support at the mesoscale, focusing the attention on extreme precipitation events. In this paper, the performance of COSMO-LEPS in forecasting precipitation is presented. An objective verification in terms of probabilistic indices is made, using a dense network of observations covering a part of the COSMO domain. The system is compared with ECMWF EPS, showing an improvement of the limited-area high-resolution system with respect to the global ensemble system in the forecast of high precipitation values. The impact of the use of different schemes for the parametrisation of the convection in the limited-area model is also assessed, showing that this have a minor impact with respect to run the model with different initial and boundary condition.

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Mesoscale Alpine Programme Demonstration of Probabilistic Hydrological and Atmospheric Simulation of Flood Events (MAP D-PHASE) is a forecast demonstration project aiming at demonstrating recent improvements in the operational use of end-to-end forecasting system consisting of atmospheric models, hydrological prediction systems, nowcasting tools and warnings for end-users. Both deterministic and ensemble prediction systems (EPSs) have been implemented for the European Alps (atmospheric models) and a selection of mesoscale river basins (hydrological models) in Central Europe. A first insight into MAP D-PHASE with focus on operational ensemble hydrological simulations is presented here.

A high-resolution ensemble system, based on five runs of a limited-area model (LAM), is described. The initial and boundary conditions for the LAM integrations are provided by the representative members (RMs) selected from the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System (EPS). @S meinbeax are grouped in five clusters; then, from each cluster, an RM is selected, according to the methodology described in the companion paper. The ability of the high-resolution ensemble system to predict the occurrence of heavy rainfall events (either five or six days ahead) is tested for four cases of floods over the Alpine region. Results show that, in two case-studies, the LAM integration corresponding to the RM of the highly populated cluster predicts the observed rainfall with a very good degree of time and spatial accuracy. In the other two cases, the extreme events are captured by at least one of the runs nested on the members of the less populated clusters. Probability maps constructed from LAM integrations provide great detail on the location of the regions affected by heavy precipitation and the information gained with respect to EPS probability maps and LAM deterministic forecasts is highlighted. The probabilistic estimates based on the LAM ensembles are also shown to be of valuable assistance to forecasters in issuing early flood alerts, contributing to the definition of a flood-risk alarm system. t In November 2000, the horizontal resolution of the operational EPS was increased to T~2 5 5 , Corresponding to a grid scale of approximately 80 km. @ Royal Meteorological Society, 2001. 209s 2096 C. MARSIGLI et al.and boundary conditions provided by the representative members (hereafter, RMs) of the ECMWF EPS. The RMs are selected first by applying a cluster analysis to the 51member EPS to define five clusters and, then, by identifying the RM of each cluster. Clusters are defined by considering the atmospheric flow at 700 hPa and by using the wind vector as clustering variable. Once the five clusters have been constructed, for each cluster the RM is defined as the member closest to all members of its own cluster and most distant from the members of the other clusters, with distances computed using an Ll norm applied to the precipitation field. The reader is referred to the companion paper, Molteni et al. (2001), and to Marsigli (1998) for a detailed description of the selection methodology. LEPS is based on integrations of the limitedarea model LAMBO (Limited Area Model Bologna), operational at ARPA-SMR since 1993. LAMBO runs are performed at high horizontal resolution (about 20 km) in order to resolve those orographic and mesoscale processes responsible for heavy -precipitation events. A probability of occurrence is assigned to each scenario, based on the population of the corresponding EPS cluster. In this way, it is possible to combine the ability of the EPS to highlight a set of possible evolution scenarios (keeping account of the intrinsic predictability of a particular synoptic situation...

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:

Abstract. The Special Observation Period (SOP1