This study examines the simulation of three torrential rain events observed on 13-14 October 1995 (the Cévennes case), 12-13 November 1999 (the Aude case) and 8-9 September 2002 (the Gard case) over the southeastern part of France using the Meso-NH non-hydrostatic mesoscale numerical model. These cases were associated with extreme Heavy Precipitation Events (HPEs) with significant precipitation amounts exceeding 500 mm in less than 24 hours. Several sets of numerical experiments were performed with 10 km and 2.5 km horizontal resolutions. In part I of this study, special attention is paid to the experimental design for obtaining realistic simulations of HPEs with the Meso-NH model, as well as the evolution of the synoptic patterns in which the rainfall events are embedded.The best 2.5 km numerical simulations show the ability of the Meso-NH model to reproduce significant quasi-stationary rainfall events. Moreover, the model fairly reproduces the low-level mesoscale environments associated with the three HPEs. The HPEs formed in a slow-evolving synoptic environment favourable for the development of convective systems (diffluent upper-level southerly flow, PV anomalies, etc.). At lower levels, a southerly to easterly moderate to intense flow provided conditionally unstable and moist air as it moved over the relatively warm Mediterranean Sea, typical for this time of the year (late summer and autumn). The two extreme cases (Gard and Aude) differ from the more classical event (Cévennes) in terms of larger low-level moisture fluxes. Weaker values of conditional convective instability, as in the Aude case, is counterbalanced by a stronger warm and moist low-level jet. The mesoscale triggering and/or sustaining ingredients for deep convection and the physical mechanisms leading to the stationarity of these rainfall events are presented and discussed in a companion paper.

A stochastic physics scheme is tested in the Application of Research to Operations at Mesoscale (AROME) short-range convection-permitting ensemble prediction system. It is an adaptation of ECMWF’s stochastic perturbation of physics tendencies (SPPT) scheme. The probabilistic performance of the AROME model ensemble is found to be significantly improved, when verified against observations over two 2-week periods. The main improvement lies in the ensemble reliability and the spread–skill consistency. Probabilistic scores for several weather parameters are improved. The tendency perturbations have zero mean, but the stochastic perturbations have systematic effects on the model output, which explains much of the score improvement. Ensemble spread is an increasing function of the SPPT space and time correlations. A case study reveals that stochastic physics do not simply increase ensemble spread, they also tend to smooth out high-spread areas over wider geographical areas. Although the ensemble design lacks surface perturbations, there is a significant end impact of SPPT on low-level fields through physical interactions in the atmospheric model.

ABSTRACT:In the western Mediterranean basin, large amounts of precipitation can accumulate in less than a day when a Mesoscale Convective System (MCS) stays over the same area for several hours. Heavy Precipitating Events (HPEs) in this region (especially southern France) are not only characterized by significant precipitation rates (typically more than 200 mm in less than 24 or 48 hours) but also by quasi-stationary behaviour. The aim of this present study is to use realistic simulations of past events to analyze and better understand the physical mechanisms which lead to the stationarity of HPEs over southern France using a high-resolution (2.5 km) non-hydrostatic mesoscale atmospheric model. We focused on three

Abstract. This paper presents the Meso-NH model version 5.4. Meso-NH is an atmospheric non hydrostatic research model that is applied to a broad range of resolutions, from synoptic to turbulent scales, and is designed for studies of physics and chemistry. It is a limited-area model employing advanced numerical techniques, including monotonic advection schemes for scalar transport and fourth-order centered or odd-order WENO advection schemes for momentum. The model includes state-of-the-art physics parameterization schemes that are important to represent convective-scale phenomena and turbulent eddies, as well as flows at larger scales. In addition, Meso-NH has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling. Here, we present the main innovations to the dynamics and physics of the code since the pioneer paper of Lafore et al. (1998) and provide an overview of recent applications and couplings.

This study assesses the potential for a detection algorithm to identify discriminating analysis-based statistical predictors of a few relevant parameters that can be used to capture heavy precipitation events (HPEs), or, at least, their associated largescale circulation (LSC) patterns in a climate scenario. HPEs are defined from a sample combining 'large-scale' fields from the ECMWF ERA-40 reanalysis with local observations from the Météo-France rain-gauge network. In a first step, LSC patterns considered as significantly favouring HPE over southern France are identified and described with the greatest robustness possible. For that purpose, an objective automatic clustering of the unfiltered 500 hPa geopotential height field is performed. Four clusters are obtained. Among them, the most discriminating for heavy precipitation is characterised by a synoptic-scale deep upper-level low northwest of the area of interest, inducing a southerly flow over the western Mediterranean Sea and southern France. In a second step, other lower-scale parameters are used to refine the characteristics of the clusters. It has been found that the low-level moisture transport is a relevant low-level ingredient to regionally characterise heavy precipitation. Indeed, 'Cévennes' cases are related to more south to southeasterly flows over the Gulf of Lion, whereas 'Languedoc-Roussillon' events occurred preferentially within a more pronounced easterly wind component with two streams of low-level moisture transport. Moreover, in-depth examination of the low-level features reveals that HPEs tend to occur when the wind blows in a specific direction and for the greatest low-level moisture flux over the Gulf of Lion. Finally, the predictive skill of a detection tool for HPEs over southern France, with only synoptic-scale favourable parameters as predictors, is discussed. It is shown that this tool allows selection of HPE situations in more than 70% of cases.

International audienceDuring the first special observation period of the HyMeX program dedicated to heavy precipitation over the western Mediterranean, several Mesoscale Convective Systems (MCSs) formed over the sea and produced heavy precipitation over the coastal regions, as for example during IOP (Intensive Operation Period) 16a. On 26 October 2012, back-building MCSs formed and renewed over the northwestern Mediterranean Sea while producing heavy rain over the French coastal urbanized regions. This paper analyses the storm evolution along with the ambient flow and the initiation and maintenance mechanisms of the offshore deep convection observed during IOP16a. The suites of water vapour lidars, wind profilers, radiosoundings and boundary layer drifting balloons over and along the coast of the northwestern Mediterranean offer a unique framework for validating the convective processes over the sea investigated using kilometric-scale analyses and simulation.The high-resolution simulation shows clearly that the convective system is fed during its evolution over the sea by moist and conditionally unstable air carried by a southwesterly to southeasterly low-level jet. The low-level wind convergence in this southeasterly to southwesterly flow over the sea is the main triggering mechanism acting to continually initiate and maintain the renewal of training convective cells contributing to the back-building system. The convergence line appears when a secondary pressure low forms in the lee of the Iberian mountains. A sensitivity test turning off the evaporative cooling within the microphysical parametrisation shows that the exact location of the main convergence area focusing the heaviest precipitation is determined by small-scale feedback mechanisms of the convection to the environment

The AROME-EPS convection-permitting ensemble prediction system has been evaluated over the HyMeX-SOP1 period. Objective verification scores are computed using dense observing networks prepared for the HyMeX experiment. In probabilistic terms, the AROME-EPS ensemble performs better than the AROME-France deterministic prediction system, and a state-of-the-art ensemble at a lower resolution. The strengths and weaknesses of AROME-EPS are discussed. Here, impact experiments are used to study perturbation schemes for the initial conditions and the model surface. Both have a significant effect on the ensemble performance. The interactions between the perturbations of lateral boundaries, initial conditions and surface perturbations are studied. The consistency between initial and lateral perturbations is found to be unimportant from a meteorological point of view. Ensemble data assimilation is not as effective as a simpler surface perturbation scheme, and it is noted that both approaches could be usefully combined.

This study assesses the impact of uncertainty on convective-scale initial conditions (ICs) and the uncertainty on lateral boundary conditions (LBCs) in cloud-resolving simulations with the Application of Research to Operations at Mesoscale (AROME) model. Special attention is paid to Mediterranean heavy precipitating events (HPEs). The goal is achieved by comparing high-resolution ensembles generated by different methods. First, an ensemble data assimilation technique has been used for assimilation of perturbed observations to generate different convective-scale ICs. Second, three ensembles used LBCs prescribed by the members of a global short-range ensemble prediction system (EPS). All ensembles obtained were then evaluated over 31- and/or 18-day periods, and on 2 specific case studies of HPEs. The ensembles are underdispersive, but both the probabilistic evaluation of their overall performance and the two case studies confirm that they can provide useful probabilistic information for the HPEs considered. The uncertainty on convective-scale ICs is shown to have an impact at short range (under 12 h), and it is strongly dependent on the synoptic-scale context. Specifically, given a marked circulation near the area of interest, the imposed LBCs rapidly overwhelm the initial differences, greatly reducing the spread of the ensemble. The uncertainty on LBCs shows an impact at longer range, as the spread in the coupling global ensemble increases, but it also depends on the synoptic-scale conditions and their predictability.