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High-resolution numerical weather prediction (NWP) systems present a strong potential to provide meteorological information in alpine terrain for diverse applications. However, they still suffer from biases highly detrimental for practical purposes. In this study, we investigate the origin of a significant wintertime screen-level temperature bias in forecasts of the AROME-France NWP system in high-altitude, snow-covered alpine terrain. For this purpose, a thorough set of meteorological and snow observations from two high-altitude instrumental sites is used. Targeted numerical simulations are carried out to disentangle the contributions to this bias coming from atmospheric fields, from the snow scheme, and from the coupling between the snowpack and the atmosphere. At both sites, the wind speed and incoming longwave radiation appear significantly negatively biased in AROME in the winter season. Using targeted offline simulations, we show that the simulation errors in these screen-level fields contribute to an average of 67% of the screen-level temperature bias of AROME, while the contribution of errors in the incoming shortwave radiation is negligible. Additionally, the screen-level temperature of AROME is not majorly impacted by changes in the complexity and especially the vertical layering of the snow model. However, it appears particularly sensitive to the parameterization of turbulent fluxes in stable conditions. Evidence suggest that these findings could at least partially be generalized to the whole AROME-France alpine domain. Hence, reducing the high-altitude, winter screen-level temperature bias in AROME may in great part proceed from improving the simulation of atmospheric fields and eliminating some bias compensations in the model.

The 1D-Var retrieval framework described hereused the NWPSAF 1D package. This can be downloaded fromthe NWPSAF website (https://nwp-saf.eumetsat.int/site/software/1d-var/download/, last access: 22 August 2022, Pavelin and Collard, 2009). The radiative transfer model RTTOV-gb v1.0 is available to licensed users free of charge. RTTOV-gb may be obtainedby registering (https://www.nwpsaf.eu/site/register/, last access: 22August 2022) and then selecting RTTOV-gb in your software preferences. Developments and updates of the RTTOV-gb code willbe published on the MWRnet website (http://cetemps.aquila.infn.it/rttovgb/rttovgb_updates.html, last access: 8 September 2022). Foraccess to the radar simulator and modified 1D-Var code, please contact pauline.martinet@meteo.fr; International audience; A new generation of cloud radars, with the ability to make observations close to the surface, presents the possibility of observing fog properties with better insight than was previously possible. The use of these instruments as part of an operational observation network could improve the prediction of fog events, something which is still a problem for even high-resolution Numerical Weather Prediction models. However, the retrieval of liquid water content (LWC) profiles from radar reflectivity alone is an under-determined problem, something which ground-based microwave radiometer observations can help to constrain. In fact, microwave radiometers are not only sensitive to temperature and humidity profiles but also known to be instruments of reference for the liquid water path. By providing the thermodynamic state of the atmosphere, to which the formation and evolution of fog events are highly sensitive, in addition to accurate liquid water path, which can be used to constrain the LWC retrieval from the cloud radar alone, combining microwave radiometers with cloud radars seems a natural next step to better understand and forecast fog events. To that end, a newly developed one dimensional variational (1D-Var) algorithm designed for the retrieval of temperature, specific humidity and liquid water content profiles with both cloud radar and microwave radiometer (MWR) observations is presented in this study. The algorithm was developed to evaluate the capability of cloud radar and MWR to provide accurate LWC profiles in addition to temperature and humidity in view of assimilating the retrieved profiles into a 3D/4D-Var operational assimilation system. The algorithm is firstly tested on a synthetic dataset, which allows the evaluation of the developed algorithm in idealised conditions. It is then tested with real data from the recent field campaign SOFOG-3D, carried out with the use of LWC measurements made from a tethered balloon platform. As expected, results from the synthetic dataset study were found to contain lower errors than that found from the retrievals on the dataset of real observations. It was found that retrieval of LWC can be obtained on idealised conditions with an uncertainty of less than 0.04 gm −3. With real data, as expected, retrievals with a good correlation (0.7) to in-situ measurements, but with a higher uncertainty than the synthetic dataset, of around 0.06 gm −3 , was found. This was reduced to 0.05 gm −3 when an accurate droplet number concentration could be prescribed to the algorithm. A sensitivity study was conducted to discuss the impact of different settings used in the 1D-Var algorithm and the for- ward operator. Additionally, retrievals of LWC from a real fog event observed during the SOFOG-3D field campaign were found to significantly improve the operational back- ground profiles of the AROME (Application of Research to Operations at MEsoscale) model, showing encouraging re- sults for future improvement of the AROME model initial state during fog conditions.

The Arome numerical weather prediction system is routinely used for weather forecasting over the mountains of the French Alps, Pyrénées and Corsica. However, its skills at temperature forecasting are altered by several 2 m temperature biases: (1) a cold bias at high altitude, (2) a low-altitude warm bias occurring in stably stratified layers and (3) a warm bias during snowfall situations.Targeted numerical simulations (successive activation of some dynamic, physical and assimilation modifications) were carried out on the day of January 12, 2021, a problematic snowy situation in the Arve valley (Haute-Savoie, French Alps).Over this period, the operational version of Arome has a mean absolute error (MAE) of 2.3°C in the valley. The increase of vertical resolution does not improve the performance of the model in the valley. The MAE is nevertheless decreased from 1.4 to 1.1°C in the mid-altitude range and from 1.5 to 1.2°C above 2000 m. Conversly, the use of a new surface scheme (ISBA-DIF) associated with a more complex snowpack model (ISBA-ES) allows to better represent the arrival of the warm front in the valley and reduces the error (to 1.8°C) whatever the altitude. The current surface scheme therefore seems too simplistic to correctly model soil-atmosphere interactions in the mountains. Forcing Arome with full-day data assimilation also reduces the bias in the valley (to 2.0°C). However, this experiment deteriorates the scores in the mid-altitude and high-altitude mountains. Furthermore, the situation has a poor initial state as biases are present even before the snow event starts. This may point towards deficiencies in the assimilation of in-situ data in mountain regions, that should be overcome in future work.These results show that the warm bias during this snowy event has multiple origins. A carefull analysis of other situations will be needed to confirm and correct theses biases.

Modelling the rare but high-impact Mediterranean Heavy Precipitation Events (HPEs) at climate scale remains a largely open scientific challenge. The issue is adressed here by running a 38-year-long continuous simulation of the CNRM-AROME Convection-Permitting Regional Climate Model (CP-RCM) at a 2.5 km horizontal resolution and over a large pan-Alpine domain. First, the simulation is evaluated through a basic Eulerian statistical approach via a comparison with selected high spatial and temporal resolution observational datasets. Northwestern Mediterranean fall extreme precipitation is correctly represented by CNRM-AROME at a daily scale and even better at an hourly scale, in terms of location, intensity, frequency and interannual variability, despite an underestimation of daily and hourly highest intensities above 200 mm/day and 40 mm/h, respectively. A comparison of the CP-RCM with its forcing convection-parameterised 12.5 km Regional Climate Model (RCM) demonstrates a clear added value for the CP-RCM, confirming previous studies. Secondly, an object-oriented Lagrangian approach is proposed with the implementation of a precipitating system detection and tracking algorithm, applied to the model and the reference COMEPHORE precipitation dataset for twenty fall seasons. Using French Mediterranean HPEs as objects, CNRM-AROME’s ability to represent the main characteristics of fall convective systems and tracks is highlighted in terms of number, intensity, area, duration, velocity and severity. Further, the model is able to simulate long-lasting and severe extreme fall events similar to observations. However, it fails to reproduce the precipitating systems and tracks with the highest intensities (maximum intensities above 40 mm/h) well, and the model’s tendency to overestimate the cell size increases with intensity.

Fog forecasts still remain quite inaccurate due to the complexity, non linearities and fine scale of the main physical processes driving the fog lifecycle. Additionally to the complex modelling of fog processes, current numerical weather prediction models are known to suffer from a lack of operational observations in the atmospheric boundary layer and more generally during cloudy-sky conditions. Continuous observations of both thermodynamics and microphysics during the fog lifecycle are thus essential to develop future operational networks with the aim of validating current physical parameterizations and improving the model initial state through data assimilation techniques. In this context, an international network of 8 ground-based microwave radiometers (MWRs) has been deployed at a regional-scale on a 300 x 300 km domain during the SOFOG3D (SOuth FOGs 3D experiment for fog processes study) that has been conducted from October 2019 to April 2020. The MWR network has been extended with ceilometers at all MWR sites and additional microphysical observations from the 95 GHz cloud radar BASTA at two major sites as well as wind measurements from a Doppler lidar deployed at the super-site. After an overview of the SOFOG3D objectives and experimental set-up, preliminary results exploiting mainly the MWR network and cloud radar observations will be presented. Firstly, the capability of MWRs to provide temperature and humidity retrievals within fog and stratus clouds will be evaluated and discussed against radiosoundings launched during intensive observation periods (IOPs). Secondly, first retrievals of liquid water content profiles within fog and stratus clouds derived from the synergy between MWRs and the BASTA cloud radar will be presented. To that end, a one dimensional variational approach (1D-Var) directly assimilating MWR brightness temperatures and cloud-radar reflectivities has been developed. 1D-Var retrievals will be validated through a dataset of simulated observations and real fog cases of the SOFOG3D experiment. The capability of MWR and cloud radar observations to improve the initial state of the AROME model during fog conditions will be discussed with a focus on selected case studies. Finally, the usefulness of ground-based remote sensing networks to improve our understanding of fog processes and to validate physical parameterizations will be illustrated using the operational AROME model and the AROME Ensemble Prediction System

A field experiment took place from July to October 2018 in a narrow valley of the central Pyrenees in order to study local flows and their impacts. This field experiment is a joint effort by CNRM, Laboratoire d'Aerologie and University of the Balearic Islands. It emerged from a recent numerical study done by the University of the Balearic Islands (Jiménez et al. 2019).This study suggests that under clear-sky conditions a jet forms in the valley and can be observed several kilometers away from the valley exit.Several instruments including a Doppler scanning lidar and three meteorological stations were deployed on the main site at the valley exit, where the jet maximum is expected, and on two other sites up valley. Data from the Atmospheric Research Center (part of the Pyrenean Platform for the Observation of the Atmosphere P2OA) in Lannemezan are also used. They include radio-soundings specifically planned for the field experiment. This instrumented platform of Laboratoire d'Aerologie, located about 10 km away from the valley exit, is an important asset for the project.An overview of the field experiment as well as the valley exit jet main features will be presented. A comparison with outputs from the NWP model AROME will be also shown.

Fog strongly perturbs the aviation, marine and land transportation, leading to human losses and high financial costs. The primary objective of SOFOG3D is to advance our understanding of fog processes at the smallest scale to improve forecasts of fog events by numerical weather prediction (NWP) models.Specifically, SOFOG3D conducts process studies on very well documented situations, using synergy between 3D high-resolution Large Eddy Simulation (LES) and unprecedented 3D detailed observations. SOFOG3D will particularly focus on the impact of surface heterogeneities (types of vegetation, rivers, orography) on the fog life cycle, on fog microphysics properties, on entrainment at fog top, on the surface energy budget, and on the impact of aerosols. SOFOG3D will also investigate how improving the initial conditions of NWP models can improve fog forecasts. To that end, data from a ground-based MWR network will be assimilated using an innovative ensemble-based variational data assimilation scheme.A 6 months field experiment took place during wintertime 2019/2020 in the South-West of France to provide 3D mapping of the boundary layer during fog events. The observation strategy is to combine vertical profiles derived from new remote sensing instruments (microwave radiometer (MWR), Doppler cloud radar and Doppler lidars) and balloon-borne in-situ measurements, with local observations provided by a network of surface stations, and a fleet of Unmanned Aerial Vehicles (UAV) to explore fog spatial heterogeneities. Three nested domains has been instrumented with increasing density to provide observations from regional scale (300x200 km) down to local scale on the super-site (10x10 km), thanks to Meteo France and U.K. Meteorological Office sensors. On the super site, meteorological conditions, visibility, aerosol optical, microphysical and hygroscopic properties, fog microphysics and liquid water content, water deposition, radiation budget, heat and momentum fluxes on flux-masts has been performed on different areas to investigate the impacts of surface heterogeneities on fog processes, as well as turbulence anisotropy. Combination of cloud radar and MWR measurements will allow optimal retrieval of temperature, humidity and liquid water content profiles.We will present the instrumental set-up that has been deployed during this campaign and discuss the main objectives of the project. An overview of fog events that occurred during the 6 months experiment will be given, and preliminary analysis of data collected during IOPs with a tethered balloon and UAVs will be presented.

Numerical weather prediction (NWP) systems operating at kilometer scale in mountainous terrain offer appealing prospects for forecasting the state of snowpack in support of avalanche hazard warning, water resources assessment, and flood forecasting. In this study, daily forecasts of the NWP system Applications of Research to Operations at Mesoscale (AROME) at 2.5-km grid spacing over the French Alps were considered for four consecutive winters (from 2010/11 to 2013/14). AROME forecasts were first evaluated against ground-based measurements of air temperature, humidity, wind speed, incoming radiation, and precipitation. This evaluation shows a cold bias at high altitude partially related to an underestimation of cloud cover influencing incoming radiative fluxes. AROME seasonal snowfall was also compared against output from the Système d’Analyse Fournissant des Renseignements Atmosphériques à la Neige (SAFRAN) specially developed for alpine terrain. This comparison reveals that there are regions of significant difference between the two, especially at high elevation, and possible causes for these differences are discussed. Finally, AROME forecasts and SAFRAN reanalysis have been used to drive the snowpack model Surface Externalisée (SURFEX)/Crocus (SC) and to simulate the snowpack evolution over a 2.5-km grid covering the French Alps during four winters. When evaluated at the experimental site of Col de Porte, both simulations show good agreement with measurements of snow depth and snow water equivalent. At the scale of the French Alps, AROME-SC exhibits an overall positive bias, with the largest positive bias found in the northern and central French Alps. This study constitutes the first step toward the development of a distributed snowpack forecasting system using AROME.

The ALADIN System is a numerical weather prediction system (NWP) developed by the international ALADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Météo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 Partner Institutes of this consortium. These configurations are called the ALADIN Canonical Model Configurations (CMCs). There are currently three CMCs: the ALADIN baseline-CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations. The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs and to document their most recent versions, and (iii) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the Partner Institutes of the ALADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here.

Lothon, Marie et al., © 2014 Author(s). Due to the major role of the sun in heating the earth's surface, the atmospheric planetary boundary layer over land is inherently marked by a diurnal cycle. The afternoon transition, the period of the day that connects the daytime dry convective boundary layer to the night-time stable boundary layer, still has a number of unanswered scientific questions. This phase of the diurnal cycle is challenging from both modelling and observational perspectives: it is transitory, most of the forcings are small or null and the turbulence regime changes from fully convective, close to homogeneous and isotropic, toward a more heterogeneous and intermittent state. These issues motivated the BLLAST (Boundary-Layer Late Afternoon and Sunset Turbulence) field campaign that was conducted from 14 June to 8 July 2011 in southern France, in an area of complex and heterogeneous terrain. A wide range of instrumented platforms including full-size aircraft, remotely piloted aircraft systems, remote-sensing instruments, radiosoundings, tethered balloons, surface flux stations and various meteorological towers were deployed over different surface types. The boundary layer, from the earth's surface to the free troposphere, was probed during the entire day, with a focus and intense observation periods that were conducted from midday until sunset. The BLLAST field campaign also provided an opportunity to test innovative measurement systems, such as new miniaturized sensors, and a new technique for frequent radiosoundings of the low troposphere. Twelve fair weather days displaying various meteorological conditions were extensively documented during the field experiment. The boundary-layer growth varied from one day to another depending on many contributions including stability, advection, subsidence, the state of the previous day's residual layer, as well as local, meso-or synoptic scale conditions. Ground-based measurements combined with tethered-balloon and airborne observations captured the turbulence decay from the surface throughout the whole boundary layer and documented the evolution of the turbulence characteristic length scales during the transition period. Closely integrated with the field experiment, numerical studies are now underway with a complete hierarchy of models to support the data interpretation and improve the model representations., The BLLAST field experiment was made possible thanks to the contribution of several institutions and supports: INSU-CNRS (Institut National des Sciences de l’Univers, Centre national de la Recherche Scientifique, LEFE-IMAGO program), Météo-France, Observatoire Midi-Pyrénées (University of Toulouse), EUFAR (EUropean Facility for Airborne Research) BLLATE-1&2, COST ES0802 (European Cooperation in the field of Scientific and Technical) and the Spanish MINECO projects CGL2009–08609, CGL2012–37416–C04–03, CGL2012–37416– C04–02 and CGL2011-13477-E

Unfortunately, the article “Extreme rainfall in Mediterranean France during the fall: added value of the CNRM‑AROME Convection‑Permitting Regional Climate Model”, written by Quentin Fumière was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 24 July 2019 without open access with incorrect copyright holder as “© Springer-Verlag GmbH Germany, part of Springer Nature 2019”.

This study focuses on the radiative impacts of dust on the thermodynamics and dynamics of a major Saharan dust-storm that occurred between 7 and 15 March 2006. The implementation of a dust module within the convective-scale operational model AROME permitted a 10-day simulation at high resolution (5 km) over a large domain (6.5-30°N; 3°W-33°E). The model is able to represent most of the life cycle of this dust-storm and of the principal dust sources. According to the comparison with a complete and comprehensive set of measurements obtained within the framework of the AMMA field campaign in 2006, the simulation succeeds in representing the main thermodynamic and radiative features of the storm both qualitatively and quantitatively. As compared with a simulation without the dust, the coupling with the dust module provides signatures of the storm that are in better agreement with radiation and temperature observations. The intense heating in the core of the dust plume (more than 2°C) resulted in a large vertical dipole of potential vorticity anomaly with higher values at low levels and weaker values at mid levels, either in the lower and the upper part of the dust plume respectively. This shows that the coupling with dust reinforces the intensity of the cold extratropical outbreak with more ascent at the cold front, more cyclonic convergence near the surface, and more anticyclonic divergence aloft. Also, the subsidence is increased at the rear of the outbreak with more northerly winds. A major result is the acceleration of the easterly along-front flow (∼3 m s−1) at low levels and in the African Easterly Jet, increasing the emission of dust and its westward long-range transport. Copyright © 2011 Royal Meteorological Society

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.

A formulation to include prognostic atmospheric layers in offline surface schemes is derived from atmospheric equations. Whereas multilayer schemes developed previously need a complex coupling between atmospheric-model levels and surface-scheme levels, the coupling proposed here remains simple. This is possible because the atmospheric layers interacting with the surface scheme are independent of the atmospheric model that could be coupled above. The surface boundary layer (SBL; both inside and just above the canopy) is resolved prognostically, taking into account large-scale forcing, turbulence, and, if any, drag and canopy forces and surface fluxes. This formulation allows one to retrieve the logarithmic law in neutral conditions, and it has been validated when coupled to a 3D atmospheric model. Systematic comparisons with 2-m observations and 10-m wind have been made for 2 months. The SBL scheme is able to model the 2-m temperature accurately, as well as the 10-m wind, without any use of analytical interpolation. The largest improvement takes place during stable conditions (i.e., by night), during which analytical laws and interpolation methods are known to be less accurate, and in mountainous areas, in which nocturnal low-level flow is strongly influenced by surface cooling. The prognostic SBL scheme is shown to solve the nighttime physical disconnection problem between surface and atmosphere models. The inclusion of the SBL into the urban Town Energy Balance scheme is presented in a paper by Hamdi and Masson in which the ability of the method to simulate the profiles of both mean and turbulent quantities from above the building down to the road surface is shown using data from the Basel Urban Boundary Layer Experiment (BUBBLE). The proposed method will allow the inclusion of the detailed physics of the multilayer schemes (e.g., the interactions of the SBL flow with forest or urban canopy) into a single-layer scheme that is easily coupled with atmospheric models.

This study evaluates the ability of three operational models, AROME, ARPEGE and ECMWF, to predict the boundary-layer turbulent processes and mesoscale variability observed during the Boundary Layer Late-Afternoon and Sunset Turbulence (BLLAST) field campaign. AROME is a 2.5 km limited area non-hydrostatic model operated over France, ARPEGE a global model with a 10 km grid-size over France and ECMWF a global model with a 16 km grid-size. We analyze the representation of the vertical profiles of temperature and humidity and the time evolution of near surface atmospheric variables as well as the radiative and turbulent fluxes for a total of 12 24h-long Intensive Observing Periods. Special attention is paid to the evolution of the turbulent kinetic energy that was sampled by a combination of independent instruments. For the first time, this variable, which is a central variable in the turbulence scheme used in AROME and ARPEGE, is evaluated with observations. In general, the 24h-forecasts succeed in reproducing the variability from one day to the other in term of cloud cover, temperature, boundary-layer depth. However, they exhibit some systematic biases, in particular a cold bias within the daytime boundary layer for all models. An overestimation of the sensible heat flux is noted for two points in ARPEGE, partly related to an inaccurate simplification of surface characteristics and over-predominance of forests. AROME shows a moist bias within the daytime boundary layer, consistently with overestimated latent heat fluxes. ECMWF presents a dry bias at 2 m above surface and also overestimates the sensible heat flux. The high-resolution model AROME better resolves the vertical structures, in particular the strong daytime inversion and the evening thin stable boundary layer. This model is also capable to capture the peculiar observed features, such as the orographically-driven subsidence and a well-defined maximum in water vapor mixing ratio in the upper part of the residual layer that arises during the evening due to mesoscale advection. The mesoscale variability is analyzed and the order of magnitude is also well reproduced in AROME. AROME provides a good simulation of the diurnal variability of the turbulent kinetic energy while ARPEGE shows a right order of magnitude.

Avec le projet AROME, METEO-France a engage le developpement d’un nouveau systeme de prevision numerique, qui devrait etre exploite operationnellement a l’horizon 2008. Ce nouveau systeme de prevision sera dedie a la prevision a tres courte echeance dans l’objectif d’ameliorer la prevision des phenomenes meteorologiques de mesoechelle comme les orages, les pluies intenses, le brouillard,… Le modele de prevision AROME, qui fonctionnera avec une resolution de quelques kilometres, federera les progres de l’operationnel et de la recherche en prevision numerique en heritant d’une partie des codes numeriques des modeles operationnels ARPEGE et ALADIN et du modele de recherche communautaire MESO-NH. Une caracteristique essentielle d’AROME est qu’il aura son propre systeme d’assimilation de donnees a mesoechelle, lui permettant d’exploiter des reseaux d’observations a mesoechelle non-assimiles actuellement par les systemes de prevision operationnel comme les donnees radar du reseau ARAMIS de METEO-France par exemple.

EnglishAlthough the evolution of the state of the atmosphere intrinsically is to be considered as a geographically global problem, numerical weather prediction also has been, and still is, dealing with limited area models besides global ones. One important reason is the opportunity offered by limited area models to increase, sometimes drastically, the spatial resolution of the model grids, since the forecast does not have to cover the whole globe. Physical processes are then potentially represented with a higher degree of realism as well as sometimes complexity. For instance, today operational limited area models describe heavy convective events, and their modelled representation of microphysics, clouds, turbulence or the exchanges with continental and oceanic surfaces is becoming increasingly realistic. At the same time, for data assimilation, the use of fine scale observations becomes widespread, such as radar data or very high density satellite observations. In this article, a historical and scientific overview of operational limited area modelling over the last twenty years at Meteo-France is presented, addressing the two specific models Aladin and Arome. francaisL'evolution de l'etat de l'atmosphere est un probleme a apprehender a priori dans sa globalite geographique, c'est-a-dire sur tout le globe terrestre. Pour autant, la prevision numerique du temps s'appuie a la fois sur des modeles a domaine limite et des modeles a domaine global. Une raison principale a cela est la possibilite offerte en domaine limite, ou a aire limitee, a augmenter, parfois considerablement, la resolution spatiale des grilles des modeles, puisque la prevision n'a plus besoin de couvrir tout le globe. Les processus physiques sont alors a priori « vus » avec plus de realisme, mais aussi parfois davantage de complexite. Ainsi, aujourd'hui, les modeles a aire limitee operationnels representent les phenomenes convectifs intenses et gagnent toujours plus en realisme quant aux descriptions des processus de la microphysique, des nuages, de la turbulence ou des echanges avec les surfaces continentales et oceaniques. De meme, en assimilation de donnees, l'utilisation d'observations de fine echelle se generalise, comme les radars ou les observations satellitaires a tres haute densite. Nous presentons ici un tour d'horizon historique et scientifique des deux modeles a aire limitee qui ont marque le paysage operationnel de Meteo-France ces vingt dernieres annees, Aladin puis Arome.

Some differences between lightning and precipitation characteristics of thunderstorms over sea and over land are analyzed. The rain field is observed by a meteorological radar. The cloud-to-ground (CG) lightning activity is observed by the French network METEORAGE, and the total lightning activity is observed by a Surveillance et Alerte Foudre par Interferometrie Radioelectrique (SAFIR) interferometric system. Several parameters are compared for 21 stormy days over land and over the ocean in different meteorological conditions. The parameters considered for precipitation are cumulative rainfall and rain rate. Those for the lightning activity are the density, rate, proportion, peak current, and multiplicity of CG flashes, and the density and rate of the total flashes and of the VHF sources. The whole data set is statistically analyzed, and some individual convective systems are discussed. The storm activity and some parameters like the CG peak current clearly seem to be affected by the surface characteristics (sea or land). Others parameters, like the positive CG flash percentage, are not affected. The land-sea ratio is found to be 1.8 for cumulative rainfall and 2.36 for CG flash number. Most of the thunderstorms observed over sea develop close to the coastline. A substantial decrease of lightning activity is observed during the lifetime of a hail-bearing thunder cell. The rain volume per CG flash, averaged for all situations and for the whole domain, is 68 × 103 m3 per CG flash. For individual cases this volume increases with the positive CG proportion. Moreover, the low values of the rain volume per CG flash correspond to a relatively strong lightning activity and are often associated with a large cloud vertical development. Assuming that a high probability of lightning flash occurrence corresponds to particularly efficient charging processes, this last observation suggests that the role of strong vertical velocities in these electrical processes is essential.

SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D runs) or in coupled mode (from mesoscale models to numerical weather prediction and climate models). An assimilation mode is included for numerical weather prediction and monitoring. In addition to momentum, heat and water fluxes, SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. The main principles of the organisation of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally, the main applications of the code are summarised. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage.

Using a snow/atmosphere coupled model, the evolution of the surface and near-surface snow temperature is modeled at Dome C, Antarctica, during the period 20–30 January 2010. Firstly, the detailed multilayer snow model Crocus is run in stand-alone mode, with meteorological input forcing data provided by local meteorological observations. The snow model is able to simulate the evolution of surface temperature with good accuracy. It reproduces the observed downward propagation of the diurnal heatwave into the upper 50 cm of the snowpack reasonably well. Secondly, a fully coupled 3-D snow/atmosphere simulation is performed with the AROME regional meteorological model, for which the standard single-layer snow parameterization is replaced by Crocus. In spite of a poor simulation of clouds, the surface and near-surface snow temperatures are correctly simulated, showing neither significant bias nor drifts during the simulation period. The model reproduces particularly well the average decrease of the diurnal amplitude of air temperature from the surface to the top of the 45 m instrumented tower. This study highlights the potential of snow/atmosphere coupled models over the Antarctic plateau and the need to improve cloud microphysics and data assimilation over polar regions.

The impact of the choice of high-resolution atmospheric forcing on ocean summertime circulation in the Gulf of Lions (GoL; Mediterranean Sea) is evaluated using three different datasets: AROME (2.5 km, 1 h), ALADIN (9.5 km, 3 h), and MM5 (9 km, 3 h). A short-term ocean simulation covering a 3-month summer period was performed on a 400-m configuration of the GoL. The main regional features of both wind and oceanic dynamics were well-reproduced by all three atmospheric models. Yet, at smaller scales and for specific hydrodynamic processes, some differences became apparent. Inertial oscillations and mesoscale variability were accentuated when high-resolution forcing was used. Sensitivity tests suggest a predominant role for spatial rather than temporal resolution of wind. The determinant influence of wind stress curl was evidenced, both in the representation of a mesoscale eddy structure and in the generation of a specific upwelling cell in the north-western part of the gulf.

International audience; The Convective and Orographically- induced Precipitation Study (COPS) is a coordinated international project, comprised of an observational field campaign and a research programme aiming to advance the quality of fore- casts of orographically-induced pre- cipitation by four-dimensional obser- vations and modelling of its life cycle. The COPS field campaign took place during June-July-August 2007 over eastern France and south-western Germany. Its main objective was to provide an unprecedented comprehen- sive set of in situ and remotely-sensed meteorological observations of the entire depth of the troposphere. After a short overview of the project, the paper focuses on the French contribution to the COPS field phase, describes the experimental setup and highlights some key observations.; L’étude des précipitations convectives induites par l’orographie (Cops selon l’acronyme anglais) est un projet inter- national coordonné qui comprend une campagne d’observations de terrain et un programme scientifique et qui vise à améliorer la qualité des prévisions des précipitations orographiques convectives à la fois par l’observation quadridimensionnelle et la modélisa- tion de leur cycle de vie. La campagne de terrain s’est déroulée en juin-juillet- août 2007 sur l’est de la France et le sud-ouest de l’Allemagne. Son objectif majeur était de fournir un jeu d’obser- vations météorologiques, in situ et à distance, aussi complet que possible et sur toute la profondeur de la colonne troposphérique.Après une brève revue d’ensemble du projet, l’article se concentre sur la contribution française à la campagne Cops, décrit le dispositif expérimental mis en œuvre et met en valeur quelques observations clés.

International audience; This paper proposes a nonlinear horizontal diffusion scheme for models using semi-Lagrangian formulations. The scheme is made flow dependent and not entirely linked to the model levels. As an extension, the implementation of the scheme to the model Aladin is given. The damping abilities of interpolation are used for the diffusion filtering. The aim is to provide a horizontal diffusion scheme of similar stability and computational efficiency as the existing linear spectral diffusion scheme in Aladin. Preserving such qualities, the new scheme brings beneficial new skills to the model. The differences between the performances of the two diffusion schemes are examined and discussed. Finally, some interesting case-studies simulated with both horizontal diffusion schemes are presented.Copyright © 2008 Royal Meteorological Society

[1] The cloud-to-ground lightning flash (CG) produced by several apparent hailstorms are analyzed in different locations of southern Europe. The hail detection is performed via four different analysis techniques: radar reflectivity factor estimation, radar echo shape analysis, polarimetric hydrometeor identification, and reflectivity difference between radars with different wavelengths. The CG parameters considered are the flash rate and density, the flash polarity, the multiplicity, and the peak current. Some of the observed storms exhibit hail-bearing cell features, while others exhibit heavy precipitation rates without any apparent hail production. One of the hailstorms can be classified as severe because reported hailstorm diameters reach 39 mm. The CG lightning characteristics of both types of storms are compared. The CG rates corresponding to all hail-bearing storms are singularly lower than those of rain-only storms, typically by a factor 5. So, the CG rate of the hail-bearing storms considered does not exceed 2 min−1 while it can reach about 12 min−1 for heavy rain-bearing storms. Moreover, some of them can produce especially high positive CG proportions associated with negative CGs with low values of peak current and multiplicity. This last observation suggests that the negative charge available for CG flashes is weak within the cloud when positive CG flashes are dominant. In order to interpret the low CG rates observed in the case of hail-bearing storms several interpretations are discussed, but it would be necessary to know the intracloud flash activity in such cases of storms in order to enrich the discussion.

This paper presents a study about correlation between cloud-to-ground lightning  ash (CG) activity, and the dynamics and microphysics of thunderclouds. Data collected during Intense Observation Period (MAP IOP) 2a of the Mesoscale Alpine Programme Special Observing Period (SOP) over the Lago Maggiore Target Area (LMTA) in northern Italy are used. IOP 2a was the most electrically active period during the SOP, representing 75% of the total CG activity. Thunderclouds were strongly vertically developed (the 30 dBZ echo tops were sometimes higher than 12 km) and produced large amounts of rainfall and some hail. Doppler and polarimetric radar data allow us to retrieve the three-dimensional wind and radar-reflectivity fields from two synchronous Doppler radars, and particle-type fields in the thunderclouds from the S-Pol polarimetric radar. Both polarities of CGs are distinguished. Temporal and spatial relationships from the global activity over the LMTA are first studied. Then, the temporal correlation between CG rates and dynamics or microphysics for five individual cells is considered. A very strong correlation is observed between CG and the presence of a mixture of graupel and hail, which strongly supports a non-inductive charging mechanism. CG impacts seem to be located underneath large radar-reflectivity values and around the maximum vertical velocities. Two individual cells are studied in more detail, in order to better understand their different electrical behaviours: the first produced mainly negative CGs, and the second produced 61% positive CGs in the second phase of its lifetime. The association of positive CGs with severe weather and especially with the presence of hail is observed.

International audience; South-East France is a region often affected by heavy precipitating events the characteristics of which are likely to be significantly impacted in the future climate. In this study, uc(cnrm-arome), a Convection-Permitting Regional Climate Model with a 2.5 km horizontal resolution is compared to its forcing model, the Regional Climate Model uc(aladin-c)limate at a horizontal resolution of 12.5 km, self-driven by the uc(era-i)nterim reanalysis. An hourly observation dataset with a resolution of 1 km, uc(comephore), is used in order to assess simulated surface precipitation from a seasonal to hourly scale. The representation of the spatial pattern of fall precipitation climatology is improved by uc(cnrm-arome). It also shows a clear added value with respect to uc(aladin-c)limate through the improvement of the localization and intensity of extreme rainfall on a daily and hourly time scale on both fine and coarse spatial scales (2.5, 12.5 and 50 km). uc(cnrm-arome) in particular is able to simulate intense rainfall on lowlands and makes sub-daily rainfall events more intense than uc(aladin-c)limate. uc(cnrm-arome) still underestimates very extreme precipitation from above 30 mm/h or 230 mm/day.