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

[1] A ground-based GPS network has been established over West Africa in the framework of African Monsoon Multidisciplinary Analysis (AMMA) in tight cooperation between French and African institutes. The experimental setup is described and preliminary highlights are given for different applications using these data. Precipitable water vapor (PWV) estimates from GPS are used for evaluating numerical weather prediction (NWP) models and radiosonde humidity data. Systematic tendency errors in model forecasts are evidenced. Correlated biases in NWP model analyses and radiosonde data are evidenced also, which emphasize the importance of radiosonde humidity data in this region. PWV and precipitation are tightly correlated at seasonal and intraseasonal timescales. Almost no precipitation occurs when PWV is smaller than 30 kg m À2 . This limit in PWV also coincides well with the location of the intertropical discontinuity. Five distinct phases in the monsoon season are determined from the GPS PWV, which correspond either to transition or stationary periods of the West African Monsoon system. They may serve as a basis for characterizing interannual variability. Significant oscillations in PWV are observed with 10-to 15-day and 15-to 20-day periods, which suggest a strong impact of atmospheric circulation on moisture and precipitation. The presence of a diurnal cycle oscillation in PWV with marked seasonal evolutions is found. This oscillation involves namely different phasing of moisture fluxes in different layers implying the low-level jet, the return flow, and the African Easterly Jet. The broad range of timescales observed with the GPS systems shows a high potential for investigating many atmospheric processes of the West African Monsoon.

Abstract. During autumn 2012 and winter 2013, two special observation periods (SOPs) of the HYdrological cycle in the Mediterranean EXperiment (HyMeX) took place. For the preparatory studies and to support the instrument deployment during the field campaign, a dedicated version of the operational convective-scale Application of Research to Operations at Mesoscale (AROME)-France model was developed: the AROME-WMED (West Mediterranean Sea) model. It covers the western Mediterranean basin with a 48 h forecast range. It provided real-time analyses and forecasts which were sent daily to the HyMeX operational centre to forecast high-precipitation events and to help decision makers on the deployment of meteorological instruments. This paper presents the main features of this numerical weather prediction system in terms of data assimilation and forecast. Some specific data of the HyMeX SOP were assimilated in real time.The forecast skill of AROME-WMED is then assessed with objective scores and compared to the operational AROME-France model, for both autumn 2012 (05 September to 06 November 2012) and winter 2013 (01 February to 15 March 2013) SOPs. The overall performance of AROME-WMED is good for the first HyMeX special observation period (SOP1) (i.e. mean 2 m temperature root mean square error (RMSE) of 1.7 • C and mean 2 m relative humidity RMSE of 10 % for the 0-30 h forecast ranges) and similar to those of AROME-France for the 0-30 h common forecast range (maximal absolute difference of 2 m temperature RMSE of 0.2 • C and 0.21 % for the 2 m relative humidity); conversely, for the 24-48 h forecast range it is less accurate (relative loss between 10 and 12 % in 2 m temperature and relative humidity RMSE, and equitable threat score (ETS) for 24 h accumulated rainfall), but it remains useful for scheduling observation deployment. The characteristics of parameters, such as precipitation, temperature or humidity, are illustrated by one heavy precipitation case study that occurred over the south of Spain.

During the African Monsoon Multidisciplinary Analysis (AMMA) field experiment in 2006 there was a large increase in the number of radiosonde data over West Africa. This has the potential of improving the numerical weather prediction (NWP) analysis/forecast and the water budget studies over that region. However, it is well known that the humidity from radiosondes can have some errors depending on sonde type, relative humidity (RH), temperature and the age of the sensor and can give rise to dry biases that are typically between 5% and 30% for RH. Three main sonde types were used in the AMMA field experiment: Vaisala RS80A, Vaisala RS92 and MODEM. In this article, a new empirical method is presented by using the operational European Centre for Medium-Range Weather Forecasts (ECMWF) short-range forecast as an intermediary dataset for computing biases. The validation of the correction method using global positioning system (GPS) total columnar water vapour (TCWV) confirms that the method is able to correct for a large part of the dry biases associated with the different sonde types. Results from analysis experiments show how the correction of humidity is particularly important in the West African region due to its impact on the development of convection in NWP models. The proposed radiosonde humidity bias correction has been applied to the special AMMA reanalysis experiment performed at ECMWF for the 2006 West African wet monsoon season. This is expected to benefit a wide number of AMMA-related studies that make use of the reanalysis, in particular those focusing on the water cycle.

A special screening procedure is developed for the removal of outliers in the GPS Zenith Total Delay (ZTD) data. ZTD data are converted to integrated water vapour (IWV) using surface pressure information from an AROME-WMED operational analysis. The reprocessed ZTD and IWV data are used to assess the accuracy of the near-real time E-GVAP ZTD data assimilated in operational numerical weather prediction systems and to validate the IWV data from the AROME-WMED operational analysis and AROME-WMED reanalysis 1, and from radiosonde observations. The mean differences between E-GVAP and reprocessed ZTD data are not negligible and lie in the range from −3 to +3 mm. The standard deviations of differences are between 4 and 8 mm. The comparisons of IWV from AROME-WMED analyses and the reprocessed GPS data show high quality of the analyses where operational GPS data are assimilated and lower quality where no GPS data are assimilated. Small but significant biases are found in the radiosonde data during daytime (−0.5 to +1.4 kg m −2 ), but their origin is not determined so far. Thanks to the high spatial density of the reprocessed GPS stations, both the large-scale and small-scale variations in IWV can be documented. The case of HyMeX Intensive Observing Period 8 is presented as an example of a heavy precipitation event. This work suggests that improved quality of the humidity fields can be expected of the future AROME-WMED reanalysis 2 as a result of the assimilation of the reprocessed GPS data.

International audienceDuring the African Monsoon Multidisciplinary Analyses (AMMA) program, which included a special observing period that took place over West Africa in 2006, a major effort was devoted to monitor the atmosphere and its water cycle. The radiosonde network was upgraded and enhanced, and GPS receivers deployed. Among all sondes released in the atmosphere, a significant number were Vaisala RS80-A sondes, which revealed a significant dry bias relative to Vaisala RS92 (a maximum of 14% in the lower atmosphere, reaching 20% in the upper levels). This paper makes use of a simple but robust statistical approach to correct the bias. Comparisons against independent GPS data show that the bias is almost removed at night, whereas for daytime conditions, a weak dry bias (5%) still remains. The correction enhances CAPE by a factor of about 4 and, thus, becomes much more in line with expected values over the region

In the framework of the European Hydrological Cycle in the Mediterranean Experiment project, a field campaign devoted to the study of electrical activity during storms took place in the south of France in 2012. An acoustic station composed of four microphones and four microbarometers was deployed within the coverage of a Lightning Mapping Array network. On the 26 October 2012, a thunderstorm passed just over the acoustic station. Fifty‐six natural thunder events, due to cloud‐to‐ground and intracloud flashes, were recorded. This paper studies the acoustic reconstruction, in the low frequency range from 1 to 40 Hz, of the recorded flashes and their comparison with detections from electromagnetic networks. Concurrent detections from the European Cooperation for Lightning Detection lightning location system were also used. Some case studies show clearly that acoustic signal from thunder comes from the return stroke but also from the horizontal discharges which occur inside the clouds. The huge amount of observation data leads to a statistical analysis of lightning discharges acoustically recorded. Especially, the distributions of altitudes of reconstructed acoustic detections are explored in detail. The impact of the distance to the source on these distributions is established. The capacity of the acoustic method to describe precisely the lower part of nearby cloud‐to‐ground discharges, where the Lightning Mapping Array network is not effective, is also highlighted.

This paper assesses the performance of the European Centre for Medium-Range Weather ForecastsIntegrated Forecast System (ECMWF-IFS) operational analysis and NCEP-NCAR reanalyses I and II over West Africa, using precipitable water vapor (PWV) retrievals from a network of ground-based GPS receivers operated during the African Monsoon Multidisciplinary Analysis (AMMA). The model analyses show reasonable agreement with GPS PWV from 5-daily to monthly means. Errors increase at shorter time scales, indicating that these global NWP models have difficulty in handling the diurnal cycle and moist processes at the synoptic scale. The ECMWF-IFS analysis shows better agreement with GPS PWV than do the NCEP-NCAR reanalyses (the RMS error is smaller by a factor of 2). The model changes in ECMWF-IFS were not clearly reflected in the PWV error over the period of study . Radiosonde humidity biases are diagnosed compared to GPS PWV. The impacts of these biases are evidenced in all three model analyses at the level of the diurnal cycle. The results point to a dry bias in the ECMWF analysis in 2006 when Vaisala RS80-A soundings were assimilated, and a diurnally varying bias when Vaisala RS92 or Modem M2K2 soundings were assimilated: dry during day and wet during night. The overall bias is offset to wetter values in NCEP-NCAR reanalysis II, but the diurnal variation of the bias is observed too. Radiosonde bias correction is necessary to reduce NWP model analysis humidity biases and improve precipitation forecast skill. The study points to a wet bias in the Vaisala RS92 data at nighttime and suggests that caution be used when establishing a bias correction scheme.