The first Special Observation Period of theHyMeXcampaign took place during autumn 2012. A specific observational network was set up in the south of France with the aim of better understanding the role and impact of complex terrain on the horizontal and vertical structure of rainfall and the associated microphysical processes. The event, referred to asIOP7a, which occurred on 26 September 2012, is studied in this article. A first analysis, based on two reference parameters of the drop‐size distribution (DSD), shows that the topography of the region has an impact on the rainfall structure at the fine scale and that rainfall intensity also has an influence on theDSDparameters. A more detailed study, based on the evolution of the shape of theDSDand of the liquid water content (LWC) within different rainfall intensities, reveals that the coalescence mechanism is of significant importance for different rainfall regimes and for different topographic areas. As we get closer to the ground, the modification of theDSDshows that other microphysical and dynamical processes (such as evaporation, break‐up, turbulence in the presence of vertical wind) might compete with the coalescence mechanism or enhance it. The respective strengths of these processes depend on the local environment; coalescence seems enhanced by a layer with higherLWCas the local terrain becomes more complex, and evaporation appears more important above flatter terrain. Thus, both the orography and the rainfall intensity can impact the rainfall structure and the associated microphysical and dynamical processes.

The “Marion Dufresne Atmospheric Program-Indian Ocean” (MAP-IO) project is a research program that aims to collect long-term atmospheric observations in the under-instrumented Indian and Austral Oceans. As part of this project, a Global Navigation Satellite System (GNSS) antenna was installed on the research vessel (R/V) Marion Dufresne in October 2020. GNSS raw data is intended to be used to retrieve Integrated Water Vapour (IWV) content along the Marion Dufresne route, which cruises more than 300 days per year in the tropical and austral Indian Ocean. This paper presents a first assessment of this GNSS-based IWV retrieval, based on the analysis of 9 months of GNSS raw data acquired along the route of the R/V Marion Dufresne in the Indian Ocean. A first investigation of GNSS raw data collected during the first 5 months of operation has highlighted the bad positioning of the antenna on the R/V that makes it prone to interference. Changing the location of the antenna has been shown to improve the quality of the raw data. Then, ship-borne GNSS-IWV are compared with IWV estimates deduced using more conventional techniques such as European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), ground-launched radiosondes and permanent ground GNSS stations operating close to the route of the R/V Marion Dufresne. The rms difference of 2.79 kg m${}^{-2}$ shows a good match with ERA5 and subsequently improved after the change in location of the GNSS antenna (2.49 kg m${}^{-2}$). The match with ground-based permanent GNSS stations fluctuates between 1.30 and 3.63 kg m${}^{-2}$, which is also shown to be improved after the change in location of the GNSS antenna. However, differences with ground-launched radiosondes still exhibit large biases (larger than 2 kg m${}^{-2}$). Finally, two operational daily routine analyses (at day+1 and day+3) are presented and assessed: the rms of the differences are shown to be quite low (1 kg m${}^{-2}$ for the day+1 analyses, 0.7 kg m${}^{-2}$ for the day+3 analysis), which confirms the quality of these routine analysis. These two routine analyses are intended to provide a continuous monitoring of water vapour above the Indian Ocean and deliver ship-borne IWV with a low latency for the entire scientific community.

We present an analysis of decadal in situ and remote sensing observations of water vapor over the Cézeaux and puy de Dôme, located in central France (45° N, 3° E), in order to document the variability, cycles and trends of surface and tropospheric water vapor at different time scales and the geophysical processes responsible for the water vapor distributions. We use meteorological stations, GPS (Global Positioning System), and lidar datasets, supplemented with three remote sources of water vapor (COSMIC-radio-occultation, ERA-interim-ECMWF numerical model, and AIRS-satellite). The annual cycle of water vapor is clearly established for the two sites of different altitudes and for all types of measurement. Cezeaux and puy de Dôme present almost no diurnal cycle, suggesting that the variability of surface water vapor at this site is more influenced by a sporadic meteorological system than by regular diurnal variations. The lidar dataset shows a greater monthly variability of the vertical distribution than the COSMIC and AIRS satellite products. The Cézeaux site presents a positive trend for the GPS water vapor total column (0.42 ± 0.45 g·kg⁻¹/decade during 2006–2017) and a significant negative trend for the surface water vapor mixing ratio (−0.16 ± 0.09 mm/decade during 2002–2017). The multi-linear regression analysis shows that continental forcings (East Atlantic Pattern and East Atlantic-West Russia Pattern) have a greater influence than oceanic forcing (North Atlantic Oscillation) on the water vapor variations.

This paper describes an innovative project which has just been launched at the "Laboratoire de Météorologie Physique" (LaMP) in Clermont-Ferrand in collaboration with the "Meteorologische Institut" in Hamburg, where a low cost X-band high resolution precipitation radar is combined with supporting measurements and a bin microphysical cloud resolving model in order to develop adapted Z–R relationships for accurate rain rate estimates over a local area such as a small catchment basin, an urban complex or even an agriculture domain. In particular, the use of K-band micro rain radars which can retrieve vertical profiles of drop size distribution and the associated reflectivity will be used to perform direct comparisons with X-band radar volume samples while a network of rain-gauges provides ground truth to which our rain estimates will be compared. Thus, the experimental suite of instrumentation should provide a detailed characterization of the various rain regimes and their associated Z–R relationship. Furthermore, we will make use of the hilly environment of the radar to test the use of novel attenuation methods in order to estimate rainfall rates. A second important aspect of this work is to use the detailed cloud modeling available at LaMP. Simulations of precipitating clouds in highly resolved 3-D dynamics model allow predicting the spectra of rain drops and precipitating ice particles. Radar reflectivity determined from these model studies will be compared with the observations in order to better understand which raindrop size spectrum shape factor should be applied to the radar algorithms as a function of the type of precipitating cloud. Likewise, these comparisons between the modeled and the observed reflectivity will also give us the opportunity to further improve our model microphysics and the parameterizations for meso-scale models.