In radar meteorology, greater interest is dedicated to weather radars and precipitation analyses. However, cloud radars provide us with detailed information on cloud particles from which the precipitation consists of. Motivated by research on the cloud particles, a vertical Ka-band cloud radar (35 GHz) was installed at the Milešovka observatory in Central Europe and was operationally measuring since June 2018. This study presents algorithms that we use to retrieve vertical air velocity (Vair) and hydrometeors. The algorithm calculating Vair is based on small-particle tracers, which considers the terminal velocity of small particles negligible and, thereby, Vair corresponds to the velocity of the small particles. The algorithm classifying hydrometeors consists of calculating the terminal velocity of hydrometeors and the vertical temperature profile. It identifies six hydrometeor types (cloud droplets, ice, and four precipitating particles: rain, graupel, snow, and hail) based on the calculated terminal velocity of hydrometeors, temperature, Vair, and Linear Depolarization Ratio. The results of both the Vair and the distribution of hydrometeors were found to be realistic for a thunderstorm associated with significant lightning activity on 1 June 2018.

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The distribution of hydrometeors in thunderstorms is still under investigation as well as the process of electrification in thunderclouds leading to lightning discharges. One indicator of cloud electrification might be high values of the Linear Depolarization Ratio (LDR) at higher vertical levels. This study focuses on LDR values derived from vertically pointing cloud radars and the distribution of five hydrometeor species during 38 days with thunderstorms which occurred in 2018 and 2019 in Central Europe, close to our radar site. The study shows improved algorithms for de-aliasing, the derivation of vertical air velocity and the classification of hydrometeors in clouds using radar data. The comparison of vertical profiles with observed lightning discharges in the vicinity of the radar site (≤1 km) suggested that cloud radar data can indirectly identify “lightning” areas by high LDR values observed at higher gates due to the alignment of ice crystals, likely because of an intensified electric field in thunderclouds. Simultaneously, the results indicated that at higher gates, there is a mixture of several hydrometeor species, which suggests a well-known electrification process by collisions of hydrometeors.

The seasonal distribution of mean precipitation and heavy rainfalls during 1960–2013 was analysed based on daily precipitation totals from 168 rain gauging stations in the Vosges Mountains area, north‐eastern France. Concerning mean precipitation, an ancient Hrudička's index designed as a half‐time of precipitation during a year, surprisingly well expresses the seasonality of precipitation and its clear correlation with the mean annual totals in the studied region. The annual course of mean precipitation leads to a distinction of four groups of stations with respect to the position of stations: MT, mountainous stations with maxima of precipitation in winter and an overall highest mean annual totals; LSp, stations situated on leeward slopes of the Vosges Mountains with two maxima of precipitation (primary in winter and secondary in summer); URP, leeward stations located in the Upper Rhine River Plain with the most humid summer season, and the lowest mean annual totals; WSd, windward stations not influenced by the Vosges Mountains, with relatively evenly distributed precipitation, and slight maxima in autumn. For the heavy precipitation, 1–10‐days totals have been considered to be ‘heavy’ subsequent to applying the three common methods – peaks over threshold (POT), block maxima (BM), and return period estimates based on generalized extreme value distribution. Varying criteria have been employed. The BM method for annual maxima indicates that the heavy rainfall generally occurs during the most humid season although it can also occur anytime during the year. The POT and return period estimates methods reveal that the seasonality of extremes is threshold‐dependent and that probably the threshold sensitivity is also related to the degree of orographic influence – higher occurrence of summer events in the lee while lesser occurrence of winter events in mountains, at higher threshold and shorter duration of event.