Radar-based rainfall information has been widely used in hydrological and meteorological applications, as it provides data with a high spatial and temporal resolution that improve rainfall representation. However, the broad diversity of studies makes it difficult to gather a condensed overview of the usefulness and limitations of radar technology and its application in particular situations. In this paper, a comprehensive review through a categorization of radar-related topics aims to provide a general picture of the current state of radar research. First, the importance and impact of the high temporal resolution of weather radar is discussed, followed by the description of quantitative precipitation estimation strategies. Afterwards, the use of radar data in rainfall nowcasting as well as its role in preparation of initial conditions for numerical weather predictions by assimilation is reviewed. Furthermore, the value of radar data in rainfall-runoff models with a focus on flash flood forecasting is documented. Finally, based on this review, conclusions of the most relevant challenges that need to be addressed and recommendations for further research are presented. This review paper supports the exploitation of radar data in its full capacity by providing key insights regarding the possibilities of including radar data in hydrological and meteorological applications.

Two long-lasting thunderstorm ground enhancement (TGE) events were registered at the Milešovka meteorological observatory in Czechia (50.55^∘ N, 13.93^∘ E; 837 m altitude) on 23 April 2018, during linearly organized thunderstorms. Two intervals of increased photon counts were detected by a plastic scintillator, respectively lasting 70 and 25 min and reaching 31 % and 48 % above the background radiation levels. Using numerical simulations, we verified that the observed increases in count rates are consistent with the energy spectrum of previously observed TGEs. We investigated the relevant data from a suite of meteorological instruments, a Ka-band cloud radar, an electric field mill, and a broadband electromagnetic receiver, all placed at the Milešovka observatory, in order to analyse the context in which these unique continental TGEs occurred at an exceptionally low altitude. The onset of the TGEs preceded the onset of precipitation by 10 and 3 min, respectively, for the two events. Both this delayed rain arrival and an energy threshold of 6.5 MeV for registered particles clearly exclude the detection the decay products of the radon progeny washout during the TGE intervals. At the same time, the European lightning detection network EUCLID detected numerous predominantly negative intracloud lightning discharges at distances closer than 5 km from the particle detector, while the occurrence of cloud-to-ground discharges was suppressed. The cloud radar recorded presence of graupel below the melting level, and the composition of hydrometeors suggested good conditions for cloud electrification. The observed variations in the near-surface electric field were unusual, with very brief negative-electric-field excursions reaching −20 kV in a quick succession. At the same time, sub-microsecond unipolar pulses emitted by close corona discharges saturated the broadband magnetic loop antenna. All these measurements indicate that a strong lower positive-charge region was present inside the thundercloud. The bottom thundercloud dipole was probably responsible for acceleration of the seed electrons in the air. These seed electrons might originate in the secondary cosmic ray particles but could also come from a high concentration of radon in the air collected during the propagation of the convective system above the uranium-rich soils before the thunderstorms overpassed the Milešovka observatory.

We analyzed two convective storms that passed over or near the Milešovka meteorological observatory. The observatory is located at the top of a hill and has been recently equipped with a Doppler polarimetric X-band radar FURUNO WR2120 for cloud investigations. Our analysis was based mainly on Doppler polarimetric radar data measured in vertical cross-sections (RHI-Range-Height Indicator). Radar data was also used for classifying hydrometeors by a newly developed XCLASS (X-band radar CLASSification) algorithm. We also used rapid scan data measured by the geostationary satellite Meteosat Second Generation to validate radar measurements at the upper parts of storms. Although an attenuation correction was applied to the reflectivity and differential reflectivity measurements, the attenuation typical of X-band radars was noticeable. It was mainly manifested in the differential reflectivity, co-polar correlation coefficient and specific differential phase. Nevertheless, radar measurements can be used to analyze the internal cloud structure of severe convective storms. The XCLASS classification was developed by major innovation of a previously published algorithm. The XCLASS algorithm identifies seven types of hydrometeors: light rain, rain, wet snow, dry snow, ice, graupel, and hail. It uses measured horizontal and vertical radar reflectivity, specific differential phase, co-polar correlation coefficient, and temperature, and applies fuzzy logic to determine the type of hydrometeor. The new algorithm practically eliminates unrealistic results around and below the melting layer provided by the original algorithm. It identifies wet snow in more cases, and areas with individual hydrometeors have more realistic shapes compared to the original algorithm. The XCLASS algorithm shows reasonable results for the classification of hydrometeors and can be used to study the structure of convective storms.

We processed five years of measurements (2018–2022) of a vertically pointing radar MIRA 35c at the Milešovka meteorological observatory with the aim of analyzing the cloud structure of thunderstorms and comparing differences in measured data for cases when lightning discharges were observed very close to the radar position, and for cases when lightning discharges were observed at a greater distance from the radar position. The MIRA 35c radar is a Doppler polarimetric radar working at 35 GHz (Ka-band) with a vertical resolution of 28.9 m and a time resolution of approximately 2 s. For the analysis, we considered radar data whose radar reflectivity was at least 10 dBZ at 5 km or higher above the radar to ensure that there was a cloud above the radar. We divided the radar data into “near” data (a lightning discharge was registered up to 1 km from the radar position) and “far” data (a lightning discharge was registered from 7.5 to 10 km from the radar position). We compared the following quantities: (i) Power in co-channel (pow), (ii) power in cross-channel (pow-cx), (iii) phase in co-channel (pha), (iv) phase in cross-channel (pha-cx), (v) equivalent radar reflectivity (Ze), (vi) Linear Depolarization Ratio (LDR), (vii) co-polar correlation coefficient (RHO), (viii) Doppler radial velocity (V), (ix) Doppler spectrum width (RMS), and (x) Differential phase (Phi). Pow, pow-cx, pha, pha-cx, and V are basic data measured by the radar, while Ze, LDR, RHO, RMS, and Phi are derived quantities. Our results showed that the characteristics of the compared radar quantities are clearly distinct for “near” dataset from “far” dataset. Furthermore, we found out that there is a clear evolution close to the time of discharges of the observed radar quantities in the “near” dataset, which is not that obvious in the “far” dataset.

Thunderstorms and especially induced lightning discharges have still not been fully understood, although they are known to cause many casualties yearly worldwide. This study aims at filling the gap of knowledge by investigating the potential of phase and power of the co- and cross-channels of a vertical cloud radar to indicate lightning close to the radar site. We performed statistical and correlation analyses of vertical profiles of phase and power spectra in the co- and the cross-channel for 38 days of thunderstorms producing lightning up to 20 km from the radar in 2018–2019. Specifically, we divided the dataset into “near” and “far” data according to the observed distance of lightning to the radar and analyzed it separately. Although the results are quite initial given the limited number of “near” data, they clearly showed different structures of “near” and “far” data, thus confirming the potential of radar data to indicate lightning. Moreover, for the first time in this study the predictability of lightning using cloud radar quantities was evaluated. We applied a Regression Tree Model to diagnose lightning and verified it using Receiver Operating Characteristic (ROC) and Critical Success Index (CSI). ROC provided surprisingly good results, while CSI was not that good but considering the very rare nature of lightning its values are high as well.

This study presents the first-ever detection of a winter continental gamma-ray glow in Central Europe, observed during a rare winter thunderstorm on Milešovka hill, Czechia. Unlike typical gamma-ray glow events, which are usually linked to significant electric field increases, this unique observation reveals that no substantial electric field change was recorded during the glow, challenging existing models of thunderstorm-related radiation. The event was captured using a combination of advanced instruments, including a Ka-band cloud profiler and a high-energy gamma-ray spectrometer, which enabled detailed analysis of the storm's microphysics. The radar data indicated the alignment of ice crystals within the cloud, strongly suggesting the presence of a substantial electric field, despite its weak measurement on the surface. This unexpected decoupling of electric field strength and gamma-ray glow generation opens new avenues for understanding the processes driving high-energy phenomena in thunderstorms. The findings offer valuable insights into winter thunderstorm dynamics in continental climates, with broader implications for the study of high-energy atmospheric physics.