The relationship between radar reflectivity (Z) and rainfall intensity (R) plays a crucial role in estimating precipitation and serves as a foundation for flood risk assessment. However, empirical Z–R relationships often introduce considerable uncertainty, making the correction of rainfall estimation errors a key challenge in remote-sensing-based applications. Developing an effective approach to reduce these deviations is, therefore, essential to improve the accuracy of radar-based precipitation measurements. This study aims to develop a methodology for analyzing radar-derived precipitation using dual-polarization radar measurements, with validation based on rain gauge observations. Three well-established Z–R relationships—Marshall–Palmer, Muchnik, and Joss—were applied to radar reflectivity values measured at two heights, 1 km and 1.5 km above ground level. The Marshall–Palmer relationship applied at a height of 1.5 km yielded the smallest deviations from rain gauge measurements. Both the mean absolute error (MAE) and average precipitation difference at this height were consistent, amounting to 1.99 mm, compared to 2.32 mm at 1 km. The range of deviations in all cases was 0.54–7.64 mm at 1.5 km and 0.65–7.18 mm at 1 km. Furthermore, all tested Z–R relationships demonstrated a strong linear correlation with rain gauge data, as indicated by a Pearson correlation coefficient of 0.98. These findings enable the identification of the most accurate Z–R relationships and optimal measurement heights for radar-based precipitation estimation. These results may have important implications for operational applications and the calibration of radar precipitation products.

This study uses dual-polarization radar data from two weather radars to assess the accuracy of estimating rainfall rate ( R ) from radar reflectivity ( Z ) using classical empirical Z–R relationships (Marshall–Palmer, Wexler, and Doumoulin–Cogombles). Three additional polarimetric relationships incorporating differential reflectivity (ZDR) were also analyzed. Calculations were carried out for seven altitude levels, representing a novel approach to verifying the vertical structure of the precipitation field. Radar data were validated against measurements from a rain gauge network, enabling an assessment of spatiotemporal consistency and rainfall estimation errors. The analysis covers measurements collected during the flood event that occurred in Poland in September 2024 (Genoa low-pressure system). The results indicate that for the analyzed extreme flood event, the most reliable precipitation totals were obtained using the polarimetric relationship based on ZDR (RMSE=2.20 mm±0.90 mm, MAE=1.84 mm±0.73 mm, and Bias=-0.67 mm±0.81 mm). It was demonstrated that under the studied extreme conditions, the proposed ZDR3 relationship exhibits approximately 69% lower Bias compared with the standard operational Marshall-Palmer method. The findings confirm the potential of polarimetric methods for rainfall estimation and their applicability in operational settings during similar extreme weather events, particularly in early warning and crisis management systems.

The paper presents the results of a preliminary study of cloudiness area with hail precipitationbased on data from a dual-polarisation electromagnetic wave radar operating in Rzeszów-Jasionkawhich is one of eight meteorological radars belonging to the POLRAD managed by the Institute ofMeteorology and Water Management – National Research Institute. Atmospheric dual-polarisationwave scanning provides a significant radar data that accurately describes detected meteorologicalobjects, including the sizes of cloud and precipitation particles. The conducted research enabled usa qualitative and quantitative description of cloudy zones with precipitation of variable intensity andvariable spatial and temporal distribution. Obtaining data on the structure of the cloud cover zonerequires the creation of new and non-standard imagery showing horizontal and vertical distributionsof radar reflectivity determined on the basis of measurements in the classic radar channel. Radar datawere processed using RAINBOW DART and RAPOK software. Completely new rainfall datasetswere generated for the selected region with consistency of location and observation date, in whichprecipitation intensity, phase state, and environmental factors were taken into account. Developedvertical cross-sections of the atmosphere along the set route provided information on the structureand activity of the studied storm cell and the precipitation core present. Precipitation intensity wasdetermined from the Marshall‒Palmer, Joss and Muchnik correlations, which used radar reflectivityat heights of 1 km, 1.5 km, and 2 km above the ground surface, taking into account the freezing level.The paper presents a comprehensive analysis of the hail situation based on synoptic data and imagesof hail intensity and hail probability. It was shown that, available in the meteorological data exchangenetwork, the standard images of precipitation intensity generated in each case based on the Marshall‒Palmer correlation for radar reflectivity at a height of 1 km above the ground surface may containerrors, which require changes in calculation algorithms to be minimised. At this stage of the research,other dependencies were used in the calculations, which took into account the type of precipitation.On the other hand, data on the structure of the studied storm cell allowed us calculations based on thevalues of radar reflectivity determined at different levels in the rain core. The analysis of the obtainedradar precipitation data was carried out on the basis of both syn-optic and climatic data for the studiedregion. In the next stage of research, the results of field meas-urements carried out in regions with anextensive network of direct precipitation measurements will be used. The results of these studies willallow us to recommend empirical relationships for determining precipitation intensity dependingon the type of precipitation, the structure of the precipitation cloud and environmental conditions.Keywords: civil engineering, geodesy and transport, remote sensing of the atmosphere, dual polarisationradar, radar reflectivity, rainfall intensity, hail