The Operational Program on the Exchange of Weather Radar Information (OPERA) has co-ordinated radar co-operation among national weather services in Europe for more than 20 years. It has introduced its own, manufacturer-independent data model, runs its own data center, and produces Pan-European radar composites. The applications using this data vary from data assimilation to flood warnings and the monitoring of animal migration. It has used several approaches to provide a homogeneous combination of disparate raw data and to indicate the reliability of its products. In particular, if a pixel shows no precipitation, it is important to know if that pixel is dry or if the measurement was missing.

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.

In the past few years, demands on flash flood forecasting have grown. The Flash Flood Indicator (FFI) is a system used at the Czech Hydrometeorological Institute for the evaluation of the risk of possible occurrence of flash floods over the whole Czech Republic. The FFI calculation is based on the current soil saturation, the physical-geographical characteristics of every considered area, and radar-based quantitative precipitation estimates (QPEs) and forecasts (QPFs). For higher reliability of the flash flood risk assessment, calculations of QPEs and QPFs are crucial, particularly when very high intensities of rainfall are reached or expected. QPEs and QPFs entering the FFI computations are the products of the Czech Weather Radar Network. The QPF is based on the COTREC extrapolation method. The radar-rain gauge-combining method MERGE2 is used to improve radar-only QPEs and QPFs. It generates a combined radar-rain gauge QPE based on the kriging with an external drift algorithm, and, also, an adjustment coefficient applicable to radar-only QPEs and QPFs. The adjustment coefficient is applied in situations when corresponding rain gauge measurements are not yet available. A new adjustment coefficient scheme was developed and tested to improve the performance of adjusted radar QPEs and QPFs in the FFI.

The Czech weather radar network (CZRAD) is operated by the Czech Hydrometeorological Institute (national weather service of the Czech Republic). CZRAD data are used for severe weather and precipitation monitoring by national civil and military weather services, operational hydrology, air traffic control and many other users including general public. Several damaging floods, which hit the Czech Republic in last decade, emphasized importance of radar data for hydrological applications and accelerated research and development in the field of rainfall estimating and nowcasting. The development of the methods is performed in cooperation with the Institute of Atmospheric Physics (Czech Academy of Sciences) and US National Weather Service (US NWS). The paper presents the Czech weather radar network and operational implementations of radar based quantitative precipitation estimates (QPE) and forecast (QPF) methods. Status of the current development and future outlook is also discussed.

Radar measurements are one of the key data sources for detection and nowcasting of convective storms and accompanying severe phenomena. Radar algorithm estimating probability of hail occurrence was first implemented in the Czech Hydrometeorological Institute (CHMI) in 2004. Development of new radar products estimating probability of severe hail occurrence and their visualization has taken place in the CHMI in recent years. This article describes evaluation of radar products which, combined with temperature sounding measurements, determine probability of hail occurrence and provide estimates of maximum hail size. These products are operationally produced in CHMI and visualized in a new JSMeteoView2 application which serves as the main tool for visualization of radar data and other remote sensing data in combination with detailed geographical layers. The article discusses performance of radar hail products tested on a large set of data and their operational usability when estimating hail presence.