Convective cells algorithm for storm data tracking / Piotr Szuster, Joanna Kołodziej // W: ECMS 2023 : proceedings of the 37th ECMS International Conference on Modelling and Simulation, June 20th – ... więcej

Convective cells algorithm for storm data tracking / Piotr Szuster, Joanna Kołodziej // W: ECMS 2023 : proceedings of the 37th ECMS International Conference on Modelling and Simulation, June 20th – June 23rd, 2023 Florence, Italy [Dokument elektroniczny] / ed. by Enrico Vicario [et al.] ; org. by ECMS - European Council for Modelling and Simulation. – Caserta : ECMS, 2023. – (European Conference for Modelling and Simulation, ISSN 2522-2422 ; Vol. 37, Iss. 1). – S. 535-541 : il. (w tym kolor.). – Tryb dostępu: https://www.scs-europe.net/conf/ecms2023/ecms2023proceedings.pdf. – Bibliogr. 14 poz., Abstr. – Wydaw. wg cop. – Miejsce wyd. wg siedziby wydaw. – ISBN 978-3-937436-80-7 (Print). – ISBN 978-3-937436-79-1 (CD-ROM)

Atmospheric conditions, such as thunderstorms, are significant factors that influence human activity. Harsh weather may severely impact both daily life and pro- fessional activities. Severe thunderstorms ... więcej

Atmospheric conditions, such as thunderstorms, are significant factors that influence human activity. Harsh weather may severely impact both daily life and pro- fessional activities. Severe thunderstorms are a con- siderable hazard – they can generate heavy rainfall, high winds, large hail and tornadoes. Tracking of thun- derstorms is necessary to gain situational awareness - knowledge of present and future storm-related threats and their corresponding significances. Thunderstorms are weather phenomena associated with cumulonimbus clouds. Those clouds are formed in deep, moist con- vection and are composed of liquid and solid water particles. Weather radars can detect those particles. Cumulonimbus-related particle concentration areas are represented in weather radar data as convective cells, making that measurement technique useful for storm- tracking applications. This paper proposes a new algo- rithm for storm data tracking in the data fusion pro- cess. The algorithm has been tested with real data from the POLRAD weather radar network and upper-air ob- servations. The efficiency of the proposed algorithm has been justified in the empirical analysis. The algorithm projections can help generate weather warnings due to accurate forecasts of storm movement.