WeaMyL project aimed at enhancing the accuracy, performance and reliability of national nowcasting warning systems by the use of machine learning (ML) techniques applied on radar, satellite and weather stations' observations. The focus was on obtaining higher precision in predicting the occurrence and the areas affected by severe meteorological phenomena, as well as attaining lower decision times (compared to former, exclusively human decision times). The project's main goal was to automate the nowcasting warning systems by creating a ML driven platform for early and accurate forecast of severe phenomena. Thus, it was aimed to be the backbone of a new framework for imminent severe weather detection adapted to current technological possibilities.

WeaMyL involved a multidisciplinary consortium including the Babeș-Bolyai University (BBU) as a leading institution in Machine Learning, the Romanian National Meteorological Administration (NMA) as a Romanian leading team in research and operational meteorology and two teams from the Norwegian Meteorological Institute (MET) one having expertise in meteorological research and the other in machine learning and software development.

The WeaMyL project was funded by Norway Grants under the number RO-NO-2019-0133. Contract: No 26/2020.

The total budget of the project was approximately 1 Million euros.

Period of realization: from September 2020 to August 2023.