Weather radar adjustment with commercial microwave links: Experiences from the HoWa-PRO project at Deutscher Wetterdienst
Maximilian Graf1, Malte Wenzel1, Matthias Gottschalk1, Julius Polz2, Christian Chwala2, and Tanja Winterrath1
1Deutscher Wetterdienst (DWD), Offenbach, Germany
2 Institute of Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU), Campus Alpin, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
Commercial microwave links (CMLs) provide valuable rainfall estimates for weather radar adjustment, offering real-time data, extensive coverage, and path-averaged measurements closer to the radar’s areal data. However, challenges include real-time acquisition, consistent processing, and merging path-averaged CML data with gridded radar data. In the HoWa-PRO project, we developed pyRADMAN, a Python framework at Deutscher Wetterdienst (DWD) that integrates CML, radar, and rain gauge data in real time. This talk will present recent results, challenges, and the potential future of CMLs at DWD.
Presentation slides:
Current status of the CML project of Météo-France
Dominique Faure1, Olivier Laurantin2, Pierre Lepetit2, Pauline Mialhe2, and Laurent Brunier2
1Centre of Radar Meteorology, Météo-France, Toulouse, France
2 Prospective and Composite Products, Météo-France, Toulouse, France
The presentation will summarise the present status of the CML project of Météo-France, the main lessons learned for the operational use of CML, and present the most recent results concerning the merging of CML rainfall estimates with radar estimation and rain gauges measurements in order to improve the best Quantitative Precipitation Estimation of Météo-France. Two approaches were used: a classic CML data processing, and a Machine Learning approach. Some numerical results will be presented (the work is still ongoing), as well as a few elements concerning the prospects for future operational use.
