Cb-Fusion – forecasting thunderstorm cells up to 6 hours

As a severe weather phenomenon, thunderstorms can cause casualties and economic loss to the human society. A reliable forecast of these weather events would help to avoid or at least mitigate this damage. To date, the forecasting of thunderstorms however is still a challenge, especially for lead times of one hour and beyond. In this study we present a methodology to forecast deep-convection for several hours lead time: Cb-Fusion estimates the likelihood of thunderstorm occurrence for up to 6 hours in advance over a part of Central Europe, using a data fusion technique that blends data of multiple sources from observations, nowcasts, and numerical weather predictions with a high update rate. The Cb-Fusion is set up to operate in near real time. The skill of Cb-Fusion is evaluated based on 1743 hours of thunderstorm observations collected during the months April to October, 2019. Three categories of thunderstorm size have been distinguished: ‘large’ for a coverage area larger than 5000 km2, ‘medium’ for a coverage area between 5000 km2 and 500 km2, and ‘small’ for a coverage area smaller than 500 km2. Compared to thunderstorm forecasts from numerical models alone, the combination of data from various sources by Cb-Fusion results in a significantly better forecast skill. The study reveals that the forecast is reliable for up to 3 hours lead time for ‘medium’ and ‘large’ scale thunderstorms (median POD of 0.6 – 0.9) but little skill is found for ‘small’ scale thunderstorms and lead times between 3 and 6 hours (median POD of 0.05). It is argued that Cb-Fusion provides meaningful improvements in forecasting thunderstorms for various users.