Characterisation and predictability of a strong and a weak forcing severe convective event – a multi-data approach

Two severe summer-time convective events in Germany are investigated which can classified by the prevailing synoptic conditions into a strong and a weak case. The strong forcing case exhibits a larger scale precipitation caused by frontal ascent whereas scattered convection is dominating convective activity in the weak forcing case. Other distinguished between the cases are faster movement of convective cells and regions with significant loss mainly due to severe gusts in the strong case. A comprehensive set of various observations is used to the two different events. The observations include measurements a lightning detection network, precipitation radar, geostationary and weather stations, as well as information from an automated cell algorithm based on radar reflectivity which is combined with severe reports, and damage data from insurances. Forecast performance at time scales is analysed ranging from nowcasting and warning to short- forecasting. Various methods and models are examined, including human, observation-based nowcasting algorithms and high-resolution ensemble systems. The analysis shows the advantages of a multi-sensor and-source approach in characterising convective events and their impacts. data from various sources allows to combine the different strengths of data sets, especially in terms of spatial coverage or data, e.g. damage data from insurances provide good spatial coverage with meteorological information while measurements at weather stations accurate but pointwise observations. Furthermore, using data from sources allow for a better understanding of the convective life. Several parameters from different instruments are shown to have a skill for convective development, these include satellite-based-top cooling rates as measure for intensive convective growth, 3D-radar, mesocyclone detection from doppler radar, overshooting top or lightning jumps to evaluate storm intensification and formation severe weather. This synergetic approach can help to improve nowcasting and thus the warning process. The predictability of the analysed convective events differs with different types of forcing which is in both, convective-scale ensemble prediction system forecasts and weather warnings. Human warnings show larger false alarm rates in the forcing case. Ensemble predictions are able to capture the of the convective precipitation. The forecast skill is strongly to the synoptic situation and the presence of large-scale increases the forecast skill. This has to be considered for potential warn-on-forecast strategies.