Institute of Meteorology and Climate Research

Two new papers

Merz, B., Kuhlicke, C., Kunz, M., Pittore, M., Babeyko, A., Bresch, D. N., Domeisen, D. I., Feser, F., Koszalka, I., Kreibich, H., Pantillon F., Parolai S., Pinto J. G., Punge H. J., Rivalta E., Schröter K., Strehlow K., Weisse R., Wurpts A. (2020): Impact forecasting to support emergency management of natural hazards. Rev. Geophys., e2020RG000704, doi:10.1029/2020RG000704.


Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While early warning systems are frequently used to predict the magnitude, location and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services or financial loss. Complementing early warning systems with impact forecasts has a two‐fold advantage: it would provide decision makers with richer information to take informed decisions about emergency measures, and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multi‐hazard early warning systems. This review discusses the state‐of‐the‐art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review.


Nisi, L., Hering, A., Germann, U., Schroeer, K., Barras, H., Kunz, M., Martius, O. (2020): Hailstorms in the Alpine region: diurnal cycle, 4D‐characteristics, and the nowcasting potential of lightning properties. Q. J. R. Meteorol. Soc., doi:10.1002/qj.3897.


Nowcasting of hailstorms still poses a major challenge to weather services, because of to the limited availability of reliable large data sets and the short spatio‐temporal scales involved. Two novel Eulerian and Lagrangian hail climatologies for the Alps are applied to address important aspects of hailstorms in the Alps: the diurnal cycle, their spatio‐temporal development and the lightning properties. The database contains more than 100’000 ordinary‐ and 30’000 hailstorms (2002‐2017). Based on that large sample of storms, the diurnal cycle of storm initiation and evolution is studied in the context of orographic forcing and cold front occurrence statistics. Results show that during daytime storms mainly initiate over the foothills (Prealps) and move towards areas with higher terrain elevations. During nighttime, the storms preferably move from the foothills to the plains. Five out of 16 years of the radar‐derived convective storms show a significant yearly positive hail anomaly, from which two years show relative hail‐initiation maxima evenly distributed over the 24 hours without a characteristic diurnal cycle. Relative hail maxima during nighttime cannot always be explained with a higher occurrence of cold fronts.

Time series of storm vertical integrated liquid water content are used to separate between ordinary and hailstorm development. Differences are found between vertical integrated liquid and its density in cold airmass storms. Finally, lightning data from a ground‐based network are combined with the radar‐derived hailstreaks and evaluated with respect to their prediction skill as a function of lead time (flash rate, density, peak current; lightning‐jumps). Results show that lightning data provide only modest skill‐scores in nowcasting hailstorms. Only the sudden increase in lightning rate (referred to as lightning‐jump) may be used as additional data for hailstorm nowcasting. However, their application in automatic nowcasting systems remains challenging as the lightning jumps occurs at various lead times in the series.