ALBERT

Description: 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 results across hazard types most relevant for Europe.

Description: There are a large number of geophysical processes affecting sea level dynamics and coastal erosion in the Baltic Sea region. These processes operate on a large range of spatial and temporal scales and are observed in many other coastal regions worldwide. This, along with the outstanding number of long data records, makes the Baltic Sea a unique laboratory for advancing our knowledge on interactions between processes steering sea level and erosion in a climate change context. Processes contributing to sea level dynamics and coastal erosion in the Baltic Sea include the still ongoing viscoelastic response of the Earth to the last deglaciation, contributions from global and North Atlantic mean sea level changes, or contributions from wind waves affecting erosion and sediment transport along the subsiding southern Baltic Sea coast. Other examples are storm surges, seiches, or meteotsunamis which primarily contribute to sea level extremes. Such processes have undergone considerable variation and change in the past. For example, over approximately the past 50 years, the Baltic absolute (geocentric) mean sea level has risen at a rate slightly larger than the global average. In the northern parts of the Baltic Sea, due to vertical land movements, relative mean sea level has decreased. Sea level extremes are strongly linked to variability and changes in large-scale atmospheric circulation. The patterns and mechanisms contributing to erosion and accretion strongly depend on hydrodynamic conditions and their variability. For large parts of the sedimentary shores of the Baltic Sea, the wave climate and the angle at which the waves approach the nearshore region are the dominant factors, and coastline changes are highly sensitive to even small variations in these driving forces. Consequently, processes contributing to Baltic sea level dynamics and coastline change are expected to vary and to change in the future, leaving their imprint on future Baltic sea level and coastline change and variability. Because of the large number of contributing processes, their relevance for understanding global figures, and the outstanding data availability, global sea level research and research on coastline changes may greatly benefit from research undertaken in the Baltic Sea.

Description: Extratropical storms are one of the major coastal hazards in the North Sea region and a substantial driver of coastal protection efforts. Skillful seasonal and decadal predictions of storm activity on a regional scale are still a challenging task, even with today’s state-of-the-art modeling capabilities. While recent studies have shown that predictions of high storm activity with large-ensemble models can be skillful for averaging periods of five years or more, the predictive skill for shorter lead times, such as the next winter, is still low and does not consistently outperform simple statistical prediction methods. In our study, we demonstrate how physical connection-based ensemble refinement can increase the prediction skill of a large-ensemble decadal prediction system based on the Max-Planck-Institute Earth System Model (MPI-ESM) for German Bight winter storm activity on seasonal-to-sub-decadal time scales. We identify physical atmospheric and oceanic predictors of German Bight winter storm activity from near-surface station observations and the ERA5 reanalysis. We then use these predictors to create first-guess predictions of winter storm activity and refine our model ensemble by discarding ensemble members that strongly disagree with the first-guess prediction. With this technique, we are able to significantly increase the prediction skill for winter storm activity at lead times of one to three years.