In recent years, the western Baltic Sea has experienced severe storm surges. By analysing the individual contributions and the total water level, these events can be put into a climate perspective. It was found that individual contributions were not exceptional in all events, and no clear trend can be identified. Often the combination of the individual contributions leads to the extreme events of recent years. This points to the importance of analysing composite events.

This study evaluates 12 sets of drought policy and planning guidelines for their alignment with the four priority areas of the SENDAI framework. The guidelines do not align very well with the contemporary disaster risk reduction agenda. The study highlights strengths, weaknesses, opportunities, and threats and provides useful insights to develop the next generation of drought guidelines that are better aligned with contemporary science–policy–practice agendas.

Tree fall events have an impact on forests and transport systems. Our study explored tree fall in relation to wind and other weather conditions. We used tree fall data along railway lines and ERA5 and radar meteorological data to build a logistic regression model. We found that high and prolonged wind speeds, wet conditions, and high air density increase tree fall risk. These factors might change in the changing climate, which in return will change risks for trees, forests and transport.

Fragile geologic features test long-term seismic hazard models. We modeled a free-standing 42 m high rock pillar in Israel’s Negev Desert using a validated finite-element model based on aerial lidar, in situ rock data, and measured vibrations. Dynamic analysis shows an M 7 quake on the Dead Sea Transform (45 km) will not break it, but an M 6 quake on the Sinai–Negev Shear Zone (6–20 km) probably will. With a fragility age of 11.4 kyr, the pillar challenges the SNSZ’s (Sinai–Negev Shear Zone) ability to produce M 6 events.

Our study investigates the initiation of snow slab avalanches. Combining experimental data with numerical simulations, we show that on gentle slopes, cracks form and propagate due to compressive fractures within a weak layer. On steeper slopes, crack velocity can increase dramatically after approximately 5 m due to a fracture mode transition from compression to shear. Understanding these dynamics provides a crucial missing piece in the puzzle of dry-snow slab avalanche formation.

The authors performed verification on the relationships between extreme monsoon rainfall over Japan and Pacific sea surface temperature variability in the “database for Policy Decision-making for Future climate changes” (d4PDF). Observations showed widespread weak relationships between hourly extremes and the warming mode but reversed relationships between daily extremes and the decadal variability mode. Biases in d4PDF could be explained by the monsoon's slower movement over Japan in the model.

Offshore wind turbines are sensitive to tropical cyclones (TCs). Wind data from super typhoons Mangkhut and Saola, impacting south China, are vital for design and operation. Despite Saola's higher intensity, it caused less damage. Both had concentric eyewall structures, but Saola completed an eyewall replacement before landfall, becoming more compact. Mangkhut decayed but affected a wider area. Their wind characteristics provide insights for turbine maintenance and operation.

This study addresses the challenge of accurately predicting floods in regions with limited terrain data. By utilising a deep learning model, we developed a method that improves the resolution of digital elevation data by fusing low-resolution elevation data with high-resolution satellite imagery. This approach not only substantially enhances flood prediction accuracy, but also holds potential for broader applications in simulating natural hazards that require terrain information.

Global flood models are key to the mitigation of coastal flooding impacts, yet they still have limitations when providing actionable insights locally. We present a multiscale framework that couples dynamic water level and flood models and bridges the fully global and local modelling approaches. We apply it to three historical storms. Our findings reveal that the importance of model refinements varies based on the study area characteristics and the storm’s nature.

On 11 July 2024, Stromboli erupted violently, generating a volcanic ash column and pyroclastic flows along the Sciara del Fuoco. The event was preceded by intense explosions, lava flows and crater rim collapses. A multiparameter analysis using seismo-acoustic and drone data was conducted to reconstruct the eruption's key features. This was done to estimate material loss and to document summit morphology changes, aiming to improve the understanding of eruption processes and to enhance forecasting and risk management.