We developed an automated workflow to detect rain-on-snow events, which cause flooding in the northeastern United States, in climate data. Analyzing the Susquehanna River basin, this technique identified known events affecting river flow. Comparing four gridded datasets revealed variations in event frequency and severity, driven by different snowmelt and runoff estimates. This highlights the need for accurate climate data in flood management and risk prediction for these compound extremes.

A framework combining a fire severity classification with a regression model to predict an indicator of fire severity derived from Landsat imagery (difference normalized burning ratio, dNBR) is proposed. The results show that the proposed predictive technique is capable of providing robust fire severity prediction information, which can be used for forecasting seasonal fire severity and, subsequently, impacts on biodiversity and ecosystems under projected future climate conditions.

The initiation of debris flows is significantly influenced by rainfall-induced hydrological processes. We propose a novel framework based on an integrated hydrological and hydrodynamic model and aimed at estimating intensity–duration (ID) rainfall thresholds responsible for triggering debris flows. In comparison to traditional statistical approaches, this physically based framework is particularly suitable for application in ungauged catchments where historical debris flow data are scarce.

Glide-snow avalanches release at the ground–snow interface, and their release process is poorly understood. To investigate the influence of spatial variability (snowpack and basal friction) on avalanche release, we developed a 3D, mechanical, threshold-based model that reproduces an observed release area distribution. A sensitivity analysis showed that the distribution was mostly influenced by the basal friction uniformity, while the variations in snowpack properties had little influence.

This study identifies a prehistoric earthquake around 4400 years ago near the city of Coyhaique (Aysén Region, Chilean Patagonia) and illustrates the potential seismic hazard in the region. We found deposits in lakes and a fjord that can be related to subaquatic and onshore landslides, all with a similar age, indicating that they were most likely caused by an earthquake. Through modeling we found that this was an earthquake of magnitude 6.3 to 7.0 on a fault near the city of Coyhaique.

This paper shows the first public and systematic dataset of flood episodes referring to the entire Pyrenees massif, at municipal scale, named PIRAGUA_flood. Of the 181 flood events (1981–2015) that produced 154 fatalities, 36 were transnational, with the eastern part of the massif most affected. Dominant weather types show a southern component flow, with a talweg on the Iberian Peninsula and a depression in the vicinity. A positive and significant trend was found in Nouvelle-Aquitaine.

European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological loss index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high-impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.

We present a catalogue of tsunamis that occurred in the Vanuatu Arc. It has been built based on the analysis of existing catalogues, historical documents, and sea-level data from five coastal tide gauges. Since 1863, 100 tsunamis of local, regional, or far-field origins have been listed; 15 of them show maximum wave amplitudes and/or run-up heights of above 1 m, and 8 are between 0.3 and 1 m. Details are provided for particular events, including debated events or events with no known origin(s).