A two-way coupled hydrometeorological model (WRF-Hydro) is used for flood forecasting purposes in medium-catchment-size basins in Greece. The results showed the capability of WRF-Hydro to adequately simulate the observed discharge and the slight improvement in terms of quantitative precipitation forecasting compared to the WRF-only simulations.

Windstorms during the last 40 years in the US Northeast are identified and characterized using the spatial extent of extreme wind speeds at 100 m height from the ERA5 reanalysis. During all of the top 10 windstorms, wind speeds exceeding the local 99.9th percentile cover at least one-third of the land area in this high-population-density region. These 10 storms followed frequently observed cyclone tracks but have intensities 5–10 times the mean values for cyclones affecting this region.

In coastal regions, floods can arise through concurrent drivers, such as precipitation, river discharge, storm surge, and waves, which exacerbate the impact. In this study, we identify hotspots of compound flooding along the southern coast of the North Atlantic Ocean and the northern coast of the Mediterranean Sea. This regional assessment can be considered a screening tool for coastal management that provides information about which areas are more predisposed to experience compound flooding.

In this paper the relation between the intensity of meteorological events and the magnitude of triggered geo-hydrological issues was examined. A back analysis was developed across a region of the central Alps. The meteorological triggers were interpreted using two approaches: the first using local rain gauge data and a new one considering meteorological reanalysis maps. The results obtained were compared and elaborated for defining a magnitude of each geo-hydrological event.

Turkey is one of the most seismically active regions. In this study, an extended and homogenized earthquake catalogue, which is essential for seismic hazard studies, is presented in an easily manageable format for a wide range of researchers in earth sciences. It is the most comprehensive catalogue for Turkey and contains approximately ~ 378 000 events between 1900 and 2018.

We use a statistical model to address the controls and interactions of environmental (wave, tide, weather, beach morphology) data on surf zone injuries along a sandy coast where shore-break and rip-current hazards co-exist. Although fair but limited predictive life-risk skill is found, the approach provides new insight into the environmental controls, their interactions and their respective contribution to hazard and exposure, with implications for the development of public education messaging.

Tsunamis are a major threat to low-lying coastal communities. Suddenly generated from their sources in deep water, tsunamis occasionally undergo tremendous amplification in shallow water. There is a need for efficient ways of predicting coastal tsunami transformation during different disaster management phases. The study proposed a novel and rigorous method based on kernel convolution for fast prediction of onshore tsunami waveforms from the observed/simulated wave data away from the coast.

This study exploits 66 years of flash flood disasters across China. The conclusions are as follows. The clustering procedure highlights distinct spatial and temporal patterns of flash flood disasters at different scales. There are distinguished seasonal, yearly and even long-term persistent flash flood behaviors of flash flood disasters. Finally, the decreased duration of clusters in the recent period indicates a possible activation induced by short-duration extreme rainfall events.

We applied a high-resolution, gridded atmospheric data set combined with landslide inventories to investigate the atmospheric triggers, define triggering thresholds, and characterize the climatic disposition of landslides in Kyrgyzstan and Tajikistan. Our results indicate the crucial role of snowmelt in landslide triggering and prediction in Kyrgyzstan and Tajikistan, as well as the added value of climatic disposition derived from atmospheric triggering conditions.

This paper presents an approach to selecting and analysing climate change adaptation measures, using a combination of scientific analysis and stakeholder interaction. This approach was applied in six cases across Europe, concerning drought and extreme precipitation. Although the cases vary widely, the approach yielded decision-relevant outcomes for the development of adaptation strategies, regarding socio-economic impacts of measures and potential barriers to implementation.

The European Centre for Medium-Range Weather Forecasts mission is to deliver high-quality global medium‐range (3–15 d ahead of time) weather forecasts and monitoring of the Earth system. We have published a new strategy, and in this paper we discuss what this means for forecasting and monitoring natural hazards.

In this study, we analyse the role of climate change in the forest fires that raged through large parts of Sweden in the summer of 2018 from a meteorological perspective. This is done by studying observationally constrained data and multiple climate models. We find a small reduced probability of such events, based on reanalyses, but a small increased probability due to global warming up to now and a more robust increase in the risk for such events in the future, based on climate models.

The current research was aimed at the description of historical drought periods that have characterized a broad area of the Mediterranean Basin and the Campania region, located in southern Italy. Knowledge of the past conditions would increase the awareness of the communities with respect to the frequency and severity of critical conditions which have affected and might further affect the environment in which they live.

Local information on epicentres and M_w magnitudes from international catalogues have been combined to compile a catalogue of earthquakes in and near Iceland in the years 1900–2019. The magnitudes are either moment-tensor modelled or proxy values obtained with regression on M_s or exceptionally on m_b. The catalogue also covers the northern Mid-Atlantic Ridge with less accurate locations but similarly harmonised magnitudes.

Disaster planning has historically underallocated resources for flood preparedness, but evidence supports reduced vulnerability via early actions. We evaluate the ability of multiple season-ahead streamflow prediction models to appropriately trigger early actions for the flood-prone Marañón River and Piura River in Peru. Our findings suggest that locally tailored statistical models may offer improved performance compared to operational physically based global models in low-data environments.

The b value is a controversial parameter that has the potential to identify the location of an upcoming strong earthquake. We conducted a case study using a newly developed algorithm that can overcome the subjectivity of calculation. The results confirmed the scientific significance of the b value for seismic hazard analysis and revealed that fluid intrusion may have been the cause of the overactive aftershocks of the studied earthquake.

In the Teskey Range of the Tien Shan (Kyrgyz Republic), four outburst flood disasters from short-lived glacial lakes in 2006, 2008, 2013, and 2014 caused severe damages in the downstream part. Short-lived glacial lakes grow rapidly and drain within a few months, due to closure and opening of an outlet ice tunnel in an ice-cored moraine complex at the glacier front. We investigated how short-lived glacial lakes store and drain water over short periods based on field survey and satellite data.

Sea level rise and its acceleration are projected to aggravate coastal erosion over the 21st century. Resulting shoreline projections are deeply uncertain, however, which constitutes a major challenge for coastal planning and management. Our work presents a new extra-probabilistic framework to develop future shoreline projections and shows that deep uncertainties could be drastically reduced by better constraining sea level projections and improving coastal impact models.