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This is a perspective based on personal experience on whether a large number of landslides caused by a single trigger (e.g. an earthquake, an intense rainfall, a rapid snowmelt event) or by multiple triggers in a period can be predicted, in space and time, considering the consequences of slope failures.

A cluster of 13 large mass flow events including five detachments of entire valley glaciers was observed in the Petra Pervogo range, Tajikistan, in 1973–2019. The local clustering provides additional understanding of the influence of temperature, seismic activity, and geology. Most events occurred in summer of years with mean annual air temperatures higher than the past 46-year trend. The glaciers rest on weak bedrock and are rather short, making them sensitive to friction loss due to meltwater.

We have developed a statistical–parametric model of tropical cyclones (TCs), to undertake hazard and risk assessments at continental scales. The model enables users to build an understanding of the likelihood and magnitude of TC-related wind speeds across full ocean basins but at a fine spatial resolution. The model can also be applied to single events, either scenarios or forecast events, to inform detailed impact assessments.

Severe convective storms (SCSs) and the related hail events constitute major atmospheric hazards in parts of Europe. In our study, we identified the regions of France, Germany, Belgium and Luxembourg that were most affected by hail over a 10 year period (2005 to 2014). A cell-tracking algorithm was computed on remote-sensing data to enable the reconstruction of several thousand SCS tracks. The location of hail hotspots will help us understand hail formation and improve hail forecasting.

Building on almost ten years of expertise and operational application of the Combined Drought Indicator (CDI) for the monitoring of agricultural droughts in Europe within the European Commission's European Drought Observatory (EDO), this paper proposes a revised version of the index. This paper shows that the proposed revised CDI reliably reproduces the evolution of major droughts, outperforming the current version of the indicator, especially for long-lasting events.

The storyline method is used to quantify the effect of climate change on a particular extreme weather event using a global atmospheric model by simulating the event with and without climate change. We present the method and its successful application for the climate change signals of the European 2003 and the Russian 2010 heatwaves.

This work proposes methods for reducing the computational requirements of hydrological simulations for the estimation of very rare floods that occur on average less than once in 1000 years. These methods enable the analysis of long streamflow time series (here for example 10 000 years) at low computational costs and with modelling uncertainty. They are to be used within continuous simulation frameworks with long input time series and are readily transferable to similar simulation tasks.

Landslides cause thousands of fatalities and cost billions of dollars of damage worldwide every year, but different inventories of landslide events can have widely diverging completeness. This can lead to spatial biases in our understanding of the impacts. Here we use a globally homogeneous model of landslide hazard and exposure to provide consistent estimates of where landslides are most likely to cause damage to people, roads and other critical infrastructure at 1 km resolution.

Satellite radar could provide information on landslide locations within days of an earthquake or rainfall event anywhere on Earth, but until now there has been a lack of systematic testing of possible radar methods, and most methods have been demonstrated using a single case study event and data from a single satellite sensor. Here we test five methods on four events, demonstrating their wide applicability and making recommendations on when different methods should be applied in the future.

The geometry of estuaries is often altered through dredging to make room for ships and with extensive landfill over wetlands to enable development. Here, we use historical maps to help create computational models of seawater flow around and into a lagoonal bay of New York City for the 1880s and 2010s. Our results show that these past man-made changes cause higher coastal storm tides and that they result specifically from deeper depths, expanded inlet width, and landfill.