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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.

Forecasting of daily fire weather indices driven by the ECMWF ensemble prediction system is shown to have a good skill up to 10 d ahead in predicting flammable conditions in most regions of the world. The availability of these forecasts through the Copernicus Emergency Management Service can extend early warnings by up to 1–2 weeks, allowing for greater proactive coordination of resource-sharing and mobilization within and across countries.

There is increasing interest and need to analyze the contribution of anthropogenic climate change to negative impacts of climate change. We study the case of glacial lake Palcacocha in Peru, which poses a significant flood risk to the city of Huaraz. We found that greenhouse gas emissions; strong urbanization processes without appropriate land use planning; and social, cultural, political, and institutional factors all contribute to the existing flood risk.