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Relative sea level in Venice rose by about 2.5 mm/year in the past 150 years due to the combined effect of subsidence and mean sea-level rise. We estimate the likely range of mean sea-level rise in Venice by 2100 due to climate changes to be between about 10 and 110 cm, with an improbable yet possible high-end scenario of about 170 cm. Projections of subsidence are not available, but historical evidence demonstrates that they can increase the hazard posed by climatically induced sea-level rise.

In this review we describe the factors leading to the extreme water heights producing the floods of Venice. We discuss the different contributions, their relative importance, and the resulting compound events. We highlight the role of relative sea level rise and the observed past and very likely future increase in extreme water heights, showing that they might be up to 160 % higher at the end of the 21st century than presently.

The city of Venice relies crucially on a good storm surge forecast to protect its population and cultural heritage. In this paper, we provide a state-of-the-art review of storm surge forecasting, starting from examples in Europe and focusing on the Adriatic Sea and the Lagoon of Venice. We discuss the physics of storm surge, as well as the particular aspects of Venice and new techniques in storm surge modeling. We also give recommendations on what a future forecasting system should look like.

Venice is an iconic place, and a paradigm of huge historical and cultural value is at risk. The threat posed by floods has dramatically increased in recent decades and is expected to continue to grow – and even accelerate – through this century. There is a need to better understand the future evolution of the relative sea level and its extremes and to develop adaptive planning strategies appropriate for present uncertainty, which might not be substantially reduced in the near future.

We mapped the subsidence of Wuhan using Sentinel-1 synthetic aperture radar (SAR) images acquired during 2015–2019. Overall subsidence coincides with the distribution of engineered geological regions with soft soils, while the subsidence centers shifted with urban construction activities. Correlation between karst subsidence and concentrated rainfall was identified in Qingling–Jiangdi. Results indicate that interferometric SAR can be employed to routinely monitor and identify geohazards.

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.

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.