Extreme climate events can cause human and economic catastrophe at the global scale. For specific sectors, such as humanitarian aid or insurance, being able to understand how (i.e., with which frequency and intensity) these events can occur simultaneously at different locations or several times in a given amount of time and hit critical assets is all-important to design contingency plans. Here we develop an indicator to study co-occurence in space and time of wet and dry extremes.

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.

We present a probabilistic approach for integrating incomplete intensity distributions by means of the Bayesian combination of estimates provided by intensity prediction equations (IPEs) and data documented at nearby localities, accounting for the relevant uncertainties. The performance of the proposed methodology is tested at 28 Italian localities with long and rich seismic histories and for the strong 1980 and 2009 earthquakes in Italy. An application of this approach is also illustrated.

In Indonesia, tsunamis represent a significant risk to coastal communities and buildings. Therefore, it is fundamental to deeply understand the tsunami source impact on buildings and infrastructure. This work provides a novel understanding of the relationship between wave period, ground shaking, liquefaction events, and potential building damage using tsunami fragility curves. This study represents the first investigation of colossal impacts increasing building damage.

We analyze earthquake damage observed in Armenia, Colombia, during the 1999 event. We investigate the reasons behind the damage and the possibility of predicting it using vulnerability studies. We show that vulnerability was a major factor and that observed damage was predicted by a vulnerability study made in 1993, which sadly had no societal impact. The comparison between two vulnerability studies, in 1993 and 2004, suggests that Armenia may still be highly vulnerable to future earthquakes.

At Piton de la Fournaise, eruptions are typically fissure-fed and form extensive lava flow fields. Most historical events have occurred inside an uninhabited caldera, but rarely has lava flowed where population and infrastructure might be at risk. We present an up-to-date lava flow hazard map to visualize the probability of inundation by a lava flow per unit area that is an essential tool for hazard mitigation and guiding crises response management.

Weather index insurance is an innovative program used to manage the risk associated with natural disasters, providing instantaneous financial support to the insured party. This paper proposes a methodology that exploits the power of machine learning to identify extreme events for which a payout from the insurance could be delivered. The improvements achieved using these algorithms are an encouraging step forward in the promotion and implementation of this insurance instrument.

Despite increased use of impact-based weather warnings, the social impacts of extreme weather events lie beyond the reach of conventional meteorological observations and remain difficult to quantify. This study compares data collected from the social media platform Twitter with a manually curated database of high-impact rainfall events across the globe between January–June 2017. Twitter is found to be a good detector of impactful rainfall events and, therefore, a useful source of impact data.

This study quantifies the performance of the Croatian meteotsunami early warning system (CMeEWS) composed of a network of air pressure and sea level observations developed in order to help coastal communities prepare for extreme events. The system would have triggered the warnings for most of the observed events but also set off some false alarms if it was operational during the multi-meteotsunami event of 11–19 May 2020 in the eastern Adriatic. Further development of the system is planned.

Computer simulations can be used to estimate the flow path and inundation of volcanic mass flows; however, their accuracy needs to be appropriately measured and handled in order to determine hazard zones. This paper presents an approach to simulation accuracy assessment and hazard zonation with a volcanic debris avalanche as the benchmark. This method helped to identify and support key findings about errors in mass flow simulations, as well as potential end-use cases for hazard zonation.

The Köfels rockslide in the Ötztal Valley (Austria) represents the largest known extremely rapid rockslide in metamorphic rock masses in the Alps and was formed in the early Holocene. Although many hypotheses for the conditioning and triggering factors were discussed in the past, until now no scientifically accepted explanatory model has been found. This study provides new data and numerical modelling results to better understand the cause and triggering factors of this gigantic natural event.

The Alpine Drought Impact report Inventory (EDII_ALPS) archives drought impact reports across the European Alpine region with an increasing number of impacts over time. The most affected sectors are agriculture and livestock farming and public water supply, for which management strategies are essential for future climate regimes. We show spatial heterogeneity and seasonal differences between the impacted sectors and between impacts triggered by soil moisture drought and hydrological drought.

This paper presents a risk assessment approach addressing the two main natural risks that affect agricultural estuarine lowlands: the scarcity of freshwater for irrigation and marine submersion. The approach is applied to an important agricultural area located in the Tagus Estuary (Portugal). Results show that the approach is appropriate to support risk owners in taking actions to mitigate the risk mainly when the possible impact of climate change in risk levels is considered.

The Bay of Bengal is well known for some of the deadliest cyclones in history. At the same time, storm surge forecasting in this region is physically involved and computationally costly. Here we show a proof of concept of a real-time, computationally efficient, and physically consistent forecasting system with an application to the recent Supercyclone Amphan. While challenges remain, our study paves the path forward to the improvement of the quality of localized forecast and disaster management.

Debris flows are fast-moving landslides that can cause incredible destruction to lives and property. Using the Andes of Santiago as an example, we developed tools to finetune and validate models predicting likely runout paths over large regions. We anticipate that our automated approach that links the open-source R software with SAGA-GIS will make debris-flow runout simulation more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.

In the last few years, some cities in the Mediterranean area have witnessed an increase in extreme rainfall events such as urban floods. The study focuses on a particularly intense urban flood that occurred in Palermo on 15 July 2020, which highlighted the need for a shift in the way stormwater in urban settlements is managed. We think that the framework used to study the impacts of the event and some conclusive remarks could be easily transferred to other urban contexts.

The online landslide database CHILDA (Czech Historical Landslide Database) summarises information about landslides which occurred in the area of Czechia (the Czech Republic). The database is freely accessible via the https://childa.cz/ website. It includes 699 records (spanning the period of 1132–1989). Overall, 55 % of all recorded landslide events occurred only within 15 years of the extreme landslide incidence.

Lightning is a multifaceted hazard with widespread negative consequences for the environment and society. We explore how El Niño–Southern Oscillation (ENSO) phases impact the lightning over India by modulating the deep convection and associated atmospheric thermodynamics. Results show that ENSO phases directly influence lightning during monsoon and postmonsoon seasons by pushing the mean position of subtropical westerlies southward.

Developed statistical models to predict the non-exceedance probability of extreme storm surge-induced typhoons. Various probability distribution models were applied to find the best fitting to empirical storm-surge data.

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.

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.

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.

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.

In order to evaluate the seismic risk, we first model the annual rate of occurrence of earthquakes on the faults near Istanbul. By using a novel modelling approach, we consider the fault system as a whole rather than each fault individually. We explore the hypotheses that are discussed in the scientific community concerning this fault system and compare the modelled results with local recorded data and a physics-based model, gaining new insights in particular on the largest possible earthquake.