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![(a) Observed (black) and a plausible future (red) distribution of sea levels, where mean sea level increases by 0.5 m. (b) Corresponding observed and plausible future pairs of sea levels and discharge Q, where the future sea level distribution is taken from (a) and Q distribution is the observed. The other rows are the same as in (a and b), but consider: (c and d) a plausible future decrease (blue) in Q by 30%; (e and f) plausible future increase (red) and decrease (blue) in positive non‐tidal residuals, that is, S, by 20%; (g and h) a potential future increase in the dependence between Q and S (g and h). In (g), black isolines represent the parametric copula density derived from data (a survival Clayton copula, selected based on the AIC among a pool of copulas available in the VineCopula package [Schepsmeier et al., 2016]); red isolines show a potential future copula with higher dependencies (i.e., copula parameters were modified increasing Kendall's tau from 0.04 to 0.3 and the upper tail dependence coefficient from 0.0001 to 0.15). Gray isolines in the right‐hand panels show the average compound water level in Barrack predicted by the multilinear regression model. In (b), orange isolines show how the compound water level may be influenced by sea level and Q in a hypothetical location upstream (water levels increasing from bottom‐left to top‐right); and the green dashed area indicates concurring sea level and Q extremes (> observed 99th percentiles). Plausible future changes in flood drivers are based on literature (see main text).](publication/355577303/figure/fig4/AS:11431281172706113@1688641768317/a-Observed-black-and-a-plausible-future-red-distribution-of-sea-levels-where-mean.png)
(a) Observed (black) and a plausible future (red) distribution of sea levels, where mean sea level increases by 0.5 m. (b) Corresponding observed and plausible future pairs of sea levels and discharge Q, where the future sea level distribution is taken from (a) and Q distribution is the observed. The other rows are the same as in (a and b), but consider: (c and d) a plausible future decrease (blue) in Q by 30%; (e and f) plausible future increase (red) and decrease (blue) in positive non‐tidal residuals, that is, S, by 20%; (g and h) a potential future increase in the dependence between Q and S (g and h). In (g), black isolines represent the parametric copula density derived from data (a survival Clayton copula, selected based on the AIC among a pool of copulas available in the VineCopula package [Schepsmeier et al., 2016]); red isolines show a potential future copula with higher dependencies (i.e., copula parameters were modified increasing Kendall's tau from 0.04 to 0.3 and the upper tail dependence coefficient from 0.0001 to 0.15). Gray isolines in the right‐hand panels show the average compound water level in Barrack predicted by the multilinear regression model. In (b), orange isolines show how the compound water level may be influenced by sea level and Q in a hypothetical location upstream (water levels increasing from bottom‐left to top‐right); and the green dashed area indicates concurring sea level and Q extremes (> observed 99th percentiles). Plausible future changes in flood drivers are based on literature (see main text).
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Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary approach combining domain knowledge of the underlying processes with, for example, statistical methods and climate model outputs. Recently, to aid the d...
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... These challenges are particularly pronounced when hazards compound, i.e. cluster either temporally or spatially, or co-occur with other types of hazards. Compound events can result in some of the most severe climate impacts (Zscheischler et al 2018, Bevacqua et al 2021. The combined effects of these compound events can lead to outcomes that exceed the individual impacts of single hazards, affecting both natural and societal systems across multiple spatial and temporal scales (Zscheischler et al 2020). ...
Heatwaves and dry spells can severely impact crop yields, making it crucial to understand the nature of these events to ensure food security in a changing climate. We use the Max Planck Institute Grand Ensemble to examine the occurrence of hot–dry extremes in key crop-producing regions known as ‘breadbasket regions’, either in single or multiple breadbasket regions simultaneously, focusing on the differences between 1.5 ∘C and 2 ∘C global warming scenarios. Our findings reveal strong increases in hot–dry events across all individual breadbasket regions between 1.5 ∘C and 2 ∘C of global warming, with ensemble mean probabilities indicating that occurrences more than double in South Asia and triple in East Asia. Moreover, the likelihood of multiple breadbasket regions experiencing extreme events simultaneously increases significantly between 1.5 ∘C and 2 ∘C of warming. Scenarios that were historically considered virtually impossible and very unlikely under 1.5 ∘C, such as at least four regions being affected by hot–dry events in the same growing season, could occur with a 1-in-14 year likelihood under 2 ∘C of warming. We find that, among the breadbasket regions, Central Europe, East Asia, and Central North America most often experience these events simultaneously within the same growing season. Between 1.5 ∘C and 2 ∘C warmer worlds, the probability of simultaneous occurrence increases the most for the connection between these regions. In contrast, South Asia is least likely to be affected simultaneously with other regions, possibly providing insights for risk management.
... Centre for research on the epidemiology of disasters 2024). The complexity of analyzing floods arises from their diverse dynamics, which sometimes classify them as compound events/objects (Zscheischler et al 2020, Bevacqua et al 2021. Following the categorization proposed by Zscheischler et al (2020), it is possible to distinguish four typologies of compound floods. ...
... For example, in large-size catchments, spatially compound rainfall events (Zscheischler et al 2020) may cause many simultaneous flood events over various tributaries (Chen et al 2012) that are routed towards the mainstream with different lag times. Moreover, the temporal clustering of rainfall events, even in small-size catchments, may not allow the complete depletion of each triggered flood event, thus generating hydrographs with more than one peak (Barton et al 2016, Bevacqua et al 2021, Banfi and De Michele 2022. MP events are very frequent among all streamflow events (not only floods). ...
Floods are the most frequent natural hazard globally (2003–2023) and rank second in economic losses, according to EM-DAT, the International Disaster Database. When flood events occur in close succession, they pose significant challenges for emergency management due to limited recovery time between events. This study focuses on multi-peak (MP) floods, where peaks occur within hours to days. Using discharge data from 77 hydrometric stations in Northern Italy’s Po district, we examined statistical differences between MP and single-peak (SP) flood events and analyzed their seasonal patterns and generating mechanisms across diverse river regimes. We demonstrated that SP and MP events exhibit distinct statistical behaviors. The first type of events has more skewed distributions with heavy tails, while the second displays flatter distributions with lighter tails and higher mean values. Seasonal analyses suggest that MP floods in glacial and nival-pluvial regimes are influenced by glacier and snow melting, whereas those in the Padanian regime are driven by tributary routing effects. These triggering mechanisms seem to be responsible of the lighter tails of the distribution of MP floods. By highlighting the distinct statistical behaviors and generating mechanisms of MP and SP floods, we identified recommendations for designing MP flood hydrograph, supporting flood-risk management.
... Apart from the studies considering statistical dependence between the drivers of compound coastal flooding to assess its risk, some studies have also been carried out to investigate the role of synoptic systems and global teleconnections on compound coastal extremes. Further, prior studies also reveal that low-pressure systems, cyclonic storms, and high precipitable water content in the atmosphere near the coast were the primary meteorological forcings responsible for the concurrence of drivers causing compound flooding at majority of coastal locations 2,4,13,18,23 . Further, global climate phenomena like El Niño Southern Oscillation (ENSO) were found to have a significant role in the interannual variability of meteorological forcings driving coastal flooding across Pacific coasts 24 and the connection between storm surge and rainfall along the Australian coast 25 . ...
... Therefore, before fitting the marginal distribution, the independence of events was ensured by taking SS-RF event pairs that are separated by at least 3 days. Furthermore, each chosen SS-RF event comprised the largest skew surge from a cluster of SS-RF event pairs and the largest 3-day rainfall in the 5-day window centered on the day corresponding to the largest skew surge 4,13,18,23 . Subsequently, the Generalized Pareto distribution (GPD) was fitted to the skewsurge values, and the best-fit distribution among Gamma and Lognormal distributions was fitted to the rainfall for the bivariate OR case. ...
... The majority of current research on compound floods is mostly based on the superposition of two disaster factors [19], such as storm surges and pluvial flow [20,21], as well as storm surges and riverine floods [22][23][24]. Research on compound floods involving more than three disaster factors is relatively limited [25]. In the Kelantan River Basin in Malaysia, efforts have been made to assess and simulate multivariate flood characteristics, such as flood peak flow (P), volume (V), and duration (D), using Vine Copula [26].In traditional numerical studies, there is a scarcity of research that incorporates the combined effects of upstream high flow rates, coastal high tides, and local extreme rainfall to assess flood hazards through the establishment of numerical models. ...
Extreme flood occurrences are becoming increasingly common due to global climate change, with coastal cities being more vulnerable to compound flood disasters. In addition to excessive precipitation and upstream river discharge, storm surge can complicate the flood disaster process and increase the hazard of urban flooding. This study proposed an integrated trivariate-dimensional statistical and hydrodynamic modeling approach for assessing the compound flood hazard associated with extreme storm surges, precipitation events, and upstream river discharge. An innovative trivariate copula joint modeling and the frequency amplification method were used to simulate designed values under different return periods (RPs), considering the correlation of the three factors. The results show remarkable differences between the inundated areas of flood events with trivariate drivers and a single driver under the same RPs, indicating that univariate frequency values are insufficient to manage flood threats in compound flood events. The proposed method provides guidelines for comprehending the compound flood process and designing flood control projects in coastal cities.
... DAMOCLES also promoted a bottom-up, impact-centric approach to compound events research. A bottom-up approach moves away from science-driven selection of research topics that could cause significant impacts towards a more pragmatic approach that grounds the focus of research on known extreme weather events-including compound events-that cause impacts (Bevacqua et al., 2021). ...
... By understanding the high-level goals of a sector or system, it is then possible to work backwards to the required outcomes, identify key enablers and barriers to delivery, and consider what actions, or policies, may facilitate the delivery. Additionally, presentations and discussions noted that some frameworks (e.g., Bevacqua et al., 2021;Hillier & Dixon, 2020) typically include detail on physical processes but often omit a quantification of the impacts or implications (Hillier & van Meeteren, 2024). Consequently, Co-RISK, which is an accessible toolkit for cocreating joint collaborative projects between universities and industry, was presented to equip participants with knowledge and guidance to prepare their own tailored and detailed frameworks for natural hazard risk management, spanning from climate knowledge right through to implications (Hillier & van Meeteren, 2024). ...
When multiple weather‐driven hazards such as heatwaves, droughts, storms or floods occur simultaneously or consecutively, their impacts on society and the environment can compound. Despite recent advances in compound event research, risk assessments by practitioners and policymakers remain predominantly single‐hazard focused. This is largely due to traditional siloed approaches that assess and manage natural hazards. Hence, there is a need to adopt a more ‘multi‐hazard approach’ to managing compound events in practice. This paper summarizes discussions from a 2‐day workshop, held in Glasgow in January 2023, which brought together scientists, practitioners and policymakers to: (1) exchange a shared understanding of the concepts of compound and multi‐hazard events; (2) learn from examples of science–policy–practice integration from both the single hazard and multi‐hazard domains; and (3) explore how success stories could be used to improve the management of compound events and multi‐hazard risks. Key themes discussed during the workshop included developing a common language, promoting knowledge co‐production, fostering science–policy–practice integration, addressing complexity, utilising case studies for improved communication and centralising information for informed research, tools and frameworks. By bringing together experts from science, policy and practice, this workshop has highlighted ways to quantify compound and multi‐hazard risks and synergistically incorporate them into policy and practice to enhance risk management.
... Beyond their direct effects on human health, extreme events disrupt global population by increasing disease transmission risks and reducing crop yields through impacts on environmental systems (Duchenne-Moutien and Neetoo 2021, Lian et al 2023. Temporal and spatial connections between extreme events have strengthened, resulting in compound extreme events that occur sequentially or simultaneously (Bevacqua et al 2021, Ridder et al 2022b, Hao and Chen 2024. Compound extreme events could result in more severe disruptions to human, socioeconomic and ecological systems globally (Ridder et al 2022a, Velpuri et al 2023. ...
The simultaneous occurrence of both extreme droughts and heatwaves has become more frequent with global warming, resulting in increases in the frequency and potential impact of compound drought and heatwave (CDHW) globally. It is critical to evaluate the impacts of CDHW and assess global socio-economic risks to formulate appropriate risk mitigation strategies. Most studies have focused on projecting the likely variation in the multidimensional hazard of CDHW. However, the discrepancies among global population projection datasets based on shared socioeconomic pathways (SSPs) and their potential impacts on disaster risk assessments remain underexplored. In this study, multiple global high-resolution population projection datasets are used in combination with projected CDHW hazards via the multimodel ensemble from Coupled Model Intercomparison Project Phase 6 (CMIP6) to investigate how different sources of population data could affect the assessment of CDHW-exposed populations under SSPs. The results show that at the global scale, the spatial pattern and temporal evolution of the CDHW-exposed population under climate change can be depicted consistently on the basis of different population data. However, at the subcontinental scale, substantial spatial heterogeneity exists in the projected exposure. For regions such as the Mediterranean, South Asia, and western Central Asia, the projections from different datasets are consistent with low uncertainty. In contrast, for regions including the northern hemisphere above 40°N, Oceania, eastern Central Asia, East Asia, the South American monsoon region, western Africa, Central Africa, etc., the uncertainty in the estimated exposed population is higher and is expected to increase from the 2020s to the end of the 21st century. Additional locational socioeconomic data should be collected in these areas to reduce uncertainty in future socioeconomic projections. The findings highlight the critical need to consider different elements-at-risk and choose fit-for-purpose datasets, providing essential guidance for disaster risk assessments that support climate adaptation strategies and sustainable development goals.
... Over the next decades, emerging novel regimes of extreme events are predicted to render a disproportionate increase in both single and compound LLHI events, potentially becoming a new but unexplored threat for biodiversity conservation ( Figure 1b). However, the ecological impacts of LLHI events on biological populations are still poorly understood (but see Anderson et al. 2017), and they currently represent a key research frontier in global change biology (Bastos et al. 2023;Bevacqua et al. 2021;Buckley et al. 2023;Jentsch et al. 2007;van de Pol et al. 2017;Wood et al. 2023;Zscheischler et al. 2018). ...
... In addition, the latest IPCC projections predict that as climate changes, LLHI events will increase further than less severe extreme events (IPCC 2021; Lemus-Canovas and Lopez-Bustins 2021; Seneviratne et al. 2021;Simolo and Corti 2022;Vogel et al. 2020), potentially emerging as an overlooked threat for insect populations Malinowska et al. 2014;Soroye et al. 2020;Warren et al. 2021;Zscheischler et al. 2018). Overall, our findings give an ecological perspective on the consequences of increasing LLHI single and compound events in novel climates, complementing recent climate research that highlights their expected crucial role in the future (Bastos et al. 2023;Bevacqua et al. 2021;Seneviratne et al. 2021;Zscheischler et al. 2018). ...
The IPCC predicts that events at the extreme tail of the probability distribution will increase at a higher rate relative to less severe but still abnormal events. Such outlier events are of particular concern due to nonlinear physiological and demographic responses to climatic exposure, meaning that these events are expected to have disproportionate impacts on populations over the next decades (so called low‐likelihood, high‐impact events —LLHI). Because such events are historically rare, forecasting how biodiversity will respond requires mechanistic models that integrate the fundamental processes driving biological responses to our changing climate. Here we built a matrix population model (MPM) from long‐term monitored populations of an insect model species in a Mediterranean area. The model simultaneously integrates the effects of extreme microclimatic heat exposure and drought‐induced host‐plant scarcity on early life stages, a key methodological step forward because these understudied life stages are usually very susceptible to climatic events. This model for the first time allowed us to forecast the demographic impacts that LLHI events will have on a well‐known insect considering their whole life cycle. We found that juveniles were the life stage with the largest relative contribution to population dynamics. In line with field observations, simulated population rates in current climatic regimes were importantly determined by drought impacts, producing a regional mosaic of non‐declining and declining populations. The simulations also indicated that in future, climate scenarios not meeting the Paris Agreement, LLHI heat extremes triggered regionally widespread and severe declines in this currently abundant species. Our results suggest that LLHI events could thus emerge as a critical new —but overlooked— driver of the declines in insect populations, risking the crucial ecosystem functions they perform. We suggest that process‐based and whole‐cycle modelling approaches are a fundamental tool with which to understand the true impacts of climate change.
... The concept of compound events, and this specific terminology, has garnered increasing attention in the scientific literature during the last ten years 5,6,8,[36][37][38][39][40] , although multiple drivers leading to extreme and coinciding events and conditions have seen attention much further back in time in, e.g., multivariate approaches such as in Loganathan et al. 41 . In the study of compound events, researchers, among others, attempt to define and classify these events based on various criteria in the need for shared characteristics and typologies for processes of a very complex nature 40 . ...
... The concept of compound events, and this specific terminology, has garnered increasing attention in the scientific literature during the last ten years 5,6,8,[36][37][38][39][40] , although multiple drivers leading to extreme and coinciding events and conditions have seen attention much further back in time in, e.g., multivariate approaches such as in Loganathan et al. 41 . In the study of compound events, researchers, among others, attempt to define and classify these events based on various criteria in the need for shared characteristics and typologies for processes of a very complex nature 40 . Different articles have proposed definitions and typologies for compound events, reflecting the diverse range of phenomena encompassed by this concept. ...
... Focussing on compound flood events, recent research underscores the amplified risks and complex impacts these events bring 40,[42][43][44] . For example, a study by Wahl et al. 36 highlights how storm surges, combined with heavy rainfall, can significantly exacerbate coastal flooding risks, particularly in low-lying regions. ...
... In recent years, extreme weather events driven by global climate change have posed a significant threat to global food security (Bevacqua et al., 2021). Cotton yields, in particular, exhibit pronounced sensitivity to climatic variability (Liu et al., 2025). ...
... However, CETD assumes that the variables involved in CEs are extreme values, which may introduce bias in the identification of CEs. Secondly, CETD can identify CE involving climate variables, while generalized CE may involve non-climate variables such as floods, crop failures, landslides, etc 18 . Thirdly, CETD does not include a parameter to filter the areal extent of CEs or to cluster events that are closer than a certain threshold distance. ...
Compound events (CEs) are attracting increased attention due to their significant societal and ecological impacts. However, their inherent complexity can pose challenges for climate scientists and practitioners, highlighting the need for a more approachable and intuitive framework for detecting and visualising CEs. Here, we introduce the Compound Events Toolbox and Dataset (CETD), which provides the first integrated, interactive, and extensible platform for CE detection and visualisation. Employing observations, reanalysis, and model simulations, CETD can quantify the frequency, duration, and severity of multiple CE types: multivariate, sequential, and concurrent events. It can analyse CEs often linked to severe impacts on human health, wildfires, and air pollution, such as hot-dry, wet-windy, and hot-dry-stagnation events. To validate the performance of CETD, we conduct statistical analyses for several high-impact events, such as the 2019 Australian wildfires and the 2022 European heatwaves. The accessibility and extensibility of CETD will benefit the broader community by enabling them to better understand and prepare for the risks and challenges posed by CEs in a warming world.
