Emanuele Bevacqua

Emanuele Bevacqua
Helmholtz-Zentrum für Umweltforschung | UFZ

PhD

About

40
Publications
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1,013
Citations

Publications

Publications (40)
Article
Full-text available
Compound flooding arises from storms causing concurrent extreme meteorological tides (that is the superposition of storm surge and waves) and precipitation. This flooding can severely affect densely populated low-lying coastal areas. Here, combining output from climate and ocean models, we analyse the concurrence probability of the meteorological c...
Article
Full-text available
Wintertime extreme precipitation from cyclone clusters, i.e. consecutive cyclones moving across the same region, can lead to flooding and devastating socio-economic impacts in Europe. Previous studies have suggested that the future direction of the changes in these events are uncertain across climate models. By employing an impact-based metric of a...
Article
Full-text available
Plain Language Summary One of the most impact‐relevant and studied effects of global warming is the intensification of precipitation extremes. When extremely wet winters occur simultaneously at multiple locations within the same region, their cumulative impacts can be particularly high and enhanced as a result of limited resources available to cope...
Article
Full-text available
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...
Article
Full-text available
Compound hot–dry events—co-occurring hot and dry extremes—frequently cause damages to human and natural systems, often exceeding separate impacts from heatwaves and droughts. Strong increases in the occurrence of these events are projected with warming, but associated uncertainties remain large and poorly understood. Here, using climate model large...
Article
Full-text available
Plain Language Summary Co‐occurrences of wind extremes and precipitation extremes, termed compound wind and precipitation extremes (CWPEs), can disrupt and endanger shipment and shipping logistics. The associated winds and floods may cause severe socio‐economic impacts in coastal and inland areas, such as paralyzed public transportation, critical i...
Preprint
Most societally relevant weather impacts result from compound events, that is, rare combinations of weather and climate drivers. Focussing on four event types arising from different combinations of climate variables across space and time, we illustrate that robust analyses of compound events – such as frequency and uncertainty analysis under presen...
Article
Full-text available
Compound climate events can strongly impact vegetation productivity, yet the direct and lagged vegetation productivity responses to seasonal compound warm-dry and cold-dry events remain unclear. Here we use observationally-constrained and process-based model data and analyze vegetation productivity responses to compound events of precipitation and...
Preprint
Climate change may systematically impact hydro-meteorological processes and their interactions, resulting in changes in flooding mechanisms. Identifying such changes is important for flood forecasting and projection. Currently, there is a lack of observational evidence regarding trends in flooding mechanisms in Europe, which requires reliable metho...
Article
Full-text available
Landslides are a major natural hazard, but uncertainties about their occurrence in a warmer climate are substantial. The relative role of rainfall, soil moisture, and land-use changes and the importance of climate change mitigation are not well understood. Here, we develop an event storyline approach to address these issues, considering an observed...
Preprint
Long-duration dry spells in combination with temperature extremes during summer have led to extreme impacts on society and ecosystems in the past. Such events are expected to become more frequent due to increasing temperatures as a result of anthropogenic climate change. However, there is little information on how long-duration dry and hot spells a...
Article
Full-text available
Climate impact models often require unbiased point‐scale observations, but climate models typically provide biased simulations at the grid scale. While standard bias adjustment methods have shown to generally perform well at adjusting climate model biases, they cannot overcome the gap between grid‐box and point‐scale. To overcome this limitation, c...
Preprint
Full-text available
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...
Article
Full-text available
Climate models' outputs are affected by biases that need to be detected and adjusted to model climate impacts. Many climate hazards and climate-related impacts are associated with the interaction between multiple drivers, i.e. by compound events. So far climate model biases are typically assessed based on the hazard of interest, and it is unclear h...
Article
Full-text available
The future climate projections in the IPCC reports are visually communicated via maps showing the mean response of climate models to alternative scenarios of socio‐economic development. The presence of large changes is highlighted by stippling the maps where the mean climate response (the signal) is large compared to internal variability (the noise...
Preprint
Full-text available
Climate models' outputs are affected by biases that need to be detected and adjusted to model climate impacts. Many climate hazards and climate-related impacts are associated with the interaction between multiple drivers, i.e. by compound events. So far climate model biases are typically assessed based on the hazard of interest, and it is unclear h...
Preprint
Full-text available
Wintertime extreme precipitation from cyclone clusters, i.e. consecutive cyclones moving across the same region, can lead to flooding and devastating socioeconomic impacts in Europe. Previous studies have suggested that the future direction of the changes in these events are uncertain across climate models. By employing an impact-based metric of ac...
Article
Full-text available
Interacting storm surges and high water runoff can cause compound flooding (CF) in low-lying coasts and river estuaries. The large-scale CF hazard has been typically studied using proxies such as the concurrence of storm surge extremes either with precipitation or with river discharge extremes. Here the impact of the choice of such proxies is addre...
Article
Full-text available
The influence of anthropogenic climate change on both mean and extremely hot temperatures in Europe has been demonstrated in a number of studies. There is a growing consensus that high temperature extremes have increased more rapidly than the regional mean in central Europe, while the difference between extreme and mean trends is not significant in...
Article
Full-text available
Compound weather and climate events describe combinations of multiple climate drivers and/or hazards that contribute to societal or environmental risk. Although many climate-related disasters are caused by compound events, the understanding, analysis, quantification and prediction of such events is still in its infancy. In this Review, we propose a...
Preprint
Full-text available
Preprint available here: https://eartharxiv.org/4x2u8/ Compound coastal and inland flooding can result in catastrophic impacts in densely populated low-lying coastal areas. The dynamics and interactions between the underlying meteorological drivers in view of climate change are not fully understood at global scale. Here, we show that under a high...
Preprint
Full-text available
Abstract. Interacting storm surges and high water-runoff can cause compound flooding (CF) in low-lying coasts and river estuaries. The large-scale CF hazard has been typically studied using proxies such as the concurrence of storm surge extremes either with precipitation or with river discharge extremes. Here the impact of the choice of such proxie...
Article
Full-text available
In low-lying coastal areas, the co-occurrence of high sea level and precipitation resulting in large runoff may cause compound flooding (CF). When the two hazards interact, the resulting impact can be worse than when they occur individually. Both storm surges and heavy precipitation, as well as their interplay, are likely to change in response to g...
Data
Relative SLR influence on extreme sea level and CF. Bivariate validation. Univariate return periods. Fig. S1: Relative SLR influence on extreme sea level and CF. Fig. S2: Extreme values of sea level and precipitation. Fig. S3: Comparison of the dependence between sea level and precipitation based on ERA-Interim and observation data. Fig. S...
Article
Full-text available
The propagation of drought from meteorological drought to soil moisture drought can be accelerated by high temperatures during dry periods. The occurrence of extremely long-duration dry periods in combination with extremely high temperatures may drive larger soil moisture deficits than either extreme occurring alone, and lead to severe impacts. In...
Preprint
Compound flooding (CF) is an extreme event taking place in low-lying coastal areas as a result of co-occurring high sea level and large amounts of runoff, caused by precipitation. The impact from the two hazards occurring individually can be significantly lower than the result of their interaction. Both the risk of storm surges and heavy precipitat...
Article
Full-text available
Compound events are extreme impacts that depend on multiple variables that need not be extreme themselves. In this study, we analyze soil moisture drought as a compound event of precipitation and potential evapotranspiration (PET) on multiple time scales related to both meteorological drought and heat waves in wet, transitional, and dry climates in...
Article
Full-text available
Compound events (CEs) are multivariate extreme events in which the individual contributing variables may not be extreme themselves, but their joint – dependent – occurrence causes an extreme impact. Conventional univariate statistical analysis cannot give accurate information regarding the multivariate nature of these events. We develop a conceptua...
Poster
Full-text available
Given a joint probability density function (pdf), copulas allows for modelling the dependence structure of the variables separately from their marginal pdfs. Copulas provide flexibility when modelling joint pdfs, and therefore have been largely used in science, e.g. in quantitative finance to model and minimize tail risk, in hydrology and more rece...
Technical Report
Full-text available
Given a joint probability density function (pdf), copulas allows for modelling the dependence structure of variables separately from their marginal pdfs. Copulas gives flexibility when modelling joint pdfs and therefore have been used in many fields, e.g. in quantitative finance to model and minimize tail risk, and more recently in climate science....
Article
Full-text available
Compound events are multivariate extreme events in which the individual contributing variables may not be extreme themselves, but their joint - dependent - occurrence causes an extreme impact. The conventional univariate statistical analysis cannot give accurate information regarding the multivariate nature of these events. We develop a conceptual...
Presentation
Full-text available
Compound events are extreme impacts which are driven by statistically dependent meteorological variables. We present a multivariate statistical model to represent and analyze the physical mechanisms driving Compound Floods, i.e. joint storm surge and high river level, in Ravenna (Italy). The model allows for the quantifications of the risk associat...
Poster
Full-text available
In the recent report of the Intergovernmental Panel on Climate Change on extreme events it has been highlighted that extreme compound events (CEs) has received little attention so far (Seneviratne et al., 2012). CEs are multivariate events in which the individual contributing events might not be extreme themselves, but their joint occurrence causes...
Article
Full-text available
We investigate both the European Project for Ice Coring in Antarctica Dronning Maud Land (EDML) and North Greenland Ice-Core Project (NGRIP) data sets to study both the time evolution of the so-called Dansgaard–Oeschger events and the dynamics at longer timescales during the last glacial period. Empirical mode decomposition (EMD) is used to extract...
Article
Full-text available
We investigate both the European Project for Ice Coring in Antarctica (EPICA) and North Greenland Ice-Core Project (NGRIP) datasets to study the time evolution of the so-called Dansgaard–Oeschger events during the last glacial period. The Empirical 5 Mode Decomposition (EMD) is used to extract the proper modes of both the datasets. It is shown that...

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Projects

Projects (2)
Project
Hazards such as floods, wildfires, heatwaves, and droughts usually result from a combination of interacting physical processes that occur across multiple spatial and temporal scales. The combination of physical processes leading to an impact is referred to as a Compound Event. Examples of high-impact Compound Events include (i) droughts, heatwaves, wildfire and/or air pollution and their interactions involving a complex interplay between temperature, humidity and precipitation; (ii) extreme precipitation, river discharge and storm surge interactions, combining coastal storm processes with fluvial/pluvial and ocean dynamics; (iii) storms including clustering of major events leading to spatial and/or temporal dependence. Climate change alters many of these processes and their interaction, making projections of future hazards based on single driver analyses difficult. Impact studies considering only one driver usually fail to assess the extent of the impacts of Compound Events. It is thus not clear whether climate models can capture major changes in risk associated with Compound Events. Existing modelling approaches used to assess risk may therefore lead to serious mal-adaptation. DAMOCLES will (a) identify key process and variable combinations underpinning Compound Events; (b) describe the available statistical methods for modelling dependence in time, space, and between multiple variables; (c) identify data requirements needed to document, understand, and simulate Compound Events, and (d) propose an analysis framework to improve the assessment of Compound Events. DAMOCLES brings together climate scientists, impact modellers, statisticians, and stakeholders to better understand, describe and project Compound Events, and foresees a major breakthrough in future risk assessments. http://www.cost.eu/COST_Actions/ca/CA17109?
Project
Compound events (CEs) are major extreme events that result from the joint occurrence of underlying contributing events. Typical examples are drought in conjunction with a heatwave, and a storm surge coinciding with heavy precipitation causing river flooding. To fully describe the dependence structure of CEs and to correctly assess their severity, multivariate statistical models are required. To understand the physical processes underlying the structure of CEs, the inclusion of physical predictors is necessary. These also provide insight into the temporal variability of CEs and their dependence structure. So far, no multivariate statistical models including predictors to describe CEs have been formulated. Based on pair copula constructions, we will develop a multivariate statistical model with predictors to describe the structure of CEs and their temporal variability. The model will be applicable to a wide class of CEs. In CE:LLO we will apply the model to the drought and flood examples mentioned above. For CEs in the observational record we will analyse the severity, their variability and underlying physical mechanisms. The representation of CEs by dynamically downscaled global climate models will be evaluated, and potential future changes in CEs will be analysed.