The Precautionary Principles of the Potential Risks of Compound Events in Danish Municipalities

The risk of compound events describes potential weather and climate events in which the combination of multiple drivers and hazards consolidate, resulting in extreme socio-economic impacts. Compound events affecting exposed societies can therefore be deemed a crucial security risk. Designing appropriate preparation proves difficult, as compound events are rarely documented. This paper explores the understanding and practices of climate risk management related to compound events in specific Danish municipalities vulnerable to flood hazards (i.e., Odense, Hvidovre, and Vejle). These practices illuminate that different understandings of compound events steer risk attitudes and consequently decisions regarding the use of different policy instruments. Through expert interviews supported by policy documents, we found that the municipalities understand compound events as either a condition or situation and develop precautionary strategies to some extent. Depending on their respective geographical surroundings, they observe compound events either as no clear trend (Odense), a trend to be critically watched (Hvidovre), or already as a partial reality (Vejle). They perceive flood drivers and their combinations as major physical risks to which they adopt different tailor-made solutions. By choosing a bottom-up approach focusing on local governance structures, it demonstrated that the mismatch between responsibility and capacity and the ongoing separation of services related to climatic risks in the Danish municipality context need to be critically considered. The findings highlight that the complex challenge of compound events cannot be solved by one (scientific) discipline alone. Thus, the study advocates a broader inclusion of scientific practices and increased emphasis on local focus within compound event research to foster creative thinking, better preparation, and subsequently more effective management of their risks.

Vulnerability of European ecosystems to two compound dry and hot summers in 2018 and 2019

In 2018 and 2019, central Europe was affected by two consecutive extreme dry and hot summers (DH18 and DH19). The DH18 event had severe impacts on ecosystems and likely affected vegetation activity in the subsequent year, for example through depletion of carbon reserves or damage from drought. Such legacies from drought and heat stress can further increase vegetation susceptibility to additional hazards. Temporally compound extremes such as DH18 and DH19 can, therefore, result in an amplification of impacts due to preconditioning effects of past disturbance legacies. Here, we evaluate how these two consecutive extreme summers impacted ecosystems in central Europe and how the vegetation responses to the first compound event (DH18) modulated the impacts of the second (DH19). To quantify changes in vegetation vulnerability to each compound event, we first train a set of statistical models for the period 2001–2017, which are then used to predict the impacts of DH18 and DH19 on enhanced vegetation index (EVI) anomalies from MODIS. These estimates correspond to expected EVI anomalies in DH18 and DH19 based on past sensitivity to climate. Large departures from the predicted values can indicate changes in vulnerability to dry and hot conditions and be used to identify modulating effects by vegetation activity and composition or other environmental factors on observed impacts. We find two regions in which the impacts of the two compound dry and hot (DH) events were significantly stronger than those expected based on previous climate–vegetation relationships. One region, largely dominated by grasslands and crops, showed much stronger impacts than expected in both DH events due to an amplification of their sensitivity to heat and drought, possibly linked to changing background CO2 and temperature conditions. A second region, dominated by forests and grasslands, showed browning from DH18 to DH19, even though dry and hot conditions were partly alleviated in 2019. This browning trajectory was mainly explained by the preconditioning role of DH18 on the impacts of DH19 due to interannual legacy effects and possibly by increased susceptibility to biotic disturbances, which are also promoted by warm conditions. Dry and hot summers are expected to become more frequent in the coming decades, posing a major threat to the stability of European forests. We show that state-of-the-art process-based models could not represent the decline in response to DH19 because they missed the interannual legacy effects from DH18 impacts. These gaps may result in an overestimation of the resilience and stability of temperate ecosystems in future model projections.

A novel method to identify sub-seasonal clustering episodes of extreme precipitation events and their contributions to large accumulation periods

Temporal (serial) clustering of extreme precipitation events on sub-seasonal timescales is a type of compound event. It can cause large precipitation accumulations and lead to floods. We present a novel, count-based procedure to identify episodes of sub-seasonal clustering of extreme precipitation. We introduce two metrics to characterise the prevalence of sub-seasonal clustering episodes and their contribution to large precipitation accumulations. The procedure does not require the investigated variable (here precipitation) to satisfy any specific statistical properties. Applying this procedure to daily precipitation from the ERA5 reanalysis data set, we identify regions where sub-seasonal clustering occurs frequently and contributes substantially to large precipitation accumulations. The regions are the east and northeast of the Asian continent (northeast of China, North and South Korea, Siberia and east of Mongolia), central Canada and south of California, Afghanistan, Pakistan, the southwest of the Iberian Peninsula, and the north of Argentina and south of Bolivia. Our method is robust with respect to the parameters used to define the extreme events (the percentile threshold and the run length) and the length of the sub-seasonal time window (here 2–4 weeks). This procedure could also be used to identify temporal clustering of other variables (e.g. heat waves) and can be applied on different timescales (sub-seasonal to decadal). The code is available at the listed GitHub repository.

Assessing Damages to Built and Natural Environments: Linking Hydrodynamic and Geospatial Enviro-Economical Models

In this study, a novel framework was developed to provide a holistic damage assessment caused by severe hydrologic events whether individually or as a compound event. The novel framework uses a developed hurricane-specific water quality model, Environmental Fluid Dynamic Code-Storm Surge model (EFDC-SS) and an ArcGIS-based framework, the Facility Economic Damage and Environmental Release Planning (FEDERAP) to assess damages to the built and natural environment. The developed framework could be used to compare different hurricanes and storms with a focus on land inundation, spill destination in both land and water and their associated risks, as well as economic loss including both physical and secondary losses. The results showed different spreading mechanisms during surge and rainfall-based hurricanes. While storm surge pushed contaminants (from spills) upstream, the rainfall-based hurricane caused a larger footprint of contamination on land. Though different in spreading patterns, spills during both hurricane types can widely spread miles away from the release location in a very short period of time. The FEDERAP economic loss model showed that facility area, average land elevation, the number of storage tanks and process units at the facility, and daily production are key drivers in the calculated total losses for a given hydrologic event.

Towards a compound-event-oriented climate model evaluation: a decomposition of the underlying biases in multivariate fire and heat stress hazards

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 how much a potential bias in the dependence of the hazard drivers contributes to the overall bias and how the biases in the drivers interact. Here, based on copula theory, we develop a multivariate bias-assessment framework, which allows for disentangling the biases in hazard indicators in terms of the underlying univariate drivers and their statistical dependence. Based on this framework, we dissect biases in fire and heat stress hazards in a suite of global climate models by considering two simplified hazard indicators: the wet-bulb globe temperature (WBGT) and the Chandler burning index (CBI). Both indices solely rely on temperature and relative humidity. The spatial pattern of the hazard indicators is well represented by climate models. However, substantial biases exist in the representation of extreme conditions, especially in the CBI (spatial average of absolute bias: 21 ∘C) due to the biases driven by relative humidity (20 ∘C). Biases in WBGT (1.1 ∘C) are small compared to the biases driven by temperature (1.9 ∘C) and relative humidity (1.4 ∘C), as the two biases compensate for each other. In many regions, also biases related to the statistical dependence (0.85 ∘C) are important for WBGT, which indicates that well-designed physically based multivariate bias adjustment procedures should be considered for hazards and impacts that depend on multiple drivers. The proposed compound-event-oriented evaluation of climate model biases is easily applicable to other hazard types. Furthermore, it can contribute to improved present and future risk assessments through increasing our understanding of the biases' sources in the simulation of climate impacts.

Assessing internal changes in the future structure of dry–hot compound events: the case of the Pyrenees

Impacts upon vulnerable areas such as mountain ranges may become greater under a future scenario of adverse climatic conditions. In this sense, the concurrence of long dry spells and extremely hot temperatures can induce environmental risks such as wildfires, crop yield losses or other problems, the consequences of which could be much more serious than if these events were to occur separately in time (e.g. only long dry spells). The present study attempts to address recent and future changes in the following dimensions: duration (D), magnitude (M) and extreme magnitude (EM) of compound dry–hot events in the Pyrenees. The analysis focuses upon changes in the extremely long dry spells and extremely high temperatures that occur within these dry periods in order to estimate whether the internal structure of the compound event underwent a change in the observed period (1981–2015) and whether it will change in the future (2006–2100) under intermediate (RCP4.5, where RCP is representative concentration pathway) and high (RCP8.5) emission scenarios. To this end, we quantified the changes in the temporal trends of such events, as well as changes in the bivariate probability density functions for the main Pyrenean regions. The results showed that to date the risk of the compound event has increased by only one dimension – magnitude (including extreme magnitude) – during the last few decades. In relation to the future, increase in risk was found to be associated with an increase in both the magnitude and the duration (extremely long dry spells) of the compound event throughout the Pyrenees during the spring under RCP8.5 and in the northernmost part of this mountain range during summer under this same scenario.

Space–time dependence of compound hot–dry events in the United States: assessment using a multi-site multi-variable weather generator

Compound hot and dry events can lead to severe impacts whose severity may depend on their timescale and spatial extent. Despite their potential importance, the climatological characteristics of these joint events have received little attention regardless of growing interest in climate change impacts on compound events. Here, we ask how event timescale relates to (1) spatial patterns of compound hot–dry events in the United States, (2) the spatial extent of compound hot–dry events, and (3) the importance of temperature and precipitation as drivers of compound events. To study such rare spatial and multivariate events, we introduce a multi-site multi-variable weather generator (PRSim.weather), which enables generation of a large number of spatial multivariate hot–dry events. We show that the stochastic model realistically simulates distributional and temporal autocorrelation characteristics of temperature and precipitation at single sites, dependencies between the two variables, spatial correlation patterns, and spatial heat and meteorological drought indicators and their co-occurrence probabilities. The results of our compound event analysis demonstrate that (1) the northwestern and southeastern United States are most susceptible to compound hot–dry events independent of timescale, and susceptibility decreases with increasing timescale; (2) the spatial extent and timescale of compound events are strongly related to sub-seasonal events (1–3 months) showing the largest spatial extents; and (3) the importance of temperature and precipitation as drivers of compound events varies with timescale, with temperature being most important at short and precipitation at seasonal timescales. We conclude that timescale is an important factor to be considered in compound event assessments and suggest that climate change impact assessments should consider several timescales instead of a single timescale when looking at future changes in compound event characteristics. The largest future changes may be expected for short compound events because of their strong relation to temperature.

Increased vulnerability of European ecosystems to two compound dry and hot summers in 2018 and 2019

In 2018 and 2019, central Europe was stricken by two consecutive extreme dry and hot summers (DH2018 and DH2019). The DH2018 had severe impacts on ecosystems and likely affected vegetation activity in the subsequent year, for example though depletion of carbon reserves or damage from drought. Such legacies from drought and heat stress can further increase vegetation susceptibility to additional hazards. Temporally compound extremes such as DH2018 and DH2019 can, therefore, result in an amplification of impacts by preconditioning effects of past disturbance legacies.Here, we evaluate how these two consecutive extreme summers impacted ecosystems in central Europe and how the vegetation responses to the first compound event (DH2018) modulated the impacts of the second (DH2019). To quantify the modulating role of vegetation responses to the impacts of each compound event, we first train a set of statistical models for the period 2001–2017 to predict the impacts of DH2018 and DH2019 on Enhanced Vegetation Index (EVI) anomalies from MODIS. These estimates can be seen as the expected EVI anomalies, had the impacts of DH2018 and DH2019 been consistent with past sensitivity to climate. These can then be used to identify modulating effects by vegetation activity and composition or other environmental factors such as elevated CO2 or warming trends.We find two regions in which the impacts of the two DH events were significantly stronger than those expected based on previous climate–vegetation relationships. One region, largely dominated by grasslands and crops, showed much stronger impacts than expected in both DH events due to an amplification of their sensitivity to heat and drought, possibly linked to changing background CO2 and temperature conditions. A second region, dominated by forests, showed browning from DH2018 to DH2019, even though dry and hot conditions were partly alleviated in 2019. This browning trajectory was mainly explained by the preconditioning role of DH2018 to the observed response to DH2019 through legacy effects, and possibly by increased susceptibility to biotic disturbances, which are also promoted by warm conditions.Dry and hot summers are expected to become more frequent in the coming decades posing a major threat to the stability of European forests. We show that state-of-the-art process based models miss these legacy effects. These gaps may result in an overestimation of the resilience and stability of temperate ecosystems in future model projections.

Compound high-temperature and low-chlorophyll extremes in the ocean over the satellite period

Extreme events in the ocean severely impact marine organisms and ecosystems. Of particular concern are compound events, i.e., when conditions are extreme for multiple potential ocean ecosystem stressors such as temperature and chlorophyll. Yet, little is known about the occurrence, intensity, and duration of such compound high-temperature (a.k.a. marine heatwaves – MHWs) and low-chlorophyll (LChl) extreme events, whether their distributions have changed in the past decades, and what the potential drivers are. Here we use satellite-based sea surface temperature and chlorophyll concentration estimates to provide a first assessment of such compound extreme events. We reveal hotspots of compound MHW and LChl events in the equatorial Pacific, along the boundaries of the subtropical gyres, in the northern Indian Ocean, and around Antarctica. In these regions, compound events that typically last 1 week occur 3 to 7 times more often than expected under the assumption of independence between MHWs and LChl events. The occurrence of compound MHW and LChl events varies on seasonal to interannual timescales. At the seasonal timescale, most compound events occur in summer in both hemispheres. At the interannual timescale, the frequency of compound MHW and LChl events is strongly modulated by large-scale modes of natural climate variability such as the El Niño–Southern Oscillation, whose positive phase is associated with increased compound event occurrence in the eastern equatorial Pacific and in the Indian Ocean by a factor of up to 4. Our results provide a first understanding of where, when, and why compound MHW and LChl events occur. Further studies are needed to identify the exact physical and biological drivers of these potentially harmful events in the ocean and their evolution under global warming.