Figure 1 shows the projected changes in frequency of climatic extreme events with respect to current climate, where increasing (decreasing) hazard occurrences are denoted by lines under (over) the bisector, the coefficient of variance (CV) describes the inter-model spread (climate uncertainty) and S values the percentage of area subject to significant changes (5 % level). The frequency analysis is complemented with the corresponding variations in Expected Annual Fraction Exposed (EAFE) shown in Fig. 2 both in terms of its magnitude and relative change with respect to the baseline; whiskers refer to the range of variability connected to the minimum/maximum hazard scenarios. Corresponding spatial patterns of EAFE are shown in Figure S4. Heat waves show a progressive and highly significant increase in frequency all over Europe (S > 73 % in near future climate, approaching 100 % in all regions by the end of this century), with larger climate variability in long-term scenarios (40 ≤ CV ≤ 60) and a more pronounced intensification in Southern Europe (where current 100-yr. events could occur almost every year in the 2080s) (Fig. 1). Consistently, EAFE values show a progressive increase as time proceeds, especially in Southern Europe where, by the end of the century, up to 60 % of the territory could be annually exposed to a current 100-year heat wave (Fig. 2). Cold waves show an opposite trend with current cold extremes tending to mostly disappear in Europe in more distant futures (current 2-yr. event may occur less than every 100 years by the end of the century, significant almost everywhere, Fig. 1). Accordingly, cold waves could experience a rapid decrease in EAFE and a change up to −100 % by the end of the century (Fig. 2). Streamflow droughts may become more severe and persistent in Southern and Western Europe (current 100-yr. events could occur approximately every 2 to 5 years by 2080, respectively, S ≥ 85) resulting from the reduced precipitation and increased evaporative demands with higher temperatures (Fig. 1). This leads to a consistent increase in EAFE and by the end of the century over 25 % of the territories could be affected every year by baseline 100-yr. droughts (Fig. 2). Northern, Eastern and Central Europe show an opposite tendency with a strong reduction in drought frequency (Fig. 1) caused by higher precipitation that outweigh the effects of increased evapotranspiration (Forzieri et al. 2014). Such effects translate mostly into consistent decreases in EAFE up to −100 % (Fig. 2). Significance increases with time while climate variability shows variable tendencies depending on the return levels (S > 75 % and CV over 60 % by the end of the century). Most of Europe, especially Western, Eastern and Central regions, could experience an increase in the frequency of extreme wildfires (current 100-yr. events will occur every 5 to 50 years) with a progressive rise in significance and model agreement (S > 10 % and CV ≤ 60 % by the end of the century) (Fig. 1). Interestingly, Southern Europe shows a decrease in the frequency of very extreme events, which is likely due to the expected reduction in net primary productivity of terrestrial ecosystem that may limit the fuel availability and, ultimately, the propagation of large wildfires (Migliavacca et al. 2013a). Progressive increases in EAFE are visible for wildfires over the whole domain (one to three-folds the baseline value, Fig. 2). River floods show in general more spatial variability and fluctuations with time in the frequency of extreme events as well as a larger climate-induced spread compared to the other hazards (higher CV values, Fig. 1). This relates to the high variability in projected geographical patterns of heavy precipitation intensity due to structural and parametric model uncertainty and internal climate variability (Fischer et al. 2013). Western Europe shows a consistent rise in future flood hazard (current 100-yr. events could manifest every ~30 years in 2080s, S up to 70 %), mainly as a result of a pronounced increase in average and extreme rainfall (Rojas et al. 2012). Such effects result in a 50–100 % increase in future EAFE (Fig. 2). A modest but significant decrease in river flood frequency is projected in Southern, Central and Eastern regions, in the latter because of the strong reduction in snowmelt induced river floods, which offsets the increase in average and extreme precipitation. Coastal floods show a progressive and pronounced increase in recurrence along Europe’s coastlines chiefly caused by sea level rise (current 100-yr. event may manifest every 2 to 8 years, or even sub-annually in Eastern Europe, in the 2080s, Fig. 1) and leading to strong increase in EAFE (Fig. 2). Noteworthy is the pronounced increase in EAFE in Eastern Europe as a consequence of the rapid intensification of inundations over the Danube delta. Evidence for changes in windstorms remains largely elusive (S < 16 %) and with considerable inter-model spread for larger return levels (up to CV > 60 % for current 100-yr. events, Fig. 1). Areas with increases in windstorm hazard are mainly located in Western, Eastern and Northern Europe, while Southern regions present slight reductions in frequency as observed in previous studies (Nikulin et al. 2011; Outten and Esau 2013). EAFE of windstorms show modest changes with respect to the baseline (up to ±10 %, Fig. 2).
Interestingly, larger increases in EAFE can be observed at higher return levels and for long-term scenarios due to the progressive intensification of very extreme events. This occurs also in regions prevalently experiencing a reduction (or slight change) in future frequency of climate hazards, such as Central and Eastern Europe for droughts, Southern Europe for wildfires and Southern, Central and Northern Europe for floods. The apparent contradiction manifests where few localized areas experience a very large increase in frequency that outweighs the opposite tendency occurring in most of the region.
Projected changes in single-hazard exposure suggest that future hazard scenarios will considerably deviate from those observed in current climate, especially for climate hazards strongly linked to temperature rises (e.g., heat and cold waves, droughts and coastal floods). Despite the general good agreement in the direction of change in exposure amongst the minimum/maximum hazard scenarios (whiskers in Fig. 2) opposite variations in EAFE are apparent in some situations. This is evident for droughts in Central, Eastern and Northern Europe where upper and lower bounds of the range are greater and lower, respectively, than the baseline value (e.g., 0.01 for 100-yr. baseline return period). A deeper inspection of the EAFEs values originated from single GCM-RCM combinations reveals that changes of different hazards may present a dependence across models, with generally more pronounced increases in exposure in models with a larger overall warming (e.g., C4I-RCA-HadCM3, METO-HadRM3-HadCM3, Fig. S5).
Changes in overall and concurrent exposures
Figure 3a shows the overall exposure of each European region resulting from the combination of all hazards, expressed by the Overall Exposure Index accounting for the different number of overlapping hazards (OEI); whiskers express the combination of model uncertainty and internal variability connected to the minimum/maximum multi-hazard scenarios. The positive gradient in ΔEAFE for increasing return levels is more pronounced than in single-hazard scenarios. This results mainly from the combined effect of the abrupt reduction of cold waves and droughts – the latter only for North-eastern and Central Europe – and the compensation occurring at high return levels when the marked positive changes of remaining hazards outweigh such effects (EAFE(100-yr) up to 0.77 by the end of the century for OEI1, about ten-fold the baseline value). The 100-yr. return level remains the most relevant in terms of projected increase of expected annual exposure, especially when overlapping of multiple hazards is accounted for (EAFE(100-yr) up to 0.25 and 0.006 for OEI2 and OEI3, respectively, about thirty-fold the baseline value). Looking at the combination of 100-yr. extreme events, results suggest that the entire Europe could face a progressive increase in overall climate exposure, with a prominent spatial gradient towards south-western regions (Fig. 3b). Heat waves, droughts and wildfires, which are particularly effective in such regions, likely provide the most relevant contribution in the estimation of future OEI (Fig. S4, Supplementary Material).
Figure 4a shows for each European region the spatial extent experiencing pronounced changes in at least four hazards as expressed by the Change Exposure Index calculated for different levels of increase in exposure (CEI), whiskers refer to the climate variability connected to the minimum/maximum multi-hazard scenarios. Areas with potential concurrent exposures tend to increase with the return level and for the long-term scenarios, consistently to the pronounced variations in very extreme events. The spatial pattern of CEI (Fig. 4b) reveals potential key hotspots that are potentially prone to an increase in exposure to multiple hazards. These are mainly located along coastlines and in floodplains where windstorms and floods will be likely relevant in combination with temperature-related hazards (hazard-specific contributions shown in Fig. S6, Supplementary Material). More exposed regions include the British Isles, the North Sea area, north-western parts of the Iberian Peninsula, as well as parts of France, the Alps, Northern Italy and Balkan countries along the Danube River. These areas, even if they may present lower overall climate exposure compared to other regions in Europe (Fig. 3b), will be prone to the largest changes in multi-hazard exposures that could potentially results in larger risks.
Relevant climate variability emerges for both OEI and CEI, more pronounced for long-term scenarios, larger return periods and higher degree of overlapping/change when compared to their median values (Fig. 3a and 4a), largely consistent to the ranges of variability observed in minimum/maximum single-hazard EAFE scenarios (Fig. 2). We argue that the uncertainty captured by the minimum and maximum scenarios tends to overestimate the one that would originate ideally from a combination of each model individually into multi-hazard metrics. Then, sampled ranges of variability should be considered as a qualitative proxy of how model uncertainties of single hazards propagate into multi-hazard metrics.
Sources of uncertainty
Despite the depth of this study, results should be viewed in light of the potential uncertainty sources and caveats of the proposed methodology. The multi-hazard maps are dependent on the chosen set of climate hazard indicators: the use of diverse input hazards (e.g., hail, landslides) might lead to different findings. We argue that the set of hazards selected includes the most relevant hazards for Europe in terms of average annual losses and deaths (Guha-Sapir et al. 2014; NatCatSERVICE 2015). Metrics used to represent the selected climate hazards are crucial for the resulting impact scenarios: changes in return periods depend on the time scale selected to characterize an event type, e.g. 1-day temperature extremes, weekly heatwaves or seasonal heat anomalies experience different changes in return periods (Perkins and Alexander 2012; Trenberth et al. 2014). In our approach we focus on hazard-specific metrics of impact relevance that have been documented in recent literature. Details on the sensitivity analysis and calibration/validation exercises for each single hazard are reported in the references (Rojas et al. 2012; Migliavacca et al. 2013b; Outten and Esau 2013; Forzieri et al. 2014; Cid et al. 2014; Russo et al. 2014). We recognize that extreme value fitting and kernel density estimators may introduce additional uncertainty in the projections of climate hazards especially at high return periods. Recent studies, though, documented its secondary role with respect to the inter-model spread (Rojas et al. 2012; Forzieri et al. 2014).
We apply a conservative approach without accounting explicitly for hazard interrelations that could lead to greater impacts. Regions exposed to the overlap of multiple hazards and subject to concurrent increases in single-hazard EAFEs, however, are indicative of a more likely exacerbation of the overall impacts due to inter-hazard triggering relationships. Estimation of probabilities of coincidental or cascading events would require finer time resolution of hazard metrics (here annual or monthly) and a better knowledge of the inter-hazard physical interactions and coupled processes.
The socioeconomic scenarios driving GHG emissions, the sensitivity of the climate models to GHG concentrations and the specific hazard modelling utilized are subject to uncertainty, and all are relevant in influencing the final multi-hazard assessment. The use of different climate model ensembles for each hazard may have introduced additional artifacts (Table S1, Supplementary Material). However, recent studies suggest that the reduced subsets utilized in this study for some hazards largely preserve main statistical properties of the initial 12-member ensemble (Russo et al. 2013). The use of identical - and possibly larger - ensembles could allow to better capturing climate-related uncertainties (Kharin et al. 2013; Sillmann et al. 2013). We used a different baseline and only one future time window for windstorms (see text S1, Supplementary Material). New dedicated runs for windstorms for the remaining temporal periods were not feasible within this study. We understand that such diversity may limit the comparability with the other hazards; however, changes in extreme winds seem to be lower compared to the other climate hazards, hence the potential bias is expected to play a minor role. Analyses of the multi-hazard indices are performed using the ensemble median (and minimum/maximum) of all climate model combinations for each hazard as input because only one single GCM-RCM configuration is common amongst the hazards. While the median can be considered a robust estimate of single-hazard ensembles, this inevitably hampers the analysis of how single-hazard uncertainties (Fig. 1) propagate to the combined metrics, especially in light of possible dependences of hazards across climate models (Figure S5).
The multi-hazard assessment presented here contributes to understanding to what extent climate-related extreme events will take place under climate change. In particular, the use of a common reference unit based on the probability of occurrence of extremes in current climatology allows comparing the changes in hazard frequency amongst multiple climate extremes and to quantitatively compare them. The adopted homogenized intensity scale permits identifying those hazards that will likely manifest larger changes in exposed areas along the twenty-first century. The combination of changes in multiple climate extremes into single indices leads to a clearer detection of changes in total hazard exposure thanks to the enhanced signal-to-noise ratio. The joint scheme proposed to quantify the overall multi-hazard exposure and concurrent increases in exposure enables the identification of areas in Europe that are likely to be most endangered by multiple climate hazards along the twenty-first century. Key findings can be summarized as in the following:
Projected changes in the occurrence of the seven climate extremes depict important variations in hazard scenarios with large spatial patterns modulated by local climate conditions.
Europe will see a progressive and strong increase in overall climate hazard with a prominent spatial gradient towards south-western regions.
Key hotspots emerge particularly along coastlines and in floodplains in Southern and Western Europe, which are often highly populated and economically pivotal.
Results – interpreted in light of exposed assets and their vulnerability – provide useful input to derive future multi-hazard risk scenarios and support adaptation strategies to increasing Europe’s resilience to climate change.