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.

Large-scale environments of successive atmospheric river events leading to compound precipitation extremes in California

Successive atmospheric river (AR) events—known as AR families—can result in prolonged and elevated hydrological impacts relative to single ARs due to the lack of recovery time between periods of precipitation. Despite the outsized societal impacts that often stem from AR families, the large-scale environments and mechanisms associated with these compound events remain poorly understood. In this work, a new reanalysis-based 39-year catalog of 248 AR family events affecting California between 1981 and 2019 is introduced. Nearly all (94%) of the inter-annual variability in AR frequency is driven by AR family versus single events. Using K-means clustering on the 500-hPa geopotential height field, six distinct clusters of large-scale patterns associated with AR families are identified. Two clusters are of particular interest due to their strong relationship with phases of the El Niño/Southern Oscillation (ENSO). One of these clusters is characterized by a strong ridge in the Bering Sea and Rossby wave propagation, most frequently occurs during La Niña and neutral ENSO years and is associated with the highest cluster-average precipitation across California. The other cluster, characterized by a zonal elongation of lower geopotential heights across the Pacific basin and an extended North Pacific Jet, most frequently occurs during El Niño years and is associated with lower cluster-average precipitation across California but a longer duration. In contrast, single AR events do not show obvious clustering of spatial patterns. This difference suggests that the potential predictability of AR families may be enhanced relative to single AR events, especially on sub-seasonal to seasonal timescales.

Changes in temperature-precipitation correlations over Europe: Are climate models reliable?

Inter-variable correlations (e.g., between daily temperature and precipitation) are key statistical properties to characterise probabilities of simultaneous climate events and compound events. Their correct simulations from climate models, both in values and in changes over time, is then a prerequisite to investigate their future changes and associated impacts. Therefore, this study first evaluates the capabilities of one 11-member multi-model ensemble (CMIP6) and one 40-member multi-run single model ensemble (CESM) over Europe to reproduce the characteristics of a reanalysis dataset (ERA5) in terms of temperature-precipitation correlations and their historical changes. Next, the ensembles’ correlations for the end of the 21st century are compared to assess the robustness of the future correlation changes. Over historical period, both CMIP6 and CESM ensembles have season-dependent and spatially structured biases. Moreover, the inter-variable correlations from both ensembles mostly appear stationary. Thus, although reanalyses display significant correlation changes, none of the ensembles is able to reproduce them. However, future correlations show significant changes over large spatial patterns. Yet, those patterns are rather different for CMIP6 and CESM, reflecting a large uncertainty in changes. In addition, for historical and future projections, an analysis conditional on atmospheric circulation regimes is performed. The conditional correlations given the regimes are found to be the main contributor to the biases in correlation over the historical period, and to the past and future changes of correlation. These results highlight the importance of the large-scale circulation regimes and the need to understand their physical relationships with local-scale phenomena associated to specific inter-variable correlations.

Compound droughts and heatwaves over the Huai River Basin of China: From a perspective of the magnitude index

Compound droughts and heatwaves have garnered increasing research attentions due to their disastrous impacts on the structure and function of ecosystems and societies. A drought is generally characterized by precipitation deficit, and its negative impact can be amplified by the simultaneous occurrence of a heatwave. More recent studies have highlighted the multi characteristics of compound droughts and heatwaves, which may call for improved efforts on assessing the impact of compound extremes. In this study, a compound drought and heatwave magnitude index (CDHMI) is built to characterize the severity of compound extremes in the Huai River Basin (HRB) during 1961-2017. The CDHMI considers the impact of both drought/extreme heat conditions and the duration of extreme heat. In addition, the magnitude index has been graded according to the degree of severity to detect the most drastic extreme compound events. The results show that from 1961 to 2017, mild and moderate events occurred more often than severe events. A significant increase in all compound events was observed from 2003 to 2017. Compound droughts and heatwaves events, especially in drought status, have increased significantly with the global climate warming in recent decades. The assessment of the impact for compound droughts and heatwaves events over the HRB needs to be improved in the context of global climate changing. Therefore, the CDHMI can be used to accurately assess the risk of compound droughts and heatwaves.

Attributing compound events to anthropogenic climate change

Extreme event attribution answers the question whether and by how much anthropogenic climate change has contributed to the occurrence or magnitude of an extreme weather event. It is also used to link extreme event impacts to climate change. Impacts, however, are often related to multiple compounding climate drivers. Because extreme event attribution typically focuses on univariate assessments, these assessments might only provide a partial answer to the question of anthropogenic influence to a high-impact event. We present a theoretical extension to classical extreme event attribution for certain types of compound events. Based on synthetic data we illustrate how the bivariate fraction of attributable risk (FAR) differs from the univariate FAR depending on the extremeness of the event as well as the trends in and dependence between the contributing variables. Overall, the bivariate FAR is similar in magnitude or smaller than the univariate FAR if the trend in the second variable is comparably weak and the dependence between both variables is moderate or high, a typical situation for temporally co-occurring heatwaves and droughts. If both variables have similarly large trends or the dependence between both variables is weak, bivariate FARs are larger and are likely to provide a more adequate quantification of the anthropogenic influence. Using multiple climate model large ensembles, we apply the framework to two case studies, a recent sequence of hot and dry years in the Western Cape region of South Africa and two spatially co-occurring droughts in crop-producing regions in South Africa and Lesotho.

Compound Flooding: Dependence at Sub-daily Scales Between Extreme Storm Surge and Fluvial Flow

Estuaries are potentially exposed to compound flooding where weather-driven extreme sea levels can occur synchronously with extreme fluvial discharge to amplify the hazard. The likelihood of compound flooding is difficult to determine due to multiple interacting physical processes operating at sub-daily scales, and poor observation records within estuaries with which to determine potential future probabilistic scenarios. We hypothesize that fluvial extremes can occur within the peak of the surge in small/steep catchments because of rapid runoff times, whilst the length-scale in larger/flatter catchments will result in fluvial and marine extremes being out-of-phase. Data (15 min river flow and hourly sea level) spanning 40 years were analyzed to assesses the behaviour and timings of fluvial and sea level extremes in two contrasting estuaries: Humber and Dyfi (United Kingdom). Compound events were common in the Dyfi, a small/steep catchment on Britain’s west coast with fast fluvial response times. Almost half of the 937 skew-surge events (95th-percentile) occurred within a few hours of an extreme fluvial peak, suggesting that flood risk is sensitive to the storm timing relative to high tide—especially since flows persisted above the 95th-percentile typically for less than 12 h. Compound events were more frequent during autumn/winter than spring/summer. For the Humber, a larger/flatter catchment on the east coast with slower fluvial response times, extreme fluvial and skew-surge peaks were less frequent (half as many as the Dyfi) and compound events were less common (15% of events co-occurred). Although flows in the Humber persisted above the 95th-percentile for typically between one and 4 days, hence overlapping several high tides and possibly other surges. Analysis of 56 flooding events across both estuaries revealed: 1) flooding is more common in the Dyfi than Humber; 2) Dyfi flooding is driven by 99th-percentile flows lasting hours and co-occurring with a 95th percentile skew-surge; 3) Humber flooding was driven by 95th-percentile flows lasting days, or surge-driven—but rarely co-occurring. Our results suggest that compound flooding studies require at least hourly data (previous analyses have often used daily-means), especially for smaller systems and considering the potential intensification of rainfall patterns into the future.

Investigating the interaction of waves and river discharge during compound flooding at Breede Estuary, South Africa

Recent studies have drawn special attention to the significant dependencies between flood drivers and the occurrence of compound flood events in coastal areas. This study investigates compound flooding from tides, river discharge (Q) and specifically waves using a hydrodynamic model at Breede Estuary, South Africa. We quantify vertical and horizontal differences in flood characteristics caused by driver interaction, and assess the contribution of waves. Therefore, we compare flood characteristics resulting from compound flood scenarios to those in which single drivers are omitted. We find that flood characteristics are more sensitive to Q than to waves, particularly when the latter only coincide with high spring tides. When interacting with Q, however, the contribution of waves is high, causing 10–12 % larger flood extents and 45–85 cm higher water depths, as waves caused backwater effects and raised water levels inside the lower reaches of the estuary. With higher wave intensity, the first flooding began up to 12 hours earlier. Our findings provide insights on compound flooding in terms of flood magnitude and timing at a South African estuary and demonstrate the need to account for the effects of compound events, including waves, in future flood impact assessments of open South African estuaries.