NH10.2

The precipitation deficit-temperature feedback can severely impact multiple sectors, such as reduction in crop yield to critical infrastructure failures, especially in low latitude areas (< 30°N). Typically, a heatwave event coincides with a significant decline in surface wind speed due to atmospheric blocking and is often compounded by persistent precipitation-deficit leading to meteorological droughts. Anomalous warm-and-dry air, which comes in torrents, results in an abrupt increase in air temperature that strengthens the local land-atmosphere feedback via soil desiccation. Based on daily meteorological observations covering the 1970-2018 period, first, I show a spatial coherence in the timing of unprecedented hot-dry events over major urban and peri-urban locations of the Indian sub-continent (8°4'N and 37°6'N). Surface wind data confirms a significant decline in low wind speed over most of the locations, especially over the eastern coastal plains of the country. Further, the compound occurrence of extreme temperature and low wind speed act as a preconditioning driver for sequential short (or long)-duration precipitation deficits across most of the sites. A copula-based joint distribution framework incorporating the compounding effect of high temperature, low wind speed, and precipitation deficit reveals a T-year severe hot-dry event tends to become more frequent. Finally, I show a median 6-fold amplifications in compound hot-dry frequency than that of the expected annual number of 50-year temperature extreme. The inferred amplifications are more pronounced in low-lying urban-coastal areas than in the interior locations, where decadal changes in (significant) increase in extreme temperature at several locations are contrasted by a concurrent decrease in surface wind speed.  

How to cite: Ganguli, P.: Compound Hot-Dry Events in Urban India: Variability and Drivers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-934, https://doi.org/10.5194/egusphere-egu22-934, 2022.

Under the challenge of climate change, the extremes, especially for extreme temperature, are observed at an increasing pace and are expected to be more severe in the future. It is critical to study heatwaves concurrently with droughts because of the intensification of negative impacts, such as exacerbating water shortage, crop failure and GPP reduction, wildfire and tree mortality, etc. This research focuses on compound events of droughts and heatwaves and presents a framework for the identification of drought or heatwave events and their compounds.

While most studies only look at the summer season, we also consider compound drought and heatwave events in the winter season, as these are also important in view of their significant influence on wildfires, insect outbreaks, seed germination, etc.

We introduce the notion of "relative heatwave" as being an extreme event compared with the average of the previous 30-year temperatures for that period. Drought and heatwave events are then identified based on SPI (standardized precipitation index) and SHI (standardized heatwave index). To overcome limitations arising from the scale inconsistency (monthly drought with daily heatwave) and coarse resolution (monthly or weekly drought), we apply the daily SPI and daily SHI, bringing a more accurate measure of the start and end dates, and severity. We also propose an objective, convenient and robust method to identify the statistically extreme and independent drought and heatwave events. Thresholds for removing small-scale events and merging proximate events are found by assuming the severity of the events to follow a generalized extreme value distribution and their arrivals to follow a Poisson process. Finally, we introduce four possible ways of identifying compound events (union, conditioned on drought, conditioned on heatwave, and intersection).

To demonstrate our methodology, we made use of 120 years of daily precipitation and daily average temperature observed at the Belgian meteorological institute in Uccle, near Brussels.

How to cite: Shan, B., De Baets, B., and Verhoest, N.: Compound drought and heatwave identification: daily-scale independent extreme events based on 120-year observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3877, https://doi.org/10.5194/egusphere-egu22-3877, 2022.

Three consecutive dry summers in western Europe (2018-2019-2020) had widespread negative impacts on society and ecosystems, and started societal debate on (changing) drought vulnerability and needs to revise adaptation measures. To facilitate that discussion, we investigate multi-year droughts in the Rhine basin, with a focus on event probability in the present climate and in future warmer climates. Additionally, we studied the temporally compounding physical processes leading to multi-year drought events. A combination of multiple reanalysis datasets and multi-model large ensemble climate model simulations was used to robustly analyse the statistics and physical processes of these rare events. In these data, we identify two types of multi-year drought events (consecutive meteorological summer droughts and long-duration hydrological droughts), and show that these occur on average about twice in a 30 year period in the present climate, though natural variability is large (zero to five events in a single 30 year period). Projected decreases in summer precipitation and increases in atmospheric evaporative demand, lead to a doubling of event probability in a world 1 °C warmer than present and an increase in the average length of events. Consecutive meteorological summer droughts are forced by two, seemingly independent, summers of lower than normal precipitation and higher than normal evaporative demand. The soil moisture response to this temporally compound meteorological forcing has a clear multi-year imprint, resulting in a relatively larger reduction of soil moisture content in the second summer and potentially more severe drought impacts. Long-duration hydrological droughts start with a severe summer drought followed by lingering meteorologically dry conditions. This limits and slows down the recovery of soil moisture content to normal levels, leading to long-lasting drought conditions. This initial exploration provides avenues for further investigation of multi-year drought hazard and vulnerability in the region, which is advised given the projected trends and vulnerability of society and ecosystems.

How to cite: van der Wiel, K., Batelaan, T., and Wanders, N.: Strong increase of probability of Northwestern European multi-year droughts in a warmer climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5455, https://doi.org/10.5194/egusphere-egu22-5455, 2022.

Strong winds and extremes in precipitation are capable of producing devastating socio-economic impacts across Europe. Although it is well known that individually these drivers cause billions of Euros of damage, their combined impacts are less well understood. Previous work has typically either focused on daily or seasonal timescales, demonstrating that compound wind and precipitation events are commonly associated with passing cyclones or particularly wet and windy years respectively. This study systematically investigates the relationships between national wind and flood damage metrics at all timescales ranging from daily to seasonal during the winter season. This work is completed using high resolution meteorological reanalysis and river flow datasets to explore the historical period (1980-present). As well as this, data from the UKCP18 climate projections at 2.2km and 12km resolution is used to understand historical sampling uncertainty, and the possible impacts of future climate change.

The correlation between national aggregate wind gusts and precipitation peaks at ~10 days; whereas, the correlation between national aggregate wind gusts and river flows peaks at ~3 weeks. When using more impact focussed metrics of compound wind and flood events, such as storm severity and flooding indices, the strongest correlations are seen at seasonal timescales. Results show the historical correlation between wind and flood damage becomes weaker as the definition of the metrics become more impact focussed, and this is true across all timescales from daily to seasonal. This change in relationship is of key importance to the insurance industry who require actionable information based on both the meteorological hazards and on the exposure of their portfolios. The work is designed to support climate analytics for financial institutions, as part of the UK Centre for Greening Finance and Investments (UKCGFI). Results incorporating the impacts of climate change on compound wind and flood events will also be discussed.

How to cite: Bloomfield, H., Bates, P., Shaffrey, L., Hillier, J., James, R., and Pianosi, F.: Quantifying the relationship between flood and wind damage over North-West Europe, in a present and future climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4727, https://doi.org/10.5194/egusphere-egu22-4727, 2022.

Compound hazards refer to two or more different natural hazards occurring over the same time period and spatial area. Compound hazards can operate on different spatial and temporal scales than their component single hazards. This work proposes a definition of compound hazards in space and time and presents a methodology for the Spatiotemporal Identification of Compound Hazards (SI–CH). The approach is applied to the analysis of compound precipitation and wind extremes in Great Britain, from which we create a database. Hourly precipitation and wind gust values for 1979–2019 are extracted from climate reanalysis (ERA5) within a region including Great Britain and the British channel. Extreme values (above the 99% quantile) of precipitation and wind gust are clustered with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, creating clusters for precipitation and wind gusts. Compound hazard clusters that correspond to the spatial overlap of single hazard clusters during the aggregated duration of the two hazards are then identified. Our ERA5 Hazard Clusters Database consists of 18,086 precipitation clusters, 6190 wind clusters, and 4555 compound hazard clusters. The methodology’s ability to identify extreme precipitation and wind events is assessed with a catalogue of 157 significant events (96 extreme precipitation and 61 extreme wind events) in Great Britain over the period 1979–2019. We find a good agreement between the SI–CH outputs and the catalogue with an overall hit rate (ratio between the number of joint events and the total number of events) of 93.7%. The spatial variation of hazard intensity within wind, precipitation and compound hazard clusters are then visualised and analysed. The study finds that the SI–CH approach can accurately identify single and compound hazard events and represent spatial and temporal properties of these events. We find that compound wind and precipitation extremes, despite occurring on smaller scales than single extremes, can occur on large scales in Great Britain with a decreasing spatial scale when the combined intensity of the hazards increases. 

How to cite: Tilloy, A., Malamud, B., and Joly-Laugel, A.: A Methodology for the Spatiotemporal Identification of Compound Hazards: Wind and Precipitation Extremes in Great Britain (1979–2019), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11194, https://doi.org/10.5194/egusphere-egu22-11194, 2022.

Many climate-related disasters often result from a combination of several climate drivers, also referred to as "compound events''. By interacting with each other, these hazards can lead to huge environmental and societal impacts, at a scale potentially far greater than any of these climate drivers could have caused separately. Marginal and dependence properties of climate drivers, as well as their changes over time, are key statistical properties influencing the probabilities of compound events. A better understanding of how the statistical properties of variables leading to compound events evolve and contribute to the change of their occurences is a crucial step towards risk assessments. Here, based on copula theory, we develop a new methodology to quantify the contribution of marginal and dependence properties to the overall probability of compound events. For illustration purposes, the methodology is applied to analyse changes of probability for compound precipitation and wind extremes, and their potential time of emergence, in a 13-member multi-model ensemble (CMIP6) over the region of Brittany (France). Results show that compound precipitation and wind extremes probabilities from CMIP6 ensembles mostly increase for the end of the 21st century. Yet, the contribution of marginal and dependence properties to these changes of probabilities can be very different from one model to another, reflecting a large uncertainty in climate modelling. These results highlight the importance of both marginal and dependence properties changes for future risk assessments due to compound events, and the need to understand the differences' sources of statistical properties between climate models.  

How to cite: François, B. and Vrac, M.: Emergence of compound events: quantifying the importance of marginal and dependence properties changes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3843, https://doi.org/10.5194/egusphere-egu22-3843, 2022.

Intense precipitation from tropical cyclones (TCs), typically accompanied by wind-driven storm surges and highly destructive winds, constitutes a significant threat for compound flooding and wind-driven impacts in many coastal regions worldwide. However, most present TC risk assessment methods only consider wind as the driving hazard and thus underestimate impacts emerging from compounding TC sub-hazards. Further, it is crucial to understand how this risk will shift and intensify in a warming climate. We thus present a coupled, physics-based modeling approach for the coastal area of Metropolitan Manila (PHL) to explicitly represent TC rainfall-induced freshwater flood, TC wind-driven storm surges, and direct impacts from TC wind for present and future climate. We use a large set of synthetic TCs generated from historical climate data (1985-2014) and from the late 21st century (2071-2100) SSP585 warming scenario to simulate TC wind fields and rainfall intensity data. Our modelling chain includes a hydrodynamical component to convert TC precipitation to freshwater flood and model wind-driven storm surges. We evaluate the compound socio-economic impacts from the TC sub-hazards using a state-of-the-art, open-source probabilistic damage model (CLIMADA). Ultimately, our advances in TC impact modelling can be applied in vulnerable coastal regions worldwide, enabling better-informed adaptation decisions and mitigation strategies.

How to cite: Meiler, S., Sarhadi, A., Emanuel, K., and Bresch, D. N.: Advancing compound modelling of tropical cyclone wind, surge and rain impacts – now and in a changing climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7289, https://doi.org/10.5194/egusphere-egu22-7289, 2022.

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 development of research on compound events, four compound event types were introduced, namely (a) preconditioned, (b) multivariate, (c) temporally compounding, and (d) spatially compounding events. However, guidelines on how to study these types of events are still lacking. Here, we consider four case studies, each associated with a specific event type and a research question, to illustrate how the key elements of compound events (e.g., analytical tools and relevant physical effects) can be identified. These case studies show that (a) impacts on crops from hot and dry summers can be exacerbated by preconditioning effects of dry and bright springs. (b) Assessing compound coastal flooding in Perth (Australia) requires considering the dynamics of a non-stationary multivariate process. For instance, future mean sea-level rise will lead to the emergence of concurrent coastal and fluvial extremes, enhancing compound flooding risk. (c) In Portugal, deep-landslides are often caused by temporal clusters of moderate precipitation events. Finally, (d) crop yield failures in France and Germany are strongly correlated, threatening European food security through spatially compounding effects. These analyses allow for identifying general recommendations for studying compound events. Overall, our insights can serve as a blueprint for compound event analysis across disciplines and sectors.

How to cite: Bevacqua, E., De Michele, C., Manning, C., Couasnon, A., Ribeiro, A. F. S., Ramos, A. M., Vignotto, E., Bastos, A., Blesić, S., Durante, F., Hillier, J., Oliveira, S. C., Pinto, J. G., Ragno, E., Rivoire, P., Saunders, K., van der Wiel, K., Wu, W., Zhang, T., and Zscheischler, J.: Guidelines for studying diverse types of compound weather and climate events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2325, https://doi.org/10.5194/egusphere-egu22-2325, 2022.

Temporal compound events are defined in recent literature as successive events which impact the same geographical region. These kinds of events have the ability to cause catastrophic impacts. If we treat them as single events in a catastrophe model, the overall event magnitude, impact, and subsequent losses would be underestimated. The United Kingdom is vulnerable to temporally-compounding events due to low-pressure systems from the north Atlantic Ocean: the storms Desmond, Eva, Frank that occurred in December 2015 and Ciara, Dennis, Jorge that occurred in February 2020 are some recent, notable temporally compounding events that caused large economic losses.

For insurers and reinsurers to appropriately manage their exposure, it is imperative the tools they use truthfully reflect the risk of an insured asset being inundated several times due to temporal compound events. It has been recognised in previous research that catastrophe models are limited in their ability to handle connected, multi-hazard events. In addition, the risk of loss from temporal compound events should be demonstrated accordingly as the loss from a second event may not be as severe as the initial impact. Therefore, the definition of an event within a catastrophe model’s event set is extremely important. This provided the motivation to review temporal compound event representation in JBA Risk Management’s stochastic event set.

We manipulated various versions of stochastic event sets for known historical temporal compound events, and we explored how these different event sets alter the losses from catastrophe models. This research allowed us to interpret the impact various modelling strategies would have on (re)insurance companies should similar events occur in the future and provided further questions on how is best to model natural catastrophes.

How to cite: Hodsman, S.: Temporal compound events: Are they represented in catastrophe models?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5659, https://doi.org/10.5194/egusphere-egu22-5659, 2022.

The successive occurrence of extreme precipitation events on sub-seasonal (weekly to monthly) timescales can lead to large precipitation accumulations and severe impacts for humans and ecosystems. We take here a global perspective to explore the spatio-temporal distribution of sub-seasonal temporal clustering of extreme precipitation (TCEP) and the physical mechanisms that are responsible for it. We first discuss the seasonal distribution of TCEP and its statistical significance, assessed with Ripley’s K function. Though TCEP is mainly confined to the tropical oceans, it is also significant regionally in the Northern Hemisphere extra-tropics, especially along the eastern margins of ocean basins. We then examine thanks to Generalized Linear Models how large-scale modes of variability and regional dynamics affect the occurrence of temporal clustering across the world. In the tropics, ENSO, the Indian Ocean Dipole and the MJO all modulate TCEP frequency, while the effect of the North Atlantic Oscillation and Pacific North American pattern dominate in the Northern Hemisphere. We conclude with an impacts-focused discussion of how TCEP affects river discharge across Europe. TCEP leads to a higher and more prolonged discharge response, especially in pluvial-dominated catchments, and thus to higher flooding risk.

How to cite: Tuel, A., Schaefli, B., Zscheischler, J., and Romppainen-Martius, O.: Sub-seasonal temporal clustering of extreme precipitation: Spatio-temporal distribution, physical drivers and impacts, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1055, https://doi.org/10.5194/egusphere-egu22-1055, 2022.

Compound drought and heatwaves (CDHWs) often cause severe ecological and socioeconomic damages; however, these impacts amplify when such temporally compound events occur concurrently in distant regions. Although spatially concurrent univariate extremes (e.g., droughts) have been explored globally and usually linked to large-scale climatic oscillations, such as El-Niño Southern Oscillation (ENSO) and global warming, spatial co-occurrence of CDHWs remains understudied. Here, we present a novel methodology to identify regions that have higher-than-expected chances of experiencing CDHWs concurrently. Using daily precipitation and temperature data from Climate Prediction Centre (CPC) and ERA5, we find robust spatially concurrent CDHWs in multiple regions that are thousands of kilometres apart, revealing teleconnections in CDHWs. Composite anomalies of geopotential heights and sea surface temperatures reveal El-Niño as the major cause of teleconnections in CDHWs in tropical and sub-tropical regions. Height anomalies during extra-tropical teleconnections reveal quasi-stationary Rossby waves that often produce persistent atmospheric blockings over climacteric locations in vicinity of compound regions. The insights gained here offer new avenues in studying spatially and temporally concurrent hydrologic extremes.

How to cite: ulhassan, W. and Nayak, M. A.: Role of climatic oscillations in causing spatially and temporally compound droughts and heatwaves, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10344, https://doi.org/10.5194/egusphere-egu22-10344, 2022.

The analysis of climate change impacts involves the utilisation of climate model output. Quite often, quantities of interest are compound events rather than “raw variables” such as temperature. Questions such as "what is the probability that temperature will exceed a high threshold for five consecutive days and how will this change in the future?" are quite common. Statistical (probabilistic) modelling of climate model output can be used to answer such questions by stochastically simulating the raw variables and then quantifying the compound events as a “by-product”. This is particularly useful since any compound event can be investigated using the same approach – since the raw variables are the ones being modelled.

Such approaches however do not always scale well with big data sets and are often too complicated to even interpret appropriately. Here we present a way of analysing such data, using the (well-established) idea of a ‘moving window’ in conjunction with penalised smoothing splines and Generalised Additive Models (GAMs). The probabilistic nature of the resulting predictions provides a way of extrapolating beyond the range of the original data to robustly quantify the likelihood of rare events and their future changes. The approach is implemented in the Bayesian framework which results in full quantification of the associated uncertainty in using this method, e.g. increased uncertainty for extreme events way outside the range of the original data.

The method is both scalable and paralleliseable and we present it in quantifying changes in regional climate model output. Due to the simplicity of the components that make up the approach, it can be argued that it is highly interpretable as well as robust to the choice of variables – we demonstrate this using temperature as well as humidity and precipitation, variables which are known to have very different statistical behaviour. We also demonstrate how the approach can be extended to capture the behaviour of more that one variable and use it to quantify the changes in compound hazard events such as the frequency of “warm-dry” days.

How to cite: Economou, T. and Garry, F.: Probabilistic modelling and simulation of big spatio-temporal climate data for quantifying future changes of compound events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3392, https://doi.org/10.5194/egusphere-egu22-3392, 2022.

Extreme events, such as marine heatwaves (MHWs), severely impact marine ecosystems. Of particular concern are compound events, i.e. situations when conditions are extreme for multiple ecosystem stressors, such as temperature and net primary productivity (NPP). In 2013-2015 for example, an extensive MHW, known as the Blob, cooccurred with low NPP and severely impacted marine life in the northeast Pacific, with cascading impacts on fisheries. Yet, little is known about the distribution and drivers of compound MHW and low NPP extreme events. We use satellite-based sea surface temperature and NPP estimates to provide a first assessment of these compound events. We reveal hotspots of compound MHW and low NPP events in the equatorial Pacific, along the boundaries of the subtropical gyres, and in the northern Indian Ocean. In these regions, compound events that typically last one week occur three to seven times more often than expected under the assumption of independence between MHWs and low NPP events. At the seasonal timescale, most compound events occur in summer in both hemispheres. At the interannual time-scale, their frequency is strongly modulated by large-scale modes of climate variability such as the El Niño-Southern Oscillation, whose positive phase is associated with increased compound event occurrence in the eastern equatorial Pacific by a factor of up to four. Using large ensemble simulations of two Earth system models, we then investigate the exact physical and biological drivers of these compound events. We find that both models suggest that MHWs in the low latitudes are often associated with low surface ocean nutrient concentrations due to enhance stratification and/or reduced upwelling, which limits the growth of phytoplankton resulting in extremely low NPP. However, the models show large disparities in simulated compound events and its drivers in the high latitudes. This identifies an important need for improved process understanding for high latitude compound MHW and low NPP events.

How to cite: Legrix, N., Zscheischler, J., Laufkötter, C., Rodgers, K., Rousseaux, C., Yamaguchi, R., and Frölicher, T.: Compound high temperature and low net primary production extremes in the ocean over the satellite period, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1469, https://doi.org/10.5194/egusphere-egu22-1469, 2022.

It is now certain that human-induced climate change is increasing the frequency, intensity, and spatial extent of climate and weather extremes globally. While a number of studies investigated these characteristics of individual extremes, an IPCC risk framework-like holistic approach introducing the potential impacts of the changes in concurrent and multivariate extremes is more informative. By using CMIP6 climate projections, historical and future population estimates we assess the influence of human and climate change on four concurrent extreme events (heatwave–drought, warm nights–high relative humidity, extreme 1-day precipitation–wind, drought–warm days-low relative humidity) in the preindustrial period (1850-1900) and at four global warming levels (GWLs from +1 °C to +3 °C). Our results show that concurrent occurrences of the investigated extremes become 1.2 to 8 times more frequent for the 3ºC GWL. The most dramatic increase is identified for compound heatwave–drought events, with an eight-fold increase in subtropical countries, a seven-fold increase in northern middle and high latitude countries, and a five-fold increase in tropical countries, respectively. Additionally, the number of events per capita showing the contribution of climate change alone exhibits a dramatic increase in compound heatwave–drought and warm days–low relative humidity-drought events over the Mediterranean countries, Europe, China, Australia, Russia, the United States, and the Northern part of South America, emphasizing the potential risk increase in the case of lack of concerted effort to cut greenhouse gas emissions.

How to cite: Batibeniz, F., Hauser, M., and Seneviratne, S. I.: Hotspots of Changes in Exposure to Multivariate Extremes at Different Global Warming Levels, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5662, https://doi.org/10.5194/egusphere-egu22-5662, 2022.

The risk of compound events is defined as probable weather and climate events where many factors and dangers combine to cause catastrophic socio-economic repercussions. Compound events affecting vulnerable societies are thus a major security risk. Compound events are rarely documented, making preparedness difficult. This study examines how climate risk management is perceived and practiced in flood-prone Danish municipalities (i.e., Odense, Hvidovre, and Vejle). These practices reveal how different understandings of compound events influence risk perceptions and, thus, policy decisions. We discovered through expert interviews and policy documents that specific Danish municipalities recognize compound events as a condition or situation and develop precautionary principles. Depending on their location, they see compound events as either a vague tendency (Odense), a trend to be monitored (Hvidovre), or a partial reality (Vejle). They see flood drivers and their combinations as serious physical hazards to which they adapt. By focusing on local governance systems, it revealed the need to critically assess the mismatch between responsibility and capability, as well as the ongoing fragmentation of services related to climate concerns in Danish municipalities. The findings show that one discipline cannot address the complicated challenge of compound events. The report recommends expanding scientific techniques and increasing local focus in compound event research to stimulate creative thinking, better planning, and enhanced risk management.

How to cite: Modrakowski, L.-Ch., Su, J., and Nielsen, A. B.: The precautionary principles of the potential risks of compound events in Danish municipalities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11062, https://doi.org/10.5194/egusphere-egu22-11062, 2022.