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Compound weather and climate events

High-impact climate and weather events typically result from the interaction of multiple hazards across various spatial and temporal scales. These events, also known as Compound Events, often cause more severe socio-economic impacts than single-hazard events, rendering traditional univariate extreme event analyses and risk assessment techniques insufficient. It is therefore crucial to develop new methodologies that account for the possible interaction of multiple physical drivers when analysing high-impact events. Such an endeavour requires (i) a deeper understanding of the interplay of mechanisms causing Compound Events and (ii) an evaluation of the performance of climate/weather, statistical and impact models in representing Compound Events.

The European COST Action DAMOCLES coordinates these efforts by building a research network consisting of climate scientists, impact modellers, statisticians, and stakeholders. This session creates a platform for this network and acts as an introduction of the work related to DAMOCLES to the research community.

We invite papers studying all aspects of Compound Events, which might relate to (but are not limited to) the following topics:

Synthesis and Analysis: What are common features for different classes of Compound Events? Which climate variables need to be assessed jointly in order to address related impacts? How much is currently known about the dependence between these variables?
Stakeholders and science-user interface: Which events are most relevant for stakeholders? What are novel approaches to ensure continuous stakeholder engagement?
Impacts: What are the currently available sources of impact data? How can they be used to link observed impacts to climate and weather events?
Statistical approaches, model development and evaluation: What are possible novel statistical models that could be applied in the assessment of Compound Events?
Realistic model simulations of events: What are the physical mechanisms behind different types of Compound Events? What type of interactions result in the joint impact of the hazards that are involved in the event? How do these interactions influence risk assessment analyses?

Public information:

Duration of the talks: 5 minutes + 2 minutes for questions and transition to the next speaker.

Including Arne Richter Award for Outstanding ECS Lecture
Co-organized by AS4/CL5.3/HS13
Convener: Emanuele BevacquaECSECS | Co-conveners: Freya GarryECSECS, Aglaé Jézéquel, Nina Nadine RidderECSECS, Seth Westra, Philip Ward
| Tue, 24 May, 13:20–18:27 (CEST)
Room 1.31/32
Public information:

Duration of the talks: 5 minutes + 2 minutes for questions and transition to the next speaker.

Tue, 24 May, 13:20–14:50

Chairpersons: Emanuele Bevacqua, Aglaé Jézéquel


Poulomi Ganguli

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.

Baoying Shan et al.

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.


The 2018 compound of hot and dry conditions in Central Europe are unprecedented in magnitude, duration and spatial extent since measurements started in 1881. During spring and summer, these compounding of extreme conditions caused a series of severe impacts on several sectors including agriculture, forestry, transport, energy and water supply. At the beginning of the same year, windstorm Friederike concurrent with heavy snowfall caused severe damages in Ireland, Great Britain, northern France, Belgium, the Netherlands, Germany, Czech Republic and Poland. Friederike reached wind gusts of the order of 100 – 150 km/h, up to 173 km/h at Sněžka in Czech Republic and 203 km/h at Brocken in Germany.

Along the trajectory from large to the local scale, the drivers and dynamics of these events are analyzed and the impacts of the compound events are provided. Exemplary for 2018, the impacts of the compound events comprise traffic disruption, power outages, property damage by e.g., falling trees, and fatalities after the windstorm. Unprecedented winter wheat yield reductions were observed as well after the hot and dry spring and summer growing season. The impact of the drought and heat wave compound further facilitated the outbreak of bark beetle in 2018 and the following years, as a cumulative hazard and increased the probability of a dry surface water anomaly to an unexpected 68 %.

Taking advantage of the transdisciplinary research and gathered expertise in the frame of the coordinated German ClimXtreme project network (www.climxtreme.net), we analyze and characterize these 2018 events that link with severe impacts in Germany and neighboring countries in Central Europe. We focus on two key storylines with respect to the selected case studies of compound wind & rain and drought & heat. We provide a detailed overview of the data, methods and approaches used, the scales and aspects involved as well as the events’ drivers/dynamics and their multi-sectorial impacts. We finally demonstrate the importance of considering the various facets of the compound nature of extremes and respond to timely research questions that the ClimXtreme research network addresses, such as: attribution of changing compound events to climate change, understanding the variability of clustered storms, understanding the role of decadal variations on compound heat metrics, understanding and predicting the effects of climate change on landslides, analysis of past and future changes in the frequencies of compound events.

How to cite: Ellsäßer, F. and Xoplaki, E. and the The climXtreme research network on climate change and extreme events: Compound events in Germany: drivers and case studies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11534, https://doi.org/10.5194/egusphere-egu22-11534, 2022.

Rihui An et al.

In river flowing areas, the co-occurrence of high temperature and low streamflow may cause compound hydrologic hot-dry events (CHHDEs). When thermal and hydrological extremes interact, the impact can be worse than when they occur individually. Evidence shows that CHHDEs have severe socio-economic effects, such as increasing pollutant concentration, endangering aquatic species, and reducing power generation. Despite the importance, large-scale risk quantification of CHHDEs remains rarely studied due to the lack of enough simulated data at the global scale.

Therefore, the objectives of this study are threefold: (1) developing the first global hydrologic hot-dry event dataset from 1901 to 2014 (containing four attributes: duration, intensity, severity, and magnitude) based on a state-of-the-art physically-based Tightly Coupled framework for Hydrology of Open water Interactions in River–lake network (TCHOIR) model, which dynamically simulates thermal and hydrological regimes; (2) developing a robust statistical framework to conduct attribution analysis to identify drivers of compound risk (distinguishing high temperature-driven, low streamflow-driven, and dependence-driven); (3) quantifying the impact of river order and hydrologic belt on compound risk to pinpoint CHHDEs hotspots.

CHHDEs have multi-sectoral impacts, including water availability, food security, and energy production. The compound risk analysis provides crucial insights to maintain regional resilience and guide adaptation strategies.

How to cite: An, R., Liu, P., and He, X.: Global Assessment of Compound Risk of High Temperature and Low Streamflow, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4916, https://doi.org/10.5194/egusphere-egu22-4916, 2022.

Karin van der Wiel et al.

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.

Bianca Biess et al.

The recent 2021 spring-to-summer season was characterized by co-occurrent hot, dry and extremely wet extremes around the globe, raising questions regarding changing likelihoods of such extreme years in a changing climate. To address this question, we assess the likelihood of spatially compounding hot, dry and wet extremes under historic and present climate as well as under different future warming levels. The occurrence-probability of spatially compounding events and area affected in future climates under scenarios at 1.5°C, 2°C and higher levels of global warming is determined using Earth System model simulations from the 6th Phase of the Coupled Model Intercomparison Project (CMIP6). As climate change impacts are particularly severe when spatially compounding events occur in multiple regions with high exposure of people or crops, this study focuses on densely inhabited regions and important agricultural areas. 

How to cite: Biess, B., Gudmundsson, L., and Seneviratne, S. I.: Changes in likelihood and intensity of spatially co-occurring hot, dry and wet extremes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7281, https://doi.org/10.5194/egusphere-egu22-7281, 2022.

Emiliano Gelati et al.
Jens Grieger and Uwe Ulbrich

While it is known that severe winter wind storms are related with strong impacts, this study investigates the enhanced impact of compound precipitation and wind extremes. Therefore, we analyse the co-occurrence of extreme wind and precipitation using ERA5 reanalysis data for the European winter season. Co-occurring events are defined by simultaneous threshold exceedance of daily wind speed and precipitation in same or neighbouring areas.

For the quantification of impacts, we are using daily insurance records of damages for residential buildings over Germany provided by the German Insurance Association (GDV). Using the definition of co-occurring extremes, those damage records can be grouped into compound and non-compound events. Analysing insurance loss data between 1997-2016 allows comparisons of the distribution of both groups. There are much more events in the non-compound group. On the other hand, the distribution of the compound group is shifted towards higher damages with an increased median of a factor of ten.

How to cite: Grieger, J. and Ulbrich, U.: Enhanced impacts of compound precipitation and wind extremes on residential buildings, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4371, https://doi.org/10.5194/egusphere-egu22-4371, 2022.

Miloslav Müller et al.

Extreme precipitation events are associated with cyclones, atmospheric fronts or convective storms which produce high winds as well. This fact increases the probability of compound wind-precipitation events. Such events can cause even more damage than single precipitation and wind events because, for example, soil moisture makes trees less stable. The joint effect is even more significant in case of solid precipitation due to snow accumulations on trees. However, as the orographic precipitation enhancement increases mainly cold-season precipitation totals in highlands, the altitude makes the difference in the seasonal distribution of precipitation in Czechia. Thus, the local lowlands and highlands also partly differ in terms of the frequency of compound wind-precipitation events. We present this fact on data series of maximum daily wind gusts, daily precipitation totals and inter-diurnal increases in show depth from the period 1961 – 2020 at selected Czech weather stations, located in various altitudes. Extreme events are defined by the method of percentiles; frequencies of compound events are evaluated in comparison to the stochastic frequencies.

How to cite: Müller, M., Kašpar, M., and Křížová, M.: Differences between lowlands and highlands in terms of compound wind-precipitation events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9715, https://doi.org/10.5194/egusphere-egu22-9715, 2022.

Hannah Bloomfield et al.

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.

Aloïs Tilloy et al.

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.

Bastien François and Mathieu Vrac

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.

Tue, 24 May, 15:10–16:40

Chairpersons: Philip Ward, Aglaé Jézéquel


Arne Richter Award for Outstanding ECS Lecture
Jakob Zscheischler

Over recent years, research on compound weather and climate event has emerged as a new research frontier at the interface of climate science, climate impact research, engineering and statistics. Compound weather and climate events refer to the combination of multiple drivers and/or hazards that contribute to environmental or societal risk. Compound event analysis combines traditional research on climate extremes with impact-focused bottom-up assessments, thereby providing new insights on present-day and future climate risk. In this talk, I will illustrate my own trajectory into compound event analysis and highlight current and future challenges in this novel and exciting field of research. 

How to cite: Zscheischler, J.: The emergence of compound event analysis as a new research frontier, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7784, https://doi.org/10.5194/egusphere-egu22-7784, 2022.

Jakob Zscheischler, Arne Richter Award for Outstanding ECS Lecture (continuation)


Simona Meiler et al.

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.

Sunna Kupfer et al.

Recent studies on compound flooding have considered the interaction of storm surge and fluvial or pluvial flood drivers, whereas the contribution of waves to compound flooding has so far been neglected. In this study, we assess compound flooding from waves, tides and river discharge at Breede Estuary, South Africa, using a hydrodynamic model. We estimate the contribution of extreme waves to compound flooding by analysing the driver interactions and by quantifying changes in flood characteristics. We further consider the effect of waves on flood timing and compare results of compound flood scenarios to scenarios in which single drivers are omitted. We find that flood characteristics are more sensitive to river discharge than to waves, particularly when the latter only coincide with high spring tides. When interacting with river discharge, however, the contribution of waves is high, causing larger flood extents and higher water depths. With more extreme waves, flooding can begin up to 12 hours earlier. Our findings provide insights on the magnitude and timing of compound flooding in an open South African estuary and demonstrate the need to account for the effects of waves during compound flooding in future flood impact assessments of similar coastal settings with similar wave climates.

How to cite: Kupfer, S., Santamaria-Aguilar, S., van Niekerk, L., Lück-Vogel, M., and Vafeidis, A. T.: Compound flooding due to interaction of waves and river discharge at Breede Estuary, South Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1222, https://doi.org/10.5194/egusphere-egu22-1222, 2022.

Fabiola Banfi and Carlo De Michele

Compound events are extreme events whose impact is enhanced by the synergy, in time and/or space, of multiple variables. An example of this typology of events is provided by compound flooding. In this case, the resulting flooded area is increased by several factors, combining together; for example, the contemporaneous occurrence of high sea level and heavy precipitation (multivariate event), the presence of high soil saturation prior to rainfall events (preconditioned event), a precipitation event affecting several basins (spatially compounding event), or a succession of precipitation events (temporally compounding event). In this respect, we have adopted a compound analysis to study a series of floods that affected the town of Como (Northern Italy). Indeed, the town experiences recurrent damages due to the flooding of the nearby lake. In particular, we collected and analyzed 53 flood events, covering the period 1981-2020, in order to gain a better and more in-depth understanding of the phenomenon. This may eventually have important implications for the prediction and risk reduction of compound flooding.

How to cite: Banfi, F. and De Michele, C.: Investigating compound flooding in Como, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7426, https://doi.org/10.5194/egusphere-egu22-7426, 2022.

Agnieszka Indiana Olbert et al.

Many large population centres are located along estuaries where freshwater flows merge with tidally-driven sea water. In these intertidal zones the river water levels are directly affected by the upstream flow and the downstream coastal conditions. Naturally, such coastal zones can be vulnerable to flood events both from a single driver or several drivers acting in a combination. The compound coastal floods levels may generate extreme impacts even if hazards from individual drivers in isolation would be unlikely. Moreover, the complexity of compound flooding is exacerbated by the presence of interactions (e.g. tide and surge) or dependencies between drivers (e.g. river discharge and surge). To fully understand the multi-driver flood dynamics, the multiple drivers and their impacts need to be assessed in an integrated manner.

In this study the statistical and hydrodynamic models are linked to determine probabilities of multiple-driver flood events and associated risks. Cork City on the south coast of Ireland, frequently subject to complex coastal-fluvial flooding is used as a study case.  The research shows that in Cork Harbour and estuary, the tide-surge interactions have a damping effect on the total water level while dependencies between the surge residual and river flow amplify the risk of flooding. The study also shows that for the most accurate assessment of flood hazard, these phenomena need to be accounted for in the joint probability analysis. From a range of uni- and multivariate scenarios, the multivariate joint exceedance probability AND scenario that includes dependence between multiple drivers represents the most realistic representation of flood probabilities. The outputs from the statistical analysis were used to force the hydrodynamic model of Cork City floodplains. The MNS_Flood model was found to be a robust tool for mapping coastal flood hazards in tidally active river channels. Ultimately, the model results were used to build a machine-learning-based flood forecasting tool. A range of machine learning algorithms were tested to explore relationships between the flood drivers and the resulting spatially variable inundation patterns.

The information derived from the integrated statistical, hydrodynamic and machine learning tools can provide a significant support for short-term early-warning applications as well as for the long-term flood management.

How to cite: Olbert, A. I., Nash, S., Comer, J., and Hartnett, M.: Linking statistical, hydrodynamic and machine learning models for assessment of compound floods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4388, https://doi.org/10.5194/egusphere-egu22-4388, 2022.

Erika Čepienė et al.

Due to climate change, extreme floods are projected to increase in the 21st century in Europe. As a result, flood risk and flood related losses might increase. It is therefore essential to simulate potential floods not only relying on the historical but also include future projecting data. Such simulations can give necessary information for development of flood protection measures and spatial planning. This paper analyzes the risk of compound flooding in the Dane River under different river discharge and Klaipeda Strait water level probabilities. Additionally, we examined how water level rise of 1 meter in the Klaipeda Strait could impacts Dane River floods in Klaipeda City. Flood extent was estimated with Hydrologic Engineering Center's River Analysis System (HEC-RAS) and visualized with ArcGIS Pro. Research results show that the rise of the water level in the Klaipeda Strait has a greater impact on the Central part of Klaipeda City, while the maximum discharge rates of the river—on the Northern upstream part of the analyzed river section. Sea level rise of 1 m could lead to the increase of area affected by Dane floods up to three times. Floods can cause significant damage to the infrastructure of Klaipeda Port City, urbanized territories in the City Center and residential areas in the Northern part of the City. Our results confirm that, in the long run, sea level rise will significantly impact the urban areas of the Klaipeda City situated to Baltic Sea coast.

How to cite: Čepienė, E., Dailidytė, L., Stonevičius, E., and Dailidienė, I.: Sea Level Rise Impact on Compound Coastal-river Flood Risk in Klaipeda city (Baltic coast, Lithuania) , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6089, https://doi.org/10.5194/egusphere-egu22-6089, 2022.

Jose A. Jiménez et al.

From a risk management perspective, the relevance of compound events lies in the fact that they can significantly increase the intensity and/or the spatial and temporal extension of the impact (and damage) due to the synergic and/or cumulative action of different hazards. This compounding effect may overwhelm the capability of emergency-response services since these have to tackle an “unusual” high-damaging situation, they have to respond to a large number of emergency situations throughout the region at the same time, and/or they have to maintain the level of response during a relatively long period. Due to this, from this perspective, it would be important to incorporate the emergency/recovery services responsiveness to identify these events, as well as to evaluate their probability of occurrence. In this work we investigate this by parameterising this response as a time window between individual extreme events (rainfall and waves) to define the presence of a compound event. This time window depends on the intrinsic capacity of response of the available services, but also on the magnitude of contributing events as well as their spatial scale. In this work we analyse the variation of the probability of occurrence of compound heavy rainfall and wave storms events along the Catalan coast (NW Mediterranean) as a function of the responsiveness.

This work was supported by the Spanish Agency of Research in the framework of the C3RiskMed (PID2020-113638RB-C21/ AEI /  10.13039/501100011033)

How to cite: Jiménez, J. A., Costa, J., Ortego, M., and Llasat, M. C.: Integrating responsiveness in the identification and characterization of compound heavy rainfall and wave storms events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7724, https://doi.org/10.5194/egusphere-egu22-7724, 2022.

Emanuele Bevacqua et al.

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.

Tue, 24 May, 17:00–18:30

Chairpersons: Aglaé Jézéquel, Emanuele Bevacqua, Philip Ward


Stephanie Hodsman

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.

Alexandre Tuel et al.

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.

Waqar ulhassan and Munir Ahmad Nayak

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.

Kai Kornhuber and Gabriele Messori

Wintertime extremes such as cold spells and heavy precipitation events can have severe societal impacts, disrupting critical infrastructures, traffc and affecting human well-being. Here, we relate the occurrence of local and concurrent cold and wet wintertime extremes in North America and Western Europe to a recurrent, quasi-hemispheric wave-4 Rossby wave pattern in the Jetstream. We identify this pattern as a fundamental mode of Northern Hemisphere (NH) winter circulation exhibiting phase-locking behavior as the associated atmospheric circulation and surface anomalies re-occur over the same locations when the pattern's wave amplitude is high. The wave pattern is strongest over the pan-Atlantic region, and is associated with an increased probability of extreme cold or wet events by up to 300 % in certain areas of North America and Western Europe. We identify a significant increase in frequency over the past four decades (1979- 2021), which we hypothesise may derive from increased convective activity in the tropical Pacific, from where the pattern originates, while a weakened meridional temperature gradient linked to Arctic warming appears to have no direct effect on its occurrence. The identified pattern and its remote forcing might provide pathways for early prediction of local and concurrent cold or wet wintertime extremes in North America and Western Europe.

How to cite: Kornhuber, K. and Messori, G.: Compounding Wet and Cold-Extremes driven by an increasing Pan-Atlantic wave-4-pattern , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6351, https://doi.org/10.5194/egusphere-egu22-6351, 2022.

Theodoros Economou and Freya Garry

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.

Homa Ghasemifard et al.

There is ample evidence that the occurrence of deep convection changes as a result of global warming and that, across Europe, increases in convective instability as measured by CAPE are an important driver in many regions. This study is a first step in disentangling the role that climate change induced changes in flow pattern occurrence plays on the evolution of the frequency of thunderstorms. Here we evaluate the association between large-scale flow patterns with the (temporal and spatial) distribution of lightning in Europe as detected by the Met Office Arrival Time Difference Network (ATDnet). The seasonal cycle shows that the largest number of lightning days occurs in the summer from May to August, the period we, therefore, focus on. The large-scale flow pattern is expressed using the daily mean 500 hPa geopotential extracted from ERA5 reanalysis data. A hierarchical clustering algorithm (Ward's method) is applied to the daily mean geopotential heights in the selected four-month period between 2007 and 2019. The algorithm produces 9 patterns (Fig. 1), with cluster 1 being the most frequent, occurring around 20% of the time and pattern 3 being the least frequent, occurring around 4% of the time. The distributions of lightning associated with the clusters show that lightning often occurs in synoptically quiescent conditions or even underneath a ridge. Furthermore, lightning occurrence over western Europe seems to be more dependent on the synoptic situation, where it is strongly associated with clusters that have a southerly flow at 500 hPa, compared to lightning over the Alpine range or south-eastern Europe.


Fig. 1: Large-scale flow patterns are shown in nine clusters, geopotential heights of ERA5 at 500 hPa are plotted in the foreground with 50hPa intervals, and the mean number of lightning strikes per day is shown as filled contours.

How to cite: Ghasemifard, H., Groenemeijer, P., Battaglioli, F., and Pucik, T.: Dependence of lightning occurrence in Europe on large-scale flow patterns, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5346, https://doi.org/10.5194/egusphere-egu22-5346, 2022.

Natacha Legrix et al.

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.

Iliana Polychroni et al.

The Mediterranean region is an area of increasing interest due to its unique climate. Nowadays, climate change has already evident consequences, such as the rise of extreme weather events, which significantly affect peoples’ life in the highly populated urban areas of the Mediterranean. Thus, in this study, ten metropolitan cities from the wider Mediterranean region with different climatic characteristics have been selected to study the frequency and the multidecadal trends of extreme events, as well as their possible connection with the large scale and synoptic scale atmospheric variability.

Four combined extreme indices have been evaluated on annual and seasonal basis for the period 1950-2018 using the high-resolution E-OBS gridded daily mean temperature and precipitation datasets (0.1° x 0.1°; v.19e) from the European Climate Assessment & Dataset (ECA&D, Klein Tank et al. 2002, www.ecad.eu). These combined extreme indices refer to the joint modes of temperature and precipitation extremes, concerning the co-occurrence of Cold/Dry days (CD), Cold/Wet days (CW), Warm/Dry days (WD), Warm/Wet days (WW), which can reflect extreme conditions better than temperature or precipitation statistics considered separately (Beniston, 2009; 2011). The links of the extreme events with the atmospheric variability are investigated based on large-scale teleconnection indices and spatiotemporal distribution of cyclonic activity. Toward this, the comprehensive climatology of Mediterranean cyclones assembled was used by applying a cyclone tracking algorithm (Murray and Simmonds, 1991; Flocas et al., 2011) with respect to the ECMWF ERA5 Interim mean sea level pressure fields since 1950.

The findings of the analysis showed distinct temporal and spatial variations of the combined extremes occurrences in the cities across the Mediterranean, which can be attributed to the effects of its complex topography, as well as to the non-uniform influence of the atmospheric variability. Specifically, the CD and WD indices have higher annual occurrences than the CW and WW, which indicates that the wider Mediterranean region experiences more dry days, either cold or warm, than wet days. The urban areas most affected by cold/dry events are located on the western Africa, while almost all urban areas around the Mediterranean coast are impacted by higher number of warm/dry events, with increasing trends.

References: Beniston M., 2009, Geophys. Res. Lett., 36, L07707; Beniston M., and Coauthors, 2011, Int. J. Climatol., 31, 1257-1263; Murray and Simmonds, 1991 Aust Met Mag 39 155 166; Flocas et al., 2010, J Climate, 23(19), 5243-5257

How to cite: Polychroni, I., Hatzaki, M., Nastos, P. T., Kouroutzoglou, J., and Flocas, H. A.: Climate extremes in Mediterranean metropolitan cities and atmospheric variability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10342, https://doi.org/10.5194/egusphere-egu22-10342, 2022.

Fulden Batibeniz et al.

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.

Sonia Quiroga et al.

Global climate change and more frequent and severe compound events poses a threat to agricultural productivity in China with important impacts on human development, and social stability. China has 18% about 25% of the world's grain production--accounting rice up to 34% of it.  Much of the existing research has focused on the important average effects of climate warming on rice yields showing. However, there is evidence about nonlinear interactions when compound events being present (ie. frost and heavy rainfall). As some of the major natural disasters in China at present, the overall spatial extent of drought and floods in China are expected to change significantly in the future, with more extreme events resulting. This paper analyzes total factor productivity growth in China's rice production to compute technological progress as an adaptative factor for total factor productivity growth response to compound extreme events. Labor inputs, education, fertilizer application and energy use are considered as control factors, jointly with socio-economic factors the the adoption of agricultural technology by growers. The Levinsohn-Petrin consistent semi-parametric estimation method was used to empirically analyze input-output panel data on rice yields in 30 Chinese provinces from 1990 to 2019 and to simulate the level of rice yield at the end of the 21st century under different RCPs scenarios. The model has stronger prediction ability for the central-eastern and southern production areas of China and reveals that rice yields may show opportunities of increase under average conditions for some climate scenarios, but it shows a bigger risk and vulnerability to compound extreme events.


How to cite: Quiroga, S., Suárez, C., Wang, H., and Hernanz, V.: Interactions between compound extreme events and technological change over rice yield in China as an opportunity to adapt. , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8014, https://doi.org/10.5194/egusphere-egu22-8014, 2022.

Fabian Reddig et al.

The Mediterranean region has been identified as a hotspot of climate change characterized by a large tree mortality. Especially holm (Quercus ilex L.) and cork oak trees (Quercus suber L.) in high-value and nature-based agroforestry systems (in Spain known as dehesa) have multiple positive effects, e.g., on the microclimate, carbon storage, erosion prevention, increase of soil water content and soil nutrient concentration. Many studies dealing with the oak decline (also called seca) reported the infestation by root pathogens, in particular the soil-born pathogen Phytophthora cinnamomi, as the main driver. However, rapidly, the focus shifted to the interaction of the pathogen and single abiotic conditions like drought.

We assume that compound events (co-occurring warm spells and soil drought) have a larger correlation with vegetation indices than single climatic drivers. We analyse time series of two vegetation indices, namely the Normalized Difference Vegetation Index (NDVI) and the kernel Normalized Difference Vegetation Index (kNDVI) as an indicator for greenness and vitality. In particular, we focus on the trend of both indices over about two decades (2003-2021) in eight different plots in our study area, on a dehesa in Huelva province, Andalusia. Subsequently, we correlate them with the decomposed signal of compound events.

Based on precipitation and temperature data, we calculated two drought indices, namely the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). We then used these indices together with temperature to calculate so-called compound events, a co-occurrence of extreme values in multiple environmental drivers. To assess the status of the vegetation, we calculated the NDVI and its newly proposed kernel variant kNDVI from MODIS (MYD13Q1) and Landsat (4-5, 7,8) data in eight different plots in our study area. The kNDVI is a non-linear generalization of the NDVI and showed good behaviour in the Mediterranean and correlates stronger with the gross primary productivity (GPP) than the original NDVI. To extract physically meaningful information, we decomposed the time series signals with the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method by Torres et al. (2011) into seasonality, trend, and a remainder part. CEEMDAN is suitable for non-linear and non-stationary time series. To analyse the relationships between vegetation indices and possible climatic drivers, we subsequently calculate lagged cross-correlations (i.e., correlation between different time series) between the Intrinsic Mode Functions (IMFs) of the signal expressing the trend and different seasonalities.

We extracted different positive and significant (p < 0.01) NDVI trend signals from the MODIS time series. The seasonal component corresponded to the expected annual cycle. Based on these first results, we will correlate the NDVI and kNDVI trend signals with the calculated compound events to observe their role in the oak tree mortality.

How to cite: Reddig, F., Bareth, G., and Bogner, C.: Effect of compound events on oak tree vitality in a climate change hotspot: analysis of time series in a traditional Spanish dehesa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9852, https://doi.org/10.5194/egusphere-egu22-9852, 2022.

Luise-Ch. Modrakowski et al.

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.