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?
vPICO presentations: Wed, 28 Apr
Impact-based, seasonal mapping of compound hazards is proposed. It is pragmatic, identifies phenomena to drive the research agenda, produces outputs relevant to stakeholders, and could be applied to many hazards globally. Illustratively, flooding and wind damage can co-occur, worsening their joint impact, yet where wet and windy seasons combine has not yet been systematically mapped. Here, seasonal impact-based proxies for wintertime flooding and extreme wind are used to map, at 1° × 1° resolution, the association between these hazards across Europe within 600 years as realized in seasonal hindcast data. Paired areas of enhanced-suppressed correlation are identified (Scotland, Norway), and are shown to be created by orographically-enhanced rainfall (or shelter) from prevailing westerly storms. As the hazard metrics used are calibrated to losses, the maps are indicative of the potential for damage.
How to cite: Hillier, J. K. and Dixon, R. S.: Seasonal impact-based mapping of compound hazards, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1247, https://doi.org/10.5194/egusphere-egu21-1247, 2021.
Positive trends of droughts and heatwaves’ frequency and severity have been reported for several regions, namely for Southeast Brazil (SEB). Nevertheless, this region still lacks a comprehensive assessment of compound drought and heatwave (CDH) events. This study aims to (1) analyse the historical evolution of CDH events in SEB, to (2) characterize the land and atmosphere conditions as well as to (3) disentangle the physical mechanisms behind the observed record-breaking dry and hot events recorded during the 2013/14 and 2014/15 austral summer seasons.
Meteorological data, including maximum temperature (Tmax) and precipitation records were extracted from the ERA5 reanalysis datasets. Soil moisture data were obtained from Global Land Evaporation Amsterdam Model (GLEAM v3.3a). Drought conditions were defined at a monthly scale, using the ERA5 precipitation records, and considering 3-month Standardized Precipitation Index (SPI) values <–1. Heatwaves were defined as periods of consecutive days with daily Tmax values above a climatological calendar day Tmax percentile (80th, 90th, 95th percentile). A compound event was defined as a heatwave period occurring during a month under drought conditions.
Our results confirm that the São Paulo, Rio de Janeiro and Minas Gerais states have recorded pronounced and statistically significant increases in the number of compound summer drought and heatwave episodes. The recent summer seasons of 2013/14 and 2014/15 were examples of an association between outstanding drought and heatwave conditions stemmed by severe precipitation deficits and a higher-than-average occurrence of atmospheric blocking patterns. This inter-relationship was controlled by two soil–atmosphere coupling regimes. The first regime (energy-limited) occurred during the first half of both summer seasons, in which consecutive hot periods coupled with a long-term precipitation deficit induced drought conditions. The absence of precipitation and the clear sky conditions maintained. Consequently, the severe dryness of the surface was enhanced, until a second high coupling regime (water-limited) was imposed, in which the hot events were amplified by the simultaneously drought conditions. At this stage, the surface started to disproportionally dissipate the incoming radiation as sensible heat, yielding the mega-heatwaves recorded over SEB during this period.
JG received funding from the COST Action (CA17109) supported by COST (European Cooperation in Science and Technology) and acknowledges FCT (Fundação para a Ciência e a Tecnologia) for the Ph.D. grant 2020.05198.BD. AR and RT acknowledge FCT under project IMPECAF (PTDC CTA - CLI28902 2017) and PMS under project HOLMODRIVE (PTDC/CTA-GEO/29029/2017). RL was supported by CNPQ (grant 05159/2018-6), by FAPERJ (grant 202.714/2019) and acknowledges project FireCast (PCIF/GRF/0204/2017); AR, PMS and RT are also grateful by the FCT funding UID GEO 50019 2013–Instituto Dom Luiz. DGM acknowledges support from the European Research Council (ERC) under grant agreement 715254 (DRY–2–DRY).
How to cite: Geirinhas, J. L., Russo, A., Libonati, R., M. Sousa, P., G. Miralles, D., and M. Trigo, R.: Historical Assessment of Compound Summer Drought and Heatwave Events in Southeast Brazil, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-930, https://doi.org/10.5194/egusphere-egu21-930, 2021.
The simultaneous or sequential occurrence of extreme climate events, often designated as compound events, has recently received further attention, due to the higher impacts they cause, when compared to individual extreme events, and also due to the expected increase in their frequency within a warming climate context. The occurrence of compound dry and hot extremes has been observed in several regions throughout the world. The recent extreme bushfire season of 2019-2020 in Australia was probably driven by the sequential occurrence of spring drought and severe summer heatwaves.
Previous works have used correlation analysis to study these extreme dry and hot compound events, but it has been shown that, although necessary, antecedent drought is not a sufficient condition for the occurrence of hot extremes. For this reason, in this work we used copula functions to study the joint probability of occurrence of these extremes. This method, already applied for this type of compound events in other regions of the globe, allows to study dependences between variables, even if they are non-linear.
The drought conditions were assessed using the Standardized Precipitation Evaporation Index (SPEI) at time scales of 1, 3, and 6 months, using data from the CRU TS 4.04 dataset. The Number of Hot Days (NHD) and Number of Hot Nights (NHN) were used to quantify the hot extremes in the summer months in Australia and were computed with temperature data from the ERA5 dataset. The probability of occurrence of hot extremes given drought/non-drought conditions were estimated over the different regions of Australia. Differences in these probabilities further suggest the effect on hot summer extremes by droughts occurring on the concurrent and on previous months.
Acknowledgements: This work was partially supported by projects FireCast (PCIF/GRF/0204/2017), and IMPECAF (PTDC/CTA-CLI/28902/2017).
How to cite: Páscoa, P., Gouveia, C., Russo, A., and Ribeiro, A.: Joint probability analysis of drought and hot extremes in Australia, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5984, https://doi.org/10.5194/egusphere-egu21-5984, 2021.
Compound weather events arise from combination of multiple climatic drivers or hazards and often result in disastrous socio-economic impacts. Compound drought and heatwave (CDHE) events have received considerable attention in recent years, but limited attention is given towards the understanding of feedback relationships between droughts and heatwaves at global hotspots of the compound events. Here, we identify the potential hotspots of extreme compound drought and heatwaves (ECDH) over the globe using standardized precipitation index (SPI) and Excess heat factor (EHF) as metrics for droughts and heatwaves, respectively. Besides the well know positive feedback between droughts and heatwaves, i.e., heatwaves amplify droughts and vice-versa, we hypothesize and test the possibility of negative feedback at distinct hotspots where heatwaves tend to abate droughts. Multiple hotspots were identified with positive and negative feedbacks among drought and heatwave intensities, supporting our hypothesis. We also analyzed the role of different local and large-scale global drivers (such as El-Niño Southern Oscillation) on the feedbacks at the hotspots. Our analysis has implications in predicting extreme compound droughts and heatwaves and provides new insights that will foster further research in this direction.
How to cite: Ul Hassan, W. and Ahmad Nayak, M.: Hotspots of extreme compound drought and heatwaves: Role of feedback and climate oscillations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11426, https://doi.org/10.5194/egusphere-egu21-11426, 2021.
Compound dry and hot events (CDHEs) are commonly defined as the concurrent or consecutive occurrences of the two events, which could lead to larger negative impacts than do individual extremes. The variation of CDHEs has gained increased attention in the past decades. Previous studies have detected changes in the frequency, duration, and spatial extent at regional and global scales based on observations and model simulations. However, these studies mainly focus on a single drought indicator. In the past decades, different drought indicators have been applied to characterize drought conditions, such as Standardized Precipitation Index (SPI), and Standardized Precipitation-Evapotranspiration Index (SPEI), and Palmer Drought Severity Index (PDSI). Due to the difference in these drought indicators in characterizing droughts, evaluation of CDHEs based on different drought indices may lead to a different magnitude of changes (or even opposite direction of changes). However, quantitative analysis of the uncertainties in the variation of CDHEs is still lacking. In this study, we quantitatively evaluate the uncertainties of CDHEs variations ove global areas due to differences in drought indices. Results from this study could further our understanding of changes in CDHEs under global warming.
How to cite: Feng, S. and Hao, Z.: Uncertainties in the variation of compound dry and hot events due to differences in drought indices, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9323, https://doi.org/10.5194/egusphere-egu21-9323, 2021.
Temperature extremes and air pollution pose a significant threat to human health. A specific concern applies to heat events and elevated ground-level ozone concentrations, due to the physical relationships between these variables, the single and combined effects of both variables on human health and the anticipated substantial changes in the scope of climate change.
The present contribution addresses relationships between air temperature and ground-level ozone, the association of these variables with atmospheric circulation patterns, the anticipated changes under future climate change as well as their association with human morbidity (i.e. myocardial infarction frequencies, Hertig et al. 2019) and mortality. The focus is on two climatically different regions in Europe, i.e., Bavaria (Central Europe) and Portugal (South Europe).
In general, a strong relationship between air temperature and ozone formation became evident. Due to the non-linear nature of the relationship, higher temperatures usually led to substantially enhanced ozone concentrations. In the scope of climate change, considerable increases of maximum temperatures were assessed for Bavaria until the end of the century. Also, future ozone concentrations were projected to rise (Hertig 2020). With respect to spell-length related extremes (heat waves and/ or ozone pollution waves), heat waves were identified as the most frequent wave type for the two European regions under investigation. Waves were associated with in-situ built-up as well as with advection of air masses. Despite different climate settings, a comparable exposure to heat and ozone waves was found in Central and South Europe. In view of excess mortality, the most severe impacts were always associated with compound heat-ozone waves (Hertig et al. 2020).
Research was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under project number 408057478.
Hertig, E., Russo, A., Trigo, R. (2020): Heat and ozone pollution waves in Central and South Europe- characteristics, weather types, and association with mortality. Atmosphere. doi: 10.3390/atmos11121271
Hertig, E. (2020): Health-relevant ground-level ozone and temperature events under future climate change using the example of Bavaria, Southern Germany. Air Quality, Atmosphere and Health. DOI: https://doi.org/10.1007/s11869-020-00811-z
Hertig, E., Schneider, A., Peters, A., von Scheidt, W., Kuch, B., Meisinger, Ch. (2019): Association of ground-level ozone, meteorological factors and weather types with daily myocardial infarction frequencies in Augsburg, Southern Germany. Atmos. Environment. DOI: 10.1016/j.atmosenv.2019.116975
How to cite: Hertig, E., Russo, A., and Trigo, R.: Compound heat and ozone pollution events relevant for human health, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-119, https://doi.org/10.5194/egusphere-egu21-119, 2021.
The Mediterranean Basin is nowadays considered as one of the most vulnerable areas worldwide to extreme climate/weather events, especially those related to photochemical pollution (tropospheric ozone) and extreme temperatures (e.g. heatwaves). Heatwaves and air pollution have a high impact on society, both from a health and an economical perspective, leading to increases on heat stroke hospital admissions and mortality. For this reason, heatwaves and their associated ozone pollution have to be taken into account for dwellers welfare.
In addition, in recent years, it has become increasingly clear that climatic or meteorological impacts often result from the compounding nature of several variables and/or events, even if they are not extreme when analysed independently. Such compound events can lead to socio-economic damage exceeding that expected if the individual hazards were to occur separately. For instance, compound events of heat wave and stagnation display higher temperature than stagnation events or heat wave events alone, so the formation of secondary pollutants like tropospheric ozone is enhanced relative to individual events.
Under this umbrella, this study assesses compound climate events using high-resolution regional chemistry/climate simulations, with the aim of characterizing and quantifying the influence of temperature/pollution compound events on mortality over Europe, with a special focus on the Mediterranean Basin. Model data from the REPAIR and ACEX projects (obtained from simulations with the on-line chemistry/coupled WRF-Chem model) is used in order to check the changes in mortality under both present-observed and future-forced conditions. The results presented in this contribution quantify the important increase in mortality causes associated to cerebrovascular diseases (CEV) and other pathologies during those compound events (especially under future climate change scenarios) with respect to episodes led by single drivers. This increase in mortality is more evident in northern countries in relative terms; and in southern European countries in absolute mortality incidence, since the concurrent presence of heatwaves and high levels of tropospheric ozone will have a higher frequency in future scenarios over the Mediterranean basin.
How to cite: Tarín-Carrasco, P., Palacios-Peña, L., Montávez, J. P., and Jiménez-Guerrero, P.: Impact of compound events (heatwaves and ozone episodes) on mortality over the Mediterranean basin under climate change scenarios, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15244, https://doi.org/10.5194/egusphere-egu21-15244, 2021.
India is severely affected by tropical cyclones (TC) each year, which generates intense rainfall and strong winds leading to flooding. Most of the TC induced floods have been attributed to heavy rain associated with them. Here we show that both rainfall and elevated antecedent soil moisture due to temporally compounding tropical cyclones cause floods in the major Indian basins. We assess each basin's response to observed TC events from 1980 to 2019 using the Variable Infiltration Capacity (VIC) model. The VIC model was calibrated (R2 > 0.5) and evaluated against observed hourly streamflow for major river basins in India. We find that rainfall due to TC does not result in floods in the basin, even for rainfall intensities similar to the monsoon period. However, TCs produce floods in the basins, when antecedent soil moisture was high. Our findings have implications for the understanding of TC induced floods, which is crucial for disaster mitigation and management.
How to cite: Rajeev, A. and Mishra, V.: Compound Events of Tropical Cyclone and Flooding in India, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15759, https://doi.org/10.5194/egusphere-egu21-15759, 2021.
Wintertime extreme precipitation from cyclone clusters, i.e. consecutive cyclones moving across the same region, can lead to flooding and devastating socio-economic impacts in Europe. Previous studies have suggested that the future direction of the changes in these events are uncertain across climate models. By employing an impact-based metric of accumulated precipitation extremes, we show that projections of cyclone clusters are instead broadly robust, i.e. consistent in sign, across models. A novel physical diagnostic shows that accumulated precipitation extremes are projected to grow by only +1.0 %/K on average across Europe, although the mean precipitation per cyclone increases by +4.7 %/K. This results from a decreased number of clustered cyclones, associated with decreased wintertime storminess, the extent of which varies from northern to southern Europe and depends on the future storyline of atmospheric circulation change. Neglecting the changes in the number of clustered cyclones, i.e. assuming that accumulated precipitation extremes would change as the mean precipitation per cyclone, would lead to overestimating the population affected by increased accumulated wintertime precipitation extremes by 130–490 million across Europe.
How to cite: Bevacqua, E., Zappa, G., and Shepherd, T. G.: Shorter cyclone clusters modulate changes in European wintertime precipitation extremes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-657, https://doi.org/10.5194/egusphere-egu21-657, 2021.
Heatwaves and extreme rainfall events are natural hazards that can have severe impacts on society. The relationship between temperature and extreme rainfall has received scientific attention with studies focussing on how single daily or sub-daily rainfall extremes are related to day-to-day temperature variability. However, the impact multi-day heatwaves have on sub-daily extreme rainfall events and how extreme rainfall properties change during different stages of a heatwave remains mostly unexplored.
In this study, we analyse sub-daily rainfall records across Australia, a country that experiences severe natural hazards on a frequent basis, and determine their extreme rainfall properties, such as rainfall intensity, duration and frequency during SH-summer heatwaves. These properties are then compared to extreme rainfall properties found outside heatwaves, but during the same time of year, to examine to what extent they differ from normal conditions. We also conduct a spatial analysis to investigate any spatial patterns that arise.
We find that rainfall breaking heatwaves is often more extreme than average rainfall during the same time of year. This is especially prominent on the eastern and south-eastern Australian coast, where frequency and intensity of sub-daily rainfall extremes show an increase during the last day or the day immediately after a heatwave. We also find that although during heatwaves the average rainfall amount and duration decreases, there is an increase in sub-daily rainfall intensity when compared to conditions outside heatwaves. This implies that even though Australian heatwaves are generally characterised by dry conditions, rainfall occurrences within heatwaves are more intense.
Both heatwaves and extreme rainfall events pose great challenges for many sectors such as agriculture, and especially if they occur together. Understanding how and to what degree these events co-occur could help mitigate the impacts caused by them.
How to cite: Sauter, C., White, C., Fowler, H., and Westra, S.: Extreme rainfall events during and following heatwaves, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8851, https://doi.org/10.5194/egusphere-egu21-8851, 2021.
In a network of binarized precipitation (i.e., wet or dry value), the connection or dependence between each pair of nodes can occur following one or more of the following conditions: wet‐wet, dry‐dry, wet‐dry, or dry‐wet. Here, we firstly investigate the different types of dependence, year by year, within a precipitation network of binarized variables. We compare the sample estimate of the probability of co‐occurrence (or occurrence with a lag time within ±3 days) of each of the four possible combinations with respect to the correspondent confidence interval in hypothesis of independence. We develop a procedure to efficiently assess the dependence behavior of all couples of nodes within the network and apply the methodology to a network of rain gauges covering Europe and north Africa.
How to cite: Meroni, V., De Michele, C., Rahimi, L., Deidda, C., and Ghezzi, A.: Dependence Types in a Binarized Precipitation Network, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15129, https://doi.org/10.5194/egusphere-egu21-15129, 2021.
Compound flooding may result from the interaction of two or more contributing processes, which may not be extreme themselves, but in combination lead to extreme impacts. Estuarine environments are particularly prone to compound flooding due to the interplay between coastal storm surge and river discharge processes, both often being driven by the same storm event. A detailed understanding of compounding mechanisms, including the dependence between flooding drivers, is necessary to avoid flood risk miscalculations when building/upgrading flood defences to mitigate risks associated with high impact events. Here, we use statistical methods to assess compound flooding potential in Sabine Lake, TX. Sabine Lake receives discharge from two rivers and is connected to the Gulf of Mexico coast through Sabine Pass. These geographic characteristics make it susceptible to compound flooding. We employ several trivariate statistical models (and simplified bivariate models for comparison) to examine the sensitivity of results to the choice of data pre-processing steps, statistical model setup, and outlier removal. We define a response function that represents water levels resulting from the interaction between discharge and storm surge inside Sabine Lake, and explore how the water level response is affected by including or ignoring dependencies between the contributing flooding drivers. Our results show that accounting for dependencies leads to water levels that are up to 30 cm higher for a 2% annual exceedance probability (AEP) event and up to 35 cm higher for a 1% AEP event, compared to assuming independence. We also find notable variations in the results across different sampling schemes, multivariate model configurations, and sensitivity to outlier removal. This highlights the need for testing various statistical modelling approaches in order to reliably capture potential compounding effects, especially under data constraints.
How to cite: Santos, V. M., Wahl, T., Jane, R., Misra, S. K., and White, K. D.: Estimating the Probability of Compound Discharge/surge Events in a Complex Estuarine System Under Data Constraints , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13789, https://doi.org/10.5194/egusphere-egu21-13789, 2021.
The simultaneous occurrence of heavy precipitation and high sea level can lead to more severe impacts than if these hazards occur in isolation. In this study, the joint occurrence of heavy precipitation and high sea level (hereafter compound events) on the Finnish coast in 1961-2019 is investigated. We use tide gauge observations from nine Finnish tide gauges and FMI ClimGrid gridded precipitation data. Two levels for the extremeness of precipitation and sea level were considered: elevated and high, with elevated corresponding to 90 percentile and high to 98 percentile of daily precipitation and maximum sea level. Elevated compound events were defined as days when both sea level and precipitation reached elevated levels, and high compound events were defined as days when both sea level and precipitation reached high levels.
First, the climatology of precipitation, high sea level, and compound events are studied. This is done by analysing frequency distributions of these events. Then, the interannual variability and long-term trends of the compound events are presented, and finally the synoptic weather patterns and the atmospheric circulation indices promoting the compound events are analysed.
We found that compound events are most abundant in late autumn and early winter, and they are typically caused by passing extratropical cyclones. The frequency of compound events has increased during the study period, in particular in the Bothnian Bay. The increasing trend of these events was linked to the more positive phase of the North Atlantic Oscillation (NAO) index during the recent decades. When the total annual number of compound events is considered, the Scandinavian blocking pattern (SCAND) was found to be the most controlling atmospheric circulation pattern, with negative SCAND promoting more compound events and vice versa.
The work presented here is part of project PREDICT (Predicting extreme weather and sea level for nuclear power plant safety) that supports nuclear power plant safety in Finland.
How to cite: Rantanen, M., Jylhä, K., Särkkä, J., Leijala, U., and Räihä, J.: Characteristics of joint heavy rain and high sea level events on the Finnish coast in 1961-2019, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10587, https://doi.org/10.5194/egusphere-egu21-10587, 2021.
Risk assessments in coastal zones usually address the maritime and continental domains separately by considering marine hazards and hydrometeorological extreme drivers individually. Although this may be reasonable for many coastlines, there are environments where this uncoupled approach will underestimate their overall risk to climate hazards and, in consequence, will affect the development of efficient adaptation plans. One of these environments is the Mediterranean, due to the magnitude of individual climate hazards, the frequency of compound events (it has been identified as one of the European areas with the highest probability of compound flooding), as well as the level of exposure along its coastal zone.
In this sense, there is an increasing number of studies addressing compound risks in the coastal zone, with most of them dealing with compound flooding. In this work, we adopt a complementary approach to help coastal managers to identify hotspot areas by classifying the coastal zone into management units of homogeneous cumulative compound risk. To this end, a Compound Coastal Zone Risk index has been developed which integrates the risks associated with the impact of marine and extreme hydrometeorological hazards. Here the risk is defined in basis of three components characterizing hazards, vulnerability and exposure, with the first two ones being specific to the intrinsic characteristics of each subdomain (marine and hydro-meteorological), whereas the last one characterizes exposed values of the coastal zone, being this area affected by both hazards.
The marine composite sub-index assesses the magnitude of hazards in terms of a sea-storm indicator (in terms of waves and storm-surge conditions), background decadal-scale shoreline evolution (to characterize erosion hazards), and SLR (both inundation and erosion). This is combined with an indicator that accounts for the “coastal” system vulnerability, which includes the geomorphology, beach width (which acts as buffer zone) and the existence of accommodation space at a given time, since both variables are t-dependent.
The hydrometeorological composite sub-index assesses the magnitude of hazards in terms of a rainfall indicator (to characterize short very-intense episodes, cumulative daily values and extreme events associated to a given probability), maximum wind gust and lightning density. This is combined with an indicator that accounts for the “terrestrial” system vulnerability, similar to the flash flood potential index.
All these indicators are assessed at the smallest possible spatial scale to be as accurate as possible. Then, they are integrated at municipal scale to characterize each management unit with a representative value which permits to classify them in terms of their integrated risk while retaining information on the partial contribution of each component. The final work will present the compound index in detail, as well as the partial sub-indexes, and it will be applied along about 800 km of the Spanish Mediterranean coast to identify the most risky stretches to cumulative compound climate hazards. The index is validated by comparing obtained values with damage data recorded along the study area after the impact of marine and hydrometeorological hazards.
This work has been developed in the framework of the M-CostAdapt project (FEDER/MCIU-AEI/CTM2017-83655-C2-1-2-R).
How to cite: Jiménez, J. A., Llasat, M.-C., Romero, R., Caballero, I., Valdemoro, H., Rigo, T., and Llasat-Botija, M.: Mapping cumulative compound coastal risk to multi-scale climate hazards in the Mediterranean, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14378, https://doi.org/10.5194/egusphere-egu21-14378, 2021.
Despite numerous studies that have examined terrestrial or marine heatwaves independently, little work has been done investigating any possible association between the two. Examination of a limited number of past events suggests that co-occurring terrestrial and marine heatwaves may have common drivers, or may interact with each other. For example, a recent study1 identified common remote drivers behind the major marine heatwave that developed in the South Atlantic during the summer of 2013/14 and terrestrial heatwaves over South America. Co-occurring events could also potentially interact via local land-sea interactions, thereby altering the likelihood of these co-occurring events. This study will explore possible links between adjacent coastal marine and terrestrial heatwaves. We will investigate the likelihood of co-occurrence of terrestrial and marine heatwaves, using statistical analysis of observational temperature data. We will also investigate the mechanisms driving co-occurring events, including the local fluxes, synoptic conditions, and links to large scale modes of climate variability
How to cite: Pathmeswaran, C., Perkins-Kirkpatrick, S., Sen Gupta, A., and Hart, M.: Are marine heatwaves increasing the likelihood of terrestrial heatwaves? , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8106, https://doi.org/10.5194/egusphere-egu21-8106, 2021.
Wildfires are recurrent natural hazards that affect terrestrial ecosystems, the carbon cycle, climate and society. An ignition can lead to a wildfire when there is biomass available for burning, typically in combination with dry and windy conditions. Wildfires are regarded as compound events defined as “an extreme impact that depends on multiple statistically dependent variables or events” , and dominant drivers include a combination of various meteorological, hydrological and biological conditions. More specifically, wildfires can be regarded preconditioned hazards  because the combination of drivers can cause the hazard only in the presence of available and burnable biomass (precondition). The availability of burnable biomass is itself driven by conditions such as soil moisture, temperature, humidity, precipitation, etc. Identifying a selection of dominant controls and their statistical dependence, can ultimately improve predictions and projections of wildfires in both current and future climate. In this study, we apply a data-driven bottom-up statistical learning approach (including random forest and logistic regression) to identify dominant factors determining burned area over northern Europe. Potential explanatory variables include temperature, precipitation, wind, soil moisture and vegetation cover, as well as meteorological drought, soil moisture drought and greenness indices. A monthly 2001-2020 burned area product derived from satellite observations is used as target variable, and multiple hydrometeorological and vegetation metrics stemming from the ERA5 reanalysis and observational datasets (e.g. EOBS) are tested as potential predictors. The derived relationships between wildfires and its compound drivers will further be used to assess the potential changes in such a combination of factors under different climate scenarios using large-ensemble global climate simulations and hydrological models. This new framework will allow us to better quantify the changes in potential wildfire risk in a changing climate using a combination of data driven and physically based models.
 Leonard et al., 2014: https://doi.org/10.1002/wcc.252
 Zscheischler et al., 2020: https://doi.org/10.1038/s43017-020-0060-z
How to cite: Bakke, S. J., Wanders, N., van der Wiel, K., Ionita, M., and Tallaksen, L. M.: Identifying dominant drivers of northern European wildfires, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11524, https://doi.org/10.5194/egusphere-egu21-11524, 2021.
Compound events lead to substantial risks to societies around the globe. As climate change is increasingly exacerbating the intensity and frequency of many hazards in vulnerable regions, ex situ responses to climate change including human mobility and displacement are starkly moving into the spotlight. Whilst proactive migration is often used as an adaptation response to the impact of climate and weather events, reactive migration following unprecedented climatic shocks is often involuntarily and can seriously disrupt livelihoods and undermine human security. The extent to which human mobility (here, measured by internal displacement) can be attributed to extreme weather and compound events and in turn, whether and to what extent extreme weather events and consequently human mobility can be attributed to anthropogenic climate change, has been largely unexplored.
Applying a framework based on probabilistic event attribution (PEA) of extreme weather events, we investigate, for the first time, human mobility responses attributed to anthropogenic climate change along a causal chain from anthropogenic climate change and changing frequencies and intensities of extreme weather and climate events to human mobility outcomes. We use the April 2020 extreme precipitation which lead to flooding and associated displacement in Somalia as a feasibility study to present the state of the art of this method. Our attribution model investigates two locations: First, we attribute extreme precipitation at the origin region of the extreme event to then attribute the resulting flood event in the displacement impact region. Event though the analysis shows no attributable link to anthropogenic climate change, our method advances the field of climate impact research regarding statistical approaches, model development and evaluation. For our feasibility study, we also find that sparsity of climate observations reveal one of many reasons for a lack of a climate change signal, which suggests an application of our model to other climate event contexts is needed to further test our method.
How to cite: Thalheimer, L., Crespo Cuaresma, J., Mechler, R., Muttarak, R., Li, S., and Otto, F.: The role of event attribution in compound flood-related displacement and anthropogenic climate change, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10845, https://doi.org/10.5194/egusphere-egu21-10845, 2021.
Rather than being isolated events, natural hazards often occur simultaneously or successively, resulting in compounding and cascading impacts. For instance, droughts and heatwaves often occur together (i.e. compound hazards) and trigger secondary hazards such as wildfires (i.e. cascading hazards). Furthermore, their impacts compound (i.e. compound impacts) and propagate through socio-economical systems (i.e. cascading impacts).
To move from cascading hazards towards cascading impacts, the use of qualitative tools such as narratives, storylines, and cognitive maps have emerged. Still, to predict how the impacts cascade across and within societies, quantitative methods are required.
Here, a new methodology for quantifying and visualizing drought compound and cascading impacts is presented using the case of the 2018/19 drought in Germany. The use of network inference and data mining tools is proposed to unravel patterns in an existing drought impact dataset (de Brito et al. 2020). Based on a co-occurrence analysis, the strength of compound impact patterns was quantified. Moreover, the most common cascading paths were identified through sequential pattern mining.
Results demonstrate that the occurrence of compound and cascading drought impacts follow a pattern and do not happen by chance. Indeed, statistically significant co-occurrence associations outnumbered randomly distributed ones (91.1% versus 8.9%). This has important implications for impact mitigation, suggesting that the understanding of past patterns can help in the prediction of future consequences. Based on this information, efforts can be directed to reduce the initiation of impact interaction networks. Moreover, the visualizations used can support the communication regarding impacts interactions, facilitating a knowledge-driven response by those involved in drought risk management.
The tools used here can be applied to other hazards. The obtained results can serve help to develop complex models for understanding causalities between drought consequences. They can, for instance, support the development of system dynamics and agent-based models. Hence, instead of using qualitative perceptions, the causal equations would be data-driven. We expect that this work will encourage a more holistic approach to natural hazards impact research.
de Brito, M.M., Kuhlicke, C., Marx, A. (2020) Near-real-time drought impact assessment: A text mining approach on the 2018/19 drought in Germany. Environmental Research Letters. doi:10.1088/1748-9326/aba4ca
How to cite: Madruga de Brito, M. and Kuhlicke, C.: Compound and cascading drought impacts do not happen by chance: a proposal to quantify their relationships, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-673, https://doi.org/10.5194/egusphere-egu21-673, 2021.
Weather events are a common cause for crop failures all over the world. Whilst extreme weather conditions may cause extreme impacts, the most common type of failure-inducing weather events are compounded. For these cases, explaining which conditions triggered a failure event is a complex task, as the links connecting climate and crop yield can be multiple and non-linear. On top of that, the climate change is likely to perturb the interface between climate and agriculture, possibly altering the occurrences or the drivers of crop failures, or generating new types of extreme impacts. In this context, the goal of this study is to demonstrate how global warming can affect the climate-crop connection. For that, we use a storyline approach and focus on an observed failure event, the extreme low soybean production during the 2012 season in hotspots regions, such as the Midwest US, Brazil and Argentina. The scale of this event drove the global soybean prices to the highest values ever recorded. We set out to quantify the change in occurrence of similar events in a warmer scenario. The storylines allow for event attribution, where a given impact can be examined and its causes disentangled. Here, four hotspots of soybean production are examined to contemplate the local consequences of climate change. The study is divided in two parts. We first link climatic features with soybean yields. For each hotspot region, a random forest classifier model is used to establish which meteorological variables are most important and how they are correlated with low soybean yields. With the model trained, we identify the climatic conditions that lead to the 2012 event. Second, we explore the influence of global warming on crop failures. Three large ensembles of simulated weather are obtained from the EC-Earth global climate model, one relating to the present-day period (including the 2012 event) and two relating to future periods with different levels of future warming . We apply the random forest model to these data, and obtain failure statistics for both present and future conditions, isolating the influence of climate change on the soybean failure.
How to cite: Moreno Dumont Goulart, H., van den Hurk, B., and van der Wiel, K.: Future storylines of the 2012 soybean failure event, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3146, https://doi.org/10.5194/egusphere-egu21-3146, 2021.
In a strongly interconnected world, simultaneous extreme weather events in far-away regions could potentially impose high-end risks for societies. In the mid-latitudes, amplified Rossby waves are associated with a strongly meandering jet-stream causing simultaneous heatwaves and floods across multiple major crop producing regions simultaneously with detrimental effects on harvests and potential implications for global food security.
While no scientific consensus on future changes in these wave events has been established so far, impacts of associated extremes are expected to become more severe due to thermodynamic factors alone, possibly enhancing crop production co-variability across major breadbasket regions and amplifying future risks of multiple harvest failures.
Quantifying future changes in crop co-variability linked to amplified Rossby waves faces a key challenge: Models need to exhibit sufficient skill along a chain of complex and non-linear features, namely i. Rossby Wave characteristics, ii. location and magnitude of associated surface extremes and iii. respective yield response. Here we investigate those relationships in the latest CMIP6 and GGCMI model simulations, providing preliminary results on future changes in crop production co-variability, linked to amplified Rossby waves.
How to cite: Kornhuber, K., Lesk, C., Pfleiderer, P., Jägermeyer, J., Schleussner, C.-F., and Horton, R.: Drivers and future changes in simultaneous extremes and their implications for global food security, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2720, https://doi.org/10.5194/egusphere-egu21-2720, 2021.
A compound disaster defines a situation with adverse consequences resulting from different, but related, disaster‐agents (ICLA 1996). These low probability extreme events can correspond to events with multiple concurrent or consecutive drivers, resulting in major financial or physical loss (Sadegh et al., 2018). In this study, disaster scenarios involving natural hazards and pandemics were developed to assess the risk and implications of a compound event to member countries of the Central Asia Regional Economic Cooperation (CAREC) area.
A partnership of 11 countries (Afghanistan, Azerbaijan, China (Inner Mongolia Autonomous Region; Xinjiang Uyghur Autonomous Region), Georgia, Kazakhstan, Kyrgyz Republic, Mongolia, Pakistan, Tajikistan, Turkmenistan and Uzbekistan) across Asia, the CAREC countries work together to promote sustainable development, economic growth and reduce poverty. High exposure to flooding and earthquake coupled with low insurance penetration means natural catastrophes are significantly material to the public sector balance sheet. This collaborative study involving multiple hazard modelling agencies assesses the potential impact of natural perils concurrent to pandemic/epidemic outbreaks.
The compound events developed represent Realistic Disaster Scenarios (RDS) for the specific areas they represent and are based on plausible low-probability, high-consequence events such as the 2015 floods in Tbilisi and the 1905 Bolnai earthquake in Mongolia. The impact of the natural events is then further compounded by modelled infectious disease outbreaks for each given scenario.
High resolution fluvial and pluvial flood hazard scenario footprints (30m x 30m), earthquake hazard intensity maps and gridded population data (Worldpop) are modelled alongside outbreaks including respiratory (including flu), Nipah and Crimean-Congo haemorrhagic fever, to assess the compounded impact. The humanitarian and financial loss potential of these events are then presented in the context of alternative disaster risk financing measures and adaptation strategies aimed at increased resilience.
ICLA (1996), International Conference on Local Authorities Confronting Disasters and Emergencies, Background Documents, Amsterdam.
Sadegh, M., Moftakhari, H., Gupta, H. V., Ragno, E., Mazdiyasni, O., Sanders, B., ... & AghaKouchak, A. (2018). Multihazard scenarios for analysis of compound extreme events. Geophysical Research Letters, 45(11), 5470-5480.
How to cite: Willis, I., Cheong, A., Au, C., Rao, A., and Millinship, I.: Compound disaster scenarios for risk management assessment in CAREC countries, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15476, https://doi.org/10.5194/egusphere-egu21-15476, 2021.
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