The simultaneous occurrence of increased river discharge and high coastal water levels may cause compound flooding. Compound flood events can potentially cause greater damage than the separate occurrence of the underlying extreme events, making them essential for risk assessment. Even though a general increase in the frequency and/or severity of compound flood events is assumed due to climate change, there have been very few studies conducted for larger regions of Europe. Our work, therefore, focuses on the high-resolution analysis of changes in extreme events of coastal water levels, river discharge, and their concurrent appearance at the end of this century in Northern and Central Europe (2070-2100). For this, we analyse downscaled data sets from two global climate models for the two emissions scenarios RCP2.6 and RCP8.5.

First, we compare the historical runs of the downscaled GCMs to historical reconstruction data to investigate if they deliver comparable results for Northern and Central Europe. Then we study changes in the intensity of extreme events, their number, and the duration of extreme event seasons under climate change. Our analysis shows increases in compound flood events over the whole European domain, mostly due to the rising sea level. This increase is concomitant with an increase in the annual compound flood event season duration.

Furthermore, the sea level rise associated with a global warming of 1.5K will result in a 50% increase in compound flood events for nearly every European river considered.

How to cite: Heinrich, P., Hagemann, S., and Weisse, R.: Changes in Compound Flood Event frequency in Northern and Central Europe under climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1988, https://doi.org/10.5194/egusphere-egu23-1988, 2023.

Heavy rainfall events and urban flash floods pose a high risk potential for humans and the environment, as a concrete prediction of the regional impacts is difficult. The effects of heavy rainfall events and urban flash floods depend, among other things, on the characteristics of the respective affected area - such as land use, soil type or topographical factors - but also on prior conditions, especially the pre-rainfall index. River floods also pose a similarly high risk, even if they can be predicted more precisely than heavy rainfall events - especially in larger river systems - and thus a more focused flood risk management can be carried out. If these events overlap in the form of compound flooding from river floods and heavy rainfall, the hazards and the risk to people and the environment increase significantly. This was shown in particular by the flood disaster in July 2021 in Rhineland-Palatinate and North Rhine-Westphalia in Germany.

Investigations are carried out into the joint occurrence of river floods and heavy rainfall. Discharge data from various stream gauges in North Rhine-Westphalia (Germany) and precipitation data from radar data of the German Weather Service as well as ERA5-Land reanalysis data of the ECMWF are used for this purpose. First, the respective single events are identified and analysed with regard to various statistical parameters. Then the analysis of the compound events is carried out, considering only events that are identical in time and space. To take this into account, simultaneous series are formed from the time series available. Since not all catchments are equally at risk from compound river flood and heavy rainfall events, one focus is on determining vulnerable areas. Here, various characteristic attributes of the catchments but also weather conditions, such as the pre-rainfall index, are considered. It turns out that special attention must be paid to small to medium-sized catchments and to areas with steep and narrow valleys.

Furthermore, the joint occurrence probability of river floods and heavy rainfall is determined. This is done with archimedean copula functions. A statement on the joint probability of occurrence of river floods and heavy rainfall has not yet been included in practice or in standards but should be adopted for the correct determination of hazards and risks. Furthermore, based on the analyses carried out, a proposal for the preparation of flood hazard maps by compound river floods and heavy rainfall is presented.

How to cite: Simon, F. and Mudersbach, C.: Analysis of compound river flood and heavy rainfall events for a development of combined flood maps, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11000, https://doi.org/10.5194/egusphere-egu23-11000, 2023.

Floods are among the most impactful disasters especially in terms of economy in affecting humans’ activities and damaging infrastructures. This is particularly the case along the coast where coastal floods happen. Such floods can be due to three different factors: meteorological (precipitation), hydrological (river runoff) and oceanographic (storm surge). A single factor but also a combination of two or more of such factors happening at the same time can lead to coastal floods also called compound floods. Flood hazards can then be underestimating when compound effects are not considered. 

This study focuses on coastal compound floods from oceanographic and hydrological phenomena at the coastal city of Halmstad (Sweden). It aims to quantify the risk of such flood events at Halmstad and to analyse the sensitivity of data sources and copula’ approaches.

Here, the copula method is used to analyse compound floods based on annual maxima of river discharge and corresponding sea level and vice-versa. A comparison is carried out with the commonly used Extreme Value theory on a single factor and the compound approach. Effects from different data time-series available from observations and models for both river discharge and sea level are studied.

This paper concludes the presence of a higher risk of flooding when compound effects are not considered and that the choices made on input datasets and copulas can have a significant impact.

How to cite: Dubois, K., Andreas Dahl Larsen, M., Drews, M., Nilsson, E., and Rutgersson, A.: Compound storm surge and river flood events in the coastal zone: Exploring the influence of data sources and compound approach on extreme recurrence levels, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11220, https://doi.org/10.5194/egusphere-egu23-11220, 2023.

Polders can be found in coastal and alluvial lowlands all over the world. These polders need an internal drainage system consisting of drainage canals, weirs and/or pumps to discharge the water out of the polder. Next to these drainage canals, dikes can protect the low-lying polder areas that are situated several meters lower than the controlled water levels in these canals. This study investigates the joint impact of extreme rainfall events on water and dike systems within Dutch polders. Previous research has shown that the combined effect of heavy rainfall and storm surge can increase flood risk in coastal polders in the Netherlands. However, the impact of extreme rainfall on multiple water-and-dike systems within a single polder, resulting in multiple hazards, has received little attention. Our analysis uses physical models that are calibrated on measurements and forced by synthetic rainfall and evaporation time series to examine the response time and interdependencies between regional drainage systems and pore-water pressures in canal dikes. Water levels and pore-water pressures and their interrelationships were analyzed as indicators of flood hazards. Our findings demonstrate the importance of considering the joint impact of multiple hazards on flood risk in polders, as the functioning of regional drainage systems and canal dikes can be affected by similar weather events.

How to cite: Strijker, B. and Kok, M.: The joint impact of rainfall events on water- and dike systems in Dutch polders, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9048, https://doi.org/10.5194/egusphere-egu23-9048, 2023.

Countless climate-related impacts are caused by compound events, i.e. by the combination of multiple climate processes at different spatial and temporal scales. For example, when precipitation and wind extremes coincide, the resulting impacts on infrastructure and humans can be very destructive. It is established that climate modes of variability, which are known to oscillate from seasonal to decadal timescales, such as the El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific-North American Pattern (PNA) and Atlantic Multidecadal Variability (AMV) favour the occurrence of extreme weather events such as heavy precipitation in several areas worldwide. However, little is known about the effect that these climate modes of variability have on compound events. In this context, understanding the physical modulators of compound events can contribute to an improved comprehension of their dynamics, and ultimately to a better prediction of their impacts. Here, focussing on compound wind and precipitation extremes, we contribute to closing this research gap by using large ensemble climate model simulations (CESM) and reanalysis data (ERA5). We identify hotspot regions in the northern hemisphere where winter (DJF) compound event occurrences are influenced by modes of variability. We also inspect whether particular combinations of modes of variability, e.g., superposition of extreme states of both ENSO and NAO indices, enhance compound event occurrences. Finally, the identified patterns in the observational data are compared to the model simulations. The findings allow us to understand whether climate modes of variability favour the simultaneous occurrence of compound events over different regions worldwide, and how well the current generation of climate model simulations represents these dynamics.  An improved understanding of these oscillating modes of variability could be used to enhance the development of sub-seasonal to seasonal forecasts of compound events, which therefore may reduce their impacts. 

How to cite: Teber, K., Francois, B., Gimeno-Sotelo, L., Küpfer, K., Brett, L., Leeding, R., Yavuzdogan, A., Domeisen, D., Suarez, L., and Bevacqua, E.: The influence of modes of variability and their interplay on compound extreme wind and precipitation events in the northern hemisphere., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5187, https://doi.org/10.5194/egusphere-egu23-5187, 2023.

Compound hot and dry events (such as recent summers of 2015, 2018 and 2022 in Europe) have an impact on a wide range of sectors, including health, transport, energy production, ecology, agriculture and forestry. The co-occurrence of extreme heat and drought poses a risk to water security in particular, since heat exacerbates moisture shortages during dry periods through increased evapotranspiration while at the same time water demand increases (e.g., for drinking water, cooling, irrigation). Current research suggests that climate change will increase the intensity, frequency, and duration of joint hot and dry extreme events in Europe. However, most studies focus on the drivers applying coarse-resolution global climate models.

This study exploits a 50-member single-model initial condition large ensemble (SMILE) of the Canadian Regional Climate Model, version 5, at 12 km resolution (CRCM5-LE, RCP 8.5 from 2006 onwards, driven by the Canadian Earth System Model Version 2 large ensemble, CanESM2-LE). The application of a regional SMILE provides an extensive database of compound events and, subsequently, robust estimations of their occurrence changes across Europe, from current to future states and in high geographical detail.

We define compound hot and dry summers based on joint exceedances of temperature and (negative) precipitation thresholds (2001-2020 JJA 95^th percentiles). By considering low soil moisture (below regional 2001-2020 JJA 10^th percentile) as an impact indicator, we further show the spatially varying connection between compound hot and dry summers and low water availability in Europe. Compound event occurrences are investigated in a current climate (2001-2020) and future 20-year slices at global warming levels (GWL, derived from the CanESM2-LE) of +2 °C and +3 °C, with each period represented by 1000 model years. Last, we investigate the underlying processes (e.g., heat budget terms) of changing event occurrences and their spatial distribution, and discuss the land use-specific (e.g., urban, agricultural, natural) exposure to impacts on water availability during compound hot and dry summers.

We identify areas in the Mediterranean and northern France as hotspots with a fivefold occurrence frequency of compound hot and dry summers for +2 °C GWL. With +3 °C GWL, the Mediterranean, France, Belgium, southern Germany, Switzerland, and the south of UK and Ireland are affected by a tenfold occurrence frequency with respect to current climate.

This study is an important boundary condition to the development of adaptation strategies for the affected regions.  At the same time, it quantifies the reduction of event occurrence in a +2°C world compared to the higher GWL of +3°C, highlighting the importance of climate mitigation strategies and policies.

How to cite: Böhnisch, A., Felsche, E., Mittermeier, M., Poschlod, B., and Ludwig, R.: Hotspots and impacts of present and future compound hot and dry summers in Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2079, https://doi.org/10.5194/egusphere-egu23-2079, 2023.

Both droughts and heatwaves cause negative impact on human health, agriculture, economy and other areas while occurring separately. However, in recent years the impact of these phenomena acting together has been increasingly analysed as it was found that such events, called compound drought and heatwave events (CHDE), may induce even more damage. The aim of this research is to identify droughts, heatwaves and CDHE in the eastern part of the Baltic Sea region during the summer months (June-August) from 1950 to 2022 and to assess their frequency and intensity. For the purpose to identify droughts the 1-month Standard Precipitation Index (SPI) values calculated for each day were used. Droughts were distinguished if the SPI values were lower than -1 for at least five or more days in a row and this condition was met in at least one third of the study area.  Heatwaves were defined as a period of five or more consecutive days when daily maximum air temperature (T_max) was higher than 90th percentile of T_max of the study period (1951–2022) for each summer day (on a 5-day moving average) and for one or more days covered at least one third of the study area. Daily T_max data as well as precipitation data that was needed to calculate SPI were obtained from European Centre of Medium-range Weather Forecast ERA-5 reanalysis dataset with a spatial resolution of 0.25° x 0.25°. CDHE events were defined as time periods when heatwave occurs during the drought period. Study showed that the number of heatwaves in the study area since 1950 increased significantly (by 1.25 per decade). The number of droughts during investigation period slightly decreased. The majority of droughts were identified in 1990’s when dry periods were recorded during six summers in a row (from 1992 to 1997). In total, 19 CDHE during the summer months were distinguished, while a lot of them occurred during 1990‘s (5 events). As a consequence, statistically significant increase of such events during the study period was not observed. CHDE of the highest intensity was found in 1994 while the longest CDHE occurred in 2022 and lasted for 19 days (from August 11^th to August 29^th).

How to cite: Klimavičius, L. and Rimkus, E.: Compound drought and heatwave events in the eastern part of the Baltic Sea region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3273, https://doi.org/10.5194/egusphere-egu23-3273, 2023.

Seasonal droughts are a common feature of the Iberian climate. They can have severe socioeconomic and ecological impacts – especially, when recurring in consecutive years. We investigate the recurrence of extreme drought events in the Iberian Peninsula (IP) for the past decades and in regional climate change projections. With this aim, we introduce and apply a new set of indices: the Recurrent Dry Year Index (RDYI) and the Consecutive Drought Year (CDY) Index. For the present climate, different gridded observational and reanalysis datasets at several spatial resolutions (10 to 25 km) are used. To analyse the potential impacts of climate change, we apply the indices to a large EURO-CORDEX multi-model ensemble with 12 km horizontal resolution consisting of 25 different global-to-regional model (GCM-RCM) chains for the historical period and future periods along the RCP8.5 scenario.

Results show that the IP is regularly affected by extreme droughts under present climate conditions, with roughly three individual events per decade. Especially the southern and central parts of IP are exposed to recurrent events, which last between two and six years. Under different global warming levels (GWLs), results reveal a general tendency towards more severe drought conditions. Moreover, recurrent drought events are projected to occur more frequent and last longer (up to 14 years). While the ensemble mean responses are only moderate for a GWL of +2°C (compared to the pre-industrial average), recurrent drought conditions are strongly enhanced for the +3°C GWL. The climate change signals are robust for most of IP and the considered recurrent drought indices, with a larger model agreement for the +3°C GWL. For both present and future climate conditions, results show some sensitivity on the choice of index and dataset.

We conclude that the new indices are suitable for the detection and evaluation of recurrent drought events under present and future climate conditions. With ongoing climate change, the Iberian Peninsula faces an increased risk of recurrent drought events. If global warming should exceed the +3°C threshold, the majority of models projects an almost permanent state of drought – with severe consequences for the Iberian population and ecosystems.

How to cite: Moemken, J., Koerner, B., Ehmele, F., Feldmann, H., and Pinto, J. G.: Recurrence of drought events over Iberia under present and future climate conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6226, https://doi.org/10.5194/egusphere-egu23-6226, 2023.

Increases in the frequency and intensity of hydroclimatic extremes (floods and droughts) and their temporal swings have led to severe consequences in many regions around the world. Traditionally, these contrasting extremes have been assessed in isolation without considering their spatial and temporal interactions, implications for infrastructure design and management and the overall compounding risks. Nonetheless, understanding the changing characteristics of such lagged compound events is critical to developing effective mitigation and adaptation strategies. In this study, we propose a novel framework to identify and characterize the hydroclimatic whiplash events and investigate their spatiotemporal projections under climate change. Multiple hydroclimate variables such as precipitation, evapotranspiration, soil moisture, runoff, and streamflow are used to identify dry and wet extremes and their transitions. Different scenarios for nonstationary hydrological swings between flood and drought are investigated based on streamflow data. Meteorological wet and dry conditions are investigated using standardized drought indices calculated based on the downscaled and statistically bias-adjusted simulations of CMIP5 for 1.5°C-4 °C global warming levels over three major river basins in northwest North America. Further, three dry-wet spell indices estimated by precipitation, soil moisture, and runoff simulations are merged into an integrated indicator to provide a thorough perspective on the changing risks of such transitions across North America using the Canadian Regional Climate Model version 4 Large Ensemble. We apply an ensemble pooling approach to enhance the sample size for index estimation, which enables projecting the characteristics more robustly. Frequency, intensity, transition time, spatial fraction, aggregation index, and seasonality are quantified for each warming period and compared with those of the baseline period to investigate their projected changes. In addition, we assess the contribution of external forcing and internal variability to the historical and projected changes of the lagged compound events. The results of this study suggest that hydroclimatic whiplash across North America is expected to become more frequent and intensified in a warmer climate. Projections show overall increases in the frequency of hydroclimatic whiplash and a decrease in the corresponding transition times as the climate gets warmer. In addition, the magnitude, intensity, and duration of wet and dry components of such lagged compound events are projected to increase based on the analyses with streamflow. Increasing trends of spatial fraction and spatial aggregation during both transitions between dry and wet spells also imply higher risks and future challenges for water resources management. The findings of this study support the necessity of developing appropriate mitigation measures targeting lagged compound floods and droughts that can lead to severe environmental and socio-economic disasters in North America.

How to cite: Najafi, M. R., Na, W., Rezvani, R., and Rahimi Movaghar, M.: Characterization of Lagged Compound Floods and Droughts Under Climate Change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16867, https://doi.org/10.5194/egusphere-egu23-16867, 2023.

Investigating the global connectivities of extreme events is vital for accurate risk reduction and adaptation planning. While human and natural systems have a certain resilience level against single extremes, they may be unable to cope with multiple extreme events whose impacts tend to be amplified in a non-linear relationship. Concurrent droughts and heatwaves are frequently linked to severe damage in socioeconomic sectors such as agriculture, energy, health, and water resources. They can also have detrimental effects on natural ecosystems. Here, we detect global scale dependencies of large-scale droughts and heatwaves using an AI-enhanced point process-based approach, where large-scale events are defined to occur when a certain amount of grid points (e.g., 20%) of a given region of interest experiences heatwave or drought conditions. The classic inhomogeneous and non-stationary J-function can determine whether the occurrence of the events shows clustering, inhibition or independence. However, the analysis and interpretation of this function are usually affected by a high degree of subjectiveness, and its application for large datasets and/or ensembles is challenging. The proposed AI-based automated interpretation tool replaces a subjective and user-dependent approach. Monte Carlo simulations based on standard point process models, reflecting the aforementioned dependence structures, are utilized, allowing the dependence structure to be labeled and the classification problem to be trained using Deep Learning algorithms. To identify the global connectivities of large-scale droughts and heatwaves, we first detect extreme events at the grid scale based on appropriately selected indices. A cluster analysis pinpoints areas with similar drought and heatwave patterns, thus identifying the regions of interest for the large-scale events. For these events we compute the J-functions, and the dependence structure of the large-scale events is then classified by the AI-tool. Links to teleconnections (such as the El Niño-Southern Oscillation and the North Atlantic Oscillation) can be further identified by analyzing the dependencies conditioning on the teleconnection phase under consideration. The proposed tool can be used in diverse research questions where a point process approach is appropriate, and thus has applications beyond climate science.

How to cite: Luther, N., Toreti, A., Pérez-Aracil, J., Salcedo-Sanz, S., Vlachopoulos, O., Ceglar, A., Hrast Essenfelder, A., and Xoplaki, E.: Detecting dependencies of large-scale heatwaves and droughts with AI-enhanced point process approaches, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8588, https://doi.org/10.5194/egusphere-egu23-8588, 2023.

Synchronous crop failure among multiple breadbaskets worldwide, a typical spatially compound event, may amplify threats to the global food system and food security and has been a growing concern among the scientific community in recent years. While the risk of simultaneous crop loss across multiple breadbasket regions has been analyzed, to date, little is known about how interdependence among regional crop production affects aggregated crop failure at the global scale. Quantifying the impact of dependencies among breadbasket regions on global food production and assessing how the dynamic of spatially compounding crop failures is simulated by climate and crop models is essential for informing the modeling of global food security risk. In this study, focusing on different crop types, we quantify the influence of dependence between crop production of individual regions on global aggregated crop yield based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) dataset. We find that spatial dependence between regional crop yields may aggravate global crop deficits and identify a characteristic spatial scale beyond which the dependence between crop production in different regions vanishes. Our results provide valuable information for designing risk strategies for food security at the suited scale.

How to cite: Feng, S., Zscheischler, J., Hao, Z., and Bevacqua, E.: Interdependence among subregional crop production affects global crop failure risk, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8705, https://doi.org/10.5194/egusphere-egu23-8705, 2023.

Although studies based on physiological models have repeatedly shown that high humidity levels lead to stronger heat stress in humans, findings from epidemiological studies have remained inconclusive on the matter till date. We aim to employ a ‘bottom-up’ strategy of identifying key drivers of compound events to explore the role played by humidity in high heat-related mortality events, spanning across multiple cities in multiple countries. We used daily data on all-cause mortality, mean temperature and mean relative humidity from 11 cities across the world and applied state-of-the-art epidemiological models to compute the daily observed total mortality counts attributable to heat (i.e., limited to days with average temperature exceeding the ‘temperature of minimum mortality’ (MMT) in each city). Each of these days with mean temperature exceeding MMT is considered as an ’event’ and events with highest mortality counts attributable to heat from multiple cities are analysed in a 2D scatter plot of the corresponding percentile rank of temperature and humidity observed during those events. The frequency of such high impact events in the temperature-humidity percentile space across multiple cities, categorised into sub-groups based on the temperature and humidity climatology of the cities, was then studied. It was observed that close to 90% of the high impact events occurred during high temperature (> 90^th percentile) and non-high humid (<50^th percentile) conditions. The events of high severity, where humidity conditions were comparatively high (> 50^th percentile), were mostly representative of cities with prevailing high humidity conditions on average during the warmest months, when compared across all the cities. Based on our preliminary findings, there is no conclusive evidence that high humidity conditions were prevalent during high heat-mortality impact events, but further analysis incorporating more cities and other climatological variables of interests such as absolute humidity, wet-bulb globe temperature etc. are planned. This novel framework provides valuable insights into the role of humidity in heat stress mortality and can be generalised to address other similar complex research questions in environmental epidemiology.

How to cite: Sivaraj, S., Lüthi, S., Lo, E., and Vicedo-Cabrera, A. M.: A bottom-up approach for exploring the role of humidity in high heat-related mortality events: A Multi-City, Multi-Country study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10996, https://doi.org/10.5194/egusphere-egu23-10996, 2023.

Climate change increases the frequency and severity of heat waves, which can negatively impact human health. Extreme heat can lead to heat stroke, dehydration, and other heat-related illnesses. Heatwaves are more severe for vulnerable populations such as older adults, young children, and people with pre-existing medical conditions. In this study, we analyze the occurrence of compound extreme heat-related mortality in five Swiss cities using neural networks.

To define the excess mortality due to compound heat extremes (Hot day, Tmax>30^oC, followed by a tropical night, Tmin>20^oC) we compared mortality during the four hot summers of 2003, 2015, 2018, and 2019 with long-term average mortality rates (1981-2020). We trained long short-term memory (LSTM) neural networks on 40-year time series of maximum and minimum temperatures, hot day / tropical night compound events, and mortality in Basel, Bern, Geneva, Lugano, and Zürich.  LSTM neural networks learn the important parts of the sequence seen so far and forget the less important ones. This makes these models predict with greater accuracy than traditional time series analysis methods.

In general, we found that over the past 40 years, more than six percent of deaths were caused by compound extreme heat waves in the five Swiss cities. Geneva and Lugano are the most affected cities by compound heat, but the risk of heat-related mortality has decreased in these two regions over time, which could be a result of the action plans that exist in the Latin regions of Switzerland.

We further used Switzerland's future climate model scenarios (CH2018), to predict mortality rates in Swiss cities in the near-future (2020–2050) and far-future (2070–2100). We projected that the number of people affected by mortality risks associated with heat could increase by three folds by the end of the century in most cities if no further adaptation is taken place.

Our results show how important it is for governments, public health agencies, and individuals to be aware of the potential impacts of climate change on heat-related mortality and to take steps to mitigate and adapt to these impacts.

How to cite: Ashraf Vaghefi, S., Muccione, V., Vicedo-Cabrera, A., Neukom, R., Huggel, C., and Salzmann, N.: Projecting the occurrence of extreme heat-related mortality using long short-term memory networks in cities of Switzerland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12245, https://doi.org/10.5194/egusphere-egu23-12245, 2023.

Heatwave events have been increasing in frequency, duration, and intensity along the past decades, leading to severe impacts on ecosystems, human health and basic resources. These events are projected to continue increasing associated to anthropogenic activity. Moreover, droughts have also been more recurrent and intense, which can significantly impact agriculture and reservoirs’ water level and quality.

Events of high temperature can occur both in the atmosphere and the seas. These warmer conditions, together with extremely dry episodes, have been affecting southern Europe and the Mediterranean region, which appear to be very sensitive to climate change. Additionally, the co-occurrence of droughts and heatwaves increases meteorological fire danger, rising the probability of wildfire occurrence and severity and resulting in economic, ecological, and even human losses.

In this sense, it becomes fundamental to pay special attention to the role of compound events and synergies in fueling extreme fire outbreaks. Therefore, we propose to address this problem by analyzing the occurrence of both marine and atmospheric heatwaves and drought conditions over Southern Europe, East Atlantic and Mediterranean Sea (relying on ERA5 reanalysis), as well as the recorded wildfires (through MODIS burned area product).

This work aims to address the occurrence of heatwaves (marine and atmospheric) and previous and contemporaneous drought episodes on a compound or cascading approach, estimating their contribution to the occurrence of extreme wildfires in the region in the last decades were analyzed on a seasonal scale.

Acknowledgments: This study is partially supported by the European Union’s Horizon 2020 research project FirEUrisk (Grant Agreement no. 101003890) and by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020- IDL,  DHEFEUS - 2022.09185.PTDC

How to cite: Santos, R., Russo, A., and Gouveia, C. M.: Assessing the impact of marine and atmospheric heatwaves on droughts and fire activity in the Mediterranean region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7779, https://doi.org/10.5194/egusphere-egu23-7779, 2023.

Extreme meteorological events such as frost, heat, and drought can induce significant damage to vegetation and ecosystems. In particular, heat and drought events are projected to become more frequent under a changing climate. It is therefore crucial to predict the frequency (on climate timescales) and the occurrence (on timescales of weeks to months) of such extremes.

The subseasonal-to-seasonal (S2S) forecasting timescale refers to forecasting timescales from two weeks to a season. Skillful S2S forecasts of hydro-meteorological hazards can be of crucial importance to prevent large-scale vegetation damage. The utility of S2S forecasts for vegetation is very broad (agriculture, biodiversity and flora protection, wildfire risk management, forest management, etc.).

We focus here on forest damage, defined as negative anomalies of the normalized difference vegetation index (NDVI). We use the AVHRR dataset, providing NDVI data over Europe. Compound droughts and heat waves are known to trigger low NDVI events in summer. A dry summer combined with moist conditions during the previous autumn can also have a negative impact. The idea is to find, among all the hydrometeorological variables available as S2S forecast in the ECMWF model, the most relevant ones to predict forest damage. For that, we establish an automated procedure to identify the compound hydro-meteorological conditions leading to low NDVI events, up to several seasons before the impact. We train a model using ERA5 and ERA5-Land reanalysis datasets for the explicative variables. These variables include temperature, precipitation, dew point temperature, surface latent heat flux, soil moisture, snow water equivalent, soil temperature, etc. Several space and time aggregations are considered in order to find the optimal scales and most relevant combinations of variables to predict low NDVI events. The overall goal of this research project is to bridge the research gap between the S2S forecast of hydrometeorological variables and vegetation damage in general. For that, we assess the forecast skill of variables identified as responsible for compound low NDVI events and vegetation biodiversity loss.

How to cite: Rivoire, P., Domeisen, D., Guisan, A., and Vittoz, P.: Compounding hydro-meteorological drivers of forest damage over Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12427, https://doi.org/10.5194/egusphere-egu23-12427, 2023.