Weather Compound Events (WCE), broadly defined as “the combination of multiple drivers and/or hazards that contributes to societal or environmental risk” [1], contribute to important societal impacts and widespread economical damages. However, the underlying mechanisms and complete storylines of these events are complex and not well understood yet.

In this study, we build an 25-year database of co-occurrent hot and dry compound events (HDCE) including heatwaves, droughts, dust storms and wildfires affecting Europe and the Mediterranean Basin from 2003 to 2020. based on Earth Observation exclusively. Individual natural hazards were systematically identified by a spatial and temporal matching algorithm applied on consistent ESA CCI Earth Observation datasets. The resulting individual natural hazard masks were then overlayed over Europe and permitted to identify regions simultaneously affected by two or more natural hazards on a daily basis. The climatology revealed HDCE hotspots among others in Northern Italy, Balkans and Caucasus regions.

Characteristics of HDCE such as their duration, intensity and spatial extension are stored in the database. HDCE could also be associated with a severity index to aid comparison across events.

Long-term statistics of the generated HDCE have shown a high interannual variability with HDCE being more frequent during the 5 last years rather than two decades ago.

The large-scale preconditions preceding and occurring during HDCE are investigated as well in this study and revealed systematic patterns in the atmospheric dynamics.

[1] Zscheischler, J., Martius, O., Westra, S., Bevacqua, E., Raymond, C., Horton, R.M., van den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M.D. and Maraun, D., 2020. A typology of compound weather and climate events. Nature reviews earth & environment, 1(7), pp.333-347.

How to cite: Fluck, E.: A 25-year assessment of Hot and Dry Weather Compound Events in Europe using Earth Observation , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-109, https://doi.org/10.5194/egusphere-egu24-109, 2024.

The variability in the occurrence of concurrent extremes like droughts and heatwaves is often attributed to climate change and anthropogenic factors, neglecting its connection with large-scale global teleconnections. The current study investigates the temporal and spatial connections between concurrent droughts and heatwaves (CDHW) in India to large scale global teleconnections like El Nino Southern Oscillation, North Atlantic Oscillation, Pacific Decadal Oscillation, and Indian Ocean Dipole. Utilizing composite and wavelet coherence analyses, we conduct a univariate assessment of droughts and heatwaves, quantified with the standardized precipitation index and standardized heat index, respectively, in association with large-scale global teleconnections (referred as climate drivers). Further, a novel attribution table framework proposed to quantify the conditional probability of CDHW given the onset of climate drivers. We found that the probability of CDHW preceeding the onset of climate drivers is much higher compared to the probability of CDHW occuring without the onset of climate drivers. The insights from this study suggest the potential use of global teleconnections for issuing season-ahead forecasts of CDHW.

How to cite: Das Bhowmik, R., Tabbussum, R., and Mujumdar, P.: Understanding the association between global teleconnections and concurrent drought and heatwaves events over India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11345, https://doi.org/10.5194/egusphere-egu24-11345, 2024.

We investigate the representation of compound hot-dry events in decadal predictions and their relationship with their univariate hot and dry components. We use a CMIP6 multi-model ensemble (MME) of 125 members from the Decadal Climate Prediction Project (DCPP) hindcast simulations and compare it with different observational references. Our analysis focuses on the first five lead years of the simulations, with the different ensemble members initialised every year from 1960 to 2014. We analyse the skill of predicting hot, dry and hot-dry events in the multi-model ensemble. Specifically, we select the days above the 90th percentile of the daily maximum temperature for hot events. For dry events, we use two indicators, the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI), with accumulation periods of 3, 6 and 12 months, and we consider a dry event a month that shows an SPI or an SPEI value ≤1. Finally, we identify days that present both hot and dry conditions according to these criteria as compound hot-dry days.

Preliminary results for the observations show a strong correlation between precipitation and the occurrence of compound events, especially for long accumulation periods, suggesting the importance of dryness as a driver for compound hot-dry events. In the DCPP hindcasts, the hot events show some robust predictive skill, mainly as a consequence of the increasing trend in temperature. On the other hand, dry events show sparse skill, concentrated in dry areas of the world and especially for extended accumulation periods. Further analysis of the skill of compound events and their relationship to their univariate counterparts in DCPP hindcasts will shed light on the representation of such events in decadal forecasts. However, these initial results underline the importance of precipitation in both the occurrence of present hot-dry compound events and the prediction of such events in the future.

How to cite: Aranyossy, A., Donat, M., Deluca, P., Delgado-Torres, C., and Solaraju-Murali, B.: Interconnections and decadal predictability of global hot, dry and compound hot-dry events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18528, https://doi.org/10.5194/egusphere-egu24-18528, 2024.

Hot and dry extreme events in Europe have become more frequent and pose serious threats to human health, agriculture, infrastructure, and ecology. Single and compound hot and dry extremes in Europe have been attributed to synoptic atmospheric circulation variations and land-atmosphere interactions. However, the exact causal pathways and their strength, as well as their historical trends, have not been quantified. An accurate understanding of the mechanisms behind these land-atmosphere extremes is crucial to improving S2S forecasts and implementing appropriate adaptation measures. Here, we use the Peter and Clark momentary conditional independence (PCMCI) based Causal Effect Networks (CENs) to detect and quantify dynamic and thermodynamic causal precursors of extremely high 2m temperature (T2m) and extremely low soil water deficit and surplus (WSD) in central Europe (CEU).

Our analysis reveals that the single hot events are driven mainly by anomalous atmospheric patterns and soil water deficiency, while single dry events are mainly driven by the soil moisture memory, and anomalous atmospheric patterns, and only marginally by temperature changes. The atmospheric circulation patterns preceding both single hot and dry events show a high-pressure system over central Europe, with a low-pressure system over the Atlantic Ocean, and partly explain the occurrence of the compound events. This atmospheric pattern is also linked to an anomalous zonal cold-warm-cold SST pattern over the Atlantic Ocean and a warmer eastern Pacific Ocean.

The identified causal links vary with temperature and humidity conditions, that is, the impact of soil moisture memory on the WSD variation is sensitive to T2m and WSD, while the influence of soil moisture condition on T2m changes is strengthened by reduced WSD. Moreover, during compound hot and dry extremes, the effect of reduced soil moisture on temperature is significantly higher than during single events, reaching twice the magnitude under moderate conditions. When historical trends are analyzed, we show that the impact of dry soil on temperature is amplified by 42% (46%) for single (compound) extremes during 1979-2020, while the influence of atmospheric drivers on soil moisture is intensified by 28% (43%).

This work emphasizes (i) the intensification of the strength of the thermodynamic causal pathways for warmer and dryer CEU over time and (ii) the stress on the varying forcing strength of the drivers, which can lead to non-linear variations of weather stressors under climate changes and thus add extra challenges to extreme adaptations.

How to cite: Di Capua, G., Tian, Y., Giaquinto, D., Claassen, J., Ali, J., Li, H., and De Michele, C.: Changes in the causal effect networks of single and compound extreme hot and dry events in Central Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10748, https://doi.org/10.5194/egusphere-egu24-10748, 2024.

In April 2023, the Western Mediterranean region was hit by an exceptional and unprecedented heatwave that broke several temperature records. In Cordoba (Spain), the previous April maximum temperature record was exceeded by almost 5ºC. In this study, we investigated the interaction between soil moisture and the extreme temperatures reached during this event, using the latest available observational data and several statistical techniques capable of quantifying this relationship. Our results revealed that soil moisture deficit preconditions, concurring with a strong subtropical ridge as a synoptic driver, had a key contribution to the amplification of this record-breaking heatwave. Specifically, we estimated that the most extreme temperature records would have been 4.53 times less likely and 2.19°C lower if the soils had been wet. These findings indicated that soil moisture content may be a crucial variable for seasonal forecasting of early HW in this region and other Mediterranean climate regimes that already suffering an increment in the frequency of compound drought–heatwave events. 

How to cite: Lemus-Canovas, M., Insua-Costa, D., Trigo, R. M., and Miralles, D. G.: Revealing the role of long-term drought in the record-shattering April 2023 heatwave in the Western Mediterranean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-134, https://doi.org/10.5194/egusphere-egu24-134, 2024.

How to cite: Rogers, C. and Warren, R.: Fast and Accurate Calculation of Wet-bulb Temperature for Humid-Heat Extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14205, https://doi.org/10.5194/egusphere-egu24-14205, 2024.

With the intensity and frequency of climate driven disasters increasing as result of climate change, there is ever more need to plan for such events and develop means to mitigate against them (UNDRR, 2015). Traditionally, the assessment of risks and impacts to regions posed by climate extreme events have been carried out in a “one at a time” approach, where the effects of each hazard, are assessed individually (Russo et al., 2023). However, it is recognised that  a transition to a more multi-hazard and multisectoral approach  is needed to be more efficient and effective in mitigating the risks/impacts posed to society, infrastructures, or the environment (Sendai Framework, 2015), (Russo et al. 2023). Whilst risk/impact assessment modelling can be complex, the derivation of risk/impacts is complicated further within a multi-hazard assessment due to the interdependent relationships between hazard, exposure and vulnerability, and that these vary over time in response to a preceding hazard (Gill et al. 2021).

The European Funded ICARIA project seeks to create an asset level modelling framework for understanding the potential risks/impacts posed by multi-hazard climate driven hazards, whilst also providing insight into cost-effective means of mitigating against them through the application of suitable adaptation measures. Two of the key challenges when transitioning from a single to a multi-hazard modelling approach are that (1) hazards are not directly comparable due differences in their processes and metrics, and (2) the effects of one hazard can influence the behaviour/characteristics of another hazard (Forzieri et al., 2016). To simulate the potential risks/impacts that could result from the modelled range of compound and consecutive hazards, a two-stage approach is being adopted that consists of (1) a deterministic physical modelling approach for quantifying the risks/impacts that can arise through simulation of various compound and consecutive hazard scenarios, along with (2) a stochastic Bayesian Network (BN) method for defining the probability distribution of such events. The BN will consider historical data for defining the probability distribution of modelled, multi-hazard scenarios for both current and future scenarios whilst data from the physical modelling will be used for defining the distribution of parameters relating to exposure, vulnerability, and impacts for the business as usual (no adaptation) and future adaptation scenarios.

Acknowledgement

The ICARIA project (Improving Climate Resilience of Critical Assets) is funded by the European Commission through the Horizon Europe Programme, grant number 101093806. https://cordis.europa.eu/project/id/101093806.

References

Forzieri, G., Feyen, L., Russo, S., Vousdoukas, M., Alfieri, L., Outten, S., Migliavacca, M., Bianchi, A., Rojas, R., & Cid, A. (2016). Multi-hazard assessment in Europe under climate change. Climatic Change, 137(1), 105–119. https://doi.org/10.1007/s10584-016-1661-x

Gill, J. C., Hussain, E., & Malamud, B. D. (2021). Workshop Report: Multi-Hazard Risk Scenarios for Tomorrow’s Cities.

Russo, B., de la Cruz Coronas, À., Leone, M., Evans, B., Brito, R. S., Havlik, D., Bügelmayer-Blaschek, M., Pacheco, D., & Sfetsos, A. (2023). Improving Climate Resilience of Critical Assets: The ICARIA Project. Sustainability, 15(19). https://doi.org/10.3390/su151914090

“United Nations - Headquarters United Nations Office for Disaster Risk Reduction.” (2015). Sendai Framework for Disaster Risk Reduction 2015-2030.

How to cite: Evans, B., Chen, A., De La Cruz Coronas, A., Russo, B., Turchi, A., Leone, M., and Büegelmayer, M.: Bayesian Network Approach for Assessing Probability of Multi-Hazard Climate Driven Events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18959, https://doi.org/10.5194/egusphere-egu24-18959, 2024.

Compound extreme weather events (CE), characterized by the concurrent influence of multiple weather and climate drivers, have the potential to exacerbate the concentration of air pollution on the atmosphere. Attributing specific extreme weather events directly to climate change is challenging; however, it is widely acknowledged that climate change will intensify different extreme events by changing their frequency, intensity, spatial extent, duration, and timing. Several types of weather extremes, such as stagnation conditions and heatwaves (HW), can lead to hazardous air quality situations by allowing some pollutants, such as ozone (O3), to accumulate and persist in the near-surface environment. O3 is in general more pronounced in the summer due to the photochemical nature of the source. Given its highly heterogeneous distribution across both space and time, combined with a relatively short life-time, it becomes imperative to gain insights into the patterns governing the global spatial data distribution related to this complex phenomenon. This study aims to evaluate the amplifying effects of CE (concurrence of stagnation and heatwaves) on O₃ peak levels globally during the summer season.

The study utilizes the simulations of historical 1980-2009) and future (2050-2079) climate under the Shared Socio-economic Pathways (SSP) SSP2-4.5 and SSP5-8.5. Using a model from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the investigation explores the global temporo-spatial trends and disparities in compound-event occurrences across countries.

We find that O₃ concentrations during the summer are higher in the center of North America and the center of the Asian continent compare with the other parts in the world (surpassing the 85 pbb during summer). A significant disparity in ozone concentrations was observed between the SSP2-4.5 and SSP5-8.5 scenarios. The SSP5-8.5 scenario demonstrates notably higher concentrations of peak O₃ compared to the historical period, with increase of up to 20 ppb in certain regions, such as the Asian continent. Furthermore, it is noteworthy that O₃ concentrations are expected to decrease in the future in the central part of North America in both scenarios up to 15 ppb during the summer season.

Focusing on CE throughout the summer season and under all scenarios studied, elevated O₃ concentrations are observed worldwide during CE compared to non-event conditions, particularly during heatwaves, with an increase of 40, 35 and 40 ppb during summer in the historical, SSP2-4.5 and SSP5-8.5 scenarios in comparison with non-event conditions. These heatwave events generally dominate the formation of O₃ peak concentrations during CE.

Comparatively, during stagnation events, the highest peak O₃ concentrations undergo a substantial increase in the mid-to-late century scenario, notably in the Asian continent, with a projected increase of nearly 12% in O₃ for the SSP2-4.5 scenario and a 25% increase for the SSP5-8.5 scenario. Conversely, during combined heatwave and stagnation events in the SSP2-4.5 scenario, a decrease in average concentrations is expected in the future across all continents.

These results underscore the imperative need to further mitigate air pollutant emissions during weather extremes to minimize the adverse impacts of these events on air quality and human health.

How to cite: Jimenez-Guerrero, P., Cvijanovic, I., Rodó, X., and Tarín-Carrasco, P.: Compound events increase the ground-level tropospheric ozone concentrations worldwide., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5986, https://doi.org/10.5194/egusphere-egu24-5986, 2024.

The intricate physical complexity of compound coastal flooding—resulting from the combination of river floods and storm surges—is known for often leading to more severe consequences than independent-driver floods. Damages from this type of flooding are expected to increase due to the impact of climate change on precipitation patterns and coastal storms, coupled with the increasing trends in population growth and economic activities along coastal regions. In the United States, the Federal Emergency Management Agency’s (FEMA) National Flood Insurance Program (NFIP) is the largest provider of flood insurance policies, and currently, more than two million NFIP flood claim transactions (1978 to present) are available to the public for analysis. However, there is a lack of studies that analyze how compound events reflect on insurance claims.

In this study, we focus on over 60,000 counties across the entire coastline of the United States to provide an exhaustive analysis of the distribution of economic losses in areas subject to river flooding, coastal flooding, and regions susceptible to compound events.

To identify the relative importance of the driving mechanisms (inland vs. coastal flows) for a particular location, we apply a published index [D-Index, readers are referred to the article, https://doi.org/10.1016/j.jhydrol.2023.130278 for details] that is capable of physically attributing the cause of flood depth to either river or coastal drivers, or a combination of both rainfall and storm surge.

We focus the analysis on the number of damages reported in the claims, comparing and contrasting claims in counties physically labeled as coastal, river, or compound. By calculating the quantile weight distance (QWD) of the damages from claims in the ‘compound’ counties and claims in the ‘independent-driver’ counties, we further investigate how rainfall and tide characteristics of storm events relate to the NFIP flood claims in the case of compound events. We further quantify differences in QWD by comparing and contrasting FEMA’s high-risk flood zones (identifying the 1-percent annual chance floodplain), where insurance is required for homes financed through federally backed or federally-regulated lenders, and FEMA’s low and moderate-risk flood zones, where flood insurance is not required.

In conclusion, this study furnishes invaluable insights into the intricate challenges of assessing compound coastal flooding impacts on insurance claims. The proposed methodology, integrating a flood type-specific mapping system and considering spatial variabilities of inundation characteristics, establishes a robust foundation for a comprehensive and improved flood risk assessment in coastal CONUS.

These findings empower coastal communities to proactively manage concealed risks and fortify their resilience against the compounding impacts of environmental forcings. This research offers a proactive and informed strategy to mitigate the potentially disastrous consequences of compound coastal flooding in a changing climate and socio-economic landscape.

How to cite: Mitu, M. F., Sofia, G., Shen, X., and Anagnostou, E. N.: Translating Flood Insurance Claims in the Coastal CONUS within the Spectrum of Compound Flood Risk, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14082, https://doi.org/10.5194/egusphere-egu24-14082, 2024.

High impact events are often compound events with relevance for a wide range of societal sectors: Infrastructure and Urban Resilience, Agricultural Adaptation and Food Security, Public Health and Healthcare Preparedness, Insurance and Financial Risk Management, Energy Systems, Natural Systems, Globally interconnected Networks: Food Networks, Supply chains, transport systems.

 Consequently, compound events and associated physical risks have been prominently acknowledged in recent high-level reports such as the sixth assessment report of the IPCC, fifth US National Climate Assessment, numerous UNDRR briefing notes and the Risk report of the world economic forum among others.

Driven by the need to enhance our physical and statistical understanding of high impact climate events, compound event research has made substantial progress and has emerged as a new inter/trans/multi-disciplinary field of study over the past decade, bridging climate, environmental science as well as statistics and data science. To be fully usable for solving real world problems substantial challenges remain, these include lack of high-resolution data, model biases in tail risks, and impact relevant event definition. This talk will provide an overview of current challenges in accurately projecting and predicting risks from compound events for various societal sectors and points towards potential solutions to address these.

How to cite: Kornhuber, K.: Usable Compound Event Research, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3151, https://doi.org/10.5194/egusphere-egu24-3151, 2024.

Coastal areas are becoming increasingly vulnerable due to climate change. These regions are exposed to various sources of flooding, such as high sea levels, river discharge and heavy rainfall. Our study focuses on understanding compound flooding from storm surges and river discharge in Croatia. This is the first study on compound floods in this country. For this purpose, we analysed the time series of water levels and discharges from hydrological stations located along ten major coastal rivers. Since there are only a limited number of tide gauges in Croatia, we combined measured data with numerical reanalyses. The sea level data for the entire Adriatic Sea were obtained from the Copernicus Marine Service (Mediterranean Sea Physics Reanalysis) and were then corrected using machine learning and measured data.

Previous studies have shown that neglecting seasonal variations in river discharge and storm surges could lead to a significant underestimation of the expected annual damage from compound floods. Different seasons bring distinct weather and river discharge patterns that influence the probability and severity of compound floods. To address this, our study investigated seasonal correlation and co-occurrence by analysing the monthly maximum values. By examining each season in detail, we uncovered the variations in the compound flood potential index.

This analysis provides a more comprehensive understanding of compound floods in Croatia, which is crucial for risk assessment and risk management. Finally, we mapped the correlation coefficients, the number of co-occurrences and the compound flood potential index along the Croatian coast and organised the results in a GIS database. These maps will improve our ability to systematically select the most vulnerable areas where the risk of compound flooding should be analysed at the local level.

How to cite: Krvavica, N., Bilić, M. M., and Ružić, I.: Compound Flood Potential from Co-occurrence of River Discharge and Storm Surge in Croatia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11560, https://doi.org/10.5194/egusphere-egu24-11560, 2024.

Coastal regions face escalating threats under climate change, necessitating a comprehensive understanding of compound flooding dynamics. This study aims to investigate the interplay between precipitation, wind waves, and meteorologically-driven storm surge, assessing their joint behavior leading to compound coastal flood risks in the Pacific Northwest. We examined two approaches to capture all possible drivers leading to compound events, which may not necessarily result from the extreme conditions of individual marginal variables. First, we used a conditional approach and assessed the block maxima (BM) of each variable in conjunction with the corresponding values of the other variables. Second, a peak-over-threshold (POT) investigation was conducted to generate datasets where all variables exceed their 95th percentiles. To calculate the joint return period of coastal flooding drivers, we used the most appropriate marginal distributions commonly used in coastal engineering, including the Generalized Pareto Distribution (GPD) for the POT-based approach and the Generalized Extreme Value (GEV) distribution for the BM. Subsequently, we computed the joint probability distribution by fitting the best-suited copula to the datasets to capture the interdependencies between the drivers. Moreover, as meteorological drivers may change under global warming, we extended our analysis to consider future projections of surge, waves, and precipitation. This enabled us to examine changes in the aforementioned dependencies and return periods. Sub-daily time series of surge and wave heights were obtained from the Canadian Coastal Climate Risk Information System (CCCRIS) (https://cccris.ca/), which provides high-resolution (~250 m along coastlines) simulations driven by ERA5 reanalysis and future projections until 2100 under the RCP8.5 emission scenario driven by four different combinations of global and regional models, namely, CanESM2.CanRCM4, CanESM2.CRCM5-QUAM, MPI-ESM-MR.CRCM5-QUAM, and GFDL-ESM2M.WRF. For each grid point, the corresponding precipitation data is obtained from the nearest grid point of the respective climate models. We assessed the degree to which each driver contributed to the overall change in the joint return period of concurring extremes in coastal flooding. We also conducted an analysis to quantify the respective contributions of each driver’s projection and their dependence structure to the uncertainty in changes of return periods. This study leveraged high-resolution data that encapsulated the regional dynamic responses, which is pivotal for precisely evaluating climatic hazards and developing efficient adaptation schemes, thereby ensuring a more informed decision-making process for coastal management and engineering applications.

How to cite: Fereshtehpour, M., Najafi, M. R., and Casas-Prat, M.: Compound Coastal Flooding Drivers in the Pacific Northwest: Understanding Precipitation-Surge-Wave Interactions and Projected Changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14796, https://doi.org/10.5194/egusphere-egu24-14796, 2024.

When different flooding drivers co-occur, they can cause compound floods. Despite the potential impact of compound flooding, few studies have projected how the joint probability of flooding drivers may change. Furthermore, existing projections are based on only 5 to 6 climate model simulations because flooding drivers such as storm surges and river run-off need to be simulated offline using computationally expensive hydrodynamic and hydrological models. Here, we use a large ensemble of simulations from the Coupled Model Intercomparison Project 6 to project changes in the joint probability of extreme storm surges and precipitation in Europe under a medium and high emissions scenario. To compute storm surges for so many simulations, we apply a statistical storm surge model trained with tide gauge observations and atmospheric forcing from the ERA5 reanalysis. We find that the joint probability of extreme storm surges and precipitation will increase in the northwest and decrease in most of the southwest of Europe. On average, the absolute magnitude of these changes is 36% to 49% by 2080, depending on the scenario. We show that due to internal climate variability and inter-model differences, projections based on small climate model ensembles can differ qualitatively depending on the specific simulations included. Therefore, our results provide a more robust and less uncertain representation of changes in the potential for compound flooding in Europe than previous projections.

How to cite: Hermans, T., Busecke, J., Wahl, T., Malagón-Santos, V., Tadesse, M., Jane, R., and van de Wal, R.: Projecting Changes in the Drivers of Compound Flooding in Europe Using CMIP6 Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5030, https://doi.org/10.5194/egusphere-egu24-5030, 2024.

Compound wind and precipitation extremes (CWPEs) can severely impact natural and socioeconomic systems. However, our understanding of CWPE future changes, drivers, and uncertainties under a warmer climate is limited. Here, analyzing the event both on oceans and landmasses via state-of-the-art climate model simulations, we reveal a poleward shift of CWPE occurrences by the late 21st century, with notable increases at latitudes exceeding 50° in both hemispheres and decreases in the subtropics around 25°. CWPE intensification occurs across approximately 90% of global landmasses, especially under a high-emission scenario. Most changes in CWPE frequency and intensity (about 70% and 80%, respectively) stem from changes in precipitation extremes. We further identify large uncertainties in CWPE changes, which can be understood at the regional level by considering climate model differences in trends of CWPE drivers. These results provide insights into understanding CWPE changes under a warmer climate, aiding robust regional adaptation strategy development.

How to cite: Li, D., Zscheischler, J., Chen, Y., Yin, B., Feng, J., Freund, M., Qi, J., Zhu, Y., and Bevacqua, E.: Intensification and Poleward Shift of Compound Wind and Precipitation Extremes in a Warmer Climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2962, https://doi.org/10.5194/egusphere-egu24-2962, 2024.

Climate change impacts are accelerating and intensifying, as observed over the past years, especially in the past year 2023.The current CMIP6 global climate simulations (GCMs) show higher climate sensitivity resulting in stronger warming and related impacts than previous simulations. Mountain regions are especially vulnerable as the warming climate relates to thawing of permafrost destabilising slopes and the emerging risk of heat and altered precipitation pattern that cause (extreme) flooding. Furthermore, the occurrence of compound events has gained increased attention as those pose substantial threat to the prevailing settlements and infrastructure.

Nevertheless, the available GCM simulations are spatially too coarse to investigate the mentioned extreme events in complex terrain. Therefore, statistical and dynamical downscaling is performed within the ICARIA project (Russo et al., 2023) to better analyse future climate impacts for the mountain regions of Salzburg. For the dynamical downscaling two regional climate models (RCMs), the WRF and COSMO-CLM (CCLM) are used to simulate the future climate conditions for the SSP126, SSP585 at spatial resolution of 2-5 km² until 2100.

The verification of the two RCMs with respect to CHELSA (Karger et al., 2017) display that the 5km² WRF model simulations overestimate the precipitation intensities, especially in mountainous regions, the same goes for CCLM. With respect to temperature, WRF and CCLM display an underestimation of temperature in higher altitudes (above 600m) and a good representation below.

Additionally, statistical downscaling has also been performed within ICARIA following the FICLIMA method. For this procedure, a set of 59 weather observations were used together with 10 CMIP6 GCMs. ERA5-Land and statistics such as MAE, Bias or Kolmogorov-Smirnov test were used for verification purposes of the methodology for each spot and model. Those that passed filters of quality and performance in the representation of past climate produced local downscaled climate projections at daily resolution for each location for the Tier 1 SSPs (1.26, 2.45, 3.70 and 5.85). Both the statistical and dynamical downscaling methods' outputs will serve to compare results and better assess the inherent uncertainties of climate projections.

Since the focus is on extreme events, the prevailing simulations are analysed with respect to the global warming levels (1.5°C, 2°C, 3°C and 4°C) and their related local impacts. To investigate extreme events related to precipitation and wind, as well as their compound occurrence, suitable indicators are investigated, such as precipitation intensity estimates through future IDF curves and wind gust events with return periods of 1, 2, 5, 10, 20, 50, 100, 500 years. Further, consecutive events, that have a compound impact on the system, are considered through investigating the region and hazard specific time period before and after the occurrence of the extreme event.

Russo, B., de la Cruz Coronas, À., Leone, M., Evans, B., Brito, R. S., Havlik, D., ... & Sfetsos, A. (2023). Improving Climate Resilience of Critical Assets: The ICARIA Project. Sustainability, 15(19), 14090

Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., ... & Kessler, M. (2017). Climatologies at high resolution for the earth’s land surface areas. Scientific data, 4(1), 1-20.

How to cite: Bügelmayer-Blaschek, M., Hasel, K., Züger, J., Monjo, R., and Paradinas, C.: Local climate change impacts - new insights for mountain regions of Salzburg based on high resolution climate simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12824, https://doi.org/10.5194/egusphere-egu24-12824, 2024.

Compound droughts and heatwaves (CDHWs) exert substantial socio-economic and ecological impacts, with their impacts reach epidemic proportions when CDHWs manifest simultaneously across multiple locations. Recent studies have begun to understand CDHWs, but their spatial compounding effects are not yet explored. This study utilizes weekly precipitation and temperature data to investigate the spatial synchronization of CDHWs and its changes. We define drought and heatwave weeks using the Standardized Precipitation Index (SPI 3-weekly) and the 90th percentile threshold of weekly temperatures. Our analysis reveals an unprecedented increase in the global land area and the number of regions experiencing concurrent CDHWs, particularly notable post-2000. The frequency of globally synchronized CDHWs (more than 5 regions affected simultaneously) has surged from 3 weeks (1982-1992) to 18 weeks (2012-2022), which is primarily attributed to a simultaneous global rise in temperatures driven by climate change. Analyzing CDHWs from observed data and counterfactual scenarios, where temperature data is detrended, we noted significantly higher likelihood of synchronization in observations due to intensified heatwaves in a warmer world. Notably, certain region pairs exhibit a higher likelihood of CDHW synchronization regardless being geographically distant. Spearman correlation and Granger causality analyses highlight major climatic modes, including El-Nino Southern Oscillation, Atlantic Multidecadal Oscillation, Western Tropical Indian Ocean, and Mode-2 of global Sea Surface Temperature, influencing changes in the areal extent of CDHWs globally as well as regionally. These insights are useful to predict the CDHWs and to quantify their socio-ecological impacts.

How to cite: ul Hassan, W., Saharwardi, M. S., Prasad Dasari, H., Gandham, H., Hoteit, I., and Abualnaja, Y.: Accelerating Heatwaves Intensify Spatial Synchronization of Compound Drought and Heatwave Events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14461, https://doi.org/10.5194/egusphere-egu24-14461, 2024.

Simultaneous occurrences of multiple heatwaves or cold spells in remote geographical regions have drawn considerable attention in the literature, due to their potentially far-reaching impacts. These include widespread crop failures, increased mortality, wildfires, power supply disruptions and more. We introduce a flexible toolbox to identify and study such concurrent temperature extremes, with adjustable parameters that different users can tailor to their specific needs and impacts of interest. We then use the toolbox to present a climatological analysis of concurrent heatwaves and cold spells in the global midlatitudes. Specific geographical areas, such as Western Russia, Central Europe, Southwestern Eurasia and Western North America, emerge as hotspots for concurrent temperature extremes. Concurrent heatwaves are becoming more frequent, longer-lasting and more extended in the Northern Hemisphere, while the opposite holds for concurrent cold spells. Concurrent heatwaves in the Southern Hemisphere are comparatively rare. However, their sharp increase in recent decades means that they are becoming an emerging hazard in the Southern midlatitudes. Notably, trends in concurrent temperature extremes are significantly stronger than the corresponding trends in all temperature extremes. This suggests that concurrent heatwaves will be an increasingly important climatic hazard in both absolute and relative terms in a future, warmer, climate.

How to cite: Segalini, A., Messori, G., and Ramos, A. M.: Climatology and Trends in Concurrent Temperature Extremes in the Global Extratropics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7651, https://doi.org/10.5194/egusphere-egu24-7651, 2024.

Attribution of high-impact weather events to anthropogenic climate change is important for disentangling long-term trends from natural variability and estimating potential future impacts. Up to this point, most attribution studies have focused on univariate drivers, despite the fact that many impacts are related to multiple compounding weather and climate drivers. For instance, co-occurring climate extremes in neighbouring regions can lead to very large combined impacts. Yet, attribution of spatially compounding events with different hazards poses a great challenge. Here, we present a comprehensive framework for compound event attribution to disentangle the effects of natural variability and anthropogenic climate change on the event. Taking the 2020 spatially compounding heavy precipitation and heatwave event in China as a showcase, we find that the respective dynamic and thermodynamic contributions to the intensity of this event are 51% (35–67%) and 39% (18–59%), and anthropogenic climate change has increased the occurrence probability of similar events at least 10-fold. We estimate that compared to the current climate, such events will become 10 times and 14 times more likely until the middle and end of the 21^st century, respectively, under a high-emissions scenario. This increase in likelihood can be substantially reduced (to seven times more likely) under a low-emissions scenario. Our study demonstrates the effect of anthropogenic climate change on high-impact compound extreme events and highlights the urgent need to reduce greenhouse gas emissions.

How to cite: Qian, C., Ye, Y., Bevacqua, E., and Zscheischler, J.: Human influences on spatially compounding flooding and heatwave events in China and future increasing risks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4229, https://doi.org/10.5194/egusphere-egu24-4229, 2024.

Global coffee production is at risk from synchronous crop failures, characterised by widespread reductions in yield occurring in multiple regions at the same time. For other crops, we know that these synchronous failures can be forced by spatially compounding climate anomalies, which in turn may be driven by large-scale climate modes like the El Niño Southern Oscillation (ENSO).

This talk will discuss the extent to which climate hazards occur and co-occur across the world’s major coffee-growing regions. These climate hazards include temperature and rainfall anomalies and are selected to cover two coffee species and different periods of the crop growing cycle. The talk will show that regional and global risk posed from spatially compounding hazards has increased over recent decades. There is a clear shift in the profile of this risk. Temperature-based hazards are now much more likely to exceed thresholds for optimal growing conditions, rather than being overly cold as observed during the 1980s.

Through multiple lines of evidence we find relationships between spatially compounding hazards and six tropical climate modes such as ENSO and the Madden Julian Oscillation. Individual regions exhibit differing relationships with these modes. ENSO is found to have the strongest links with multiple regions during the same crop cycle, posing implications for ENSO-driven global impacts to supply.

How to cite: Richardson, D.: The risk to global coffee supply from synchronous climate hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13620, https://doi.org/10.5194/egusphere-egu24-13620, 2024.

Attribution of compound events informs preparedness for emerging hazards. However, the task remains challenging because of complex space-time interactions amongst extremes, climate models’ deficiency in reproducing dynamics of various scales, and uncertainties in dynamic aspects of climate change. 
During June-July 2020, a historic flood hit the Yangtze River Valley and to its south the hottest summer since 1961 was observed, leading to disproportionate socioeconomic and environmental impacts to southern China. For attributing the recording-breaking spatially compounding event, we conduct a storyline attribution analysis by designing a series of simulation experiments via a weather forecast model, with large-scale dynamics equally constrained and thermodynamics of the climate system modified. We report that given the large-scale dynamic setup, anthropogenic influence has exacerbated the 2020 extreme Mei-yu rainfall by ~6.5% and warmed the southern co-occurring seasonal heat by ~1℃. The framework further details human influence on key elements to the two extremes individually and their coupling in space. If the same compound event unfolds in the 2090s, it is plausible to expect the monsoonal rainfall extremes ~14% wetter and the accompanying South China heat ~2.1°C warmer than observed.
This method opens an avenue for attribution of low-likelihood, dynamically-driven, spatially and temporally compounding events.

How to cite: Chen, Y.: Storyline attribution and projection of the 2020 spatially compounding flood-heat event in southern China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-185, https://doi.org/10.5194/egusphere-egu24-185, 2024.

Globally, climate change is a vital issue which exacerbates many severe consequences and causes the increasing frequency and severity of extreme weather events. Extreme climatic events, such as flash flooding, heatwaves, and droughts, pose severe impacts on societies and ecosystems, due to their large spatial coverage and high intensity. These extreme climatic events often occur simultaneously or sequentially as so-called compound events (CEs), causing high economic and societal losses as compared to the losses due to individual climatic extreme events. In the last two decades, Pakistan was ranked among the top ten countries which are most vulnerable to climate change and disasters, such as intense flooding, extreme heat, and droughts, among others. This paper presents case studies of extreme and compounding events in the last two decades with severe devastating impacts on people, infrastructure, and ecosystems. Specifically, two worst-case studies have been focused such as a flood in 2010 followed by a drought and a flood in 2022 followed by the heatwave. The post-disaster analysis shows that major part of the country was severely affected by these two CEs as a result of damaging the standing crops, destroying land, and causing displacement of millions of people along with losses and damages in fatalities and monetary terms. Therefore, this study is very vital for decision-making authorities to perceive the expected risk for human life, environment, and infrastructure in the future. So that pre and post-disaster mitigation policies and strategies could be formulated at local and national levels. The paper concludes with a discussion of the implications for CE adaptation in Pakistan. Key recommendations are provided to mitigate the impacts of future CEs.

How to cite: imran, A.: Extreme and compounding events in Pakistan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20174, https://doi.org/10.5194/egusphere-egu24-20174, 2024.

We investigate the most extreme but physically plausible heat-loaded European summers in current and near future climate conditions using ensemble boosting. With this approach, we identify the most extreme summers in an initial-condition large ensemble with the model CESM2 and boost them, creating a large ensemble of re-initialized simulations with slightly perturbed atmospheric initial conditions. This allows us to efficiently generate storylines for summers that are even more extreme than the original simulations, either due to a higher number of days or grid cells exceeding extreme heat thresholds, or original heatwave clusters exceeding such thresholds by larger margins.

We compare these storylines of summer heat clusters to the most extreme European summers in the observational record, and determine the necessary and exacerbating mechanisms behind these clusters of extreme heat. We quantify how factors such as the intensity and persistence of atmospheric patterns as well as sea surface temperatures and terrestrial water budgets contribute to the most extreme simulated summers. Furthermore, we disentangle the effects of extreme early heat in May-June acting as a preconditioning factor in driving more extreme conditions during the rest of the summer, due to it causing more heat-prone conditions such as warmer oceanic basins and dryer soils, versus the effects of large-scale preconditioning factors that may lead to more persistent and intense heat through the summer, regardless of if it starts early in the season or not.

Ensemble boosting is a computationally efficient approach that allows us to sample extreme rare events, now over time scales of several months, while preserving physical consistency both in time, space and across variables. This is an ideal setup for disentangling contributions from different driving factors, and the generated boosting storylines can be used in impact studies that require physical consistency, a prolonged simulation time, and successive or compounding hazard exposure.

How to cite: Suarez-Gutierrez, L., Beyerle, U., Mittermeier, M., Vautard, R., and Fischer, E. M.: Summers full of extreme heat: using ensemble boosting storylines to quantify the drivers of heatwave clusters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12906, https://doi.org/10.5194/egusphere-egu24-12906, 2024.

Recent wildfire seasons broke records in terms of severity and damage in different regions of the world, e.g. in California in 2021 and in Southern Europe in 2022. The  probability of such severe and large wildfires is enhanced by compounding meteorological conditions of hot, dry and windy weather, which lead to dry fuels supporting the spread of fires. Drivers of low-frequency but high-impact fire events operate on different spatio-temporal scales and are difficult to identify with classical regression methods. Here, we use causal inference methods to describe the relationships between different variables driving fires and quantify their effect on the occurrence of fire events. We examine hydro-meteorological and land-surface drivers of wildfires in different European climate regions by leveraging ESAs’ FireCCI burnt area product together with CERRA reanalysis data from 2002 to 2022. Our results show region-specific patterns of the different variables prior to the wildfire events, which allow us to identify different wildfire pre-condition types. Highlighting the spatial variability of different wildfire drivers in various climate regions of Europe provides valuable insights for the development of targeted fire prevention measures and management. 

How to cite: Miller, J., Macakova, M., Touma, D., and Brunner, M.: Compounding preconditions leading to wildfires differ across European climate regions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5210, https://doi.org/10.5194/egusphere-egu24-5210, 2024.

This study focuses on a new compounding concern, the sudden turn from drought to flood (STDF), that is becoming increasingly prominent. Droughts usually end due to increased precipitation, but if excessive rainfall occurs, it can lead to secondary impacts on already barren land, increasing the likelihood of landslides and making farmland flooding significantly costlier than it would have been if only flooding had occurred. Therefore, we must pay more attention to compound disasters that increase the vulnerability of populations and ecosystems. Most studies on rapid drought-to-flood transitions have analyzed individual cases, whereas few have studied the STDF characteristics in China or even globally or the long-term changes in the STDF trend. In this study, we selected an STDF screening method that is accurate on a daily scale.

In this study we calculated the SPEI on a 1-month scale, sliding a 30-day window in order to obtain the SPEI values for each day. Second, we used a relative threshold rather than an absolute threshold to define a flood in consideration of regional precipitation differences. A definition of STDF as follows:

,where t_o is the drought start time, t_d is the drought end time, and t_p is the time when flooding starts. Here, a drought is said to have occurred when the SPEI ≤-0.5 for more than 40 consecutive days. Our reference method considers drought duration to be more than 20 days, which is based on the persistence of the drought. And the main reason for our choice of 40 days is mainly to exclude the effect of flash droughts, although that type of event proved not to have a significant impact on our results in the subsequent discussion. PREt represents the t-d precipitation (for example, t=3, PRE3 is the 3d cumulative precipitation), when PREt is greater than the 99.5th (for PRE3)/99.3th (for PRE5)/98.7th (for PRE10) percentile precipitation for each reference period (1961-2020) as the flood threshold. (Based on the natural disasters released by the Emergency Management Department and the China’s Yearbook of Meteorological Disasters , 234 floods events were obtained for the period of 2010-2020, and so a threshold of 99.5th, 99.3th, and 98.7th percentile (corresponding to 3d/5d/10d continuous precipitation) was determined for their ranking in the rainfall series from 1961 to 2020.)

The results show that STDFs have been increasing more frequently in China at a rate of average 2.8 events per decade. The most significant increases occurred in May and June, resulting in an advance of one month for the STDF peak. The STDF hotspots are concentrated in north and northeast China and YRD. Nearly 35% of droughts in northern and northeast China have been immediately followed by a flood rather than a gradual drought mitigation or a drought alone. STDFs have become more prevalent in northern China as a result of increased flood frequency and precipitation volatility, while in southern China, the increase in STDF frequency is primarily due to an increase in drought frequency.

How to cite: Wang, H., Wang, S., Shu, X., He, Y., and Huang, J.: Increasing occurrence of sudden turns from drought to flood over China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4582, https://doi.org/10.5194/egusphere-egu24-4582, 2024.

Extreme droughts and pluvials are recurrent natural hazards that often lead to disastrous socio-economic impacts. These hydroclimatic extremes are generally characterized by large-scale spatial-temporal patterns spanning thousands of kilometres with time-evolving features of expansion or shrinkage. The spatial-temporal dynamics of these hydroclimatic extremes can pose compound impacts across multiple locations. Understanding the propagation behaviour, including movement and propagation, is crucial for disaster response and mitigation. The spatial propagation dynamics of droughts/pluvials are inherently complex as they are often associated with and modulated by natural climate variability, such as El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and atmospheric dynamics like Rossby waves. However, the specific influences of these drivers on the spatial propagation pathways of droughts and pluvials remain elusive. Here, we conduct a multi-layer complex network-based analysis to explore the interactions between drought/pluvial propagation pathways and potential modulating mechanisms with a focus on the conterminous United States. We first identify extreme drought and pluvial occurrences using self-calibrated Palmer Drought Severity Index (scPDSI) and Standardized Precipitation Index (SPI) during 1948–2016. We then apply event coincidence analysis (ECA) for all location pairs to construct fully-connected drought and pluvial complex networks, based on which we identify the spatial-temporal propagation pathways through community analysis. Subsequently, partial event coincidence analysis is carried out to elucidate the direct links from potential climate modulators (e.g., ENSO, NAO, and Rossby waves) to extreme event propagation. Our results provide insights into how climate variability and large-scale circulation patterns affect the spatial propagation of droughts and pluvials, offering valuable information for pre-emptive actions to mitigate remotely synchronized extreme events.

How to cite: Wang, H.-M. and He, X.: Lagged Synchronizations of Hydroclimatic Extremes and Their Propagation Dynamics Revealed by Complex Event Coincidence Networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-842, https://doi.org/10.5194/egusphere-egu24-842, 2024.

Many studies have shown that compounding extreme events are likely to exacerbate socio-economic risks compared to single extremes. Despite this important fact, studies focussing on the connectivity of extreme events and their associated impacts frequently have some shortcomings. First, extreme events such as droughts and heat waves are often predefined through thresholds, restricting the class of meteorological events leading to the observed impacts. The choice of threshold for defining these extreme events is also often of meteorological and/or statistical nature and thus potentially unsuitable for the holistic identification of the associated impacts. Furthermore, impacts can arise from combinations of non-extreme events that might fall short of the threshold-based identification, thereby limiting the ability to account for key dynamics that determine the risk associated with compound events. Our study aims to overcome those shortcomings by linking climate events with their observed impacts in agriculture. We analyse wet and warm late winters followed by dry and hot springs, and the associated agricultural damages in Europe with the aim of reconstructing these compound events based on the observed impact. A first analysis is conducted for winter wheat impacts in France, the largest European winter wheat producer. We identify agro-climatic zones based on multivariate time series clustering and employ a regularized generalized canonical correlation analysis to identify the large-scale drivers of crop variability for these regions. The patterns that emerge from the analysis are characterized by wet and warm conditions in January and February linked to a positive North Atlantic Oscillation (NAO) state, followed by warm and dry conditions in April induced by a tripole with a blocking high over Central Europe. Using imbalanced random forests, we construct objective bounds and define thresholds to identify which temperatures are warm enough or which water balances are low enough to be associated with significant effect on crop yield reduction. Our results indicate that imbalanced random forests can predict these types of events reasonably well at the local scale, and that the derived thresholds are mostly lower than the commonly used thresholds for detecting similar extreme events. The latter illustrates that the combination of non-extreme climate events can indeed be detrimental to agricultural production in Europe, which is also crucial as the analysed types of events are predicted to occur more often in the future as a result of climate change. 

How to cite: Luther, N., Essenfelder, A. H., Ceglar, A., Toreti, A., Vlachopoulos, O., and Xoplaki, E.: Reconstructing compound events from crop variability in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8594, https://doi.org/10.5194/egusphere-egu24-8594, 2024.

Hot extremes impose severe effects on human health and the ecosystem, especially when high-temperature extremes sequentially occur in both daytime and nighttime within 1 day, known as Compound Hot Extremes (CHEs). Although a number of studies have focused on independent hot extremes, not enough work is devoted to compound ones, not to mention the coupling strength in covariations between the two variables (daytime and nighttime temperature: Tmax and Tmin) over a given region. The instantaneous coupling strength can be derived by Dynamical System (DS) approach from covariations between Tmax and Tmin over a given region, and used to classify CHEs into coupled and decoupled types. Results show that coupled CHEs tend to be more intense with prolonged duration and extensive spatial extent compared with decoupled CHEs. Also, the mechanisms behind these two types of CHEs are largely different. Coupled CHEs are accompanied by a significant intensification and westward extension of the western North Pacific subtropical high (WNPSH), and the extremely high-temperature is mainly caused by receiving more solar radiation under the corresponding anticyclone. It is found that barotropic structure, weak jet stream and developing La Niña are conducive to the enhancement and persistence of WNPSH, in favor of the occurrence of long-lasting CHEs. Decoupled CHEs are associated with strong sea-land breeze (SLB), whose diurnal cycle could weaken the persistent large-scale circulation and suppress covariations between Tmax and Tmin. This kind of decoupled hot extremes are attributed to the combined effect of receiving more solar radiation during the day and trapping more long-wave radiation at night, where moisture and cloud cover play an important role.

How to cite: Guo, Y. and Fu, Z.: Regional coupled and decoupled day-night compound hot extremes over the mid-lower reaches of the Yangtze River: characteristics and mechanisms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5420, https://doi.org/10.5194/egusphere-egu24-5420, 2024.