The frequency and intensity of heat stress are expected to escalate markedly in the near future under various global climate change scenarios, with densely populated cities becoming hotspots because of the urban heat island effect. Therefore, heat stress analysis for highly populated cities is crucial since changes in this stress exacerbate vulnerability, increase health-related risks and impose constraints on outdoor activity. This study investigates changes in heat stress during 21st century in terms of frequency, intensity and durations while quantifying population exposure to heat stress covering Northwestern Türkiye, with particular attention to Istanbul, the most populous city in Türkiye with nearly sixteen million population.
In this study, we use climate simulations from convection-permitting model COSMO-CLM under SSP3-7.0 emission scenario to investigate future changes in heat stress. The analysis focuses on calculating Wet Bulb Temperature (WBT) values and assessing consecutive hours when Wet Bulb Temperature (WBT) is above specific thresholds, which are critical indicators of heat stress severity. In addition, we conduct comprehensive heat stress evaluation by computing Environmental Stress Index (ESI) values, an effective alternative to WBGT, to assess outdoor activity limitations. These analyses are performed for the reference period of 1985-2015 and extended to future periods of 2030-2039, 2050-2059, 2070-2079 and 2090-2099, providing a detailed temporal perspective on the progression of heat stress and its implications under changing climatic conditions.
WBT uses air temperature and relative humidity as its primary parameters while ESI incorporates radiation alongside air temperature and relative humidity. Thus, this study also comprehensively analyzes the role of radiation in amplifying heat stress. Our results reveal a remarkable seasonal shift in heat stress pattern within the study area with Istanbul standing out as a hotspot where heat stress indices are notably higher than those of other cities in the covered region, highlighting the effect of urbanization in heat stress dynamics.
Notably, ESI values in the southern parts of Istanbul, where urbanization is more concentrated, exceed critical thresholds that makes any physical activity to be hazardous especially by the end of this century. Moreover, projections demonstrate that in the late 21st century, majority of Istanbul’s population will be exposed to heat stress levels exceeding the risky thresholds. Furthermore, this study explores the extent of population exposure to heat stress, the duration of consecutive hours exceeding critical thresholds, and the percentage of areas where indices exceed their limits.
Key words: Climate modelling, heat stress, heat extremes, population exposure, COSMO-CLM
How to cite: Tiryaki, G. O., Sonuç, C. Y., Moral, A. C., and Ünal, Y.: Future Heat Stress Projections in Northwestern Türkiye: Urbanization and Population Impacts in Istanbul, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17450, https://doi.org/10.5194/egusphere-egu25-17450, 2025.
The marine heatwave in the North Atlantic in summer 2023 set new temperature records and raised concerns about the impact of climate change on oceanic extreme events. This study examines this record-breaking marine heatwave with a focus on the subpolar North Atlantic by analysing ECMWF ERA5 reanalysis data and the Max Planck Institute Grand Ensemble CMIP6 version (MPI-GE CMIP6).
We demonstrate that due to a superposition of the global warming background state and natural variability, individual members of MPI-GE CMIP6 reproduce a North Atlantic summer heat wave within recent decades, which matches the strength of the observed 2023 heatwave. We assess possible atmospheric and oceanic drivers, including those not discussed in the literature so far, such as the atmospheric circulation state and associated surface heat flux in the preceding winter or the oceanic heat transport convergence across the subpolar North Atlantic. Our results indicate that for the subpolar North Atlantic processes related to oceanic and atmospheric variability have significantly contributed to the record observed and simulated heatwaves. Based on the historical and future scenarios of MPI-GE CMIP6, we suggest that both frequency and intensity of marine heatwaves in the North Atlantic will increase significantly, which may have various impacts on marine ecosystems and regional climate.
How to cite: Lohmann, K., Nasirova, H., Liu, Q., Jungclaus, J., Matei, D., and Marzeion, B.: Assessing record-breaking North Atlantic warming extremes in summer 2023 using reanalysis and Grand Ensemble simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14842, https://doi.org/10.5194/egusphere-egu25-14842, 2025.
With climate change, heavy-impact extremes have become more frequent in different regions of the world. It is therefore crucial to further physical understanding of extremes, but due to their rarity in samples, this remains challenging.
One way to overcome this under-sampling problem is through Ensemble Boosting, which uses perturbed initial conditions of extreme events in an existing reference climate model simulation to efficiently generate physically consistent trajectories of very rare extremes in climate models. However, it has not yet been possible to estimate the return periods of these storylines, since the conditional resampling alters the probabilistic link between the boosted simulations and the underlying original climate simulation they come from.
Here, we introduce a statistical framework to estimate return periods for these simulations, by using probabilities conditional on the shared antecedent conditions between the reference and perturbed simulations. This theoretical framework is evaluated in and applied to simulations of the fully-coupled climate model CESM2. Our results show that return periods estimated from Ensemble Boosting are consistent with those of a 4000-year control simulation, while using approximately 5.8 times less computational resource use.
We thus outline the usage of Ensemble Boosting as a tool for gaining statistical information on rare extremes. This could be valuable as a complement to existing storyline approaches, but also as an additional method of estimating return periods for real-life extreme events.
How to cite: Bloin-Wibe, L., Noyelle, R., Humphrey, V., Beyerle, U., Knutti, R., and Fischer, E.: Estimating Return Periods for Extreme Climate Model Simulations through Ensemble Boosting, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10393, https://doi.org/10.5194/egusphere-egu25-10393, 2025.
The occurrence of climate extremes is influenced by climate forcing as well as internal climate variability: internal variability may temporarily obscure or enhance the forced signal in climate extremes. The role of signal versus noise plays an important role, for instance in the analysis of emergence. The climate extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) are routinely used to assess the impacts of forced change on climate extremes, but in such analyses internal variability is often ignored. We present a comprehensive catalogue of the importance of internal variability for the 27 ETCCDI indices to inform climate extreme analysis and guide impact science.
In our assessment, we use a 50-member ensemble of the CMIP6 generation MPI-ESM 1.2 LR Earth System Model for 1961-2014 to highlight combinations of regions and indices that are strongly affected by internal variability. Unlike previous work, we consider all ETCCDI indices in the same model ensemble to provide a clean identification of internal variability. Using the coefficient of variation as initial metric, we find that the total signal is strongly affected by internal variability
- over ocean regions for temperature indices based on percentile thresholds (e.g. tx90p),
- along quasi-zonal mid-latitude bands for absolute maximum/minimum temperature indices (e.g. txx), and
- in characteristic (sub-)tropical “hot-spot” regions such as northern Africa, the eastern central Pacific, and the south-east of all ocean basins for precipitation-based indices (e.g. r95p).
This grouping illustrates the differing relative importance of internal variability for the extreme signal depending on the index and the region, and sheds light on processes that contribute to the occurrence of climate extremes. Further, the catalogue provides a tangible resource that enables users of ETCCDI indices to better understand the robustness of index information they might derive from single model runs or observations. Based on our catalogue, users, e.g. impact scientists, may select suitable indices specific to their region of interest and application.
How to cite: Borchert, L., Poschlod, B., Brunner, L., Mithal, V., Castillo, N., and Sillmann, J.: The importance of internal variability for climate extreme indices, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5625, https://doi.org/10.5194/egusphere-egu25-5625, 2025.
The polar regions are among the most affected by global warming, making them particularly vulnerable to extreme events with significant impacts on the cryosphere, permafrost, and wildfires. Record-breaking temperature and precipitation extremes are becoming increasingly widespread and intense globally. Extreme heat events are projected to increase in frequency, intensity, and duration throughout the 21st century. Furthermore, a sea-ice-free Arctic is becoming a probable scenario. This raises critical questions with significant implications for hazard assessment and adaptation policies: how will compound temperature-precipitation extremes evolve in the polar regions, and which areas will be most vulnerable? Addressing these questions is challenging due to the coarse resolution of current state-of-the-art (CMIP6) future projections. We use state-of-the-art simulations from the EU project PolarRES. They offer an unprecedentedly high-resolution (11 km) Pan-Arctic ensemble developed within the Polar-CORDEX framework. The simulations downscale two different CMIP6 models that are representative of the spread for CMIP6 projections under the SSP3-7.0 scenario. They provide a continuous 120-year (1985-2100) time series of hourly temperature and precipitation data. We assess compound temperature-precipitation extreme events in the Arctic by mid and end of the century, with a focus on the intensity and persistence of these extremes. This extensive dataset allows us to confidently (1) pinpoint areas that may become more vulnerable to increased occurrences of extreme events in the future, (2) compare near-term, mid-century and end-century distributions and patterns, and (3) identify emerging trends. A clustering analysis will be used to identify regions of the Arctic with similar precipitation-temperature characteristics. With this approach, we can determine whether regions with distinct climate profiles exhibit different trends and behaviours.
How to cite: De Falco, C., Mooney, P. A., Kumar Samantaray, A., Mottram, R., Landwehrs, J., Rinke, A., van de Berg, W. J., van Dalum, C., Landgren, O. A., Haakenstad, H., Bhatt, B. C., Lambin, C., and Fettweis, X.: Projected Evolution of Compound Temperature-Precipitation Extremes in the Arctic: Insights from a multi-model High-Resolution regional climate ensemble , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10851, https://doi.org/10.5194/egusphere-egu25-10851, 2025.
Continued greenhouse gases emissions are warming our planet, with catastrophic consequences for its habitability and the natural world. Rapid and deep decarbonization to "net zero" carbon dioxide emissions will be needed to halt global warming, and must be achieved by 2050 to stay within the 2015 Paris Agreement thresholds. However, the public debate is increasingly exposed to claims that technological geoengineering "fixes" could reduce projected climate impacts, including in polar regions where current and projected changes have severe and irreversible consequences locally and globally.
As a community of polar and cryosphere scientists, we have evaluated five highly publicized geoengineering proposals that are either focused on the polar regions or would have major impacts on these systems: stratospheric aerosol injection, sea curtains/sea walls to prevent warm waters reaching glaciers and ice shelves, sea ice management through modifying albedo and thickening sea ice, slowing ice sheet flow through basal water removal and ocean fertilization. Based on our rigorous analysis of technological availability, logistical feasibility, cost, predictable adverse consequences, environmental damage, scalability (in time and space), governance, and ethics, we conclude that none of these geoengineering ideas pass an objective and comprehensive test regarding its use in the coming decades. Instead, many of the proposed ideas are environmentally dangerous. Furthermore, funds spent in researching these ideas further is divesting from much needed research on mitigation and adaptation to climate change and bestow unwarranted public credibility to these geoengineering schemes. We stress that given their feasibility challenges and risks of negative consequences, these ideas should not distract from the foremost priority to reduce greenhouse gas emissions and achieve successful adaptation.
How to cite: Cavitte, M. G. P., Siegert, M., and Sevestre, H. and the Authors of "Safeguarding the polar regions from dangerous geoengineering": Many reasons to safeguard the polar regions from dangerous geoengineering, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15749, https://doi.org/10.5194/egusphere-egu25-15749, 2025.
As the climate warms, cold waves are expected to become less intense and less frequent. Is there still a risk of reliving events comparable to the most intense cold spells we can remember? We analyze four remarkable cold spells that have occurred since 2010 in different regions: Western Europe, Texas, China, Brazil. We show that all these recent events have a moderate to high probability of not happening again by 2100 – typically 50% to 90% in an intermediate emissions scenario, depending on the event. The probabilities are even higher for iconic events of the 20th century or earlier. Our results suggest that the most intense cold snaps, and their associated icy landscapes in mid-latitude regions, are disappearing or have already disappeared due to anthropogenic climate change.
How to cite: Ribes, A., Robin, Y., Tessiot, O., and Cattiaux, J.: Recent extreme cold waves are likely not to happen again this century, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15644, https://doi.org/10.5194/egusphere-egu25-15644, 2025.
Cut-off lows are, and will be in the future, one of the main threats related to severe weather in the Iberian Peninsula, especially in the Mediterranean arc. Cut-off lows are often accompanied by heavy precipitations in a short time promoting flash-floods, as well as hail, strong convectively wind gusts and/or tornadoes.
On the week of October 27th – November 4th, 2024, a cut-off low affected the Iberian Peninsula with extreme socio-economical impacts in several Spanish regions and, especially, in the Valencia area. The phenomena on the surface have varied depending on the region: large hail (5-7 cm), several tornadoes, strong wind gusts and, above all, extreme precipitations. The most severe day was October 29th in the Valencia region, with rainfall accumulations higher than 300 mm in a notable area and locally registering 771 mm in 24 hours. In addition, the Turís official weather station registers numerous rainfall intensity national records. Moreover, the convective system promotes 11 tornadoes (two of them with intensity IF2) and large hail (~ 5 cm). The social impact of the floods in Valencia was very high, with more than 16.5 billion euros of damage to infrastructure (roads, railways, etc.), housing and croplands, as well as 231 fatalities and three missing.
In this survey, we focus on Valencia’s floods on October 29th. Here, by performing model simulations with the WRF-ARW model and using a storyline approach, we find an enhancement in intensity and a significant increase in extreme accumulated rainfall area (e.g., 100 mm, 180 mm, 200 mm, and 300 mm) caused by current anthropogenic climate change conditions compared to preindustrial ones.
How to cite: Calvo-Sancho, C., Díaz-Fernández, J., González-Alemán, J. J., Azorín-Molina, C., Halifa-Marín, A., Montoro-Mendoza, A., Bolgiani, P., Beguería, S., Vicente-Serrano, S. M., Morata, A., and Martín, M. L.: Anthropogenic Climate Change Attribution to a Record-breaking Precipitation Event in October 2024 in Valencia, Spain , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15941, https://doi.org/10.5194/egusphere-egu25-15941, 2025.
Accurately modeling emerging physical climate risks to natural and societal systems—such as global supply chains, the food system, health, and critical infrastructures—is essential for effective preparedness and honest discussions about the consequences of rising greenhouse gas emissions.
A series of anomalous weather events that shattered previous records by wide margins has —yet again—highlighted the need for an improved understanding of the physical processes behind weather and climate extremes, their statistical characteristics, and our ability to project them under future emission scenarios using climate models.
In this Award lecture, I will present an overview of recent studies and preliminary findings that explore the mechanisms and physical drivers of high-impact climate extremes, as well as their statistical characteristics, such as simultaneous or sequential occurrences, which can lead to high societal impacts under current and future climate conditions and will reflect on our capacity to reproduce such events in climate models.
How to cite: Kornhuber, K.: Physical drivers and statistical properties of high impact climate extremes , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16597, https://doi.org/10.5194/egusphere-egu25-16597, 2025.
In the last decades, highly impacting climate extremes have become increasingly frequent in many different global hotspots. According to climate projections, such events are likely to become even more severe during the 21st century, to the point that under the less conservative scocio-economic scenarios, they could become so recurrent that they possibly constrain the ability to adapt and mitigate, especially in poorly developed countries.
This study investigates the future occurrence of unprecedented heatwaves, droughts, rainfall and snowfall, namely the time of their emergence and when and where they will become the new climate normals, defined here as at least one such event any other year. As input data, we use an ensemble of high-resolution bias-adjusted climate simulations from the ISIMIP3b family and we focus on four SSPs (SSP1 to SSP5, excluding SSP4). Using population, land-use, and GDP projections without climate change, we also analyse their exposure to such unprecedented climate extremes from 2041 to 2100, focusing on continental and macro-regional scales.
We also present preliminary results obtained by using emulated scenarios, with a special focus on the possibility of preventing such unprecedented extremes under low-emission scenarios (SSP1-1.9 and SSP1-2.6) with specific temperature overshoot trajectories. We show that limiting frequent record-breaking heatwaves and droughts could be highly beneficial, especially in regions with lower income and higher vulnerabilities as Africa and Latin America.
The results presented in this study are included in the framework of the EUNICE project, which aims at quantifying the economic and non-economic impacts of future climate extremes, providing robust quantification of uncertainties.
How to cite: Spinoni, J., Mastropietro, M., Rodriguez-Pardo, C., and Tavoni, M.: Human and land exposure to future recurrent unprecedented extremes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5022, https://doi.org/10.5194/egusphere-egu25-5022, 2025.
Temperature extremes have a substantial impact on society and the environment, however a full physical understanding of their formation mechanisms is still lacking. In particular, the relative importance of the three key processes – horizontal temperature transport, subsidence accompanied by adiabatic warming, and diabatic heating – is still debated. Here, we present a global quantification of the contributions from these processes to near-surface warm and cold extremes using the Lagrangian framework. To this end, we apply two different Lagrangian temperature anomaly decompositions: one based on the full fields of the respective terms, and the other one based on the anomaly fields of the respective terms (i.e., deviations from their corresponding climatologies). We will show that the results from the full-field decomposition mostly align with those of a previous study, while the anomaly-based decomposition offers a completely new assessment of the roles of the different processes, especially with regard to warm extremes.
How to cite: Mayer, A. and Wirth, V.: A global Lagrangian analysis of near-surcface warm and cold temperature extremes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1556, https://doi.org/10.5194/egusphere-egu25-1556, 2025.
Following the extreme European summer heatwave of 2003, it has been suggested that the event might have been associated with changes in the distribution of summer temperatures. Here we revisit this hypothesis and investigate observed European and Swiss summer temperatures for the period 1864-2024.
The pronounced increase in skewness has a number of important implications: (1) It implies that extreme hot summers have become more frequent than expected from the median warming. In particular, the increase in skewness strongly affects estimates of the probability of extreme summer heatwaves such as 2003 and 2018. (2) It is demonstrated that the increase in skewness can partly be explained by the accelerating warming around 1980. It is thus not clear whether the high values in skewness will persist into the future. (3) There is a statistically significant difference in the trends of median and mean warming, with mean temperatures warming stronger than the median. (4) These different warming rates explain a non-negligible fraction of the so-called mismatch (i.e., summer temperatures in observations have warmed stronger than in CMIP and CORDEX scenarios). (5) It is demonstrated that understanding this mismatch requires an assessment of extreme summer temperatures, beyond the more commonly used mean summer temperature trends.
We will also provide estimates of the frequency of 2003-like summer heatwaves for the current and future climate, making different assuptions about the persistence of the aformentioned changes in skewness.
How to cite: Schär, C. and Chiriatti, F.: Revisiting recent changes in European summer temperature distributions and assessing their role for extreme summer temperatures, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17421, https://doi.org/10.5194/egusphere-egu25-17421, 2025.
In the past two decades, the intensity of European summer heatwaves has strongly increased due to anthropogenic emissions and associated rising global mean temperatures. On the one hand, the anthropogenic forcing is causing an increase in European summer temperatures, shifting European summer temperature distributions towards warmer values and intensifying European summer heatwaves. On the other hand, the anthropogenic forcing is expected to affect the internal climate variability under global warming, changing the variability of European summer temperatures. While the effects of the forced changes in internal variability have been long debated for mean or maximum summer temperatures, the effects of the forced changes in internal variability on European summer heatwave intensity under increasing global warming levels remain unknown. Using four state-of-the-art global climate model large ensembles, we find that the forced changes in internal variability will intensify central and northern European summer heatwaves. In central and northern Europe, soil moisture is projected to decrease, leading to frequent moisture limitations, enhancing land-atmospheric feedback, and increasing heatwave intensity and variability. On the contrary, the forced changes in internal variability will weaken southern European summer heatwaves. Southern Europe is projected to face significant soil moisture depletion, leading to more stable moisture-depleted conditions that reduce extreme temperature variability and heatwave intensity. Our findings imply that while adaptation to increasing mean temperatures in southern Europe should suffice to reduce the vulnerability to increasing European summer heatwave intensity, adaptation to increased temperature variability will also be needed in central and northern Europe.
How to cite: Beobide-Arsuaga, G., Suarez-Gutierrez, L., Barkhordarian, A., Olonscheck, D., and Baher, J.: Increased central and northern European summer heatwave intensity due to the forced changes in internal climate variability, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15386, https://doi.org/10.5194/egusphere-egu25-15386, 2025.
The frequency, duration and intensity of summer extreme temperatures over Europe have increased since the mid-20th century due to dynamic changes, thermodynamic factors, and their interaction via land—atmosphere feedbacks. However, a comprehensive analysis of all the mechanisms underlying their future trends, including an assessment of uncertainties due to inter-model differences and internal variability, is still lacking.
In this study, we investigate historical and future trends in the occurrence of atmospheric circulation patterns that triggered the three most intense heat waves during 1940—2022, identified using the Heat Wave Magnitude Index daily (Russo et al., 2015): the 2010 Russian, the 1972 Scandinavian and the 2003 French heat wave. To do that, we adopt the atmospheric flow analogue technique. We then decompose the trends of summer extreme temperature occurrences associated with these analogues in their thermodynamic, dynamic and interaction components, following Horton et al. (2015). The analyses are performed using large ensemble of climatic projections from six different models (three CMIP5 and three CMIP6), under the “business-as-usual" emission scenario. This approach allows us to investigate the role of the global warming, internal climate variability and model uncertainties on the European extreme temperature trends.
The results show a future increase in the occurrence of atmospheric circulation patterns similar to the 2003 French heat wave across all models. However, models generally underestimate observed historical trends, suggesting that future trends may be even higher. Furthermore, the results show that the extreme temperature occurrences associated with these analogues have increased in the historical period and will keep increasing in the future. In this context, trend partition analysis indicates that, while the historical trends were primarily driven by thermodynamic component, the future trends will be mainly driven by the interaction term. Interestingly, the interaction and dynamic components will explain a larger percentage of the total trend compared to the past, while the thermodynamic contribution will become less significant. Finally, the results suggest that land—atmosphere coupling processes will play a critical role in explaining the physical meaning of future interaction term and, thus, in driving projected increase in extreme temperature occurrences.
Results for the 2010 Russian and 1972 Finland heat waves generally align with those of the 2003 French heat wave. However, their dynamic trends are subjected to a certain degree of uncertainty due to inter-model differences, limiting the reliability of future dynamic projections and trend partition.
Bibliography
Horton, D. E., et al. (2015). Contribution of changes in atmospheric circulation patterns to extreme temperature trends. Nature, 522 (7557), 465-469.
Russo, S., et al., (2015). Top ten European heatwaves since 1950 and their occurrence in the coming decades. Environmental Research Letters, 10 (12), 124003.
How to cite: Famooss Paolini, L., Pascale, S., Ruggieri, P., Brattich, E., and Di Sabatino, S.: The drivers of summer extreme temperature trends in Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11794, https://doi.org/10.5194/egusphere-egu25-11794, 2025.
The study of the statistical and dynamical characteristics of extreme and very extreme events in the climate system is impaired by a strong under-sampling issue. Here we use a rare events algorithm to massively increase the number of extremely hot summers simulated in the state-of-the-art IPSL-CM6A-LR climate model under present and future anthropogenic forcings. This allows us to reach precise climatological results on the dynamics leading to centennial hot summers. We demonstrate that the dynamics leading to these hot summers tend to be more local and less large scale-organized with climate change. In the future, high temperatures are still reached via a large anticyclone, but anomalies do not extend as far longitudinally as in the present and arise mainly as a result of an increase in the intensity of surface heat fluxes.
How to cite: Noyelle, R., Caubel, A., Meurdesoif, Y., Faranda, D., and Yiou, P.: Dynamical evolution of extremely hot summers in Western Europe in response to climate change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3474, https://doi.org/10.5194/egusphere-egu25-3474, 2025.
In July 2021 extreme rainfall associated with a cut-off low pressure system led to huge impacts in western Germany, Belgium, and the Netherlands. The event was costly both in terms of loss of life and insurance damages. We use a multi-method approach to examine the event and to assess whether it could have been even worse. Using atmospheric analogues from reanalysis, pseudo global warming simulations, and a boosted ensemble of a dynamically similar event we show that the observed rainfall pattern is highly sensitive to the large-scale dynamics. For example, although good dynamical analogues are found in reanalysis, these do not all show the same hazards – with many showing very little rainfall.
Our results suggest the magnitude of rainfall experienced was very unusual, perhaps close to the worst possible in the current climate, as small dynamical changes lead to a drastic reduction of the rainfall.
How to cite: Thompson, V., Stoffels, R., de Vries, H., and Lenderink, G.: Was July 2021 extreme rainfall in western Germany close to the worst possible? , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8204, https://doi.org/10.5194/egusphere-egu25-8204, 2025.
How to cite: Leach, N., Ermis, S., Brocklehurst, A., Kumar, D., Georgiadis, A., Braun, L., and Shaffrey, L.: The perfect storm: loss potential of Eunice-like cyclones in a counterfactual climate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6589, https://doi.org/10.5194/egusphere-egu25-6589, 2025.
It is widely recognized that climate change is altering the likelihood and intensity of extreme weather events globally, including hydrological extremes such as floods. Compound flooding is driven by fluvial, pluvial and coastal flooding occurring simultaneously, resulting in a potentially larger impact when co-occurring than the sum of the univariate drivers happening separately. Identifying and communicating the effect of climate change on compound flooding remains challenging. A method to quantify the effect of climate change on these events is through climate attribution assessments.
This research assesses how existing climate attribution methods can be applied to compound events instead of univariate events. An event-based storyline attribution approach for compound flooding from historical tropical cyclones (TCs) in Mozambique is used to examine the effect of climate change on multiple flood drivers propagated to impact. TC Idai hit Mozambique in 2019 and caused over 600 fatalities, affected over 1.8 million people, resulting in $3 billion in damages. Idai is used as a case study, representing a highly destructive compound flood event.
Compound flooding is modelled using a state-of-the-art hydrodynamic modelling chain that combines the Super-Fast INundation for coastS (SFINCS) model with the hydrodynamic model Delft3D Flexible Mesh and hydrological model wflow, linked to a fast impact assessment tool Delft-FIAT to calculate the flood impact, here the direct economic damages. The drivers of compound flooding from TCs that are known to be affected by climate change, such as precipitation, wind and sea-level rise, are adjusted to create counterfactual scenarios. The compound flooding is modelled for the multiple factual and counterfactual scenarios, adjusting the separate drivers individually and simultaneously.
This approach enables the attribution of climate change effects on compound flooding from TCs while identifying potential changes in the contributions of individual flood drivers. Next steps include attribution uncertainty partitioning, comparing multiple climate attribution approaches for these events, assessing regional differences with relation to climate change effects on compound flood impact and comparing this methodology for multiple TCs in the same region, which may have different driver contributions.
How to cite: Vertegaal, D., van den hurk, B., Couasnon, A., Aleksandrova, N., Bovenschen, T., Treu, S., Mengel, M., and Muis, S.: Storyline climate attribution for compound flooding from tropical cyclone Idai in Mozambique. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2889, https://doi.org/10.5194/egusphere-egu25-2889, 2025.
Statistics-based extreme event attribution is often limited by the scarce availability of data and by the potentially inadequate representation of relevant physical processes in climate models. Storyline approaches, such as the ones involving large-scale flow analogs, can be used to constrain the impact of anthropogenic climate change on extreme events in a physically robust manner, complementing the information gained from statistics-based approaches.
In this work, we employ operational ECMWF analysis data and simulations from the CESM large ensemble (providing up to 1000 years of data) to characterize the dynamical evolution of Storm Boris, that brought a record-shattering precipitation event over central Europe between the 13th and the 16th of September 2024. Leveraging on the available large ensemble, we perform an analog-based attribution of the associated extreme precipitation informed by the peculiar atmospheric dynamics of the event.
The analysis is articulated in two parts. The first concerns a description of the salient dynamical features that made Storm Boris so extreme. Such features are: 1) a deep upper-level cut-off cyclone over the Mediterranean; 2) a slow-moving surface cyclone over eastern Europe; 3) a strong high-latitude blocking anticyclone building up during the event; and 4) moisture contributions from several sources across storm lifetime, rotating from the North Atlantic to the central and the eastern Mediterranean/Black Sea.
The second part is an analog-based attribution of the extreme precipitation that takes into account the pinpointed dynamical features. We show that a correct representation of the upper-level cut-off cyclone (using potential vorticity as a target field to determine analogs) and of the surface cyclone position at the time of the extreme precipitation (using a cyclone detection algorithm) drastically improves the quality of the detected large-scale flow analogs. Those two adjustments, informed by the knowledge of the dynamics of the event, allow to isolate the thermodynamical effect of climate change in a consistent manner and indicate a robust enhancement of extreme precipitation over central Europe for Boris-like storms occurring in a warmer climate.
How to cite: Riboldi, J., Agayar, E., Binder, H., Federer, M., Noyelle, R., Sprenger, M., and Thurnherr, I.: Dynamics-informed attribution of a record-shattering heavy precipitation event over Central Europe during Storm Boris (2024), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13073, https://doi.org/10.5194/egusphere-egu25-13073, 2025.
In September 2024, cyclone Boris brought intense precipitation to Central and Eastern Europe, causing severe flooding in Austria, Czech Republic, Poland, and neighboring countries. Understanding the processes that led to this event is important for improving the prediction and mitigation of similar events in the future. Here we trace the origin and transport pathways of the moisture contributing to the precipitation during the event using a Lagrangian moisture source diagnostic. The results show that evapotranspiration from land played a more important role than previously thought: most of the moisture came from the European continent, with additional contributions from the Mediterranean, Black, and Baltic Seas. To place the results in a broader context we compare them with a climatology of moisture sources based on a Lagrangian reanalysis dataset for the years 1940 - 2023. This provides additional insight into atmospheric processes driving heavy precipitation events in this region and highlights anomalous patterns associated with cyclone Boris.
Contributions of different source regions to precipitation in Central and Eastern Europe in September 2024. The figure shows the total precipitation from ECMWF (orange line) compared with the precipitation estimated by the Lagrangian moisture source diagnostic (blue line) and the contributions of different regions (defined in the upper left panel) in colors.
How to cite: Duetsch, M., Furian, S., Bakels, L., and Stohl, A.: Moisture origin for the heavy precipitation event in Central and Eastern Europe in September 2024, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19798, https://doi.org/10.5194/egusphere-egu25-19798, 2025.
The severity of the impacts of (convective) rainfall extremes in the past year alone, e.g., storm Boris and the flooding in middle Europe, or the flooding in the Valencia region, is mind blowing. With several hundreds of millimeters of rain falling in often fewer than 48 hours, the flooding was locally very disruptive, or even catastrophic. While often embedded in large-scale and reasonably well predictable (but anomalous) flow conditions, the level of small-scale detail and the role of smaller-scale (convective) processes that ultimately determine whether the situation "gets out of hand" - or not - is challenging both observation networks, and the NWP and climate-modelling centers.
In this presentation we take the example of storm Boris that caused widespread flooding in Middle Europe in September 2024 to illustrate that only by simulating the event at very high resolution the true changes in the impacts are revealed. Using a pseudo-global warming (PGW) framework in which the event is placed in historic and possible future climate conditions, we show that on a local scale the response strongly exceeds the regional response. By subsequently matching the patterns to underlying population densities an impression is obtained of how this leads to a greatly elevated impact on society.
Different frameworks have been developed to analyse, attribute and project extreme events often immediately after, or even prior to the event. The regional PGW framework we are adopting here is but one of the several existing approaches based on analysing 'counterfactuals', i.e., simulating the event in a different climate. Another framework is that of dynamic analogues which relies on deriving paste-to-present or present-to-future changes, by selecting and comparing similar (observed or modelled) events based on large-scale flow similarity. In this approach therefore, the event is also captured. Structural similarity in terms of flow conditions is not required by the approach of world-weather attribution (WWA). The WWA-approach examines changing frequency and intensity of local or regional extremes using non-stationary extreme-value analysis of observational and model data, and blends these two lines of information. All methods have their advantages and disadvantages. At best, these methods give overlapping results, but in practice they highlight different aspects of the (past or future) changes. This forces one to think how to combine or merge the output from the different methodologies to provide society with the most relevant information and to better anticipate on the future changes.
How to cite: de Vries, H. and Lenderink, G.: Local versus regional impact changes for storms like Boris (2024): insights from high-resolution pseudo global warming simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19142, https://doi.org/10.5194/egusphere-egu25-19142, 2025.
An increase in the intensity of daily precipitation extremes is among the most robust responses to anthropogenic climate change. However, while many studies have focused on moderate extremes corresponding to the mean of annual maxima, or their median which corresponds to a return period of 2 years, high-impact extreme precipitation events are related to less studied events with much longer return periods (e.g. 100 years, or longer). The physical and statistical study of these events is hampered by the difficulty in building robust statistics in climate records only a few-decades long. In particular, it is still poorly understood whether moderate and high-impact precipitation extremes may intensify at the same rate, or whether differences may arise due to, for instance, changes in the frequency or meteorology of the driving weather events, in their seasonality, or in the balance between convective and stratiform precipitation.
We address this question by exploring the projected changes in tail heaviness of daily precipitation extremes in 63 single-member simulations from the EURO-CORDEX ensemble, run at 12km resolution, in the RCP8.5 scenario. Tail heaviness (TH) is here defined as the ratio between the quantiles corresponding to the 100-year return period relative to the 2-year return period. Due to the difficulty in evaluating long return periods from single-member simulations, we first use the 50-member initial condition CRCM5 regional large ensemble, for which statistics can be accurately estimated, to test the ability of extreme value theory (GEV distribution) and Simplified Metastatistical Extreme Value theory (SMEV) in estimating changes in TH.
The results show that SMEV has a smaller root mean squared error than GEV in estimating changes in TH from 30-year long climate records extracted from the CRCM5 ensemble, proving it a better methodology for this purpose. When SMEV is applied to the CORDEX ensemble, a likely (66% to 90% of models) increase in TH is found in the Mediterranean region, while small and non robust changes are found in Central and Northern Europe. The robustness of the Mediterranean response is not detectable using GEV. The increase in TH is shown to constitute a sizable contribution to the increase in the 100-year level of Mediterranean precipitation extremes. A reduction in the number of precipitation events partly balances the increase in the 2-year return period, but has little impact on the 100-year return period, contributing to its faster relative intensification.
We conclude that while in Central and Northern Europe the rate of change in moderate (2-year) and high-impact extremes cannot be distinguished from estimation uncertainties, great care is needed in the Mediterranean region, where the risk of exposure to high-impact precipitation events due to climate change may be increasing faster than what perceived based on the trends of moderate extremes
How to cite: Zappa, G., Marra, F., and Pascale, S.: High-impact Mediterranean precipitation extremes to increase faster than moderate extremes in the CORDEX future projections, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13285, https://doi.org/10.5194/egusphere-egu25-13285, 2025.
On 17 August 2022, the western Mediterranean experienced an unusual thermodynamic environment with extremely high unstable atmospheric conditions, combined with strong wind shear. These conditions, occurring ahead of an eastward-moving weather disturbance called a shortwave trough, led to the formation of a bow-shaped system of thunderstorms. This system produced a long path of severe winds, stretching from the Balearic Islands to southern Czech Republic on 18 August. The strongest wind gust reached 62.2 m s⁻¹ at Corsica, where numerous records were beaten. Unfortunately, 12 people lost their lives, and 106 were injured during this event. Such a system was classified as a derecho, a type of long-lasting and severe windstorm generated by a line of thunderstorms.
A record-breaking marine heatwave (MHW) was present in the western Mediterranean simultaneously during the summer of 2022, peaking in July. The sea surface temperature (SST) was more than 3 °C above normal levels in the region where the storm developed. The extremeness of the summer 2022 MHW is evidenced by the high SST anomalies in the first half of August 2022, ranking first among all years since 1940. An attribution exercise with numerical experiments and novel results (González-Alemán et al., 2023) indicated that this derecho event was substantially amplified by the extreme MHW and suggested that current anthropogenic climate change forcing contributed to triggering the severe storm by creating an environment more favourable for convective amplification. The study demonstrated that in case a similar dynamical synoptic situation had happened in a preindustrial climate, the derecho would have not developed, highlighting the role of thermodynamic contributions from global warming. However, no answers can be obtained regarding its dynamical contribution.
Thus, to further investigate this event and the dynamical role of global warming in it, we explore the atmospheric mechanisms that potentially can lead to such a record-breaking event, from the atmospheric dynamics and circulation point of view, and try to answer why climate change has played a crucial role from this perspective.
How to cite: González-Alemán, J. J., Oltmanns, M., González-Herrero, S., Donat, M., Doblas-Reyes, F., Vitard, F., Riboldi, J., Álvarez-Castro, C., Barriopedro, D., and Jiménez-Esteve, B.: From Greenland to the Mediterranean Sea: Unveiling a new cascade mechanism under anthropogenic warming?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15809, https://doi.org/10.5194/egusphere-egu25-15809, 2025.
Cyclone Daniel was the deadliest Mediterranean storm on record and struck Greece and Libya in September 2023. In our study, we aim to disentangle the factors contributing to the severity of the event, with a focus on the influence of anthropogenic climate change. To this end we utilized a process-based, conditional attribution approach and simulated storylines of the event with a convection permitting regional climate model under actual and counterfactual conditions. Specifically, we tested how cyclone Daniel would have unfolded (1) in a 1970s world with 1°C less climate change; (2) without the prevalent Mediterranean sea surface temperature anomaly of +1.3 °C; and (3) with decreased soil moisture in the Balkans assuming no rainfall anomalies had occurred in the months prior to the event. Climate response uncertainties have been approximately accounted for by imposing climate change signals from different GCMs.
Our simulations show that 1°C of climate change only moderately influenced the cyclone's extreme precipitation during its early phase in Greece. In contrast, during its tropical-like Libyan phase, this level of climate change has amplified the severity of the event by a staggering 30 to 60%. Increased energy availability and convection led to the formation of a rare and destructive Medicane with a warm and rapidly deepening core. Artificially lowering only the sea surface temperatures reduced the meteorological hazards in both phases and underpins the importance of the Mediterranean as an energy and moisture source. Reducing soil moisture over the Balkans alone, although an important source for evapotranspiration during the early phase, did not substantially affect the intensity of the cyclone.
Our results demonstrate that current climate change can already be a game changer for individual extreme events and highlight the power of storylines to analyze the potentially destructive influence of climate change on rare extreme weather events.
How to cite: Roither, L., Maraun, D., and Truhetz, H.: Climate change caused the catastrophic severity of Cyclone Daniel over Libya in 2023, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8602, https://doi.org/10.5194/egusphere-egu25-8602, 2025.
Between July 19 and 24, 2023, a multi-day outbreak of severe convective storms impacted Europe, affecting several countries. Northern Italy experienced multiple severe storms during this period, with July 24 marking the most intense day, particularly for hailstorms. On this day, three long-lived hailstorms caused significant damage, injured 119 people, and produced the largest hailstone ever observed in Europe—and the second largest globally—with a diameter of 19 cm. Recent studies highlight positive trends in both the frequency and intensity of convective environments favorable to thunderstorm activity in this region, alongside an increase in reports of large hail events.
This case study examines these trends in the context of the July 24, 2023, event, aiming to determine whether significant changes have occurred that may have increased the likelihood or severity of such an event. We employ a storyline approach based on circulation analogs to analyze the atmospheric conditions leading to this hailstorm.
Results show that similar events are fuelled by much larger CAPE today compared to just a few decades ago, likely linked to the strong upward trend in Mediterranean sea surface temperatures, coupled with a modest decrease in bulk wind shear. Additionally, the data suggest a potential intensification of the dynamics underlying similar configurations over the past 70 years, due to steepening of the horizontal geopotential gradient across the region.
How to cite: Pons, F.: Analogs-based attribution of the July 24th, 2023 extreme hail storms in northeastern Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6770, https://doi.org/10.5194/egusphere-egu25-6770, 2025.
Transitions from dry to wet states challenge water management and can lead to severe impacts on infrastructure and water quality. Such transitions occur both in the atmosphere and hydrosphere, that is, from dry-to-wet spells and from droughts to floods, respectively. While transitions from dry-to-wet spells, i.e. from negative to positive precipitation anomalies, are relatively well studied, it is yet unclear how they propagate to hydrological transitions from negative to positive streamflow anomalies. Here, we address the question of how often, where, when, and why meteorological transitions do propagate to drought-to-flood transitions using a large-sample dataset of precipitation and streamflow observations over Europe. Our analysis of the relationship between meteorological and hydrological transition events shows that only 10% and 25% of the dry-to-wet transitions propagate to drought-to-flood transitions at a monthly and annual time scale, respectively. The limiting factors for transition propagation are clear differences in the seasonality of meteorological and hydrological transitions and the limited propagation of wet spells, in particular those with low precipitation intensities and small volumes. Transition propagation is most likely in small and rainy catchments, that is, catchments with a relatively direct link between precipitation and streamflow and limited storage influences. We conclude that hydrological transitions are only weakly related to meteorological transitions, which highlights the important influence of land-surface and storage processes for the development of hydrological transitions. As a consequence, changes in dry-to-wet transitions are a relatively poor proxy for future changes in drought-to-flood transitions.
How to cite: Brunner, M. I., Anderson, B., and Munoz-Castro, E.: How do transitions from dry to wet states propagate to drought-to-flood transitions?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1678, https://doi.org/10.5194/egusphere-egu25-1678, 2025.
Record-shattering events, defined as extreme events that exceed previous records by large margins, pose increasing risks under climate change. Concurrent soil moisture droughts across multiple crop-growing regions can severely impact the agricultural sector and global food security by exposing a large fraction of the global crop area to water stress. Here, using soil moisture data from Single Model Initial-condition Large Ensembles (SMILEs) over 1950-2099, we investigate the evolution of the probability of spatially compound droughts that shatter previous records in terms of total global crop area affected by droughts within the same year. Our results indicate that trends in mean soil moisture related to climate change are the major driver in the evolution of the record-shattering compound drought probability, while changes in variability (standard deviation of the time series) are less important. We further attribute changes in the probability of such global-scale record-shattering events to trends in soil moisture in individual large crop-growing regions. By separating the distinct roles of long-term trends in mean conditions, variability of the soil moisture time series, as well as contributions from individual regions to global-scale record-shattering droughts across breadbaskets, this study provides novel insights on compound events threatening the global food security system.
How to cite: Li, J., Zscheischler, J., and Bevacqua, E.: Evolution of the probability of record-shattering spatially compounding droughts in a changing climate , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12916, https://doi.org/10.5194/egusphere-egu25-12916, 2025.
In the past decades European summers were marked by extreme heat, marking the most severe warm seasons of temperature records. In particular, in 2003, 2018, and 2022, Europe experienced unprecedented extreme temperatures with temperature anomalies exceeding 2.5 standard deviations. The prolonged heat affected human health, agriculture, economy, and our whole ecosystem, highlighting the need for reliable climate predictions. By using the Max-Planck-Institute Earth System Model, we demonstrate that these extreme summers could have been predicted at least three years in advance by taking into account the preceding sub-decadal variations of heat content in the North Atlantic Ocean. By using a subset of ensemble members that can explicitly include the heat accumulation in the North Atlantic, the prediction skill of physical states, i.e. temperature could be improved, but also user-specific quantities in the agricultural sector, such as growing degree days, for both, Europe-wide and smaller scales for certain regions and specific growing degree day thresholds for crop harvests. These findings underscore the value of incorporating sub-decadal oceanic processes into user-relevant climate prediction methodologies. We demonstrate that the agricultural sector particularly benefits from improved predictions for growing degree days which allow for timely adaption and preparation against extreme heat.
How to cite: Wallberg, L., Suarez-Gutierrez, L., and Müller, W. A.: Extremely Warm European Summers predicted more accurately by considering Sub-Decadal North Atlantic Ocean Heat Accumulation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10125, https://doi.org/10.5194/egusphere-egu25-10125, 2025.
Climate change is bringing more marine heatwaves and more rainy extratropical cyclones, both trends already detectable. In parallel, storms are usually responsible for the ending of surface-based marine heatwaves. We employ a newly-developed regional coupled system at km-scale over Northwest Europe to show the relationships between marine heatwaves, storms and phytoplankton activity. We show that a marine heatwave amplified the rainfall, river flows, waves and surge of the most impactful storm of 2023 over the United Kingdom (storm Babet). We also show that storms terminating marine heatwaves can either increase or decrease phytoplankton activity, depending on seasonality. Finally, we show the high resolution, high frequency coupling system is also able to represent meteotsunamis (sub-tidal sea surface disturbances linked with slow-moving pressure disturbances), and opens a whole new area of research on compound convective systems and meteotsunami research. In addition to case-studies, we will present plans to use this coupled system across weather and climate time-scales, to increase our understanding and resilience to extreme compound events.
How to cite: Berthou, S., Makrygianni, N., Mahmood, S., Partridge, D., Castillo, J., Arnold, A., and Goswami, P.: Interlinks between marine heatwaves, multi-hazard extratropical cyclones, meteotsunamis and phytoplankton blooms over Northwest Europe: insight from a km-scale regional coupled model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19550, https://doi.org/10.5194/egusphere-egu25-19550, 2025.
Puerto Rico is a tropical island that frequently receives heavy rainfall from a variety of systems, including tropical cyclones like Hurricane Maria (2017), mesoscale convective systems (MCSs), and isolated convection. Its two distinct rainy seasons are dictated by moisture convergence associated with the North Atlantic Subtropical High, while sea breezes and complex topography influence precipitation on the mesoscale. Previous research has examined how tropical precipitation could change in a future climate, showing a decrease in precipitation by 2100 using global climate models (GCMs). However, relatively little research has been conducted using convection-permitting climate models over the tropical Atlantic to understand how precipitation extremes could change in a warmer climate. Here, we fill this gap by dynamically downscaling a 0.25 degree GCM 10-member ensemble to 3 km using the Model Prediction Across Scales (MPAS) model for extreme precipitation events in a current (2001-2021) and future climate (2041-2061) over Puerto Rico. We show that MPAS is largely able to reproduce extreme precipitation events in the current climate when compared to observations and captures a variety of systems. We explore how future changes in extreme rainfall events in the early rainy season, which are largely driven by MCSs and isolated convection, compare to changes in the late rainy season, which are primarily due to tropical cyclones.
How to cite: Dougherty, E., Prein, A., and O'Gorman, P.: Future Changes to Extreme Rainfall over Puerto Rico in an Ensemble of Convection-Permitting Simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4554, https://doi.org/10.5194/egusphere-egu25-4554, 2025.
India has experienced a notable rise in the intensity, frequency, and spatial extent of extreme weather events in recent decades, with extreme precipitation along the southwest coast being particularly alarming. The drivers behind these events remain uncertain due to the variability in meteorological and oceanic factors and associated large-scale circulations. The present study attempted to identify a combination of dynamic, thermodynamic, and cloud microphysics processes contributing to the anomalous precipitation over the southwest coast of India from 1-10 August 2019 against its climatology using reanalysis and observational datasets. Key findings reveal the critical role of warm sea surface temperature anomalies (>1.4°C), reduced outgoing longwave radiation (<-50 W/m²), and elevated atmospheric temperatures (>1.6°C over the ocean) in enhancing atmospheric moisture capacity by nearly 10%. Strengthened low-level winds (anomalies >4 m/s) transported this moisture from the ocean to the land, while vertical updrafts (> -0.4 m/s anomalies) increased atmospheric instability and moisture convergence. Additionally, significant anomalies in cloud hydrometeors (>2.5×10⁻⁴ Kg/Kg) supported prolonged intense precipitation. These results improve our understanding of the interaction between ocean-atmosphere dynamics and wind patterns, highlighting their vital role in shaping regional weather and climate.
Keywords: Extreme precipitation, Western ghats, Atmospheric processes, Reanalysis.
How to cite: Khadke, L., Budakoti, S., Verma, A., Bhowmik, M., and Hazra, A.: Atmospheric and Oceanic Processes Behind Extreme Precipitation: A Case Study of the Western Ghats, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-916, https://doi.org/10.5194/egusphere-egu25-916, 2025.
Possibility of the occurrence of extreme weather and climate is often predicted in recent climate impact studies under certain global warming scenarios using climate models. However, it is usually unclear how such weather extremities occur as the resolution of the current generation climate models is not good enough to resolve individual storm system let alone pinning down the physical mechanisms. This ambiguity in physical mechanism impedes the better understanding of the nature of these extreme weather/climate events and can lead to ineffective mitigation and/or adaptation measures. For example, when the term extreme rainfall is mentioned, it is unclear whether it is caused by severe convective storms or by regular storms that have higher liquid water contents (LWC), as both can lead to large amount of rainfall. But the detailed physical mechanisms of these two types of storms are different. Clearly it is desirable to remove such ambiguity and clarify what type of storms would occur in certain climate regime.
In this study, we utilize the meteorological series derived from the REACHES climate database compiled from Chinese historical documents (Wang et al., 2018; 2024) as well modern weather data to pin down the type of storms and the respective physical mechanisms responsible for the extreme events that preferably occur in cold versus warm climate regime. We use the REACHES reconstructed temperature series in China in 1368-1911 and construct convection index series to show that the severe deep convective storms are the preferable type that causes extreme weather events in cold climate regime and utilize modern observational data to demonstrate that the high LWC (but not necessarily severe) storms are the type most likely to lead to extreme events.
Finally, physics-based storm model simulation results will be used to illustrate the dynamical processes of these two types of storms and explain why they lead to different precipitation patterns.
How to cite: Wang, P. K.: Extreme weather types and their physical mechanisms in cold versus warm climate regimes: evidence from historical and modern climate data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4671, https://doi.org/10.5194/egusphere-egu25-4671, 2025.
Posters on site: Wed, 30 Apr, 08:30–10:15 | Hall X5
Extratropical cyclones (ETCs) can cause severe storm surges, leading to extreme sea levels, coastal flooding and significant economic losses. Accurate estimates of storm surge frequency and intensity are crucial for flood hazard assessments and effective risk mitigation. However, limited observational records pose a challenge for predicting low-probability high-impact events and unprecedented extreme surges, particularly in regions yet to experience such events.
Global synthetic datasets have demonstrated to be crucial in addressing these limitations by providing larger datasets that reduce uncertainties in risk estimates and capture unprecedented events. Despite their potential, a comprehensive large-scale dataset for ETC-induced storm surges is currently lacking.
In this study, we explore the feasibility of pooling ensembles from ECMWF’s SEAS5 seasonal forecasting system and integrating them with the Global Tide and Surge Model (GTSM) to generate realistic synthetic storm surge events. Using the resulting extended storm surge time series, we assess the storm surge risk for Europe, identify unprecedented surge events, and advance our understanding of their underlying large-scale physical drivers.
How to cite: Benito Lazaro, I., Aerts, J. C. J. H., Ward, P. J., Eilander, D., Kelder, T., and Muis, S.: Using seasonal forecast ensembles to estimate of low-probability high-impact events and unprecedented extremes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10026, https://doi.org/10.5194/egusphere-egu25-10026, 2025.
The Earth’s climate is heading into unprecedented territory, with the global mean surface temperature reaching record-breaking levels in 2024. Meanwhile, on regional scales, extreme events are becoming both more frequent and more severe, with some events being without precedent in the observational record. These types of ‘unseen’ events could result in very high-impact, potentially catastrophic impacts for society on a variety of temporal and spatial scales. However, due to the inherent uncertainty in the complex climate system, we have a poor understanding of the risk of unprecedented events, including what is physically and statistically plausible, and the role of critical thresholds in both the physical climate and societal responses. We also have limited capacity to imagine and anticipate events with no historical precedent. Given the risk of very high societal impacts, including mortality, morbidity, and other socio-economic vulnerabilities already possible under present climate conditions, and the potential for a substantial increase in the number of people exposed to these threats under climate change, it is critical that we improve our understanding of these unknown-likelihood unseen events.
In late 2024, a workshop was hosted at King’s College London to address the question of how to reduce the catastrophic risk potential from unseen climate extremes. Twenty-seven researchers participated from a range of disciplines to solicit a variety of perspectives on the question. This included, amongst others, contributions from physical climate scientists, researchers in existential threats, and social scientists. Here, we present the outcomes from these interdisciplinary discussions, including perspectives on the framing and definition of the problem, open research questions, and a research agenda to advance toward a more comprehensive understanding of risk and improved societal preparedness to facilitate pragmatic policy decisions. Areas of discussion included developments in large ensemble climate modelling; modelling of connected systems; counterfactual thinking; and risk-based limits to adaptation; as well as wider philosophical questions regarding what constitutes a catastrophic or existential risk and how this should be defined in a climate context.
How to cite: Wood, T., Nicholson, H., Justine, J., and Matthews, T.: How can the catastrophic risk potential of unseen climate extremes be understood?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9252, https://doi.org/10.5194/egusphere-egu25-9252, 2025.
Future projections suggest that compound heat and drought in Europe will occur more frequently under increasing global warming. Year-to-year variability driven by atmospheric circulation patterns and decadal phenomena like the Atlantic Multidecadal Variability (AMV) temporarily dampens or amplifies these changes. As such, the frequency and intensity of these events can be affected by anthropogenic and natural drivers.
Disentangling these contributions is essential for understanding current events and the reliability of future projections, as well as for improving long-term predictions of such events and refining risk assessments. Although recent attribution studies have started to address the impact of natural climate variability, these studies are often limited to heat waves and do not explore other high-impact phenomena. Further, they are often based on observational data exclusively and therefore lack the sampling of internal variability that is required for a robust assessment. To address these gaps, we present a comprehensive analysis that quantifies the dynamical and thermodynamical contributions of not only global warming, but also considers internal climate variability using conditional attribution with atmospheric flow analogues. We use the CMIP6 version of the MPI Grand Ensemble (MPI-GE6) single-forcing (30 member) and historical (50 member) experiments to identify analogues based on real events from ERA5. This approach enables a clear separation and quantification of dynamical and thermodynamic contributions and how these change under different global warming states and under different forcing configurations, helping to better distinguish how both anthropogenic and natural factors influence high-impact heat and drought events in Europe.
How to cite: Dietz, V., Suarez-Gutierrez, L., Borchert, L., and Müller, W.: Disentangling drivers of compound heat and drought in Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17451, https://doi.org/10.5194/egusphere-egu25-17451, 2025.
Heatwaves heavily affect European public health, society and economy. A full understanding of the drivers behind the occurrence and intensity of heatwaves (HWs) is one of the priorities of H2020 CLimate INTelligence (CLINT) project. Particular attention is given to the detection and attribution of HW and on the understanding of their future evolution thanks to the Storylines method. For the implementation of this technique, it is important to assess the capability of climate models in thoroughly identifying relationships between the drivers and the occurrence and intensity of HW. The relevant drivers of this extreme event are selected among a set of clustered variables on European and Global domains. This step is performed applying a feature selection algorithm (Probabilistic Coral Reef Optimization with Substrate Layers, PCRO-SL, Pérez-Aracil et al., 2023) to ERA5 summer data between 1981 and 2010, using as a target the Po Valley HW occurrence. The PCRO-SL is then applied to CMIP6 models, considering for each of them the period in which their Global Surface Air Temperature (GSAT) corresponds to the one of ERA5 between 1981 and 2010 (“current-climate”, 14.2°C). If a benchmark driver is selected for a CMIP6 model, its relationship with the target event is well resolved. The models that satisfy this requirement can be considered for an inspection of the non-linear and joint impacts of the drivers on Po Valley HWs in a future-climate scenario with higher GSAT. Thanks to this procedure it is possible to identify relevant pairs of drivers, whose combined influence on the target event is inspected by constructing Storylines. The projected evolutions of HWs over Po Valley corresponding to each scenario are displayed, highlighting the role of teleconnections and unveiling undocumented impacts.
Pérez-Aracil, J., Camacho-Gómez, C., Lorente-Ramos, E., Marina, C. M., Cornejo-Bueno, L. M., & Salcedo-Sanz, S. (2023). New probabilistic, dynamic multi-method ensembles for optimization based on the CRO-SL. Mathematics, 11(7), 1666.https://doi.org/10.3390/math11071666
How to cite: Squintu, A. A., McAdam, R., Pérez-Aracíl, J., Peláez Rodríguez, C., Álvarez-Castro, C., and Scoccimarro, E.: Storylines of heatwaves over Po Valley in a warmer World: drivers and impacts , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9371, https://doi.org/10.5194/egusphere-egu25-9371, 2025.
Large Ensembles, or Single Model Initial Condition Large Ensembles (SMILEs) of climate model simulations, have been produced by different modelling centres in recent years. Here, we present the HadGEM3 Large Ensemble recently completed within the UK NERC multi-centre CANARI project. In the context of existing all-forcings Large Ensembles, noteworthy properties of the CANARI Large Ensemble are (i) a relatively high model resolution (60 km in the atmosphere in the mid latitudes, and about 25 km in the ocean), (ii) the availability of sub-daily output on a range of pressure levels to study weather systems, and (iii) boundary conditions allowing for regional modelling driven by the CANARI Large Ensemble for a range of CORDEX-like domains covering most land regions.
In this poster, we document the ensemble design and evaluate key aspects of historical ensemble performance against observational data, such as the global mean surface temperature evolution, the climatology of the Stratospheric Polar Vortex and of Sudden Stratospheric Warmings, the historical evolution of the Atlantic Meridional Overturning Circulation (AMOC), and trends of midlatitude storm tracks, Arctic Sea Ice area, and tropical Pacific sea surface temperature. Furthermore, an application is presented showing that analogues of the extremely hot North Atlantic sea surface temperature anomalies in the summer of 2023 can be found in the CANARI Large Ensemble, whereas there are no close analogues in the historical record.
(This poster has 40 authors, which exceeds the number of authors allowed in the abstract submission form.)
How to cite: Schiemann, R., Lister, G., Hatcher, R., Hodson, D., Lawrence, B., Shaffrey, L., Harvey, B., Woolnough, S., Robson, J., Schröder, D., Blaker, A., Lu, H., and Phillips, T.: The CANARI HadGEM3 Large Ensemble: Design and evaluation of historical simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12412, https://doi.org/10.5194/egusphere-egu25-12412, 2025.
As global warming intensifies, the building of adaptation and mitigation strategies has become an urgent task. In the centre of these strategies often lie extreme weather events, which are expected to become even more severe and more frequent in the next decades. Therefore, extending our knowledge on the potential changes in these events is crucial to provide assistance for appropriate preparation and planning necessary actions. Using the latest CMIP6 global climate model simulations available in the IPCC’s Interactive Atlas (IA), a study on extreme events focusing on Europe was completed, with special emphasis on Central Europe.
Our goal was to study the potential changes of extreme temperatures over the continent, in order to analyse the spatial patterns and trends of changes for the end of the 21st century. First, monthly multi-model mean data were downloaded from the IA for two different extreme temperature indices. The number of days with maximum temperature above 35 °C (i.e. TX35) and the number of days with a minimum temperature below 0 °C (i.e. frost days or FD) were selected for the analysis. The use of both hot and cold extreme temperature indices enabled us to cover every month in our study with TX35 analysed in the May–September and FD in the October–April period. Our target period was the 2081–2100 period compared to the values of 1995–2014 (i.e. the last two decades of the historical simulation period) as a reference. Every scenario available in the IA was considered, namely, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5.
Six zonal segments were defined over Europe to analyse the projected changes, ensuring that the segments fairly cover the continent. This approach is able to reveal the major effects creating the spatial patterns in different regions. The most important effects are (i) the differences due to the north-south or east-west locations (i.e. the zonal and continental effects), (ii) elevation above sea level (i.e. the orographical effect), and (iii) the different levels of anthropogenic forcing (i.e. the different scenarios).
Our results show that the anthropogenic effect is a key factor due to the direct connection between the greenhouse effect and air temperature. Moreover, the sea-land surface differences have the greatest effect on the magnitude of changes in the indices, while continentality is also an important factor. Potential differences due to elevation, however, are often supressed by the spatial patterns created by sea-land differences.
How to cite: Divinszki, F., Kis, A., and Pongrácz, R.: Analysis of projected monthly changes of extreme temperature indices to support decision-makers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1049, https://doi.org/10.5194/egusphere-egu25-1049, 2025.
Heat stress has lately been acknowledged as a significant threat to public health, with heat waves becoming more frequent and severe due to global warming. The Simplified Wet Bulb Globe Temperature (sWBGT) is a effective indicator for heat stress, combining both temperature and relative humidity. Using observations and reanalysis datasets, we identify annual heatwave days (HWD) and analyze sWBGT variations and trends during HWD. We focus on three European regions: Northern Europe (NEU), Western and Central Europe (WCE), and the Mediterranean (MED). We observed an increasing trend in sWBGT over most of Europe , with the exception of areas around the Black Sea, parts of eastern and western WCE, and the western MED. Importantly, the contribution of temperature and humidity on heat stress vary by regions. In NEU, positive trends in both temperature and relative humidity contribute to increased heat stress, with temperature showing a more significant rising trend (0.4°C/decade). In WCE, while the overall trend in sWBGT is positive, changes in relative humidity are minimal (0.007% /decade), with temperature trends being the primary driver. In MED, a positive trend in sWBGT of 0.3 /decade is a residual of a negative trend in relative humidity and a positive temperature trend. Comparing ERA5 dataset with meteorological station data revealed biases in the ERA5 data in Mediterranean cities with pronounced urban heat island effects. Analysis of sWBGT threat levels showed that NEU and WCE regions currently remain at safe levels. In contrast, most MED regions are at alert levels, with some areas escalating to caution levels. Our research provides comprehensive insights into heat stress variations across European regions over recent decades. This work can provide scientific evidence to help policymakers develop effective adaptation to address potential future heat stress threats.
How to cite: Zhang, Q., Kjellsson, J., Black, E., and Krüger, J.: Heat Stress Threats in Europe: A Comprehensive Analysis of sWBGTVariations and Trends (1979 -2023), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-848, https://doi.org/10.5194/egusphere-egu25-848, 2025.
Humid heatwaves negatively affect human health due to the integrating effect of temperature and humidity, and thus the early warning and timely mitigating on climate extremes are essential. Yet, systematic assessment on the intra‐annual onset and end of humid heatwaves, which is associated to the occurrence of first and last humid heatwaves, are missing globally. Using a new station‐based data set of daily maximum wet‐bulb temperature, the start and end dates, cumulative anomaly and extremely humid heat of the first and last humid heatwaves in the Northern Hemisphere were explored. It was found that at 91.54% of stations, humid heatwaves started earlier or ended later in the period of 2001–2020 compared to 1981–2000. High cumulative anomalies of the first or last humid heatwaves were found in the mid‐ and high‐latitude regions. Average difference between all humid heatwaves and the first humid heatwaves in cumulative anomalies increased steadily at stations north of 35°N. At regional scales, South East Asia had become the most prominent area with intensification of intra‐annual onset and end of humid heatwaves and will experience more frequent extreme events by 2100.
Furthermore, our focus goes from physical understanding to exposure impacts. Human exposure to humid heatwaves develops with the significant intensification of extreme humid-heat and population agglomeration. Although urban areas are typical spaces of the heat stress, urban heat is expanding outward to rural areas spatially. However, the difference of long-term changes and attributions between urban and rural human exposure to humid heatwaves is still unclear, especially lacking global comparisons supported by continuous series. We also used the new wet-bulb temperature dataset and integrated scenario data to assess historical and future human exposure to humid heatwaves in the Northern Hemisphere. The differences between urban and rural areas in the contribution of enhanced heatwaves and increasing population were quantified. The results showed that about 96.62 % of the stations had pronounced increases in human exposure among those with significant changes. The domination of enhanced heatwaves to human exposure rate was stronger in urban areas in typical developed countries, while domination of increasing population was higher in rural areas in eastern China, with 87.5 % of rural stations dominated by population growth. Under extremely increasing conditions in SSP5 scenario, average rates of human exposure to humid heatwaves in rural areas would be 11.78 % higher than urban areas.
Our findings demonstrated more intensified characteristics of the intra‐annual onset and end of humid heatwaves and provide a scientific cognition for the local risk of humid heatwaves.
How to cite: Dong, J.: Intra‐annual occurrence and risk of humid heatwave in the Northern Hemisphere, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2790, https://doi.org/10.5194/egusphere-egu25-2790, 2025.
The population approaching 14 million in the Bengaluru's metropolitan area in South India and is grappling with various environmental challenges like poor urban planning, including unchecked urbanization, air pollution, water scarcity, and waste management issues etc. The impact of climate change (CC) is also well observed in the urban Bengaluru resulting in the local Urban Heat Island (UHI). The interaction between local UHI and global CC creates challenges to human health, wellbeing and development. This study uses MODIS-Aqua Land Surface Temperature (LST) data for a decade (i.e., 2015-2024) to examine the UHI effect over the city. Climatological analysis of night time LST shows an average annual temperature-increasing trend between the urban Bengaluru and its neighboring suburbs and villages. This difference is computed at monthly scale and the fluctuations are being estimated using the satellite and validated against the ground observations. The Land use Land cover estimation are also linked to the UHI effect and the role of vegetation cover in the LST distribution is also quantified and it indicates the direct impact. This study will help in understanding the LST dynamics in the UHI effect over a rapidly urbanization city and can be used in the climate projection studies offering a ways to guide the urban planners, disaster managers and policy makers.
How to cite: Mohapatra, S. and Gouda, K. C.: Assessment of Surface Urban Heat Island over Bengaluru City in India, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21505, https://doi.org/10.5194/egusphere-egu25-21505, 2025.
How to cite: Mishra, V., Chuphal, D. S., Vegad, U., Malik, I., Solanki, H., and Singh, R.: High-impact climate extremes in India, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14675, https://doi.org/10.5194/egusphere-egu25-14675, 2025.
Climate extremes jeopardize human health and the environment. Recent unprecedented extremes suggest a complex interplay between anthropogenic warming and internal variability of the climate system, with large-scale circulations exhibiting considerable uncertainty in response to climate change. Therefore, understanding the influence of large-scale atmospheric and oceanic circulations on extreme events in a changing climate is crucial for climate adaptation and risk assessment. Traditional physical climate models, while powerful, require extensive computational resources to explore the broad spectrum of potential future circulation states and their implications for the infrequent occurrence of extreme events. This study takes Southeast Asia as an example to demonstrate the influence of Madden–Julian Oscillation (MJO) on extreme precipitation and droughts in a changing climate, as MJO strongly modulates local convective systems in Southeast Asia. We develop an AI-empowered emulator framework based on a conditional diffusion model to generate the precipitation field in a counterfactual world, where the enhanced convective phases of MJO are more (less) frequent than the current climate. We then estimate the intensity-frequency curves of extreme precipitation (drought) events and quantify the uncertainty using the generated large ensemble of samples. This counterfactual emulator allows us to isolate the influence of MJO phases and frequencies on extreme event probabilities, making it feasible to simulate a wide array of circulation states and examine their impacts under various climate change scenarios. By overcoming computational barriers, the study offers a clearer understanding of climate extremes in response to changing circulations for policymakers and stakeholders, enabling climate-informed resilience planning and evidence-based governance policy.
How to cite: Liu, X., Peng, X., and He, X.: A Counterfactual Emulator for Circulation-Driven Extremes in Southeast Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6594, https://doi.org/10.5194/egusphere-egu25-6594, 2025.
Extreme weather events have been increasing as global temperatures rise. Semi-enclosed basins such as the Black Sea and the Mediterranean are particularly susceptible to extreme weather due to their unique topographic features and land-sea distribution. Extreme precipitation events on the north-facing slopes of the mountains in the Black Sea Region occur due to relatively cold air interacting with the warm sea and being orographically lifted over the mountains. On August 10-12 2021, a deadly flash flood occurred on the coast of the Black Sea in Northern Türkiye which resulted in excessive precipitation (200-450 mm) causing loss of lives of 97 people and leaving 228 injured. We investigated extreme weather event which occurred near the Black Sea along with future climate conditions using the Pseudo-Global Warming method. In order to analyze the event, we used a numerical weather prediction model (WRF) in convection-permitting 3 km horizontal resolution with a domain covering the Black Sea and surrounding area. The model simulations are driven by ECMWF Reanalysis 5th Generation (ERA5) data for initial and boundary conditions. To derive climate change signals, we used 25 CMIP6 Earth System Models and eliminating the rest of the models that have no ocean model component over the Black Sea. The signals are computed for three different future periods (2025–2049, 2050–2074, and 2075–2099) relative to the 1990–2014 historical period. Each climate change signal which represents different periods were added to ERA5 6-hourly data as ensemble means. In the first future period (2025-2049), sea surface temperature (SST) in August is projected to increase by 1.7 °C, and by the end of the period (2075-2099), SST is expected to rise by 5 °C over the Black Sea. Additionally, while near-surface air temperatures in August are projected to increase by 1.5 °C to 2.5 °C initially, they are expected to rise by approximately 5.5 °C to 8.5 °C in the final period over the simulation domain. Moreover, near-surface relative humidity over land in August is simulated to decrease by nearly 10% in the last quarter of the century. The findings of this study will contribute to our understanding of how extreme precipitation events develop under future climate conditions and provide insights of the physical and dynamic processes that could drive these events in a warmer world.
How to cite: Şahinoğlu, S. and Önol, B.: Convective Permitting Simulations for Excessive Precipitation Event Under Pseudo-Global Warming in the Black Sea Region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6834, https://doi.org/10.5194/egusphere-egu25-6834, 2025.
The United Arab Emirates (UAE) experienced unprecedented rainfall on 16th April 2024, with Al-Ain recording 254 mm and Dubai 142 mm in a single day, driven by a Mesoscale Convective System (MCS). This extreme event resulted from the interaction of cold air from higher latitudes pushed eastward by the subtropical jetstream with warm, moist air from the Arabian Sea. The unusually high sea surface temperature (SST) in the Arabian Sea, reaching 30.5°C (1°C above the 40-year average), was influenced by El Niño and one of the strongest positive Indian Ocean Dipole episodes on record, which enhanced evaporation and atmospheric moisture content.
To investigate the role of anomalous SSTs, we conducted two numerical experiments using the Weather Research and Forecasting (WRF) model: one with the actual 2024 SST conditions from ERA5 and another with 1981-2020 SST climatology. Time series and probability density function analyses revealed that extreme rainfall was more widespread in the 2024-SST simulation compared to the climatology, with higher precipitable water content (40–60 mm) observed in the former, a range rarely seen in the latter. Further analysis of moisture transport and equivalent potential temperature confirmed that the warm SST-induced moisture played a pivotal role in driving the enhanced transport and heavy precipitation.
These findings underscore the critical role of anomalously high SSTs in intensifying extreme rainfall events, highlighting the need for improved predictive models and resilient infrastructure to mitigate the growing risks posed by climate change in the region.
How to cite: Halder, S., Khan, B., Pauluis, O., Lachkar, Z., and Paparella, F.: On the role of sea surface temperature variability in southern Arabian Peninsula extreme rainfall on 16th April 2024, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15441, https://doi.org/10.5194/egusphere-egu25-15441, 2025.
Extreme precipitation events and hot-weather events are usually examined at separate grids of a longitude-latitude map. A spatiotemporal perspective can provide additional insights, such as the spatial extent of extreme events and their potential traveling across the spatial domain over time. Here, we present the regular long-distance traveling patterns of these extreme events, highlighting the preferred spatial pathways through which the extreme precipitation events and hot-weather events tend to travel. Our in-depth analysis reveals that such long-distance traveling behaviors are influenced by midlatitude Rossby waves, and these preferred pathways can offer valuable information for early warning of downstream extreme events, potentially enhancing preparedness and response strategies.
How to cite: Huang, Y., Li, K., Wang, M., and Boers, N.: Preferred pathways of traveling extreme events in land precipitation and temperature, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11051, https://doi.org/10.5194/egusphere-egu25-11051, 2025.
Compound precipitation and wind (CWP) extreme events can bring a destructive impact to cities located along coastal areas. Total seasonal occurrence of CWP extreme events reaches its highest number of more than sixty events per year in several coastal cities of Southeast Asia (SEA) with a peak occurrence during summer (June-September). This study investigates nine meteorological variables to identify linkages between atmospheric conditions and CWP extreme events using the Coordinated Regional Climate Downscaling Experiment for Southeast Asia (CORDEX-SEA) dataset. These nine variables are chosen due to their importance as trigger factors to convections and wind gusts, e.g. equivalent potential temperature to represent moist enthalpy and atmospheric static stability as affecting wind gusts. Twelve coastal cities across Vietnam (five cities), the Philippines (three cities), Thailand (two cities), Cambodia (one city), and Myanmar (one city) are grouped into four groups with similar climatological patterns of the nine meteorological variables during the historical summer period (1975-2005). All groups imply the importance of their regional underlying zonal and meridional wind anomaly, outgoing longwave radiation (OLR) anomaly, and low-level moisture flux conditions during CWP extreme events days. CWP days for Group 1 (Cebu, Davao, and Metro Manila) are associated with low-level moisture convergence, negative OLR anomaly, and stronger zonal wind anomaly that enhances the precipitation intensity and wind gusts. The presence of a low-pressure system over the northern part of Metro Manila may also influences the CWP extremes for Group 1. Similarly, as a group that is prone to tropical cyclones, Group 2 (Da Nang, Hanoi, and Hai Phong) are also affected by similar dominant factors as Group 1 with an additional factor from the meridional wind anomaly. Located in between the South China Sea and the Indian Ocean, Group 3 (Yangon, Bangkok, and Chon Buri) is dominantly affected by low-level moisture convergence, zonal wind anomaly, and warm-moist transports from the Indian Ocean. Group 4 (Can Tho, Ho Chi Minh City, and Phnom Penh) shows a similar metrological pattern as Group 3 without notable changes in warm-moist transports. The regional means of these nine meteorological variables are further applied to train a Support Vector Machine (SVM) with an additional unbalanced data handling stage prior to the model training process. The best-trained SVM model results in the highest f1 score of 0.78 and 0.76 on the model’s testing set for Group 3 and 4. Further evaluation of the trained SVM model shows that the model’s predictions on a testing dataset fall within the 95% confidence interval. The best model is next used to predict the occurrence of CWP extreme events in the summer of 2006-2023. This model results in a predictive f1 score of 0.61 for Group 3 and 0.54 for Group 4, corresponding to a total of 98% and 97% correctly predicted (true positive), respectively.
How to cite: lestari, D. V., jian, W., and lo, E. Y.: Meteorological Conditions during Compound Wind and Precipitation Extremes in Coastal Southeast Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8539, https://doi.org/10.5194/egusphere-egu25-8539, 2025.
Taiwan faces significant challenges due to climate change, as rainfall patterns are increasingly shifting toward short-duration, high-intensity events. Although the government has implemented various flood control projects, the protective capacity of existing infrastructure remains limited. Extreme rainfall can still lead to severe flooding, as evidenced by the 2018 flood in southern Taiwan. In addition to structural measures, non-structural approaches—such as the mobile deployment of mobile pumps, community-based disaster prevention initiatives, and water monitoring systems—are essential for mitigating risks and reducing losses.
Currently, the deployment of mobile pumps heavily relies on personnel experience and ad hoc government requests, underscoring the need for systematic and scientific dispatch mechanisms. This study integrates data from rainfall forecasts, QPESUMS, flood sensors, and pump distribution to develop a comprehensive dispatch mechanism for proactive deployment and disaster response. The proposed strategy aims to enhance the efficiency of flood prevention and mitigation efforts in vulnerable areas during extreme weather events.
Keywords: Mobile Pumps; Dispatch Mechanism; Climate Change
How to cite: Lin, J.-L., Chan, H.-C., and Tang, C.-C.: Study on the Establishment of Dispatch Mechanism for Mobile Pumps Under Climate Change: A Case Study of Taiwan, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14912, https://doi.org/10.5194/egusphere-egu25-14912, 2025.
Carbon neutrality is an essential approach for the mitigation of climate change and plays a key role in the implementation of the Paris Agreement. This study analyzes future climate change in East Asia using carbon neutrality scenarios(Shared Socioeconomic Pathways SSP1-1.9, SSP1-2.6, SSP4-3.4, and SSP5-3.4-OS) and evaluates how earlier carbon neutrality could mitigate the impact of extreme climate events. Using carbon neutrality scenarios and indices of temperature and precipitation based on ETCCDI(Expert Team an Climate Detection and Indices), we analyzes frequency and intensity of climate extremes. Furthermore, we defined the Fraction of Avoidable Impact(FAI) to evaluate the extent of impact that can be avoided when achieving carbon neutrality, similar to the SSP1-1.9 scenario. For the extreme temperature, FAI values of intensity(frequency) were projected to be approximately 33-42%(33-35%) in the SSP1-2.6 scenario and 49-54%(49-53%) in the SSP4-3.4 scenario, indicating a relatively larger increase in intensity. In the case of extreme precipitation, FAI values of intensity(frequency) were projected to be about 25%(26-31%) in the SSP1-2.6 scenario and 40%(38-47%) in the SSP4-3.4 scenario, showing a similar trend of relatively larger increase in intensity as observed for extreme temperature. These findings emphasize that if the timing of achieving carbon neutrality is advanced to align with the Paris Agreement, the impact of climate extremes will be significantly reduced.
This research was funded by the Korea Meteorological Administration Research and Development Program “Development and Assessment of Climate Change Scenario” under Grant (KMA2018-00321).
How to cite: Kang, S.-J., Sung, H. M., Kim, J., Lee, J.-H., Shim, S., Lee, H., Chang, P.-H., and Byun, Y.-H.: The impact of carbon neutrality timing on climate extremes in East Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16878, https://doi.org/10.5194/egusphere-egu25-16878, 2025.
