Orals: Wed, 30 Apr | Room E2
Previous studies, based on satellite optical data and VLF network observations, determined that lightning superbolts (SBs) that have exceptionally high peak currents occur predominantly over the oceans. Satellite measurements were categorized according to optical intensity out of which the highest 1% were categorized as SBs and occurred predominantly over the NW Pacific near the coast of Japan. In contrast, VLF measurements were categorized according to their energy, out of which the highest 0.001% of the cloud-to-ground lightning strikes (CG) were categorized as SBs and occurred predominantly over the oceans (>90%) and during the wintertime of the northern hemisphere.
This study analyzed the spatial-temporal distribution of 3.8·109 CG strokes observed during 2018-2023 by the Earth Networks Total Lightning Network (ENTLN). It was determined that the proportion of high peak current (Ipeak) CG over the oceans compared to land was greater than 1 starting at PC>80 kA and no more than ~2 for PC=180-310 kA. Above 200-kA, 67% of the CG occurred over the oceans. The percent of PC>200 kA from the total CG (PC>2 kA) is ~0.3%. The percent of the total CG is 0.001% at PC~935 kA, where the sea-to-land ratio is only ~1.2. Over the annual cycle, CG with PC>200 kA was not observed at all during the months of May-September in both hemispheres, while during the rest of the year, most of the events over land occurred in the southern hemisphere at a ratio of 4.4:1 relative to the northern hemisphere, while over the oceans there was a 1:1 ratio between hemispheres. Finally, the hourly distribution of CG over land with PC>200 kA is consistent with the shape of the Carnegie curve as determined for lightning in general in previous studies. The hourly distribution over the oceans exhibits a higher number of events from midnight until 06:30 local time and is relatively constant and low throughout the daytime until 17:30 and afterward increases up to the midnight maximum frequency. These results demonstrate the small contribution of CG with PC>200 kA over the oceans to the atmospheric electric field variations in the Carnegie curve.
How to cite: Asfur, M., yair, Y., and Silverman, J.: The sea-land ratio of extremely strong cloud-to-ground lightning is significantly smaller than previously estimated, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-793, https://doi.org/10.5194/egusphere-egu25-793, 2025.
Exceptional rainfall hit West Central Africa in October 2019. We analyzed regional moisture and Moist Static Energy (MSE) budgets to understand the underlying mechanisms, focusing on dynamic and thermodynamic effects. The moisture budget analysis revealed that precipitation anomalies were primarily driven by dynamic effects. In the north of the region, horizontal moisture advection induced by horizontal wind anomalies dominated, while vertical moisture advection was key in the south. Thermodynamic effects, though secondary, contributed up to 35% in the north and 15% in the south. The MSE balance showed that anomalous vertical motion was dominated by dynamic effects in the north, particularly wet enthalpy advection induced by horizontal wind anomalies. West of the Congo Basin, increased net energy balance was the primary driver of vertical motion changes. Horizontal and vertical MSE advection appeared less significant. Strong MSE balance anomalies in the north were linked to its meridional component, especially meridional wind anomalies in the dynamic effect and meridional latent heat anomalies in the thermodynamic effect. Our findings suggest that both dynamic and thermodynamic effects must be considered to adequately anticipate such extreme events. Understanding these mechanisms could enhance forecasts and projections, ultimately improving the region's resilience to extreme weather.
How to cite: Kenfack, K., Marra, F., Yepdo Djomou, Z., Angennes Djiotang Tchotchou, L., Tchio Tamoffo, A., and Appolinaire Vondou, D.: Dynamic and thermodynamic contribution to the October 2019 exceptional rainfall in West Central Africa, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-347, https://doi.org/10.5194/egusphere-egu25-347, 2025.
Severe convective weather systems, characterized by their small spatial scale and rapid, violent development, frequently give rise to disasters such as rainstorms, lightning, gales, and hail. Accurate forecast of such systems has long been a challenging issue of weather forecasting and a dilemma for disaster prevention and mitigation in Shanghai. This research introduces an intelligent forecasting technology for severe convective rainfall systems in Shanghai, encompassing adaptive radar observation of strong convection targets, identification and prediction of typical convective features, machine learning-based correction of numerical prediction errors, and system integration.
In this technology, to address the problem of unbalanced samples with a scarcity of heavy rainfall cases, an autoencoder for noise reduction and ordinal boosting regression module is designed. A FocalLoss method is employed to weight the Loss function, thereby transforming the regression task of precipitation values into multiple classification tasks. An adaptive scale selection method is constructed to better represent the heavy rainfall system. In this method, the spatio-temporal scales of convective systems are adaptively selected, enabling targeted correction of heavy rainfall prediction.
Finally, an intelligent monitoring and early warning system capable of predicting the three-dimensional structure and evolution of strong convective systems has been established and put into operation. This system was evaluated during the flood seasons of 2022-2023. The results indicate that the TS score for 24-hour heavy rainfall (50mm) was significantly enhanced compared to the operational numerical weather prediction system of Shanghai Meteorological Service (SMS). This technology has been extended to application in urban disaster prevention and mitigation.
How to cite: Ma, L.: An Intelligent and Targeted Forecasting Technology for Severe Convective Rainfall Systems in Shanghai, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1914, https://doi.org/10.5194/egusphere-egu25-1914, 2025.
The recent flood event in Valencia (Spain) in October 2024 has revealed the need for real-time flood forecasts. Flood forecasts are based on meteorological forecasts that supply the feasible precipitation for the coming hours and a hydrological model to simulate the rainfall-runoff processes in the catchment. Distributed hydrological models require several parameters to simulate basin processes, though estimating their values accurately in each cell remains a challenge. Calibration processes that compare the hydrological model results with observations, in order to identify the best model parameter values, usually have an inherent uncertainty due to errors in the data, initial conditions and the simplified nature of the models. Furthermore, usually there is not a single set of parameter values that can characterise the hydrological response in all flood events. Therefore, the model calibration should consider diverse flood events, to optimize model performance under varying conditions.
This study presents the calibration and application of the Real-time Interactive Basin Simulator (RIBS) distributed hydrological model combined with precipitation forecasts based on the analog method to supply flood forecasts in the Francolí River Basin located in the Catalonia region in Northeast Spain.
First, observed rainfall and streamflow data recorded at gauging stations in the catchment for a set of real flood events have been used to calibrate the RIBS model. Five flood events were identified and used in the hydrological model calibration. The Nash–Sutcliffe Efficiency (NSE) coefficient showed good agreement between observed and simulated hydrographs for some events with values in the range 0.6179-0.9114.
Second, an ensemble of spatially distributed precipitation forecasts were used as input data to the calibrated hydrological model in the Francolí catchment. A set of five past events were used. A set of 10 meteorological analogs associated with the flood event was generated for each of the events analysed. The search for meteorological analogs was conducted using the 500 hPa and 1000 hPa geopotential height fields as predictors, and the similarity metric was based on a combination of Euclidean distance and Pearson spatial correlation. The generated set of analogs for each event can be used as an ensemble for generating a probabilistic precipitation field forecast for the region. The accuracy and reliability of the analog forecasts were assessed comparing the hydrological model outputs with the streamflow and precipitation observations at the gauging stations considered in the study. The best analog for each event obtained a Root Mean Square Error (RMSE) value ranging from 0.894 to 6.344, emphasizing performance variability.
The method proposed supplies a probabilistic flood forecast at the Francolí catchment outlet. This method improves the knowledge about the hydrological catchment response in flood events, supplying a probabilistic forecast. The method proposed enables more accurate flood predictions that can be used to supply informed response actions.
How to cite: Carril Rojas, D., Guzzon, C., Mediero, L., Garrote, L., Llasat, M. C., and Marcos Matamoros, R.: A flood forecasting method in the Francolí River Basin by using a distributed hydrological model and an analog-based precipitation forecast, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9626, https://doi.org/10.5194/egusphere-egu25-9626, 2025.
On June 21st, 2024, the iconic village of La Bérarde, in the centre of the massif Les Ecrins, French Alps, was destroyed by the mountain stream “Les Etancons”, that flooded the houses and deposited more than 200,000 m3 of raw material. This catastrophic event was caused by the concomitance of rapid warming with a heavy rain on top of a snowpack unusually thick in a glaciated watershed ranging from 1700 m to 4000 m a.s.l. during which a glacial lake drained simultaneously. Using observations (in-situ and remotely sensed) and the Météo-France modelling chain S2M, reanalysing meteorological and snow conditions in mountainous areas, we characterize a posteriori this rain-on-snow event and evaluate its contribution to the flood as well as its genuine nature within the last 65 years. Change in precipitation extremes was estimated by fitting a time dependent Generalized Extreme Value model within a Bayesian framework on available data. This analysis suggests an intensification of extreme precipitation in the studied high alpine region which is undergoing profound landscape changes with permafrost thawing and glacial retreat leading to favorable conditions for the formation of glacial lakes. This concomitance of intense meteorological events within a rapidly changing landscape is a striking reminder of how climate change is reshaping flood risk in high alpine regions.
How to cite: Filhol, S., Dumont, M., Hagenmuller, P., Doussot, F., Nicolas, E., Gascoin, S., and Blanc, A.: An unusual Rain-on-Snow event preconditioning the catastrophic fate of the village La Bérarde, French Alps, June 2024, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13270, https://doi.org/10.5194/egusphere-egu25-13270, 2025.
Flash floods represent the most devastating natural hazard in Mediterranean Spain, resulting in significant fatalities and economic losses. Their characterization has been hindered by the absence of a comprehensive database. This study addresses this challenge by compiling and analyzing data using established methodologies. The analysis is structured into two parts. The first part explores extreme daily rainfall patterns in Mediterranean and semi-arid climatic zones during the extended warm season. It utilizes data from 99 flash floods to investigate spatial and temporal distributions and derive envelope curves. The findings reveal that the spatial and temporal patterns of extreme flash floods closely align with those of extreme daily precipitation. The envelope curves are consistent with other regions. In the semi-arid region, flash floods exhibit higher magnitudes, but its envelope curve declines more steeply with increasing drainage size, reflecting distinct climatic and physiographic factors. The second part examines 13 major flash flood events using high-resolution hydrometeorological data. These events are characterized based on climate, basin morphology, precipitation, runoff ratio, lag time, and flashiness. The results confirm previous observations regarding relief ratio, rainfall intensity, and flashiness. However, runoff coefficients are lower than those in other European regions due to the high initial soil storage capacity, which prolongs lag times in smaller basins. In larger basins, flow hydraulics lead to reduced lag times that fall below the lower limit of the European envelope curve. These findings contribute to the expansion of the European flash flood database and provide insights for enhancing flood risk management strategies in Mediterranean Spain.
How to cite: Amengual, A.: Study of Extreme Flash Flood Events in Mediterranean Spain, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2174, https://doi.org/10.5194/egusphere-egu25-2174, 2025.
Recent years have seen floods of unprecedented intensity, leading to large loss of life, including in Spain (October 2024), Libya (September 2023) and Germany, Belgium, Luxembourg and the Netherlands (July 2021). The potential for conventional methods to underestimate extreme events was vividly and tragically illustrated in the devastating flooding of the Ahrtal associated with the latter event.
As well as the intensification of rainfall resulting from global heating, the anomalous behaviour of extreme floods may result from changes in hydrological processes, such as a transition to infiltration excess overland flow (Mushtaq et al, 2023). There is evidence of a large reduction in response time as rainfall intensity increases, for some catchments (Faulkner and Benn, 2019).
Empirical methods of flood frequency estimation have potential for estimating extreme floods (Bertola et al.,2023; Merz et al., 2022). However, they have limited ability to deal with changes in the physical processes of flood generation. Similarly, conceptual hydrological models can struggle to represent the impact of heterogeneous, nonlinear or otherwise complicated processes.
We investigate and benchmark the ability of a physically-based model (SHETRAN) to simulate extreme events beyond the range of observed conditions, examining how it represents changes in hydrological processes as the rainfall becomes more extreme, up to the probable maximum precipitation. Using a case study in the headwaters of the River Wye in Wales, UK, we find that the model represents the expected acceleration and intensification of runoff-generating processes. It does so partly by routing more runoff over the ground surface.
The findings are important for testing the resilience of society to extreme hazards, in a time of rapid environmental change.
Bertola, M., Blöschl, G., Bohac, M. et al. (2023). Megafloods in Europe can be anticipated from observations in hydrologically similar catchments. Nat. Geosci. 16, 982–988. https://doi.org/10.1038/s41561-023-01300-5.
Faulkner, D. and Benn, J. (2019). Reservoir flood estimation: the way ahead. Dams and Reservoirs, https://doi.org/10.1680/jdare.19.00028.
Merz, B., Basso, S., Fischer, S., Lun, D., Blöschl, G., Merz, R., et al. (2022). Understanding heavy tails of flood peak distributions, Water Resources Research, 58, e2021WR030506.
Mushtaq, S., Miniussi, A., Merz, R., Tarasova, L., Marra, F., & Basso, S. (2023). Prediction of extraordinarily high floods emerging from heterogeneous flow generation processes. Geophysical Research Letters, 50, e2023GL105429. https://doi.org/10.1029/2023GL105429.
How to cite: Faulkner, D., Rohrmueller, I., and Griffith, H.: Can physically-based models represent changes in hydrological processes expected during megafloods?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11977, https://doi.org/10.5194/egusphere-egu25-11977, 2025.
Inland flooding is one of the costliest natural hazards, inflicting substantial economic and societal damage annually, with floods causing almost USD 5 billion of insured losses across Europe in 2023 alone. Due to its proximity to major cities such as Berlin and Hamburg, a significant proportion of European exposures are vulnerable to extreme events over the Elbe River catchment. These risks need to be robustly quantified both to ensure adequate societal preparedness and so that (re)insurers are sufficiently well capitalised, which highlights the need to estimate the tails of the flood risk distribution. As fluvial flooding is driven by the frequency, duration, and intensity of weather events, standard approaches to assess flood use extreme value theory to extrapolate from observations and simulate new and unprecedented weather events and thus river response. These methods often fall short in generating spatially coherent and physically plausible weather events, particularly those that differ substantially from the historical record, limiting flood risk estimation.
Ensembles of weather forecasts over extended lead times could offer a promising alternative to statistical extrapolation by generating a diverse set of realistic weather outcomes. While this is not computationally feasible with numerical forecast models, artificial intelligence (AI) weather models, particularly FourCastNet based on Spectral Fourier Neural Operators (FCN SFNO), can rapidly produce large ensembles of weather forecasts while maintaining stability over long lead periods. Crucially, FCN SFNO enables forecasts to decouple from their initial conditions, facilitating the generation of numerous plausible, unseen weather events.
Leveraging NVIDIA Earth-2, a platform for developing AI augmented weather forecasting pipelines, we demonstrate the use of the FCN SFNO-based huge ensemble (HENS) pipeline to generate a counterfactual analysis of winter seasons for the Elbe basin. Our AI-driven weather simulations are integrated with hydrological models to connect the weather events and the subsequent river response. The resulting ensemble improves our estimate of present-day flood risk, driven by a wide array of physically plausible flood events that are grouped into seasonally coherent blocks. Our approach not only surpasses the limitations of standard statistical methods but also offers an efficient, scalable, and reliable framework for flood risk estimation and management globally.
How to cite: Poulston, A., Ashcroft, J., Koch, M., and Ertl, G.: Flood risk from AI-based, seasonal weather forecasts for the River Elbe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5729, https://doi.org/10.5194/egusphere-egu25-5729, 2025.
This lecture provides a critical analysis of drought indices, emphasizing their role in evaluating drought severity while addressing the challenges associated with their application. It highlights the inherent complexity of drought assessment, given the multifaceted nature of drought phenomena, the various types of drought, and the intricate mechanisms underlying their development. A central focus is the distinction between drought and aridity, as well as between drought metrics and indices—concepts that are frequently misunderstood or conflated.
Particular attention is given to atmospheric drought indices, especially those incorporating atmospheric evaporative demand (AED). These indices are crucial for assessing water stress but have faced criticism for certain limitations. One notable issue is the "index-impact gap," where atmospheric drought indices often indicate more severe droughts than those reflected in hydrological and ecological metrics derived from Earth System Models (ESMs), particularly in future climate scenarios. Atmospheric indices do not directly account for soil moisture or vegetation dynamics. Nonetheless, AED reflects atmospheric conditions rather than direct water reservoirs and fluxes, making AED-based indices valuable for understanding atmospheric drivers of drought. This value is reinforced by AED's critical role in intensifying drought through increased evaporation, heightened plant water stress, and reduced photosynthesis.
The lecture further focuses into the uncertainties inherent in ESM projections of ecological and hydrological variables, such as soil moisture and runoff. These uncertainties arise because ESMs often underestimate drought severity due to challenges in simulating complex hydrological and physiological processes. The difficulties stem from limitations in modelling plant physiology, water cycles, and ecosystem responses, compounded by biases in key variables such as evapotranspiration. While ESM outputs are valuable for drought assessments, relying exclusively on them risks producing misleading conclusions.
This issue connects with the role of rising atmospheric CO₂ concentrations, a factor commonly incorporated into ESM simulations, which adds another layer of complexity. Elevated CO₂ levels can enhance plant water-use efficiency and photosynthesis but also introduce uncertainties regarding their impacts on evapotranspiration and soil moisture. These dynamics generate complex feedbacks with AED and other variables, further complicating drought severity assessments, particularly in future ESM simulations.
To address these challenges, the lecture advocates for an integrated approach that combines atmospheric drought indices with hydrological and ecological metrics. Such an approach ensures that the intensifying role of AED under global warming is neither overlooked nor overstated, thereby improving the accuracy of drought assessments, especially in the context of future climate scenarios.
How to cite: Vicente Serrano, S. M.: On the Use of Drought Indices for Drought Severity Assessment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1572, https://doi.org/10.5194/egusphere-egu25-1572, 2025.
Global warming will lead to strong drought challenges in China. Exploring the spatiotemporal patterns of and changes in meteorological drought in China in the future is therefore of great significance for minimizing drought risks and for mitigating agricultural losses. It is crucial to consider the drought seasonality and aggregation while exploring the spatiotemporal patterns of and changes in meteorological drought in China. This study applied the ST-Moran scatterplot method to identify the drought spatiotemporal aggregation areas (DSTAAs) in China during 2021-2100 under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5 emission scenarios). Based on the identification results, we further analyzed the spatiotemporal patterns of and changes in drought in different seasons, agricultural regions, and time periods in China, and the detailed drought conditions on the Northeast China Plain. The results highlight that: (1) The drought will abate, become slightly worse, and become significantly worse over time under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. (2) Seasonally, the main drought seasons exhibit a transition trend from spring-winter to summer-autumn over time. As the emission level increases, this transition trend becomes increasingly evident. Detailed results in the Northeast China Plain confirm this seasonal transition trend in China and indicate that droughts in the major grain-producing areas in summer require more attention for preparedness and mitigation. (3) Spatially, the Northeast China Plain, Qinghai Tibet Plateau, and the northern arid and semiarid region have the largest number of significant DSTAAs. These results will support relevant institutions in formulating strategies for drought preparedness and mitigation.
How to cite: Wang, Z., Cheng, C., and Yang, J.: More evident trend of main drought seasons transition from spring‑winter to summer‑autumn in future China with higher emission scenarios, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10884, https://doi.org/10.5194/egusphere-egu25-10884, 2025.
Droughts, as severe climatic phenomena, pose substantial risks to sensitive areas globally. In Taiwan, where critical sectors such as semiconductor manufacturing are particularly vulnerable, the effects of droughts are of great concern. Various satellite indices have been developed to monitor drought status. The Temperature-Vegetation Dryness Index (TVDI), based on the Land Surface Temperature (LST) and Fractional Vegetation Cover (FVC), has been extensively used. The newly-proposed Temperature-Soil Moisture Dryness Index (TMDI), derived from the LST–Normalized Difference Latent Heat Index (NDLI) trapezoidal space, presents a more effective alternative to the TVDI. This study enhances TMDI by incorporating the novel Fractional Surface Water Availability (FSWA), focusing on better edge definition in the LST–FSWA space for drought monitoring. The capabilities of these indices were evaluated against metrics such as Surface Energy Balance Algorithm for Land (SEBAL)-based evapotranspiration (ET), Crop Water Stress Index (CWSI), Gross Primary Productivity (GPP), and in-situ precipitation. Notably, the TMDI showed stronger correlations with ET (r = –0.94) and CWSI (r = 0.93) compared to other indices. Moreover, the TMDI closely aligns with CWSI and GPP and is most responsive to precipitation (r = –0.60). Leveraging CWSI classifications, a novel TMDI threshold is proposed to assess drought conditions across southwestern Taiwan from 2014 to 2021. Generally, the TMDI effectively captures spatiotemporal drought patterns, providing essential insights for water management, irrigation planning, and the achievement of sustainable development goals.
How to cite: Thai, M.-T. and Liou, Y.-A.: Advanced Techniques for Enhanced Drought Monitoring Utilizing the Temperature-Soil Moisture Dryness Index (TMDI), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15247, https://doi.org/10.5194/egusphere-egu25-15247, 2025.
Taiwan's semiconductor industry is a significant contributor to the global semiconductor market and requires substantial water resources for its operations. The severe drought during 2020−2021, which garnered global attention, highlighted the importance of understanding water dynamics. This study examines the link between typhoon activity and drought severity. We analyzed tropical cyclone best-track data and satellite-based precipitation records from 1981 to 2020, using anomalies, correlation matrices, and wavelet coherence to investigate the typhoon-drought relationship, seasonal variations, and long-term trends. Our results reveal a complex relationship: typhoon characteristics near Taiwan, such as frequency, duration, path length, and intensity, positively correlate with drought occurrence and severity on 2- to 4-year cycles. Conversely, in the broader Western North Pacific (WNP), typhoon duration and path length correlate negatively with Taiwan’s drought indices, driven by large-scale atmospheric patterns. Notably, WNP typhoon duration and path length exert a stronger influence on Taiwan’s drought conditions than typhoon frequency, demonstrating significant coherence with multi-year and decadal drought trends. These findings illuminate the intricate dynamics between typhoon activity and drought patterns, offering valuable insights for hydrological management and disaster preparedness in typhoon-prone regions.
How to cite: Le, T.-V. and Liou, Y.-A.: Exploring the Typhoon-Drought Interplay in Taiwan, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15246, https://doi.org/10.5194/egusphere-egu25-15246, 2025.
Climate change and heat waves are among the most pressing challenges impacting water resources and intensifying wildfire occurrences worldwide. Understanding and predicting these extreme temperature events is crucial for developing effective mitigation strategies. To address this need, we conducted a comprehensive study focusing on heatwave prediction across Iran. This project utilized a novel approach, combining global climate change models with advanced statistical techniques such as copula functions [1]. This methodology enabled the detailed examination and correlation of three critical heatwave parameters: intensity, duration, and frequency. By establishing these interrelationships, the study provided a robust framework for predicting future heatwave characteristics [2].
The projections from our study reveal alarming trends for the future. Under various Shared Socioeconomic Pathways (SSPs), including SSP2.6, SSP4.5, and SSP8.5 [3], the intensity, duration, and frequency of heatwaves are expected to increase significantly by the year 2100. Specifically, the SSP8.5 scenario, which assumes high greenhouse gas emissions and limited mitigation, predicts the most dramatic escalation in these parameters. These findings underscore the urgent need for climate-resilient infrastructure and adaptive planning to safeguard public health, ensure the functionality of essential services, and minimize economic and environmental damage.
The integration of global climate models with copula-based statistical analyses proved to be a powerful tool in capturing the complex dynamics of heatwaves. This approach not only enhanced the accuracy of predictions but also provided valuable insights into the probabilistic behaviour of heatwave events under changing climatic conditions. By leveraging these insights, policymakers and planners can make informed decisions to mitigate risks and enhance resilience against future climate extremes.
Given the accelerating pace of global climate change, the implications of this research extend beyond Iran, offering a framework that can be adapted and applied to other regions facing similar challenges. Proactive measures, informed by predictive models such as ours, are essential to address the multifaceted impacts of heatwaves, from public health crises to disruptions in water and energy systems [4]. This study highlights the critical importance of integrating climate science with policy and infrastructure planning to build a sustainable and resilient future.
References
1 Chen, L., Guo, S., Chen, L., and Guo, S.: ‘Copula Theory’, Copulas and its application in Hydrology and Water Resources, 2019, pp. 13-38
2 Mazdiyasni, O., Sadegh, M., Chiang, F., and AghaKouchak, A.: ‘Heat wave intensity duration frequency curve: A multivariate approach for hazard and attribution analysis’, Scientific reports, 2019, 9, (1), pp. 14117
3 Usta, D.F.B., Teymouri, M., and Chatterjee, U.: ‘Assessment of temperature changes over Iran during the twenty-first century using CMIP6 models under SSP1-26, SSP2-4.5, and SSP5-8.5 scenarios’, Arabian Journal of Geosciences, 2022, 15, (5), pp. 416
4 Marx, W., Haunschild, R., and Bornmann, L.: ‘Heat waves: a hot topic in climate change research’, Theoretical and applied climatology, 2021, 146, (1), pp. 781-800
How to cite: Mirzaei, M. E., Izadi, A., and Alizad, K.: Heat Wave Assessment in Iran's Vulnerable Locations Incorporating Climate Change Scenarios, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15165, https://doi.org/10.5194/egusphere-egu25-15165, 2025.
The Multi-sensor Approach for Satellite Hail Advection (MASHA) is a new multi-instrument technique conceived for real-time tracking of hail-bearing clouds. MASHA can identify hail clouds from satellite measurements and monitor the evolution of hail-bearing systems every 5 min, combining the strength of the MicroWave Cloud Classification-Hail (MWCC-H) method to detect hail through the whole GPM sensor constellation (Laviola et al., 2020a-b) with the high temporal rate of the Meteosat Rapid Scan Service (MSG-RSS). This opens the way to operational applications of MASHA method by offering an unprecedented support to the nowcasting of hailstorms and to regional numerical weather predictions.
Recent applications experimented the ingestion in the MASHA scheme of lightning strikes and radar hail indices. This new configuration of the final products significantly refines the reconstruction of hail maps when the GPM constellation overpasses are missing. The result is a near-real time, more consistent and high-resolution hail map described by a proper Hail Severity Index (HSI). Recent applications demonstrate the ability of the MASHA technique to identify severe flash flood events in mountain catchments. These results draw new perspectives to optimally investigate hydro-meteorological events over mountain areas where more traditional methodologies might underestimate the severity of events. Thus, the MASHA scheme provides a useful tool in support to nowcasting systems of hailstorms and severe weather over complex areas.
References
Laviola S., V. Levizzani, R. R. Ferraro, and J. Beauchamp: Hailstorm Detection by Satellite Microwave Radiometers. Remote Sens. 2020a, 12(4), 621; https://doi.org/10.3390/rs12040621.
Laviola S., G. Monte, V. Levizzani, R. R. Ferraro, and J. Beauchamp: A new method for hail detection from the GPM constellation. A prospective for a global hailstorm climatology. Remote Sens. 2020b, 12(21), 3553; https://doi.org/10.3390/rs12213553.
How to cite: Laviola, S., Vermi, F., Monte, G., and Cattani, E.: Multi-sensor Approach for Satellite Hail Advection (MASHA): a new technique to support the nowcasting of hailstorms, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9621, https://doi.org/10.5194/egusphere-egu25-9621, 2025.
Hail-proxy indices have been developed over the past years to overcome shortages in hail parameterization in meteorological and climate models. They are mainly focused on reconstructing hail climatology or the frequency of occurrence of hail events during the present or past climate (Prein and Holland 2018, Torralba et al, 2023). Because of their sensitivity to spatio-temporal resolution, they are, however, not specifically designed to simulate long-term changes in the occurrence of large hail events under future climate scenarios.
In this study, we present a novel methodology tailored for CMIP6 climate models under various SSPs scenarios, and in synergy with higher resolution ERA5 reanalysis. Our approach is based on 34 commonly employed hail predictors: their probability distribution functions (pdf) are compared to the hail-conditioned pdf during observed large hail events (hail diameter >2 cm), in order to identify all 3-hourly intervals during the hail season (April to November) in which hailstones might form. These intervals are then combined with coarser GCM trends (individually for each quantile of the pdf) to project future changes in the frequency of hailstorms. The proposed technique provides a simple yet robust framework for assessing future changes in the occurrence of large hail events.
Such a trend-based scaling was rigorously validated using a multi-model ensemble of CMIP6 historical daily simulations and ERA5 reanalysis data. In order to assess the method over the Mediterranean basin and nearby lands, the newly released satellite dataset MASHA was exploited (Laviola et al, 2022). MASHA is the first large hail dataset derived from passive microwave observations; it offers a 3-hourly time resolution and a 1°×1° spatial resolution over the whole Mediterranean basin [5W-35E, 25N-50N] during 1999-2023.
Results of the assessment revealed a good agreement between the simulated and observed average monthly frequency of large hail events and their intradaily variability, highlighting the reliability of the index and its usefulness for climate change projections.
How to cite: Cortesi, N., Arnone, E., Cassardo, C., Monte, G., Capozzi, V., and Laviola, S.: Future changes in the occurrence of large hail events in the Mediterranean region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10730, https://doi.org/10.5194/egusphere-egu25-10730, 2025.
The frequency and severity of extreme meteorological and hydrological events, including tropical cyclones (TCs), are being reshaped by global climate change, posing significant challenges to infrastructure resilience and disaster management. This study evaluates the performance of satellite-derived quantitative precipitation estimates (QPEs) for hydrological applications during landfalling TCs, focusing on the interplay between localized rainfall and flooding. Using globally available datasets, we analyze eight TCs, including Hurricane Charley (2004) and Hurricane Michael (2018), to address three critical questions: (i) the reliability of satellite QPEs during TC scenarios, (ii) variability among gridded precipitation products (ground-based, radar, and satellite), and (iii) the implications of these differences for surface hydrology and flood risk.
Results indicate that the IMERG, satellite product underpredicts precipitation at higher quantiles but aligns well with ground-based and radar-derived products at lower quantiles. Urban areas exhibit the largest discrepancies in runoff estimates, with errors up to 18 mm, while agricultural and forested regions show more stable performance. Along TC tracks, IMERG reliably estimates hydrological variables in 90% of scenarios, with errors ranging from 0 to 10 mm. These findings underscore the utility of satellite QPEs like IMERG in understanding and forecasting short-term hydrological impacts of TCs, even amidst variations in precipitation intensity and location.
This research highlights the critical role of satellite precipitation products in addressing global disparities in real-time flood prediction systems, informing infrastructure planning, and mitigating societal vulnerability to extreme events. It contributes to the broader effort of enhancing early warning systems and proactive disaster risk management in the face of evolving climate extremes.
How to cite: Tiwari, A., Cherkauer, K., Marks, F., Tung, W., and Niyogi, D.: Enhancing Hydrological Insights for Tropical Cyclones Using Satellite Precipitation Data., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11548, https://doi.org/10.5194/egusphere-egu25-11548, 2025.
Between 29 and 30 October 2024, Spain experienced one of the most intense and destructive natural disasters in its history, predominantly affecting the Valencian Community but also parts of the Murcia region and the province of Albacete. The floods impacted approximately 75 municipalities, affecting over 400,000 inhabitants, damaging around 100,000 homes and 137,000 vehicles, and resulting in a total of 232 fatalities across Spain, 224 of which occurred in the province of Valencia alone. This extreme meteorological event not only recorded the highest rainfall accumulation in Spain’s history, with 771.8 mm in just 14 hours at the Túris station in Valencia but also highlighted inefficiencies in the authorities’ ability to convey extreme danger alerts to the population. The State Meteorological Agency (AEMET) issued the alert at 07:36 on 29 October, but it was passed on by the local authorities only 20:11, approximately 12 hours after the event started and the onset of precipitation, which significantly increased the risk to the population. In this study, simulations were conducted using the NCAR/MPAS model with a global resolution mesh of approximately 92 km, which converged to a finer mesh centred on Spain with a resolution of 25 km. The resolution increase was smoothed due to the numerical scheme used by the model, which employs Voronoi hexagons. The MPAS was initialised with initial conditions from the NCEP/NOAA dataset, obtained at 00Z for the period 23–29 October 2024. The study aimed to evaluate how far in advance it would have been possible to predict the configuration and position of the centre of the Cut-Off Low (DANA), the atmospheric phenomenon responsible for the extreme precipitation totals. The goal was to determine how early the risk associated with the DANA could have been identified, regardless of the precipitation totals forecasted by the model, focusing solely on the atmospheric phenomenon itself. The MPAS simulations revealed that as early as 24 October, the DANA configuration could be identified, based not only on the position of its vorticity centre at 500 hPa but also on the intense moisture transport at 850 hPa originating from the Mediterranean, which surface temperature was approximately 2–3°C above its average, directed towards the Valencian region. This pattern persisted in all simulations initialised between 24 and 29 October, with some precipitation cores showing accumulations of 200–300 mm between 29 and 30 October in the Valencian region. Thus, this study encourages reflection on the extent to which meteorology should rely on precipitation totals forecasted by atmospheric models when issuing alerts and warnings, or whether such alerts could instead be guided by the configuration of specific atmospheric phenomena. This approach could potentially increase lead times, as forecasting wind fields generally involves lower uncertainty compared to precipitation. Such an increase in lead time could be crucial to save lives in extreme weather events like this one.
How to cite: Ventura de sa, R., Cataldi, M., Raluy Lopez, E., Cristian Segado Moreno, L., Von Ruette, J., Sanchez Marroquin, A., and Chiva Polvillo, B.: Forecasting Cut-Off Lows Events with MPAS: A Study of Valencia's Historic Rainfall in October 2024 , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10875, https://doi.org/10.5194/egusphere-egu25-10875, 2025.
Extreme precipitation events are climatic hazard phenomena that can lead to riverine floods, flash floods, and landslides, posing significant threats to society and the environment. In this study, we examine the effects of climate change on the frequency and intensity of extreme precipitation events in the Middle East and North Africa (MENA) region. Our analysis focuses on daily precipitation simulations at a spatial resolution of approximately 50 km, provided by both regional and global climate models. Detecting changes in extreme precipitation events is challenging due to their high variability in time and space. Therefore, we employ the Simplified Meta-statistical Extreme Value (SMEV) method, an advanced extreme precipitation frequency analysis approach that enables a more robust frequency analysis of extreme precipitation by reducing uncertainty compared to traditional methods. We find that, while average precipitation levels exhibit heterogeneous changes across the MENA region, a general intensification of extreme precipitation is expected. Notably, the intensification is stronger for rarer events. Our results also indicate that changes in both average and extreme precipitation across the MENA region are spatially non-uniform, with some areas experiencing intensification while others show a downward change, with regional variability in change strength. The strongest intensification in extreme precipitation is projected over central Africa and the northern Arabian Sea region. We also find that the regional patterns in extreme and average precipitation changes are not always aligned. Notably, mean annual precipitation is expected to decline over the Mediterranean, while extreme precipitation return levels are projected to intensify in much of the area.
How to cite: Goldschmidt, Y., Marra, F., and Morin, E.: The impact of climate change on the frequency and intensity of extreme precipitation events in the Middle East Nort Africa (MENA) region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-460, https://doi.org/10.5194/egusphere-egu25-460, 2025.
The Middle East, with its diverse and complex geographical and environmental conditions, is one of the world's most vulnerable regions to climate change making it particularly susceptible to extreme precipitation events (EPE). These events often are driven by complex interactions between tropical and extratropical weather systems, seasonal variability, and atmospheric rivers. This study presents a specified probability map of extreme precipitation events across the Middle East region. It highlights areas at a higher risk due to heavy rainfall events and extreme events like flash floods.
The study includes 80 years of ERA5 reanalysis data (1941–2020) and three high-resolution AR6 models under two scenarios: the middle-of-the-road scenario (SSP2-4.5) and the pessimistic, high-emissions scenario (SSP5-8.5) for the period 2021–2050. By considering the trends of 10 certain indices (EPIs) based on both historical precipitation data and future projections, The findings categorize areas into four distinct risk levels, ranging from no risk to high risk. The statistical significance of EPIs was assessed using the nonparametric Mann–Kendall test.
Extreme precipitation events in the Middle East are influenced by various climatic and meteorological factors, and certain areas are more susceptible to these events. The outcome of this analysis show several regions of high risks in north and west part of Iran, northern and central Turkey, central Iraq, and eastern Saudi Arabia. Regions closer to the Caspian Sea and Persian Gulf exhibit higher vulnerability, while low-to-medium risk regions involve parts of Syria, Jordan and southern Iran. Countries such as Egypt and southern Saudi Arabia have just a very slight chance of hazard. In the SSP2-4.5 scenario, the general risk map closely resembles the risk based on historical data. However, in the pessimistic scenarios, most regions that were in the low-to-medium risk classes shift toward high risk.
These findings give confidence to the potential impacts of flooding and infrastructure challenges in regions unfamiliar to dealing with heavy rainfall. This information is important for water management strategies that are part of preparing for climate change impacts, which clearly emphasize the rise in extreme weather patterns across the Middle East.
Keywords: Precipitation, Extreme events, Heavy rainfall, Risk assessment, Middle East
How to cite: Fakour, P. and Ustrnul, Z.: Assessing Susceptible Areas for Extreme Precipitation in the Middle East: Insights from Historical Data and Their Shifts Under Future Projections, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-903, https://doi.org/10.5194/egusphere-egu25-903, 2025.
Floods have major impacts in the Mediterranean regions, but their evolution with climate change is unclear. This issue is related to the inadequacy of climate and hydrological models in terms of spatial and temporal resolutions to simulate flash floods over small basins. This study explores future flood scenarios of 12 Mediterranean basins using meteorological forcings from an ensemble of high-resolution convection-permitting climate models. Results indicate an overall increase in flood intensity across all basins, particularly for the most severe events, but also a strong spatial variability of the climate change signal given the geographic location and catchment characteristics. There is a good agreement between the models towards an increase of hourly rainfall extremes, but these changes are not well correlated with changes in floods, indicating that rainfall intensity alone is a poor predictor of future floods. An overall conclusion towards an increase of floods in this region is limited by the short length of the available high-resolution climate simulations. Longer time series are required to better assess the robustness of the projected changes.
How to cite: Lucas-Picher, P., Poncet, N., Tramblay, Y., Thirel, G., and Caillaud, C.: Projections of extreme rainfall and floods in Mediterranean basins from an ensemble of convection-permitting models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13283, https://doi.org/10.5194/egusphere-egu25-13283, 2025.
Posters on site: Thu, 1 May, 08:30–10:15 | Hall X3
Extreme windstorms are among the most destructive and costly extreme weather phenomena in the European region. Extreme wind speeds can directly damage or destroy structures like power pylons. Indirect damages are caused by falling trees, which can break power lines or block roads and railways. Assessing long-term trends in windstorm losses and attributing them to climatic and socio-economic changes requires comprehensive and systematic collection of historical information. Here, we present windstorm impact data for Europe that is part of the HANZE (Historical Analysis of Natural HaZards) database.
The dataset covers windstorms that have occurred in 42 European countries between 1950 and 2020. The data was obtained by extensive data-collection from more than 800 sources ranging from news reports through government databases to scientific papers. The dataset includes 1358 events characterized by at least one impact statistic: area affected (forest felled by wind), fatalities, persons affected (loss of electricity) or economic loss. Economic losses are presented both in the original currencies and price levels as well as inflation and exchange-rate adjusted to the 2020 value of the euro. The spatial footprint of affected areas is consistently recorded using subnational units corresponding, to the European Union’s Nomenclature of Territorial Units for Statistics (NUTS), level 2 and 3. Daily start and end dates, information on causes of the event, notes on data quality issues or associated non-wind impacts, and full bibliography of each record supplement the dataset. The database can be viewed, filtered and visualized online: https://naturalhazards.eu. The dataset is designed to be complementary to HANZE-Exposure, a high-resolution model of historical exposure changes (such as population and asset value), and be easily usable in statistical and spatial analyses, including multi-hazard studies.
How to cite: Terefenko, P., Paprotny, D., Śledziowski, J., and Giza, A.: Database of windstorm impacts in Europe, 1950–2020, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1600, https://doi.org/10.5194/egusphere-egu25-1600, 2025.
Meteorological drought poses significant challenges in Morocco, underscoring the need for accurate precipitation data to monitor and assess drought characteristics, particularly given the limited availability of ground-based measurements. This study evaluates the utility of two Satellite Precipitation Products (SPPs) for drought monitoring across Morocco: the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). The assessment utilizes the Standardized Precipitation Evapotranspiration Index (SPEI) at multiple spatial and temporal scales. Ground-based monthly precipitation data from 27 stations spanning 1987 to 2017 served as the reference for evaluating the satellite-derived products. SPEIs derived from the SPPs and reanalysis data were compared with those based on ground observations to analyze drought trends and characteristics across Morocco. Performance metrics, including correlation coefficient (CC), mean error (ME), root mean square error (RMSE), relative bias, and mean absolute error (MAE), were used for evaluation. The findings show a strong correlation between satellite-derived and observed precipitation data, with low estimation errors overall, though RMSE values indicate some dispersion, particularly in mountainous regions. Both CHIRPS and PERSIANN-CDR effectively capture drought occurrences and characteristics across Morocco, albeit with slight discrepancies compared to ground-based data. PERSIANN-CDR exhibits particularly high accuracy in simulating drought events, and both products effectively illustrate the progression and trends of droughts, providing valuable tools for drought monitoring and management in Morocco.
How to cite: Hadri, A., Rachdane, M., Iazza, K., El Khalki, E. M., Hanadé, I., and Saidi, M. E.: Evaluating Satellite-Derived Precipitation Products for Drought Monitoring in Morocco, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4083, https://doi.org/10.5194/egusphere-egu25-4083, 2025.
Extratropical cyclones (ETC) generate hazardous weather conditions, such as windstorms, which often result in substantial societal impacts. The Royal Netherlands Meteorological Institute (KNMI) has developed high-resolution wind climatology for the Netherlands using downscaled reanalysis data (2.5 × 2.5 km2) from 1979 to 2021, and they created ensembles for various climate scenarios based on IPCC projections. While these datasets offer valuable insights into windstorm hazards (e.g., maximum wind gust, maximum hourly wind speed), further evaluation of trends and probabilistic analysis are needed to create hazard maps tailored to specific return periods.
Our study addresses this research gap by exploring the application of extreme value theory (EVT) to windstorm hazard data to assess the likelihood of extreme wind speeds at specific locations. We analyse thresholds, seasonal variations, and storm frequency trends. Historical records and projections are analysed. A key novelty is the use of high-resolution post-disaster insurance claims data on the losses of windstorm. These data are used to create a risk model that converts windstorm hazards into quantifiable risks, such as expected annual damage and high-resolution risk maps (2.5 × 2.5 km2). This risk-based approach provides insights for stakeholders and decision-makers, aiding in the design of strategies to mitigate and adapt to windstorm impacts.
How to cite: Fonseca Cerda, M. S., de Moel, H., Aerts, J., Botzen, W., and Haer, T.: Windstorm Hazard and Risk Maps for the Netherlands in a Changing Climate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4336, https://doi.org/10.5194/egusphere-egu25-4336, 2025.
After an exceptionally wet October 2019, the city of Bafoussam in the Cameroon Highlands was hit by a devastating landslide on 29 October, resulting in around 50 deaths. This study examines the atmospheric drivers leading up to this fatal event on a sub-monthly scale. Leveraging long-term station rainfall data from Bafoussam and the nearby city of Dschang, three marked wet spells during October 2019 are identified, the multi-day rainfall amounts of which exceed the maximum value within the historical data of the stations. Using ERA5 reanalysis data of the European Centre for Medium-Range Weather Forecasts to explore the meteorological background, favourable conditions in each of these wet spells were created by moist southwesterlies from an anomalously warm eastern equatorial Atlantic, induced by cyclonic-anticyclonic vortex couplets over the eastern Gulf of Guinea. The release of the intense rainfalls is associated with strong moisture flux convergence (MFC), likely through an interaction between the southwesterlies and prevailing easterlies from central Africa. On the large scale, the Saharan heat low, extending anomalously far to the northeast towards Libya during large parts of October 2019, appears to have facilitated the recurrence of such vortex couplets by establishing an environmental setting usually found during peak monsoon in August. Eventually, a tropical-extratropical interaction caused the wettest period of the month over the Cameroon Highlands. Dry and initially cool airmasses were advected equatorward from the Mediterranean towards the study region, generating the last strong episode of MFC linked with the landslide event. Subsequently, tropical-extratropical interactions were also involved in the termination of the rainy season. This study highlights not only the importance of the extratropics for rainfall variability in the African inner tropics, but also points to the hitherto understudied role of recurring vortex couplets over western tropical Africa and the Gulf of Guinea for multi-day wet spells.
How to cite: Vondou, D. A., Maranan, M., Fink, A., and Knippertz, P.: Meteorological conditions leading to a catastrophic, rain-induced landslide in Cameroon in October 2019, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4516, https://doi.org/10.5194/egusphere-egu25-4516, 2025.
The present research poster considered a comprehensive case study of the medicane ‘Daniel’. The storm struck Central Greece, particularly Thessaly, between September 4-7, 2023. The event was primarily triggered by omega blocking, where a high-pressure system became trapped between two low-pressure zones, leading to severe weather conditions and extreme precipitation. The following severe flooding caused loss of lives, widespread destructioon of road infrastructure, property damage and devastation to agricultural lands.
A combination of upper-air and surface data was employed to perform in-depth analysis of the atmospheric dynamics before, during, and after the event. Wind patterns, pressure systems, and temperature variations, which contributed to the formation and intensification of the medicane were the key meteorological factors taken into consideration. The Weather Research and Forecasting Model (WRF) was utilized in various simulation scenarios to simulate the event’s behavior, providing valuable insights into its development, progression and the associated extreme weather conditions.
Overall, the case study highlights the critical importance of an deeper understanding of the meteorological factors driving such phenomena, as well as the role of simulations in forecasting and minimizing their impacts. Hopefully, the present effort will contribute to the further implementation of robust early-warning systems and enhance governmental preparedness to safeguard citizens from future extreme weather events.
How to cite: Chantziara, A. N. and Kioutsioukis, I.: Medicane Daniel in Greece: A Model Evaluation Study, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4698, https://doi.org/10.5194/egusphere-egu25-4698, 2025.
Extreme rainfall events are becoming increasingly frequent in Northeast Brazil (NEB). The state of Alagoas, located on the eastern coast of the region, is one of the most affected areas in recent years, with records of high-magnitude events over the past four years. These events cause significant socioeconomic impacts, resulting in considerable human and material losses, underscoring the importance of a deeper understanding to mitigate short-term risks better. This study aims to investigate the synoptic and mesoscale conditions driving the extreme precipitation event occurred on May 6-7, 2024, which rainfall totals surpassed 270 mm/day across multiple areas of Alagoas, marking the highest 24-hour rainfall accumulation in the region this century. The study also evaluated the ability of the global Model for Prediction Across Scales (MPAS) to perform simulation for the extreme precipitation event, using a variable grid of 60-3 km and convection-permitting parameterization through two microphysics schemes: WSM6 and Thompson. Infrared channel (10.35 µm) images from the GOES-16 satellite were used to monitor the cloudiness development. ERA5 global reanalysis data were utilized to evaluate the synoptic conditions as a first analysis step. Observed precipitation data from MERGE/INPE, S-band meteorological radar, and rain gauges operated by CEMADEN were used to analyze accumulated precipitation. Synoptic analysis, through streamlines, revealed strong wind shear between 200 and 850 hPa, which was responsible for developing a Squall Line that propagated and reached Alagoas on May 6. The propagation of eastward-moving cloudiness towards the study area was observed on the same day, resulting from an Easterly Wave Disturbance (EWD) identified through the transport of kinetic energy originating near the African continent (1°E; 20°S). The displacement and intensification of this system towards NEB were confirmed by the intense vertical integrated moisture transport convergence (1000–200 hPa) over time, enhancing convection as it encountered the mesoscale system over the continent. As confirmed by anomalies, Sea Surface Temperature (SST) played an essential role in intensifying vertical motions, which were unusually high for this time of year. Overall, the EWD trough axis propagating along the trade winds, combined with intense moisture convergence, symbolized the intensification of upward movements in the region, where the dynamic conditions necessary for the development of the extreme precipitation event were established. The simulations showed that the MPAS underestimated the intensity of precipitation associated with the extreme event, although the simulations predicted values exceeding 50 mm/day in the most affected area. The results show similar performance in reproducing weather variables, with slightly better results for the WSM6 run. Preliminary results provide valuable insights into the performance of MPAS, emphasizing the need for further evaluation using additional physical parameterizations and alternative model configurations to enhance its predictive accuracy.
How to cite: Lyra, M., Herdies, D., Gomes, H., Pendharkar, J., Silva, M. C., Silva, F., Gomes, H., Lins, M., Figueroa, S. N., Mantovani Jr, J., Ramirez, E., Quadro, M., Coelho, W., Vendrasco, É., and Calvetti, L.: Multiscale analysis and simulations of an extreme rainfall event in Northeast Brazil with the MPAS model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6378, https://doi.org/10.5194/egusphere-egu25-6378, 2025.
The climate change and related phenomena is one of the biggest challenges of today’s civilisation. The data shows an upward trend of occurrence of meteorological, hydrological, and climatic phenomena worldwide, with the largest increase observed in extreme hydrological phenomena, such as floods and mass movement. Intense rainfall and resulting floods can lead to erosion and transport of large amount of natural and anthropogenic material and thus influencing the spatial distribution of chemical elements on Earth surface. The redistribution of potentially toxic elements (PTEs) is of special concern as they are largely persistent, non-biodegradable, and many are known to accumulate along the food chain. The environmental consequences of remobilization and redistribution of pollutants during flood events are not yet widely recognized and understood.
An extreme rainfall and floods severely affected Slovenia (EU) at the beginning of August 2023, resulting in more than 10,000 landslides and spatial redistribution of large quantity of sediments, including heavily polluted ones. One of the most affected areas was the Carinthia region at the north of Slovenia. This area is strongly impacted by a 300-years of lead and zinc mining in the Mežica area. Although the mining activities have ceased 30 years ago, the environment (e.g., soil, floodplains) is still heavily contaminated with Pb, Zn, Cd, Mo, and other PTEs, and there are several mine waste deposits prone to erosion. The Geological Survey of Slovenia has been studying the geochemical characteristics of the wider Mežica area for several decades. Levels of PTEs in stream sediments were regularly monitored (every 3 years) since 2013.
To determine the potential influence of extreme rainfall and floods on redistribution of PTEs in the environment that have been previously contaminated with PTEs, the following samples in the Mežica area in 2023 were collected: (1) stream sediment samples before the extreme weather event in August as a part of regular monitoring, (2) repeated samples of stream sediment after heavy storm at the end of July and after the extreme event in August at selected monitoring locations, (3) flood sediment samples along the Meža Valley after the extreme weather event in August. All samples were prepared (dried at 35 °C and sieved <0.125 mm) and analysed (determination of PTEs levels by ICP-MS after aqua regia digestion) by the same methods.
The comparison of PTEs levels in stream sediments from a decade long monitoring with flood sediment and stream sediment sampled after an extreme flood event illuminate the complexity of redistribution processes during such events, which may result in increase or decrease of PTEs levels. For example, the median levels of As, Cd, Mo, Pb, and Zn in flood sediments were higher than their median levels in stream sediment during usual hydrological conditions indicating erosion of contaminated areas and mine waste deposits dominated over erosion of non-contaminated materials. On the other hand, levels of PTEs at some specific sampling locations were much lower after the extreme flood event than before, indicating higher erosion of non-contaminated materials that may lead to the dilution effect.
How to cite: Gaberšek, M., Gosar, M., Miler, M., and Bavec, Š.: The influence of extreme flood event on redistribution of potentially toxic elements: a preliminary results from a former mining area, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8859, https://doi.org/10.5194/egusphere-egu25-8859, 2025.
Convection is a vital process which helps to redistribute energy in the Earth atmosphere and is often conducive to cloud formation connected to severe weather events worldwide. Hail production can occur in these severe events highly impacting infrastructures and properties. Italy and the Mediterranean Basin in general are witnessing an increasing trend in the number of occurrences of such events in the last decades, thus calling for an advancement in the observational capability and retrieval methodologies for the analysis of convective storm associated to hail production.
This work focuses on the analysis of few case studies occurred in Italy in August and September 2024. The aim is to evaluate the complementarity and the effectiveness of active and passive, GEO and LEO satellite instruments and satellite-based retrieval algorithms in convection and hailstorm identification. Convective clouds are analysed through the convection products from the EUMATSAT Satellite Application Facility in support to nowcasting and very short range forecasting computed using Meteosat Rapid Scan Service (RSS) data. Further information about updrafts and overshooting tops is acquired from the EarthCARE Cloud Profiling Radar (i.e., reflectivity and vertical velocity of cloud particles). The Multi-sensor Approach for Satellite Hail Advection (MASHA), a new multi-instrument technique conceived for real-time tracking of hail-bearing clouds, completed the set of analysis tools. It combines the hail probabilities computed through the Global Precipitation Measuring PMW sensor constellation, with the high temporal rate acquisition of GEO infrared brightness temperatures (IR-BT) from the Meteosat RSS. Exploiting constantly updated relationships between spatio-temporal co-located IR-BTs and PWM hail probabilities, MASHA monitors the evolution of hail-bearing systems at high spatio-temporal resolution (i.e., 4-5 km and 5 min., respectively).
How to cite: Cattani, E., Vermi, F., Monte, G., Galfione, A., Battaglia, A., and Laviola, S.: Hailstorm characterization with a synergistic active and passive, GEO and LEO observation strategy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8964, https://doi.org/10.5194/egusphere-egu25-8964, 2025.
How does climate change impact extreme events and which is the future change of their dynamics? How will the ongoing and future changing climate control the evolution and intensification of severe storms? These are among the most frequent and significant questions for the scientific community, stakeholders and decision-making structures. The project tackles these open issues by investigating hailstorms in the Mediterranean region through the synergistic application of satellite observations, meteorological reanalysis and climatic modelling. Focusing on determining the atmospheric variables most relevant for the formation and intensification of hail-bearing storms, we delineate specific metrics describing the hail formation potentially applicable at operational level. The proposal stems from the 22-yearlong database of hail episodes described by Laviola et al. (2022), whereby events associated with large and extreme hail (above 2 and 10 cm in diameter, respectively) were preliminarily identified and shown to be on a 30% increase trend. Extending and refining this climatology at daily scale, the large-scale and mesoscale atmospheric scenarios that trigger hail events in the central Mediterranean area are investigated through a cluster analysis with the use of meteorological reanalysis data in the recent past. Hail-prone conditions are associated with the optimization of a hail-proxy index based on environmental variables extracted from global and regional reanalysis products. Such index and the reference hail-prone conditions are then be investigated in the ensemble of climate model projections to outline the future evolution of hail-precursors triggering and sustaining deep convection over the Mediterranean basin to the end of the century. This investigation will be also exploited to identify the environmental key variables controlling hail hazards in the recent past, and prospect future changes of storm extremization. The first-year results presented in this work delineate a new paradigm of knowledge for better understanding the effects of climate change on hailstorms by using hail-bearing convective systems as a driver for evaluating the potential impact of future changes in the Mediterranean basin.
Reference
Laviola S., G. Monte, E. Cattani, V. Levizzani, 2022: Hail Climatology in the Mediterranean Basin Using the GPM Constellation (1999-2021). Remote Sensing, 14(17), 4320. https://doi.org/10.3390/rs14174320
How to cite: Laviola, S., Arnone, E., Budillon, G., Monte, G., Cattani, E., Cortesi, N., and Capozzi, V. and the other authors of the Hail Hazard in the Mediterranean (H2Med) PNRR Project: Hail Hazard in the Mediterranean (H2Med), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9333, https://doi.org/10.5194/egusphere-egu25-9333, 2025.
Flood events are significant hydrological phenomena that can lead to severe human and economic damages. In the Seine River basin (France), the floods of May-June 2016 resulted in four fatalities and economic losses estimated between 0.8 and 1.25 billion euros, according to the French reinsurance fund. This event followed an unusually wet month of May, marked by intense rainfall concentrated in the southern part of the basin, primarily within the Loing River watershed. At the outlet of this watershed, an unprecedented peak discharge of nearly 500 m3.s-1 was recorded, with a return period now estimated to be between 400 and 1,000 years. The latest IPCC report emphasizes the increasing frequency and severity of extreme weather events driven by climate change, highlighting the need for a better understanding of the hydrological processes leading to major floods to improve forecasting and mitigation efforts.
Given that flood dynamics typically result from a combination of processes including river overflow, subsurface runoff and groundwater discharge, a coupled surface and groundwater hydrological application of the Loing River watershed is currently being developed. The CaWaQS modeling platform is used to (i) simulate the key hydrological processes within each component of the Loing hydrosystem (soil, river system, vadose zone, and aquifer system) and (ii) generate daily key variables of interest, such as distributed discharge and hydraulic heads. The simulation of surface flow processes relies on a reservoir-based conceptual approach, utilizing sets of seven calibration parameters (or production-functions), distributed according to the intersection of soil and land use types. An initial simulation solely based on production-function parameters inherited from the CaWaQS-Seine basin regional application (15 production-functions, 105 parameters) led to largely underestimated flows. As a result, local specificities such as the extensive artificial drainage of arable lands was incorporated through four additional functions, bringing the total number of parameters to 133. Bayesian inversion and frequency analysis of observed discharge data were used to calibrate AET fluxes and effective rainfall partionning into runoff and infiltration flows, although this approach was still insufficient to accurately represent flood dynamics. To address this, the CaWaQS source code was enhanced to explicitly incorporate Dunne-type runoff processes related to soil saturation. A new calibration was based on analogies between physical and conceptual parameters, reducing the number of parameters requiring adjustment from 57 to just 2: drainage efficiency and kinematic porosity. These two parameters, initially not spatially discretized, are calibrated using an automated screening procedure.
This revised conceptualization and its associated fitting methodology enable the simulation of runoff processes triggered by soil saturation and drainage in agricultural areas, providing a differentiated assessment of their impact on the hydrosystem. It also allows a more accurate representation of flow dynamics during flood events.
How to cite: Girod, L.-M., Flipo, N., and Gallois, N.: Modeling dunnian runoff dynamics during flood events in the Loing watershed (France), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10792, https://doi.org/10.5194/egusphere-egu25-10792, 2025.
On 29 October 2024 torrential rainfall exceeding locally 300 mm within less than 24 h, triggered devastating flash floods in the province of Valencia in Spain. Rainfall sums equivalent to more than half a year’s total precipitation occurred within just a few hours. In this region, more than 150 low-cost weather observation devices, referred to as personal weather stations (PWSs), are located. The network density of PWSs in this region is seven times higher than that of the Spanish Meteorological Agency (AEMET), being able to provide more detailed insights in the rainfall dynamics. Another advantage is that rainfall observations from PWSs are available near real-time for everyone.
In this study we used rainfall observations from PWSs to get local insights into the rainfall event of October 29. Several PWSs measured already more than 180 mm of rainfall in parts of the Magro catchment (1661 km2) in the morning, consequently generating a flash flood in the upstream parts of this rapidly responding catchment. Areal rainfall maps, based on interpolating the PWS data, indicated daily catchment averaged rainfall sums exceeding 150 mm d-1 across an area of more than 2500 km2. Daily rainfall sums recorded by the PWSs showed a slight underestimation of the rainfall with a bias of 4% and a high correlation (r = 0.96) when compared to reported rainfall from AEMET.
This presentation shows the relevance of utilizing PWSs for near real-time rainfall monitoring and potentially flood early warning systems.
How to cite: Rombeek, N., Hrachowitz, M., Wüthrich, D., and Uijlenhoet, R.: Insights from personal weather stations in the rainfall dynamics preceding and during the 29 October 2024 Valencia floods, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10932, https://doi.org/10.5194/egusphere-egu25-10932, 2025.
The increasing frequency and severity of extreme storms and floods in the Eastern Mediterranean under climate change pose significant challenges for modern societies. These events often trigger cascading effects that extend far beyond the immediate disaster zone, disrupting interconnected systems such as power, transportation, and communication networks. Despite advancements in flood risk management and growing awareness of cascading hazards, the mechanisms driving these interdependencies and their broader impacts remain poorly understood. This study investigates the cascading effects triggered by the catastrophic Storm Daniel, which struck Thessaly, Greece, in September 2023, as a case study to explore the nature, scale, and ways of impact propagation.
This work also provides an analysis of cascading effects, based on evidence on historical storm and flood disaster impacts in the Mediterranean region, identifying the interactions between primary hazards (flooding, landslides, erosion) and secondary consequences as well as the diverse sectors that suffer impacts. The analysis reveals different propagation mechanisms of these effects, highlighting the vulnerability of interconnected systems as well as the vulnerability of the natural and the built environment. The cascading effects identified underscore systemic risks of modern societies posed by extreme events, particularly in urban areas with dense, interdependent, and critical infrastructure.
The findings contribute to the growing body of literature on cascading disasters, addressing critical knowledge gaps in understanding how extreme weather events propagate through modern societal systems. These insights are particularly relevant in the context of climate change, which is expected to amplify the frequency and intensity of such events.
How to cite: Diakakis, M., Kapris, I., Gogou, M., Sarantopoulou, A., Filis, C., Nastos, P., Vassilakis, E., Konsolaki, A., and Lekkas, E.: Cascading effects of extreme storms and floods: Evidence on impact propagating mechanisms., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11513, https://doi.org/10.5194/egusphere-egu25-11513, 2025.
Tornadoes are significant meteorological hazards, causing extensive damage to infrastructure and loss of life. Their small spatial scale (approximately 1km or less), short lifespan (order of 1000s) and, highly nonlinear chaotic behaviour makes their prediction problematic using current operational weather predictions and climate models. Developing methods to overcome these limitations is crucial for providing reliable early warnings and forecasts through civil protection services and determining whether human-induced climate change will affect the frequency and intensity of tornadoes. We estimate the expected occurrence of tornadoes using a set of empirical formulas based on meteorological parameters extracted from the ERA5 reanalysis for the period 2000-2024 and compare these estimates to the actual number of observed tornadoes, as recorded by the Strom Prediction Center (SPC) (https://www.spc.noaa.gov/wcm/#dat) for USA and the European Severe weather database (ESWD) https://www.essl.org/cms/ for Europe. The formulas incorporate WMAX (updraft maximum parcel vertical velocity, linked to the Convective Available Potential Energy CAPE), WS700 (the wind shear in the lower troposphere), LCL (the lifting condensation level), SRH900 (low-level storm relative helicity) and provide a probability for the occurrence of tornadoes (see Ingrosso, et al. https://doi.org/10.5194/nhess-23-2443-2023 for details). Results show a good capability of reproducing the seasonal cycle of tornadoes in the USA and some skill to simulate their interannual variability, with a score depending on season and larger in spring. Results are not satisfactory for tornadoes in Europe. Reasons for this partial failure need a further investigation. This study is carried out with the financial support of ICSC – Centro Nazionale di Ricerca in High Performance Computing, Big Data and Quantum Computing, funded by European Union – NextGenerationEU… Project code CN_00000033, CUP C83C22000560007.
How to cite: Muhammadi, A. and Lionello, P.: Empirical estimate of intraseasonal and interannual variability of occurrence of tornadoes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13018, https://doi.org/10.5194/egusphere-egu25-13018, 2025.
An important challenge associated with climate change is the increase in the intensities of extreme precipitation events, which produce severe flooding and cause substantial damage to hydraulic infrastructure. This intensification has been particularly evident in recent decades and is attributable to increased daily precipitation and the temporal concentration of rainfall over shorter durations. This results in increased precipitation pulses and, consequently, higher rainfall intensities. In Chile, the National Water Agency (DGA) published standardized duration coefficients in the year 1993, which may no longer align with the current climatological period, potentially underestimating the design parameters for extreme storms.
Using ERA5 reanalysis data, this study investigates changes in duration coefficients for extreme storms across a large area of Chile, covering latitudes from 17°S to 43°S. Two climatological periods are defined: the first from 1964 to 1993, that represent the past climatology, and the second from 2004 to 2023 that represent the current climatology. For each period, duration coefficients are computed by identifying annual extreme precipitation events for specific durations and normalizing these by annual maximum daily precipitation totals. Representative duration coefficients are computed for each period, taking the averages and the 90% exceedance probability envelope, reflecting an adverse scenario. The obtained coefficients are compared with those published by the National Water Agency, and change factors are computed for each hourly duration, using both representative coefficients. The computations were performed for each of the 31 stations with available historical data to enable comparative analysis.
The results indicate that the average 24-hour duration coefficients closely align with the 1.1 value suggested in the national design guidelines. However, significant variance is observed across the years of analysis, with the spatial mean of the exceedance envelope reaching 1.3. In northern Chile, characterized by the Atacama Desert and the Altiplano, ERA5 systematically underestimates short-duration coefficients associated with convective storms. Regarding changes in duration coefficients between the two climatological periods, an increase of up to 20% is observed in central Chile for durations shorter than six hours.
These findings highlight the critical need to regularly update duration coefficients in the context of a changing climate to ensure robust hydraulic infrastructure design and to mitigate risks associated with underestimation in regions experiencing intensified extreme events.
How to cite: Ricchetti, F. and Vargas, X.: Variability of Extreme Precipitation Duration Coefficients in Chile: Implications for Hydraulic Design, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13170, https://doi.org/10.5194/egusphere-egu25-13170, 2025.
It is evident that windstorms rank among Europe's most destructive natural hazards; however, they have received comparatively less attention from researchers. This can be attributed partly to the absence of a consensus on windiness trends and the variability in reported events depending on the databases used. Research on windstorms is predominantly concentrated in Central Europe, and the assessments conducted are often lacking in detail.
The present study aims to address this gap by establishing a new Swedish windstorm database. The database is based on the 99th percentile of wind gusts, with the objective of identifying extreme events. While lower percentile thresholds (e.g., the 98th) are commonly employed, they have been deemed inadequate for regions such as Scandinavia, prompting the selection of a higher threshold. The 99th percentile has been determined to ensure that Sweden's distinctive climatic and geographical conditions are sufficiently captured in the data.
The employment of this more accurate methodology is instrumental in facilitating a more profound comprehension of the impact of windstorms in Sweden. The identification of areas susceptible to risk assumes a pivotal role in informing efficacious disaster preparedness and mitigation strategies, given the propensity of windstorms to inflict considerable damage.
How to cite: Georgali, E. and Karagiorgos, K.: Winds of change: Mapping Extreme Windstorm Events in Sweden, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18369, https://doi.org/10.5194/egusphere-egu25-18369, 2025.
The ClimXtreme program[1,2], funded by the German Ministry of Education and Research, consists of 25 subprojects investigating extreme events in central Europe focussing on heat/drought, extreme precipitation and wind storms. Extreme events occurring during project runtime are assessed within the research program by forming a post-event assessment group (PostAG). This group aims at rapid response using both pre-defined methods and workflows as well as cutting edge methods of the research program.
The basis for the assessment is the evaluation framework Freva (Free Evaluation System Framework)[3,4] which provides an efficient possibility to handle customisable evaluation systems of large research projects. Several projects and institutions are already using this framework for educational or research purposes. Among them is worthy to mention the Freva instance hosted at the German weather service (DWD) which allows an exchange of methods and assessment workflows between research projects and the DWD. The Freva instance of ClimXtreme[5], hosted at DKRZ, enables the possibility to access more than 10 million data files from models (e.g. CMIP, CORDEX) and observations (e.g. ERA5, HYRAS, stations). Near-realtime data of observations are operationally updated for the PostAG assessment.
This contribution shows an interplay of the evaluation framework and scripted workflows to rapidly assess extreme events directly after their occurrence with pre-defined methods (e.g. plugins) providing the option to easily expand the analysis by new methodologies developed by the research program.
References:
[1] https://www.fona.de/de/massnahmen/foerdermassnahmen/climxtreme.php
[2] https://www.climxtreme.de/
[3] http://doi.org/10.5334/jors.253
[4] https://github.com/FREVA-CLINT/freva
[5] https://www.xces.dkrz.de/
How to cite: Grieger, J., Kunz, T., Lucio-Eceiza, E. E., and Ulbrich, U.: Post-event assessment of extreme events within an evaluation system framework, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18379, https://doi.org/10.5194/egusphere-egu25-18379, 2025.
Compound Dry and Hot Events (CDHEs) are increasingly recognized as critical
challenges of the 21st century, marked by the simultaneous occurrence of prolonged
dry periods and high temperatures. These events, more severe than individual
extremes, adversely impact water resources, agriculture, public health, and
infrastructure. Globally, CDHEs are becoming more frequent, longer, and intense,
particularly in climate-sensitive regions, including India. Urban areas like New Delhi,
with its high population density, limited water resources, and susceptibility to extreme
weather, are particularly vulnerable. This study examines CDHEs in New Delhi over 66
years (1958–2023) using monthly precipitation and temperature data from the
TerraClimate database. Standardized indices like the Standardized Compound Event
Indicator (SCEI), Standardized Precipitation Index (SPI), and Standardized
Temperature Index (STI), along with the joint probability density function (JPDF), are
applied to assess trends in frequency and severity. The analysis reveals a marked
increase in CDHEs post-1990, linked to regional climate changes, accelerated
urbanization, and evolving land-use patterns. Future projections under +2°C and +4°C
global warming scenarios indicate a substantial rise in both the frequency and severity
of CDHEs, posing critical threats to urban systems, including water scarcity, heat stress,
and economic losses. The results also suggest potential interactions between extreme
temperatures and declining rainfall, which could amplify the vulnerability of socio-
economic sectors. This research underscores the urgent need for integrated climate
adaptation and mitigation strategies tailored to urban environments. By linking historical
patterns of CDHEs with future projections, the study provides a comprehensive
perspective on hydroclimatic extremes in New Delhi. These findings are crucial for
informing urban planning, resource management, and policymaking aimed at enhancing
resilience against the cascading impacts of compound extremes in a rapidly warming
world.
How to cite: Sahu, V., Swarnkar, S., and Raj, C.: Understanding Compound Dry-Hot Events in New Delhi: HistoricalTrends and Projections under +2°C and +4°C Warming Scenarios, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1044, https://doi.org/10.5194/egusphere-egu25-1044, 2025.
How to cite: Zhou, M.: A real-time storm surge prediction system for the Guangdong–Hong Kong–Macao Greater Bay Area under the background of typhoons: model setup and validation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1929, https://doi.org/10.5194/egusphere-egu25-1929, 2025.
Drought is one of the most complex natural disasters, which has serious socioeconomic and ecological impacts across the world. With a changing climate, not only drought events have occurred more frequently, but also the characteristics of drought propagation have been changed. Under the joint effects of climate change and human activities, the assumption on the stationarity of hydrological time series has been overturned, which is of great significance in the field of hydrology. However, the current research on drought propagation is generally based on the assumption of sequence stationarity, in which related results may be biased. Therefore, it is necessary to construct a nonstationary standardized drought index to explore the dynamics of drought propagation and its driving factors for further understanding the mechanism of drought propagation. The Generalized Additive Models for Location, Scale, and Shape (GAMLSS) were applied in Luanhe River Basin to construct a time-varying drought index. The seasonal propagation characteristics from meteorological to hydrological drought were examined based on conditional probability, and the moving window was utilized to explore the dynamic change of propagation characteristics. The driving factors were investigated by using the variable importance in projection. The results indicated that using a time-varying drought index was more reasonable than using a stationary assumption; the propagation time showed a significant downward trend; hydrological drought was more likely to be triggered by meteorological drought in autumn and winter; and the precipitation, decreasing runoff, and increasing evaporation were the main factors affecting the seasonal propagation characteristics. These findings are valuable for clarifying the nonstationary characteristics of drought propagation and its seasonal dynamics, providing scientific support for drought early warning systems.
How to cite: Dai, M., Feng, P., Li, J., and Shi, X.: Drought propagation dynamics and driving factors from a nonstationarity perspective, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2629, https://doi.org/10.5194/egusphere-egu25-2629, 2025.
Extreme temperature changes from one day to the next, whether warming or cooling, have profound impacts on human health, ecosystems, and socio-economic, and their potential future changes can result in even more significant challenges. In the previous study, we quantified the physical processes—advection, adiabatic, and diabatic heating or cooling—that drive extreme day-to-day temperature (DTDT) changes in present-day climate. However, the role of these processes in projected changes of DTDT extremes under future warming scenarios has remained unexplored. This study addresses this gap by examining these processes globally using the Community Earth System Model (CESM) Large Ensemble under a high-emission scenario together with Lagrangian backward trajectory calculations. The findings reveal that reduced temperature changes due to advection and altered diabatic processes primarily drive the projected decreases in DTDT extremes in the extratropics during December-February (DJF) and June-August (JJA). In contrast, increases in DTDT extremes in the tropics are primarily caused by enhanced local processes, such as radiative heating during DJF, and mostly by intensified diabatic processes during JJA, with advection playing a minor role. Therefore, there is a strong need for adaptive strategies and informed decision-making in response to climate change, particularly in underdeveloped countries in the tropics and subtropics.
How to cite: Hamal, K. and Pfahl, S.: Physical Processes Leading to Extreme Day-to-day Temperatures Changes: Future Climate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4416, https://doi.org/10.5194/egusphere-egu25-4416, 2025.
Hail is a weather phenomenon that can cause significant damage to material goods, crops, infrastructure, and motor vehicles, resulting in human injuries. Large and severe hail is often associated with severe convective storms, which are strongly related to atmospheric instability and the formation of intense thunderstorms. Predicting these thunderstorms, including their initial timing, location, and intensity, remains one of the most challenging aspects of modern weather forecasting. Current numerical weather forecast models often fall short in resolution, making accurate forecasting difficult. Therefore, meteorologists use convective indices as additional tools to predict thunderstorm development; these indices are considered valuable predictors for forecasting the occurrence of thunderstorms.
Convective indices are calculated from radiosondes' vertical temperature and water vapour profiles. In this research, we analysed 13 convective (or stability) indices derived from radiosonde measurements collected at the meteorological station Košutnjak in Belgrade, Serbia (φ = 44°46′ N, λ = 20°25′ E, h = 203 m above sea level) during days when at least one rocket-launching station, as part of the hail suppression system of the Republic Hydrometeorological Service of Serbia (RHMZ), reported occurrences of large and severe hail. Data for the warm season (April to October) at 12 UTC was gathered from 2002 to 2020. The term 12 UTC was selected based on the fact that approximately 96% of all hail events in Serbia, recorded from 1975 to 2009, occurred between 12:00 and 24:00 local time (UTC + 1). To statistically assess if there is a monotonic upward or downward trend, the Mann–Kendall test was used. If there is a trend, its magnitude is calculated using the Sen’s slope.
Recently, discussions about extreme weather conditions have increased. In response, we have focussed our attention on convective indices related to the occurrence of large and severe hail, defined as hailstones with a diameter of 21 mm or more. During the period analysed, days with such extreme hail accounted for 20% of all hail days. From 2005 to 2020, we identified significant monotonic trends in six out of thirteen convective indices: a decreasing trend for the Lifted Index (LI) and Boyden Index (BI), and increasing trends for the Severe Weather Threat Index (SWEAT), K Index (KI), Totals (TT), and Convective Available Potential Energy (CAPE). We could not conclude that days that meet the previously established threshold criteria for stability indices are becoming more frequent.
The number of hail days featuring hailstones with diameters between 21 mm and 30 mm and between 36 mm and 50 mm has been decreasing over time. Yet, the calculated coefficients of determination for both linear regression equations (R² = 0.108 and R² = 0.068, respectively) indicate that these trends are not significant. The number of days with hailstones between 31 mm and 35 mm also did not increase significantly (R² = 0.024). The overall frequency of extreme hail days has therefore not increased.
This research was supported by the Science Fund of the Republic of Serbia, No. 7389, Project „Extreme weather events in Serbia - analysis, modelling and impacts” - EXTREMES
How to cite: Vujovic, D. and Vuckovic, V.: Convective indices and their trends on days with observed large and severe hail in Serbia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9798, https://doi.org/10.5194/egusphere-egu25-9798, 2025.
While warm season heat waves are extensively studied, winter heat waves, which are extended periods of above-average temperature during winter months, largely remain overlooked. These events can disrupt typical water availability patterns and degrade water quality, particularly in regions already facing environmental stress.
The identification of heat waves varies depending on the context and objective. For example, variable percentile thresholds are used to study heat wave mechanisms, while fixed temperature thresholds are often applied to assess their ecological impact. In the context of biogeochemical processes that govern contaminant retention and mobilization, variations in surface and groundwater flow can be particularly important.
We analyzed the CAMELS‐SE dataset, which includes long-term observations of daily temperature, precipitation and streamflow from 1961 to 2020 across 50 sites in Sweden, along with local groundwater measurements, to identify and quantify heat-wave events using various approaches, and explore their correlation with observed surface and groundwater flow variability.
The main objective of the study is to determine the timing, duration, frequency, and magnitude of winter heat waves in Sweden, and to assess trends in surface and groundwater flows associated with these events. We also explore whether certain specific geographical regions in Sweden are more vulnerable to the effects of winter heat waves.
How to cite: Khan, U. A., Teutschbein, C., Ashraf, F., and Lai, F. Y.: Evaluating approaches to identify winter heat wave events and their hydrological impacts in Sweden, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18944, https://doi.org/10.5194/egusphere-egu25-18944, 2025.
Posters virtual: Mon, 28 Apr, 14:00–15:45 | vPoster spot 3
EGU25-12497 | ECS | Posters virtual | VPS12
Rainfall Interpolation Analysis in the Ijzer Basin Based on Neural NetworksMon, 28 Apr, 14:00–15:45 (CEST) | vP3.16
Accurate spatial distribution of rainfall during extreme weather events is crucial for hydrological analysis and flood forecasting. Despite the availability of numerous neural network-based models for spatiotemporal rainfall interpolation, challenges remain due to the limited number of rain gauges and the presence of missing values in the recorded data. These limitations introduce significant uncertainties into existing models. This study focuses on the Ijzer Basin in Belgium, using 20 years of data collected at 15-minute intervals, including rainfall, humidity, and temperature measurements et. etc. By training several neural network models on these data, we aim to identify the most accurate model for rainfall interpolation. Results indicate that Long Short-Term Memory (LSTM) networks demonstrate superior performance compared to other models in capturing the spatial distribution of rainfall.
How to cite: Xiao, W.: Rainfall Interpolation Analysis in the Ijzer Basin Based on Neural Networks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12497, https://doi.org/10.5194/egusphere-egu25-12497, 2025.
EGU25-395 | ECS | Posters virtual | VPS12
Impact of Geoengineering in Offsetting Climate Change-Induced Dam Break RiskMon, 28 Apr, 14:00–15:45 (CEST) | vP3.30
Dam safety is a primary concern for countries worldwide, as dam failure can have catastrophic consequences, including fatalities and losses to the economy, ecology, and environment. In recent decades, there has been growth in consensus that climate change has enhanced the risk to dams due to floods triggered by more frequent and intense extreme precipitation events. It necessitates reviewing the Probable Maximum Floods (PMFs) considered for planning and designing large dams and updating them for different speculated climate change scenarios to determine the projected future changes in dam break risk. Global initiatives, such as the Paris Agreement, are focused on developing strategies to limit the increase in global temperatures well below 2°C (preferably 1.5°C) above pre-industrial levels by 2050. However, significant discrepancies have been identified between the current global greenhouse gas emissions trajectory and the reductions needed in emissions to achieve the Paris Agreement's target. To bridge this gap, geoengineering climate intervention methods such as Stratospheric Aerosol Injection (SAI) and Solar Dimming (SD) have been proposed as potential solar radiation management (SRM) options to offset climate change effects. The latest Geoengineering Model Intercomparison Project (GeoMIP6) provides simulations from a suite of climate model experiments designed to assess the effect of potential SRM methods, including SAI and SD. To shed light on the effectiveness of geoengineering, this study assesses the impact of the current generation climate models (from Coupled Model Intercomparison Project Phase 6, CMIP6) and geoengineering models (from GeoMIP6) on Probable Maximum Precipitation (PMP) and the corresponding Probable Maximum Flood (PMF) at a typical large dam (Hemavathi) located in the Cauvery River basin in India. The current PMF of the dam is compared with future projections of the same derived corresponding to a CMIP6 high forcing scenario (SSP585) and two GeoMIP (G6sulphur and G6solar) scenarios. For both near and far future periods, the PMF hydrograph’s peak for the SSP585 scenario (GeoMIP6 scenarios) is significantly (marginally) greater than that of the current PMF of the dam. It indicates that geoengineering methods can offset climate change's impact on PMP and the corresponding PMF (depicting hydrological risk) at dams, which is of significance as worldwide many large dams have completed their design life.
How to cite: Goel, A. and Srinivas, V. V.: Impact of Geoengineering in Offsetting Climate Change-Induced Dam Break Risk, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-395, https://doi.org/10.5194/egusphere-egu25-395, 2025.
