The disastrous flood of May 2023 in Emilia-Romagna, Italy, displaced thousands of residents and had severe impacts on the economy, with extensive damage to infrastructure—roads, buildings, bridges— and losses in agriculture and livestock.

The flood was caused by two consecutive precipitation events, during which no hourly rainfall extremes were recorded, but for which accumulated rainfall over several days produced nonetheless extreme flooding, with a return period of over 500 years. The persistent, long-lasting precipitation was fueled by an uninterrupted vertically integrated water flux from the Adriatic Sea over the Po Valley, driven by a cyclonic circulation over Italy that remained stationary for several days.

A “cul-de-sac” effect, due to mountains that blocked moisture fluxes from the Adriatic Sea, amplified rainfall and was a root cause of the disaster. In this study, we analyze the dynamics of this case study in the context of the large-scale atmospheric circulation, focusing on the role of the stationary cyclonic structure over Italy, a feature that also characterized a similar event over the same area in 2024.

Furthermore, by examining the frequency of stationary cyclones in the Mediterranean region over recent decades, we are able to suggest that the persistent, dangerous configuration observed during the 2023 and 2024 events should be of concern to other Mediterranean areas that share similar conditions. A preliminary analysis also suggests that this class of events may become more frequent in a changing climate with important implications for the early warning systems. This work is part of ARTEMIS EU project # 101225852.

How to cite: Scoccimarro, E., Borrelli, A., Sangelantoni, L., Cavicchia, L., Tibaldi, S., Pasqui, M., and Boccaletti, G.: A cul-de-sac effect makes Emilia-Romagna more prone to floods in a changing climate, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3130, https://doi.org/10.5194/egusphere-egu26-3130, 2026.

Global warming is profoundly reshaping the terrestrial water cycle. Relative Humidity (RH), serving as a critical nexus between the water and carbon cycles, plays a pivotal role in maintaining ecosystem stability. Although a consensus exists regarding the long-term decline in global surface RH, focusing exclusively on the mean state often masks the asymmetric amplification of extreme RH events in terms of frequency and intensity, potentially leading to an underestimation of future climate risks. Based on ERA5-Land reanalysis data from 1980–2023, this study systematically evaluates the spatiotemporal characteristics of extreme low (RH05d) and extreme high (RH95d) RH events and unravels their driving mechanisms using detrended partial correlation analysis. Our study find that the significant decreasing trend in global land surface RH (−0.49%/decade) is primarily driven by the surge in extreme low RH events. Over the past 44 years, the evolution of extreme RH events has exhibited distinct asymmetry: the frequency of extreme low RH events has increased significantly (0.22 days/year), a rate approximately three times that of the decrease in extreme high RH events. This intensification is statistically significant across 47.2% of global land pixels, particularly concentrated in the Amazon, Central Africa, and the mid-to-high latitudes of the Northern Hemisphere. Attribution analysis confirms that this asymmetry stems from a "mechanistic divergence": the intensification of extreme low RH events is dominantly driven by thermodynamic factors (temperature and radiation), reflecting the surge in "atmospheric water demand" caused by the exponential increase in Vapor Pressure Deficit (VPD) under warming. Conversely, extreme high RH events are strictly limited by "moisture supply constraints"; the supplementation rates of precipitation and soil moisture fail to keep pace with the rising thermodynamic demand, thereby suppressing the occurrence of high-humidity events in most regions. The "mechanistic divergence" framework proposed in this study elucidates the non-linear response of RH from its mean state to its extremes. This finding provides a novel physical perspective for understanding the evolution of extreme humidity under non-stationary climate conditions and offers a scientific basis for overcoming the limitations of the traditional mean-state perspective to accurately assess the asymmetric eco-hydrological risks under global warming.

How to cite: Yu, Z. and Xia, H.: Stable decline in global surface relative humidity masks the distinct intensification of extremes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6658, https://doi.org/10.5194/egusphere-egu26-6658, 2026.

Pakistan is one of the most vulnerable countries to climate change due to its large exposure and vulnerability. In particular, climate models project an increase in heavy precipitation and flood intensity or frequency in the area. However, some uncertainties remain, which are in part related to its complex orography interacting with local dynamics, such as the Karakoram high-mountain region and the Indian summer monsoon. As a consequence, convection-permitting high-resolution simulations are needed. These allow for a better representation of steep orography and resolve deep convection, improving the simulation of precipitation. However, physics parametrization options need to be tested at high-resolution in order to improve these models.

This work evaluates the performance of different parametrization schemes in the Weather Research and Forecasting (WRF) model in simulating the extreme precipitation events that occurred in Pakistan in August 2022. This extreme precipitation primarily affected Southern provinces and led to disastrous flooding that resulted in numerous deaths, displaced people and loss of infrastructure and crop production. It was caused by westward propagating cyclones interacting with hot, moist air advected from the Arabian sea.

Results show differences in the spatial distribution and intensity of precipitation. In most setups, cyclones show a northward bias, where they interact with steep orography producing anomalous precipitation. Simulations are most sensitive to the microphysics parametrization, with the Thompson microphysics scheme producing the best results with respect to observations and reanalysis.

How to cite: Martínez-Vila, A. and González-Rojí, S. J.: Sensitivity of extreme 2022 Pakistan precipitation to physics parametrization options in WRF, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8991, https://doi.org/10.5194/egusphere-egu26-8991, 2026.

The Clausius-Clapeyron (CC) relation has - over the past two decades - been extensively discussed as a benchmark for the scaling of short duration rainfall extremes [1-3]. Recent work [4], using a large dataset from Germany, suggests that both convective and stratiform extremes scale approximately at the Clausius-Clapeyron rate of 7%/K when detecting the two types individually at high temporal and spatial resolution. Here we ask if such short-duration extremes also respond at similar rates to the observed temperature trends in Germany over the past 30 years. Indeed, over this timespan, our analysis shows a pronounced warming trend for Germany. However, short-duration precipitation extremes display relatively modest increases or no detectable increase during the same period. Conditioning on temperature at (dry) intervals leading up to precipitation events we find that the temperature trend of this conditioned dataset is also far more modest. In line with previous reports we find relative humidity to remain all but constant. Our results imply that, whereas mean and extreme temperatures in Germany increase markedly with global warming, changes in rainfall extremes may be much more gentle as the occurrence of rainfall appears to be tied to moderate temperatures. Deeper mechanistic understanding of the exact conditions for rainfall initiation under global warming, perhaps using cloud-resolving models, would therefore be useful for the projection of future meteorological flood risk.   

[1] Lenderink, Geert, and Erik Van Meijgaard. "Increase in hourly precipitation extremes beyond expectations from temperature changes." Nature Geoscience 1.8 (2008): 511-514.

[2] Haerter, Jan O., and P. Berg. "Unexpected rise in extreme precipitation caused by a shift in rain type?." Nature Geoscience 2.6 (2009): 372-373.

[3] Berg, Peter, Christopher Moseley, and Jan O. Haerter. "Strong increase in convective precipitation in response to higher temperatures." Nature Geoscience 6.3 (2013): 181-185.

[4] Da Silva, Nicolas A., and Jan O. Haerter. "Super-Clausius–Clapeyron scaling of extreme precipitation explained by shift from stratiform to convective rain type." Nature Geoscience (2025).

How to cite: Haerter, J. O., Hollstein, M., and Da Silva, N.: Do short-duration precipitation extremes follow observed temperature trends as predicted by the Clausius-Clapeyron relation?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14767, https://doi.org/10.5194/egusphere-egu26-14767, 2026.

Waterspouts are small-scale vortices occurring over water and may be associated with severe impacts in the Mediterranean region. However, their climatological characteristics and related environmental drivers remain only partially documented at the basin scale, particularly regarding the combined influence of large-scale atmospheric conditions and observed sea surface temperature (SST) variability.

This ongoing study addresses the characterization of Mediterranean waterspouts and investigates their relationship with atmospheric variables obtained from the ERA5 reanalysis and satellite-derived SST fields. Waterspout occurrences are identified using the reports from the European Severe Weather Database, focusing on the last two decades; the analysis aims to characterize both the seasonal and environmental context associated to these events.

Reanalyses are used to characterize the atmospheric conditions associated with waterspout occurrence, including convective instability, moisture availability, vertical wind shear, and large-scale circulation patterns. In parallel, high-resolution daily Mediterranean SST datasets are employed to characterize the background oceanic conditions at the time of the events. Particular attention is given to the combined role of favorable convective environments identified in ERA5 and concurrent SST anomalies. This contribution provides a first integrated assessment of atmospheric and oceanic variability in the framework of the Mediterranean waterspout climatology, with the goal of improving the understanding of these occasionally impactful events over the Mediterranean Sea.

How to cite: Avolio, E., Fanelli, C., Pisano, A., and Miglietta, M. M.: Large-scale atmospheric conditions and sea surface temperature variability associated with Mediterranean waterspouts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14864, https://doi.org/10.5194/egusphere-egu26-14864, 2026.

In this study, the diurnal characteristics and long-term changes of extreme precipitation over South Korea were investigated using hourly precipitation data from 59 Automated Synoptic Observing System (ASOS) stations for the 50-year period from 1973 to 2022. The analysis focused on the summer season (June–September), during which extreme precipitation events most frequently occur. Extreme precipitation events were defined using station-specific thresholds based on the 95th percentile of 3-hourly precipitation amounts during the early period (1973–1997).

During the early period, both the amount and frequency of extreme precipitation exhibited a pronounced maximum during the 01–09 LST period. In contrast, precipitation intensity showed two comparable maxima during 01–09 LST and 16–24 LST, with smaller diurnal amplitudes than those of precipitation amount and frequency. In the later period (1998–2022), a substantial increase in extreme precipitation amount and frequency was observed during the 04–12 LST period, accompanied by a shift in the timing of their diurnal maxima toward this time frame.

To better understand the mechanisms associated with extreme precipitation, the characteristics and changes of related atmospheric variables were also examined. During extreme precipitation events, a negative sea-level pressure anomaly was identified over western Korea, inducing southerly winds and positive moisture anomalies over southern Korea relative to the summer mean state. Compared to the early period, the later period exhibited increased atmospheric moisture and a higher frequency of moist conditions over South Korea. These moisture changes are likely associated with the enhanced extreme precipitation amount and frequency during the 04–12 LST period. In contrast, no statistically significant changes were found in the strength or frequency of southerly winds.

How to cite: Kim, D.-H., Kim, J.-U., Shim, J., Chung, C.-Y., and Boo, K.-O.: Diurnal Variability and Long-Term Changes in Extreme Summer Precipitation over South Korea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19102, https://doi.org/10.5194/egusphere-egu26-19102, 2026.

A detailed study of the role of Kelvin waves in the development of dust storms resulting in the subsequent large-scale transport of dust was performed for three severe dust storm cases that occurred in China and Mongolia on May 3, 2020, March 15, 2021, and March 20, 2023. Observational and numerical model data were analyzed in depth. These data include MODIS satellite images, MERRA reanalysis, surface observations, atmospheric soundings, NAAPS aerosol modeling plots, and WRF simulations. This study found that there were adjustment processes resulting in Kelvin waves in all three cases. The resulting lower tropospheric wind and instability forced by these Kelvin waves caused dust ablation and transport parallel to the Tien Shan, Gobi Altai, and Khangai Mountains. The Kelvin waves developed in association with a cold air mass behind the large-scale cold front that propagated along the periphery of these major mountains. This study demonstrated that the interaction between those mountains and the rapidly changing background atmosphere were the contributing factors for the genesis and propagation of Kelvin waves. These waves caused three dust storms and the subsequent synoptic scale transport of dust impacting East Asia.

How to cite: Pokharel, A. K. and Kaplan, M.: Dust Storms and Long-Range Transport of Dust by Kelvin Waves in East Asia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1783, https://doi.org/10.5194/egusphere-egu26-1783, 2026.

This study presents a novel unified extreme value theory (UEVT) for the simultaneous analysis of positive and negative anomalous events derived from anomaly time series. This framework enables the characterization of the return level–return period relationship, and by providing clear definitions for the critical and average intensity of N-year anomalous events, quantifies the temporal evolution of their intensity and frequency characteristics. Based on the UEVT, an interval extreme value distribution (IEVD) is further developed, which offers a statistical model for fitting both the upper and lower tails of anomaly series and for predicting changes of anomalous events with longer return periods. The UEVT and IEVD demonstrate broader applicability, higher accuracy, and improve practical utility compared to the traditional extreme theory and distributions. The results for N-year temperature anomalies suggest that there is a consistent increase in the intensity and frequency of warm events and a decrease in those of cold events under global warming. Regions exhibiting warming holes or cooling blobs, driven by internal climate variability, offer critical areas for future research on climate extremes. Notably, a southward expansion of warm events from the northern high latitudes and the increasing intensity of warm events in tropical regions show new characteristics of climate change. The hindcast intensity of anomalous events under longer return periods agrees well with the observed trend, and this framework is used to derive short-term predictions for future climate extremes. Additionally, a new prediction method integrating sliding trend with variability can provide a new perspective for modeling non-stationary extremes under strong climatic trends. These methods can be extended to the detection and attribution of extreme events and applied to the future climate projection with climate models.

How to cite: Ban, W. and Li, J.: The unified extreme value theory for characterizing changes in return periods and levels of N-year temperature anomalies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4696, https://doi.org/10.5194/egusphere-egu26-4696, 2026.

How to cite: Francis, D., Fonseca, R., Nelli, N., Cherif, C., Zittis, G., and Jan de Vries, A.: Examining extreme weather events in the Middle East: Trends and future outlooks., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5137, https://doi.org/10.5194/egusphere-egu26-5137, 2026.

Extreme weather events, such as heavy precipitation, strong winds, and convective storms, pose significant challenges to societies. Accurate forecasting of these events at high spatial and temporal resolutions, including uncertainty estimates, is crucial for effective disaster preparedness and mitigation.
In this work, we present recent developments in the EPS (Ensemble Prediction System) aspects of the Destination Earth On-Demand Extremes Digital Twin (DE_330_MF), which offers a highly configurable, on-demand workflow capable of detecting extreme weather events and triggering high-resolution forecasting at subkilometer scales. These features are valuable in supporting decision-makers in impact sectors such as hydrology, air quality, and energy. We showcase and evaluate the performance of the ensemble forecasting capabilities of this workflow with respect to prediction skill and uncertainty estimates.
We assess the workflow's performance for a selection of European extreme weather events relative to kilometer-scale forecasting systems like DINI-EPS, which is operationally deployed in the UWC West Consortium (Denmark, Ireland, the Netherlands, and Iceland). The subkilometer results from these investigations generally demonstrate skillful performance compared to the coarser models, providing potential added value for national meteorological services and decision-makers.

How to cite: Frølund, M., Yang, X., Alerskans, E., Wignes, O., and Andrae, U.: Ensemble Forecasting of Extreme Events at Subkilometer Scales, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5414, https://doi.org/10.5194/egusphere-egu26-5414, 2026.

Understanding the extreme weather events — such as heat waves, heavy precipitation, and episodes of strong winds — is crucial for assessing and managing climate-related impacts on human activities, ecosystems, and the environment. Global reanalysis datasets, including ERA5, and ERA5-Land, are widely used for studying such extremes; however, their relatively coarse spatial resolution can limit their ability to accurately capture localized and high-impact events. The high-resolution Copernicus European Regional ReAnalysis (CERRA) provides a regional alternative that has the potential to improve the representation of extreme meteorological conditions. This study benchmarks the performance of CERRA against established ERA-based reanalyses (ERA5 and ERA5-Land) using in-situ observations from Poland as an independent reference. The evaluation focuses on a set of temperature, precipitation, and wind-related extreme indices to assess how effectively each reanalysis reproduces observed extremes. The results indicate that CERRA outperforms the ERA-based products in representing extreme temperature and precipitation events, while improvements for wind speed extremes are more limited. In addition, three representative case studies — a severe heat wave from July 2010, a heavy rainfall event which led to a flood in June 2010, and a strong wind episode caused by the cyclone Kyrill in 2007 — are examined to provide a process-oriented comparison of CERRA and ERA reanalyses. Overall, the findings demonstrate that CERRA offers clear added value over ERA5 and ERA5-Land for the analysis of extreme weather events in Poland, highlighting its suitability for high-resolution climatological applications.

How to cite: Kulesza, K., Jefimow, M., and Strużewska, J.: Assessing the performance of the CERRA dataset in reproducing extreme weather events in Poland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6588, https://doi.org/10.5194/egusphere-egu26-6588, 2026.

Ongoing climate change is increasing the need for reliable climate information to support adaptation, particularly for climate extremes whose frequency and intensity are projected to rise and cause substantial societal and environmental impacts. Adaptation planning often requires highly localized information, yet global climate models (GCMs) typically operate at coarse spatial resolutions (~100 × 100 km) and have limited skill in representing extremes. To address this, downscaling techniques are widely used to generate higher-resolution climate information. Statistical downscaling links large-scale model output to local observations, while dynamical downscaling employs high-resolution regional climate models driven by GCM boundary conditions. The strengths and limitations of each approach need to be evaluated.

In this study, temperature- and precipitation-related climate extreme indices were computed using multiple publicly available datasets, including global model outputs from CMIP5 and CMIP6, statistically downscaled products (NEX-GDDP-CMIP6 and CIL-GDPCIR), and dynamically downscaled regional simulations from EURO-CORDEX. All datasets were harmonized to a common spatial resolution to enable direct comparison. The analysis covers a historical period (1990-2019) and a future period (2071-2100) under a middle-of-the-road emissions scenario (RCP4.5/SSP2-4.5). Historical simulations were evaluated against a gridded observational dataset (E-OBS) and two reanalysis products (ERA5 and GMFD). Using daily temperature and precipitation data, 17 climate extreme indices were calculated, along with detailed analyses of mean conditions and two representative extremes: annual maximum temperature and maximum 5-day precipitation.

Downscaling generally improves the representation of the European climate compared to global models. Statistically downscaled and bias-corrected datasets perform better for mean and extreme temperature and for mean precipitation, while improvements for precipitation extremes are limited. Dynamically downscaled EURO-CORDEX simulations show systematic regional biases, particularly in Nordic regions, and generally produce higher precipitation extreme indices. No single dataset consistently outperforms others across all regions, with complex terrain and coastal areas remaining challenging. Despite performance differences, all datasets project similar overall trends in climate extremes under warming, although the magnitude and regional patterns vary. Uncertainties in observational and reanalysis datasets, especially for precipitation, further complicate model evaluation. Overall this analysis highlights the need for clearer guidance on dataset selection for adaptation applications.

How to cite: Laakso, A., Hulkkonen, M., Deshmukh, A., Brosnan, I. G., Park, T., Lee, H., Wang, W., Thrasher, B., McCarty, J. L., Kokkola, H., and Mielonen, T.: Climate Extremes in Europe: A Comparative Analysis of Climate Model Datasets, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9971, https://doi.org/10.5194/egusphere-egu26-9971, 2026.

Europe suffers great financial loss and loss of life every year due to extreme events, particularly heat waves, flooding, droughts, and wildfires. The impacts of these events are increasing with both the increasing exposure of society and the increasing intensity and frequency of the events themselves under a warming climate. Accurate projections of the future changes in extreme events are vital for those stakeholders responsible for preparing the European cities to withstand future extreme events. They are also highly valuable to many industries which are heavily exposed to the impacts of extreme events, including insurance, construction, agriculture, health and energy. However, any adaptation requires information that is tailored to the needs and workflow of the decision makers.

In the EU-Impetus4Change project (I4C), we worked with stakeholders from four cities across Europe to select hazard indicators that are relevant to their ongoing adaptation work. The cities of Paris, Prague, Barcelona, and Bergen, were selected because they represent a wide range of climates across Europe and because they provide a sample of the different types of hazardous events faced by most European cities. The selected indicators focus primarily on extreme temperatures and precipitation hazards, though some relate to other sectors including energy and human health. The indicators have been calculated in 67 Euro-CORDEX simulations covering 120 years from 1980 to 2100 at a horizontal resolution of 0.11°. They have also been calculated in various convection permitting simulations of 10-year time slices in the current, mid-century and end of century, with a horizontal resolution of 3 km. This talk will present highlights from the analysis of this unique dataset, show the projected changes in these stakeholder-relevant indicators across different Global Warming Levels (GWLs), explore the biases compared to reanalysis, and examine the improvements of the convection permitting simulations compared to the lower resolution Euro-CORDEX simulations. The full dataset of these indices is planned to be made openly available through an online, user-friendly toolkit as part of the ongoing I4C project.

How to cite: Outten, S., Raffaele, F., Zazulie, N., and Vandeskog, S.: Indicators of extreme hazards in regional and convection-permitting climate models from the EU-Impetus4Change project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11491, https://doi.org/10.5194/egusphere-egu26-11491, 2026.

On 2 June 2017, a slow-moving Mei-Yu front produced extreme rainfall along the northern coast of Taiwan, with a maximum observed daily accumulation of 645.5 mm. This study employs Weather Research and Forecasting (WRF) Model simulations to investigate how variations in barrier jet intensity influence frontal movement and rainfall distribution during this event. The control simulation (CTRL) successfully reproduces the quasi-stationary Mei-Yu front, a pronounced barrier jet along the northwestern coast of Taiwan, and a maximum daily rainfall of about 680 mm.

A series of sensitivity experiments was designed to systematically modify barrier jet intensity while retaining the interaction between the front and northern Taiwan’s terrain. The results reveal a clear dependence of frontal propagation on barrier jet strength. When the barrier jet is weakened, the front advances southward more rapidly, shortening its residence time over northern Taiwan and leading to reduced rainfall accumulation. In contrast, a stronger barrier jet maintains a more northward frontal position, enhances low-level convergence and upward motion, and shifts the rainfall maximum northward, producing rainfall amounts comparable to those in CTRL.

The low-level equivalent potential temperature () gradients are similar across all experiments, indicating that the contribution of the large-scale environment to the frontal system is comparable among cases. Consequently, differences in frontal evolution and rainfall distribution can be attributed primarily to variations in barrier jet intensity. Vorticity budget analyses further demonstrate that a stronger barrier jet enhances low-level convergence and moisture transport, thereby slowing frontal propagation and resulting in increased rainfall accumulation over northern Taiwan.

How to cite: Lin, P.-L., Huang, M.-Q., and Tu, C.-C.: Effect of Low-Level Jets on the Movement of the Mei-Yu Front and Heavy Rainfall, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12007, https://doi.org/10.5194/egusphere-egu26-12007, 2026.

Human-induced climate change is rapidly increasing the magnitude and frequency of temperature extremes across the Mediterranean Basin. Türkiye is critically situated within this region due to its distinctive peninsular nature, being bounded by seas on three sides and intersected by complex mountain chains that strongly modulate local climate patterns. Observations indicate a distinct transition in summer temperatures. Between 1970 and 1990, average summer temperatures persisted within the 22–23°C. However, a rapid warming phase beginning in the early 2000s increased the mean summer temperature to the 24–25°C range. This steady warming trend peaked in 2024, when the average summer temperature reached a historical maximum of 26.1°C. Against this backdrop, this study prioritizes the analysis of extreme heat intensity rather than mean temperature trends. Accordingly, a comprehensive spatiotemporal assessment of heatwave magnitudes across Türkiye is conducted for the 1950–2024 period, using the HeatWave Magnitude Index daily (HWMId) derived from daily maximum temperatures obtained from the ERA5-Land reanalysis dataset. The resulting time series reveal a robust upward trend in heatwave magnitude, characterized by a progressive escalation in annual mean values. Quantitative analysis establishes a baseline mean HWMId of 1.68 for the reference period. While the pre-2000 era was dominated by a low-magnitude regime, with annual averages largely remaining below 1.6, the post-2010 period marks a clear regime shift, frequently sustaining annual averages nearly 100% higher than the historical baseline. Specifically, the summer of 2023 experienced an unprecedented increase in severity, with the spatially averaged HWMId reaching approximately 10.5 marking an increase of more than 5 times the reference period mean. In contrast, although seasonal mean temperatures peaked in the summer of 2024, the corresponding HWMId exhibited only a 60% increase above the reference period. These findings indicate that the magnitude of extreme heatwaves is not always highly correlated with record-breaking seasonal mean temperatures, suggesting that extreme heat events are evolving into a more acute and non-linear phase. Overall, these results point to a fundamental shift in the regional climate regime, underscoring the urgent need for enhanced predictive capabilities and robust adaptation strategies.

How to cite: Karakaya, T. and Önol, B.: Multidecadal Heatwave Magnitude Variability of Türkiye, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14320, https://doi.org/10.5194/egusphere-egu26-14320, 2026.

Rain-on-snow (ROS) events—during which liquid precipitation falls on an existing surface snowpack—are highly impactful to society, with severe flooding being the primary hazard. ROS events remain a highly challenging problem in several aspects of land surface model development, pushing the limits of land-atmosphere, snowpack, and runoff modeling. In particular, the representation of turbulent fluxes during these events is critical as energy into the snowpack controls the rate of melt and may impact the magnitude of resulting flooding. In this study, we investigate the representation of these turbulent fluxes in the Weather Research & Forecasting (WRF) model coupled to the Noah-MP land model during a ROS event.

For this case study, we use an extreme ROS event which occurred on 12-13 March 2019 across Nebraska, Iowa, and Missouri, resulting in historic flooding and damages. Our WRF simulation of this event was compared with observations from AmeriFlux, snow products, and ERA5 reanalysis fields. While the simulation was able to produce the synoptic dynamics leading up to and during the event, there were notable discrepancies between the observed and modeled turbulent fluxes, suggesting that during ROS events, latent heat flux into the snowpack is underrepresented. Furthermore, analysis of the kilometer-scale WRF simulation run across the CONtiguous United States for 40 years at 4-km resolution (CONUS404) reveals the same underrepresented latent heat fluxes. Simple snowmelt and runoff models, forced with the observed fluxes as well as an experiment with reduced latent heat fluxes, shows that including the latent heat flux melts the snowpack quicker than without it, which has implications for the modeling of flooding in the region.

In order to improve the model representation of this event, we explored the model sensitivity to evaporative resistance and snow surface roughness. Our results show that the evaporative resistance, which is usually represented as symmetric for fluxes into and out of the surface, is critical for producing latent heat flux into the surface. Adjusting these parameters can significantly improve representation of turbulent fluxes during ROS events.

How to cite: Dixon, R. D., Janzon, E. J., Roy, T., and Suriano, Z. J.: Improving the Numerical Representation of Turbulent Fluxes During the March 2019 Nebraska Rain-on-Snow Event, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15886, https://doi.org/10.5194/egusphere-egu26-15886, 2026.

Heatwaves represent one of the most impactful categories of extreme climate events and remain difficult to simulate accurately in numerical weather prediction and regional climate models. In tropical regions like Bangladesh, where strong monsoonal circulations, heterogeneous land-use patterns, and sparse in situ observations limit constraint of model physics and thus remain constant challenge for heatwave representation. This study evaluates the performance of the Weather Research and Forecasting (WRF) model and the Model for Prediction Across Scales-Atmosphere (MPAS-A) in reproducing a documented heatwave event during 26 April - 3 May 2024, to identify the modeling configuration that more reliably represents near-surface thermodynamic conditions. Model-simulated 2-m air temperature (t2) and 2-m specific humidity (q2) were evaluated against the MERRA reference dataset (0.5° × 0.625° spatial resolution) using root mean square error (RMSE) and Pearson correlation coefficients. Both models employed an identical suite of physical parameterizations, including WSM-6 microphysics, the Kain-Fritsch cumulus scheme, the Yonsei University planetary boundary layer scheme, MM5 surface layer physics, and the Noah land surface model, while radiative transfer was represented using the Rapid Radiative Transfer Model for Global Climate Models (RRTMG) and the Community Atmosphere Model (CAM) schemes. WRF was configured with two nested domains at 27 km and 9 km spatial resolution, whereas MPAS-A employed a variable-resolution mesh refined from 46 km globally to 12 km over the study region. Results indicate that WRF with RRTMG achieved the highest skill score in simulating 2-m air temperature (RMSE = 2.52 °C; r = 0.95), outperforming MPAS-A configured with CAM (RMSE = 3.04 °C; r = 0.82). For 2-m specific humidity, WRF-RRTMG minimized overall error (RMSE = 0.003), while WRF-CAM exhibited the strongest temporal correlation (r = 0.899); within the MPAS-A framework, the RRTMG configuration consistently outperformed CAM. Moreover, WRF-RRTMG more accurately captured the timing of heatwave onset, showing smaller temporal displacement relative to the reference dataset than MPAS-A configurations, indicating improved representation of the initiation phase of extreme heat events. Overall, the findings demonstrate that WRF provides more accurate heatwave simulation over Bangladesh under the adopted configuration, while MPAS-A shows competitive performance when configured with radiation transfer schemes, supporting its potential utility for multiscale atmospheric modeling applications.

How to cite: Rabbany, Y., Fahim, S. I., Laskor, Md. A. I. H., Dipu, S. U. A., Bhuiyan, F., and Islam, A. S.: Sensitivity of heatwave simulation to radiation parameterization in WRF and MPAS-A: A case study over Bangladesh, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16320, https://doi.org/10.5194/egusphere-egu26-16320, 2026.

Global mean temperatures reached unprecedented levels in 2023, and large parts of the world experienced prolonged and recurrent heatwave conditions, resulting in severe consequences for public health and socioeconomic systems (Perkins-Kirkpatrick et al., 2024). North Africa was among the regions most severely affected. However, quantitative assessments of the spatial extent and seasonal progression of record-breaking heatwaves over North Africa remain limited. This study uses the Excess Heat Factor (EHF, Nairn et al. 2009) to characterize heatwaves across North Africa in 2023, examining their spatial patterns and seasonal evolution with reference to the past five decades. 

North Africa experienced exceptionally warm conditions in 2023 characterized by prolonged heatwaves and a markedly expanded spatial extent compared with the 1972–2022 reference period. Indeed, temperature anomalies reached up to 5K over most of the region, with the strongest differences occurring during the boreal autumn (SON). Notably, approximately 35% of the study domain experienced the highest seasonal mean near-surface temperature on record since 1972. The heatwave analysis revealed pronounced anomalies in 2023 relative to the baseline climatology; the event frequencies ranged from 2 to 5 events per year, and their duration exceeded the reference by 4 to 7 days across large parts of the domain during summer (JJA) and autumn (SON), particularly over Morocco, the central Sahara, and surrounding regions. In addition, record-breaking daily maximum temperatures (Tmax) were detected at multiple timescales over the 50-year record. During two major episodes in 2023, the spatial extent affected by these record-breaking conditions exceeded 4 × 10⁶ km², occurring from 25 July to 5 August and from 25 October to 10 November, respectively.

These hot events were also assessed in terms of related large-scale atmospheric circulation. The mid-atmosphere conditions were characterized by positive geopotential height anomalies at 500 hPa, with an anomalous ridge centered over northern Morocco and Algeria bringing persistent atmospheric blocking and enhanced warm air advection, favoring the development and persistence of extreme surface temperatures. Concurrently, temperature anomalies at 850 hPa ranged from 2 to 4 K over northeastern Morocco, Algeria, and Egypt, while more moderate anomalies of approximately 1 to 2 K were observed along the Atlantic coasts and across the southern Sahara. These findings highlight the exceptional severity, persistence, and spatial extent of the 2023 heatwaves in North Africa, underscoring the region’s increasing vulnerability to extreme thermal events under ongoing global warming.

References:

Perkins-Kirkpatrick, S., Barriopedro, D., Jha, R. et al. Extreme terrestrial heat in 2023. Nat Rev Earth Environ 5, 244–246 (2024).  https://doi.org/10.1038/s43017-024-00536-y

Nairn, J., R. Fawcett, and D. Ray, 2009: Defining and predicting excessive heat events: A national system. CAWCR Tech. Rep. 017, 83–86

How to cite: Arjdal, K. and Driouech, F.: The 2023 record-breaking heatwave in North Africa: characteristics and driving mechanisms, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18338, https://doi.org/10.5194/egusphere-egu26-18338, 2026.