Including Tromp Foundation Travel Award to young scientists (TFTAYS)
The aim of this session will be studies that bridge the spatial scales and reach the timescales of extreme events that impact all our lives. Papers are solicited on advancing the understanding of causes of observed changes in mean climate, in its variability and in the frequency and intensity of extreme events, including the detectability and emergence of these changes from background variability. In particular, papers are invited on trends in the regional climate of Europe, not just the mean, but variability and extremes, often for the latter measured through well-chosen indices. Contributions addressing uncertainties in climate modelling, particularly via model-observation comparisons in the detection and interpretation of climate trends and extremes, are also welcome.
Mountain regions are often considered particularly sensitive to climate change, yet the magnitude and drivers of enhanced warming remain uncertain. Here we assess whether the Greater Alpine Region (GAR) represents a climate warming hotspot relative to surrounding parts of Western-Central Europe and how the past warming patterns are reflected in global climate models.
We analyse long-term mean temperature changes from observational and model-based datasets, including the ERA5 and ERA5-Land reanalysis, the E-OBS gridded dataset, and global climate model simulations assessed in the IPCC Sixth Assessment Report (CMIP6). Trends are evaluated for 1950–2025 and compared with global mean warming to estimate amplification ratios.
Observations and reanalyses consistently indicate strong mean warming across the GAR since 1950, with particularly rapid increases in all seasons during recent decades. The region exhibits an amplification ratio relative to the global mean warming of roughly 2 to 2.4 that has remained remarkably stable for the last 25 years.
Whether Alpine warming exceeds that of neighbouring lowland regions is less clear. ERA5 suggests stronger Alpine warming, whereas ERA5-Land and E-OBS indicate similar trends in the surrounding regions of Western-Central Europe. Higher-resolution national datasets show the strongest warming at the Alpine foothills compared to high elevations in recent decades.
CMIP6 global climate models substantially underestimate the observed warming over the GAR, producing an amplification ratio of only about 1.3. The reasons are still under discussion but likely include substantial uncertainties related to the impacts of regional circulation changes, aerosol forcing and land-atmosphere coupling.
Overall, the results indicate that Western–Central Europe including the GAR behave as a persistent regional warming hotspot and highlight a substantial mismatch between observed and modelled temperature change. Improving the representation of local climate processes in reanalyses, observational datasets, and climate models is therefore essential to better understand regional warming mechanisms and to produce reliable regional climate projections and impact assessments, especially in mountain environments.
How to cite: Scherrer, S. C., Muelchi, R., and Kotlarski, S.: Persistent Alpine Warming Amplification and Its Underestimation in Climate Models, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-51, https://doi.org/10.5194/ems2026-51, 2026.
A substantial increase in the frequency and intensity of extreme climatic events is clear evidence of climate change, which can be observed across South-Eastern Europe, including the Carpathian Basin and Hungary. This trend constitutes an increasing risk to human health, as populations are progressively exposed to environmental stressors with amplified recurrence and severity. Heatwave days, defined as daily mean temperature of at least 25 °C and tropical nights, when temperature does not drop below 20 °C at night are among those weather related phenomena that pose serious health risks. Due to heat stress, mortality rises during time periods characterized by such temperature extremes.
In our study the co-occurrence of heatwave days and tropical nights is analysed for the 21st century. In addition, we investigate the appearance of a second level heat alert (when the daily mean temperature is at least 27 °C) combined with higher minimum temperatures up to 25 °C. For this research five regional climate models (RCMs) of the EURO-CORDEX initiative were selected (CCLM, HIRHAM, RACMO, RCA, REMO), all available at a horizontal resolution of 0.11° and driven by two different representative concentration pathway scenarios (RCP4.5 and RCP8.5, respectively). In addition to the raw simulations, bias-corrected versions of these RCMs were also investigated: the RCM projections available from the EURO-CORDEX project using MESAN as reference data, the FORESEE-HUN database and BC-HUCLIM, a bias-corrected set of simulations specifically established for this research. For BC-HUCLIM, bias-correction was performed using the percentile-based quantile mapping method with the quality controlled HuClim data serving as reference. The bias-correction was carried out separately for each raw simulation on a monthly basis.
The results are presented for the regions of two Hungarian cities: Budapest, the capital city of Hungary and Szeged, located in the south-eastern part of the country, which often experiences increased heat advection from the Mediterranean. The co-occurrence of the climate indices are shown throughout the year for the past (1976-2005), for the near future (2021-2050) and for the end of the 21st century (2070-2099). The investigation focuses on the question of (i) how many RCM simulations project the occurrence of the events at least once in 30 years on a given day of the year (ii) in which part of the year can these temperature extremes occur.
How to cite: Simon, C., Kis, A., and Torma, C. Z.: The co-occurrence of heat-related climate indices in Hungary during the 21st century using raw and bias-corrected EURO-CORDEX simulations, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-23, https://doi.org/10.5194/ems2026-23, 2026.
This study synthesizes two related research efforts to investigate the spatiotemporal characteristics, driving mechanisms, attribution, and future projections of winter extreme cold events and annual mean temperature changes over China since 1961. For extreme cold events, three indices are analyzed, including the intensity of cold extremes (TNn), frost days (FD), and ice days (ID), based on station observations, CMIP6 model simulations, and large-scale circulation indices. Results show an overall weakening of winter cold extremes across China, accompanied by pronounced regional and interdecadal variations. The decreasing trends tend to slow down in eastern China, while extreme cold events have intensified in Northeast China since the 1990s. In western China, cold extremes continue to weaken but at a reduced rate. Anthropogenic forcing is identified as the dominant driver of the weakening of extreme cold events in eastern China, whereas the negative phase of the Arctic Oscillation (AO) and the strengthening of the Siberian High significantly enhance cold extremes. In addition, Arctic amplification and the associated weakening of the polar vortex contribute to increased southward outbreaks of cold air.
For annual mean temperature, detection and attribution analyses are conducted using CMIP5 and CMIP6 model simulations based on the optimal fingerprinting method, combined with an observation-constrained approach to reduce model biases. The results demonstrate that anthropogenic forcing is the primary contributor to the observed warming over China, while some CMIP6 models tend to overestimate the warming magnitude. After applying attribution constraints, projected warming under high-emission scenarios (2081–2100) is substantially reduced compared to unconstrained projections, leading to improved consistency between CMIP5 and CMIP6 results and a significant reduction in uncertainty.
Despite the overall decrease in the risk of extreme cold events under global warming, internal climate variability associated with large-scale circulation continues to modulate regional cold extremes. These findings highlight the importance of considering the interplay between long-term warming trends and interdecadal variability, and emphasize the need to improve regional climate simulations to better support climate adaptation and disaster risk reduction strategies.
How to cite: Yin, H.: Attribution and Projection of Winter Extreme Cold Events and Temperature Changes over China, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-114, https://doi.org/10.5194/ems2026-114, 2026.
Winter plays a key regulatory role in the natural environment of the temperate zone. It determines the dormancy period of plants, enables the accumulation of water in the form of snow, and limits populations of pests and pathogens. Rising temperatures during the winter season, the shortening of thermal winter, and increasingly frequent warm episodes are leading to the loss of a stable, long-lasting cold phase, which is an important factor regulating ecosystem functioning.
The aim of this study is to assess winter warm episodes and heat waves in the context of the duration of thermal winter in Central Europe. Cases of anomalously high air temperature were analyzed, taking into account the spatial extent of the extreme event, its intensity, and its duration. Variability in the frequency, affected area, and magnitude of the region’s heat load in recent decades was examined using high-resolution (2 km × 2 km) gridded data developed for the years 1961–2024.
The obtained results clearly confirm the shortening of thermal winter in Central Europe – sometimes to only a few to a dozen days – while it is increasingly interrupted by prolonged episodes of above-zero temperatures. An extended area of the region is exposed to thermal extremes (positive values of minimum air temperature and days with maximum temperature exceeding the 95th percentile), and heat surpluses anomalous for the winter months are leading to a progressive destabilization of climate seasonality.
The research findings indicate that the observed changes are not limited solely to an increase in mean temperature but also involve a transformation of the seasonal structure of the climate. The shortening and fragmentation of thermal winter, together with the increasing frequency of warm episodes, weaken the regulatory mechanisms of the natural environment, increasing ecosystem vulnerability to thermal stress and phenological disturbances. In light of projections of continued climate warming, this process may intensify further, making winter one of the key seasons in the analysis of contemporary climate change in Central Europe.
Research funded by the National Science Centre, Poland under the OPUS call in the Weave programme 2022/47/I/ST10/02144
How to cite: Wypych, A., Sulikowska, A., Ustrnul, Z., Štěpánek, P., Zahradníček, P., Skalák, P., Řehoř, J., and Brázdil, R.: From Frost to Heat: Changes in Thermal Winter and Winter Warm Extremes in Central Europe, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-414, https://doi.org/10.5194/ems2026-414, 2026.
This study examines asymmetric warming in Croatia by analysing changes in the distribution of maximum daily air temperature and the characteristics of cumulative heat intensity in compound dry and hot (DH) extreme events in the JJA season. The analysis covers the period 1963–2025 and is based on observations from the main meteorological stations in Croatia, grouped into mountain, inland, and coastal regions.
Compound DH events are defined as periods of consecutive dry days (daily precipitation < 1 mm) and the maximum of maximum daily air temperatures (Tx) during these dry spells, while extremes of such events are defined as the simultaneous exceedance of the 90th percentile for these parameters, based on the 1981–2010 reference period. Event intensity is quantified using cumulative heat intensity (CHI), defined as the sum of positive daily temperature anomalies during an event. To further characterise high-intensity events, two additional metrics are analysed: the number of days with positive temperature anomalies (CHI_ndays) contributing to the CHI and the mean temperature anomaly (CHI_meanTa) of those days.
The results reveal pronounced regional differences. At coastal stations, high-CHI events are mainly associated with longer durations of moderately elevated temperatures, reflected in higher CHI_ndays. In contrast, inland stations show high-CHI events characterised by fewer days than at coastal stations, but with stronger temperature anomalies, indicated by higher CHI_meanTa.
Trends in temperature distribution during the JJA season are analysed using quantile trends based on 30-year sliding windows. Inland stations exhibit approximately linear increases across percentiles, with the largest trends at the highest percentiles, indicating a stronger amplification of the upper tail of the distribution. Coastal stations show increasing trends up to the lower-to-middle percentiles, followed by a relative stabilisation of trends at higher percentiles, although trends remain positive.
The same analysis applied to other seasons reveals geographically consistent patterns with varying magnitudes. Overall, the results indicate strong spatial and seasonal variability in temperature distribution changes and provide additional insight into the characteristics of cumulative heat intensity in compound DH extreme events in Croatia.
How to cite: Boras, M., Herceg-Bulić, I., and Pasarić, Z.: Asymmetric Warming over Croatia: Quantile Trends in Temperature Distribution and Cumulative Heat Intensity of Compound Dry-Hot Extreme Events, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-461, https://doi.org/10.5194/ems2026-461, 2026.
The Barcelona Metropolitan Area (AMB), with nearly 3.5 million inhabitants, is one of the largest conurbations in Southern Europe. Furthermore, population growth is expected in the coming decades as a result of both internal and external migration. In the context of climate change, the projected increase in temperature is expected to have a profound impact on infrastructure management, urban design and ultimately in urban population.In this study, we present a set of high spatial resolution climate projections for temperature and derived climate indices. These projections have been obtained through statistical downscaling using the delta bias correction methodology applying Kernel Density Estimation (KDE) to compute the Cumulative Distribution Functions (CDF). Climatic data is based on a set of Euro-CORDEX CMIP5 simulations and a high-resolution observational grid (1 km) derived from historical data provided by the Meteorological Service of Catalonia is used as a ground truth. Two subsets of Euro-CORDEX models were selected: one comprising models that best reproduce the observed temperature trends in Catalonia over the observational period 1971–2005, and another including models that perform worst in reproducing these trends. Results indicate a substantial spread in projected maximum and minimum temperatures across models. However, the spatial distribution of the warmest areas remains broadly consistent among simulations.Based on these projections, it is plausible that the threshold of 50 °C could be reached by the end of the century in several locations within the AMB. This threshold has not yet been recorded in the AMB, where absolute maximum temperatures reach 43–44 °C, nor in the warmest areas of Catalonia (44–45 °C) or across the Iberian Peninsula (47–48 °C), since the beginning of instrumental records (19th century). In addition, urban heat island effects are particularly evident in projections of minimum temperatures. Nevertheless, the intensification of night-time temperatures in urban areas should be better represented in future projections, as these processes may exhibit their own dynamics and are strongly dependent on urban design and development models currently being implemented.Finally, we emphasize the need to incorporate Euro-CORDEX CMIP6 simulations as soon as these datasets become available to the scientific community.
How to cite: Amérigo-Veys, H., Altava-Ortiz, V., Barrera-Escoda, A., Cunillera, J., Moré, J., Prohom, M., and Amaro, J.: High resolution temperature projections for the Barcelona Metropolitan Area (AMB), EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-564, https://doi.org/10.5194/ems2026-564, 2026.
Long-term air temperature series are crucial for examining modern climate warming within a historical context and assessing changes in the frequency, duration, intensity, and distribution of extreme air temperature events. This knowledge is crucial for reducing vulnerability, enhancing resilience, and mitigating the impact of future events in the context of climate change, as part of climate adaptation and mitigation policies.
Environmental impacts during heat wave events include increased water consumption and water shortages (which are exacerbated when coupled with drought events), higher energy demand, crop failures, heat stress in cattle, and an increased risk of wildfires.
Ireland has a rich historical record of daily maximum and minimum air temperature observations dating back to the 19th century. The objectives of this research were to assess the magnitude and statistical significance of trends at the station level and for Ireland in the number, frequency, intensity, magnitude, and duration of heat waves for the period from 1885 to 2023. This assessment was based on long-term, quality-controlled, and homogenised air temperature series and employed a range of definitions. Long-term trends in the timing of events, accounting for changes in start and end dates, were assessed.
This presentation will highlight methodologies for heat wave indices and statistical methods, present and discuss the results.
Upward trends were identified in the number of heat waves, indicating that heat waves have become markedly more common over time at most stations. The number of days contributing to heat waves has increased markedly. The longest heat wave of each year has become markedly longer across nearly all sites. Several stations show significant increases in the probability of experiencing a heat wave.
Heat waves have become longer and more seasonally extensive, beginning earlier and persisting later into the year. This pattern indicates a progressive broadening of the period in which extreme heat events occur, consistent with a lengthening and intensifying warm season across stations.
How to cite: Mateus, C., Mimnagh, N., and Potito, A.: Changes in heat waves in Ireland, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-703, https://doi.org/10.5194/ems2026-703, 2026.
Climate change is a well-known topic for most people nowadays, being present in a considerable proportion of conversations worldwide. Albeit scientists have a data-based perception of the global climate change, most people relationship with it is based on their daily experiences and memories, which can be unreliable especially in the medium and long ranges. One statement commonly heard by the authors in relation to people’s experience with climate change is that intermediate seasons are retreating, leading to a cold-hot season dipole. This work aims to verify if data confirm this general perception using quality-controlled observational data. In this study, we select over 1000 climatological stations around the world and analyse the trends in the number of days belonging to each climatological season. For a station to be selected, a simple two-step procedure is followed to ensure the reliability of the trends computation: 1) any year with at least 20 days without data is removed from the time series; 2) then, if a station has less than 8 years with remaining data in any decade, that station is discarded from the selection. Once station selection is performed, the number of days belonging to one season is computed by creating a yearly cycle of temperature using data between 1955 and 1984 as climatological reference period. Then, the days belonging to a climatological season are computed as follows for the northern (southern) hemisphere stations: a) days with a temperature above (below) the climatological mean of June 1st are considered summer (winter) days; b) days with a temperature below (above) the value of the climatological mean of December 1st are considered winter (summer) days; c) values in between have been considered as spring or autumn days, depending if they occur before the yearly higher peak of temperature, or after it. Both daily maximum and minimum temperatures, and several reference periods, are used for the analysis with similar results in all cases. We find that, in general, the durations of intermediate seasons have remained steady or slightly increased since 1955 around the world, in contrast with the popular feeling. Furthermore, the length of summer has increased in Europe, Australia and China at a rate of 3-4 days/decade in average, whereas the number of winter days has decreased in those regions at a rate of between 5 and 10 days/decade. However, these trends are not as clear in the continental United States of America, with a region in central USA with a reverse trend –longer winters and shorter summers. These findings highlight the importance of data availability for climatological studies and discussions and reveal an area of interest inconsistent with the general global trend, which should be further studied.
How to cite: Rodríguez-Sánchez, A. and Martilli, A.: Are some seasons disappearing from our lives?, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-411, https://doi.org/10.5194/ems2026-411, 2026.
Estimates of very rare but still possible rainfall events on sub-daily or even sub-hourly scales are essential to properly manage flood risk, design hydraulic structure, and plan insurance and reinsurance business. For example, we need to estimate rain intensities that are expected to occur on average in 100 or 200 years. The problem is that we can only rely on a few decades of past observations, which may not be representative of the future anymore. Convection permitting simulations represent the state-of-the-art for what concerns climate modeling but still come short at addressing these issues. This is because they provide rather short simulation periods due to the high computational costs, because they require bias-adjustments, and because they usually provide information at hourly resolutions, which may be insufficient for some applications such as urban flooding.
Past works showed that using a conceptual model of the atmospheric column and some simple assumptions, the distribution of precipitation amounts over appropriate time intervals has stretched exponential (i.e., Weibull) tails. Using these arguments, it is possible to derive a physics-based approach to model the statistics of extreme precipitation on temporal scales ranging from a few minutes to 24 hours. This is a natural framework for including the impacts of climate change in the formulation of our extreme value models because it allows to consider multiple types of storms (e.g., convective, frontal, etc.) and to explicitly account for changes in their intensity distributions as well as in their occurrence probability. Non-stationary implementations of the intensity distributions based on relevant covariates provide a physics-based manner for handling future changes in extreme precipitation statistics. I will introduce the theory behind these approaches, and I will show applications for the case of cyclones and other types of Mediterranean storms in the eastern Mediterranean and for the case of convective summer storms in the greater Alpine area.
How to cite: Marra, F.: A physics-informed perspective on the statistics of future precipitation extremes, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-157, https://doi.org/10.5194/ems2026-157, 2026.
Accelerated transformations in the European hydrological cycle during the early 21st century call for a rethinking of approaches used to detect regions susceptible to precipitation extremes. This study presents a risk map for extreme precipitation events (EPEs), categorizing areas into four risk levels: from no risk to high risk. Four risk levels were defined based on the direction, magnitude, and statistical significance of trends in extreme precipitation indices (EPIs), with the highest category representing significant positive trends within the upper percentile of the distribution. The study includes 70 years of historical data from E-OBS (1951-2020) and 13 bias-adjusted CORDEX models under two future scenarios, SSP2-4.5 and SSP5-8.5, for the period 2021-2100. To ensure reliable detection of long-term changes, the analysis employs the Mann-Kendall test with an iterative pre-whitening procedure.
The historical risk assessment derived from seven decades of E-OBS observational data shows a heterogeneous distribution across Europe. Elevated risk zones are predominantly concentrated along the western coastal regions of Scandinavia, particularly in Norway's Atlantic-facing territories. In contrast, large portions of the continental interior, including substantial areas of Poland, Germany, and the eastern Baltic states, exhibit medium to low risk levels. Under the SSP2-4.5 scenario, some areas may experience heightened risk of precipitation extremes, notably in Scandinavia, yet considerable uncertainty remains across models. Model agreement is not spatially uniform across the domain; the most pronounced disagreement occurs in southern Norway, where a relatively large area exhibits substantial variability among risk levels.
The SSP5-8.5 scenario presents a noticeable increase in risk levels, with widespread agreement among climate models. Almost the entire study domain transitions into medium to high-risk categories. This wholesale shift represents not merely an intensification of existing patterns but a fundamental reorganization of the region's extreme precipitation climatology. The changes are especially pronounced across the Scandinavian countries, with almost the entire region falling into the high-risk category.
The contrast between two emissions scenarios emphasizes the strong sensitivity of extreme precipitation patterns to greenhouse gas concentration pathways. Overall, the results emphasize the urgency of mitigation and inform adaptation planning in regions likely to face higher extreme precipitation risk.
How to cite: Fakour, P., Ustrnul, Z., and Messori, G.: A Multi-Model Risk Assessment of Extreme Precipitation Hazards in North-Central Europe, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-20, https://doi.org/10.5194/ems2026-20, 2026.
Localized convective precipitation, characterized by short duration and high intensity, remains difficult to investigate using observations alone. Convection-permitting regional reanalyses provide valuable information on such events and their temporal evolution, particularly when adopting event-based approaches. Several convection-permitting reanalyses are available over Italy (e.g. SPHERA, MERIDA HRES, MORE, CHAPTER and VHR-REA_IT), obtained by dynamical downscaling of ERA5. They provide the opportunity to analyse extreme precipitation at hourly resolution and using an ensemble approach. Although a multi-model ensemble can improve precipitation average statistics, simple averaging of model fields tends to smooth intensity peaks, thereby degrading the representation of extreme events. To address this limitation, this study proposes an event-ensemble framework that combines information from multiple convection-permitting reanalyses without directly averaging precipitation fields.
First, extreme precipitation events are independently extracted from each reanalysis dataset. Event identification is based on the Extreme Rain Multiplier (ERM), defined as the ratio between hourly precipitation at a given grid point and the climatological mean of the RX1hour index (that is, the annual maximum 1-hour precipitation) at that location. This reference threshold is also compared with observational estimates derived from a high-resolution gridded hourly dataset (GRIPHO). The ERM provides a physically interpretable measure of event rarity and enables the classification of extreme events across datasets. In a second step, events identified in the different reanalyses are combined probabilistically within an event-ensemble framework. This approach allows uncertainty to be quantified through the spread in precipitation structures extracted from different reanalyses in terms of event timing and location, peak values, spatial extent.
The proposed methodology opens several perspectives for investigating extreme precipitation over Italy and is transferable to other regions where multiple convection-permitting reanalyses are available. First, it allows detailed investigation of individual exceptional events and their robustness across different reanalysis datasets. Moreover, it supports analyses of long-term variability and emerging changes in hourly extremes, including the detectability of such changes against background variability. Overall, this work demonstrates how the growing availability of convection-permitting reanalyses can be leveraged to study extreme precipitation at short timescales using a probabilistic, event-based and multi-dataset approach that explicitly accounts for model uncertainty while preserving the intensity of extreme rainfall events, offering a new framework for the assessment of regional extreme-precipitation variability and change in Italy.
How to cite: Cavalleri, F., Stocchi, P., Brunetti, M., and Davolio, S.: An event-ensemble approach to investigate hourly extreme precipitation over Italy using convection-permitting reanalyses, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-169, https://doi.org/10.5194/ems2026-169, 2026.
Sub-daily precipitation plays a key role in Mediterranean hydrometeorological hazards, where short-lived, high-intensity events are the main drivers of flash flooding. This study analyses observed changes in hourly precipitation patterns across the Internal Basins of Catalonia (NE Iberian Peninsula) over the period 1996–2025, using a dense network of automatic rain gauges from the Meteorological Service of Catalonia. Data quality was ensured through a combination of operational quality control and advanced automated procedures developed within the INTENSE project, allowing for a robust characterization of extreme events.
The results reveal a consistent intensification of short-duration precipitation extremes. Significant positive trends are detected in maximum precipitation over 1-hour and multi-hour aggregations (3h, 6h), as well as in the frequency of high-intensity episodes exceeding fixed thresholds (e.g. 30 mm in 1 hour). In parallel, a tendency toward shorter event durations is observed, indicating a shift toward more temporally concentrated rainfall. These changes are particularly pronounced in coastal and southern sectors, suggesting an increasing dominance of convective processes.
Despite the strengthening of sub-daily extremes, no clear corresponding increase is found in longer-duration accumulations (24h), pointing to a redistribution of rainfall toward more intermittent and intense bursts. Complementary daily-scale analysis (1950–2024) indicates a general decline in total precipitation and in the frequency of rainy days, reinforcing the interpretation of a more irregular precipitation regime.
Overall, the results highlight a marked transition toward fewer but more intense and short-lived precipitation events. This evolution has significant implications for flood risk, urban drainage performance, and water management in Mediterranean catchments under ongoing climate change.
How to cite: Prohom, M. J. and Peña-Rabadan, J. C.: Emerging changes in sub-daily precipitation extremes in Catalonia (1996-2025), EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-217, https://doi.org/10.5194/ems2026-217, 2026.
In the context of anthropogenic climate change, France represents a critical study area where regional warming is observed to exceed the global average. Understanding the future evolution of precipitation is essential for water resource management and flood risk mitigation. In this work, we employ a unified statistical framework based on the generalized gamma distribution, selected for its flexibility in capturing the full range of the daily precipitation, including extremes, to assess future changes in daily precipitation across Metropolitan France. A central feature of our methodology is the integration of non-stationarity through physical covariates. We account for thermodynamic forcing using Sea Surface Temperature (SST) anomalies averaged over the North Atlantic and the Mediterranean Sea, which govern the atmospheric moisture content available for precipitation. Simultaneously, we incorporate dynamic drivers of regional climate variability by employing the North Atlantic Oscillation (NAO) index and the Western Mediterranean Oscillation (WeMO) index. These indices serve as proxies for the large-scale atmospheric circulation patterns that dictate storm tracks and moisture transport into Western Europe.
We started by training our statistical model using high-resolution reanalysis data to establish robust historical baseline relationships. We then derive the future projections by extrapolating these relationships using covariates from 15 CMIP6 Global Climate Models (GCMs). These specific models were selected based on their demonstrated ability to reliably simulate European hydro-climatic processes. We present near-future and long-term changes across four fundamental metrics: wet-day frequency, mean wet-day precipitation, mean of all-days precipitation, and the 20-year return level. Our results highlight a complex spatial and seasonally-dependant response, reflecting the competing influences of thermodynamic moistening and dynamic shifts. Beyond the regional projections for France, this unified framework offers a scalable approach for non-stationary weather generators. Such tools are increasingly vital for stochastic climate simulations and the development of localized adaptation strategies in a rapidly changing environment.
How to cite: Haruna, A., Blanchet, J., Evin, G., and Paquet, E.: Projected future changes in mean and extreme daily precipitation in France conditioned on large-scale thermodynamic and dynamic drivers, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-376, https://doi.org/10.5194/ems2026-376, 2026.
Increasing air temperature is the factor causing relevant changes in humidity conditions in the long-term perspective. The growth of saturation water vapour pressure impacts the essential changes in relative humidity and saturation deficit, mostly in the warmer half of the year. As achieving a saturation state is advantageous for precipitation and cloud formation, the saturation deficit strengthening will disrupt these processes. Therefore, the drought indices were used to verify the frequency of dry months and the intensity of atmospheric droughts. The Standardised Precipitation-Evapotranspiration Index (SPEI), thermal-precipitation index (also called Ped index) and Sielianinov index were calculated using the air temperature and precipitation from April to September from the Polish Institute of Meteorology and Water Management – National Research Institute database for 46 measurement stations in Poland in 1966-2020.
The results for drought indices vary, but in a wider perspective, they point to spatial differentiation in the possibilities of droughts occurring and their intensity. The highest frequency in atmospheric drought is detected using the Sielianinov index. On the other hand, the Ped index points to the increasing frequency of drought throughout the year. Using the SPEI, the frequency of drought is similar. The trends in the indices are also varied, but there are some relevant similarities. In all of Poland, there are drying trends in April, which is caused by the relevant increase in the air temperature then (Ustrnul et al. 2021). From June to August, a visible drying trend is observed in Central and Southern Poland. The previously mentioned observations formed the basis of the drought risk regionalisation, which consists of three regions: Northern, Central and Southern Poland. Northern Poland has 11 stations, where the frequency of dry months was lower, and the trends were weaker. In Central Poland (25 stations), there is a higher frequency in dry months, and there are prominent drying trends in April, June and August. So, the dry conditions are frequent, and these conditions are not very changeable. Stronger drying trends are observed in the region of Southern Poland (10 stations), but the frequency of dry months is lower than in Central Poland.
Regarding the results, Northern Poland is a region with quite stable conditions and a lower risk of droughts. Atmospheric drought is more frequent in Central Poland, which is unfavourable for the region with well-developed agriculture. In Southern Poland, the long-term changes in meteorological conditions lead to drying trends of the atmosphere. It might cause the limited supplies of water to the upper parts of rivers, disrupting the hydrological cycle, and then leading to soil and hydrological drought.
This research was funded by the National Science Center (NCN) (grant number 2023/51/B/ST10/01926)
How to cite: Krawczyk, E.: The humidity conditions and atmospheric drought risk in Poland in 1966-2020, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-218, https://doi.org/10.5194/ems2026-218, 2026.
Vapour pressure deficit (VPD) is a key indicator of atmospheric dryness and it plays an important role in plant water stress, stomatal behaviour, and crop productivity. In a warming climate, rising temperatures increase the atmospheric demand for moisture, leading to higher VPD. This means that plants lose water more easily, even if precipitation does not decrease. This process strengthens atmospheric drought, which remains barely represented in conventional drought assessments that mainly focus on precipitation and soil moisture. As a result, atmospheric drought becomes more pronounced, yet it is still not well captured in traditional drought assessments that mainly focus on precipitation deficits and soil moisture conditions.
This study investigates changes in VPD over Czechia using a 50-year daily datasets (1975–2024), combining station observations with widely used gridded datasets (E-OBS, ERA5, ERA5-Land). By intercomparing these datasets, we assess to what commonly used gridded datasets can reliably represent VPD variability and extremes relevant for impact studies.
Long-term changes in VPD are analysed across annual and growing-season scales, with a focus on drought-relevant characteristics such as extreme VPD events and their frequency. Trend analyses are completed by an assessment of the relative roles of temperature and humidity in driving observed changes, providing insight into the mechanisms behind increasing atmospheric demand.
The study also investigates the relationship between atmospheric dryness and soil moisture across different time scales, highlighting the interaction between atmospheric and soil drought. These results help to better understand drought processes and to assess whether commonly used datasets are suitable for drought monitoring and impact studies. Overall, this study improves our understanding of atmospheric drought in Czechia and supports the development of more comprehensive drought indicators under climate change.
How to cite: Kalmár, T. and Beranová, R.: Rising atmospheric drought in Central Europe: Long-term changes and dataset uncertainties in vapour pressure deficit over Czechia, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-335, https://doi.org/10.5194/ems2026-335, 2026.
Studying droughts as individual, evolving events rather than as a static phenomenon reveals that some droughts are highly dynamic, with shifting epicenters. To investigate the dynamics of the Earth’s largest droughts in recent decades, we used the newly developed catalog of global land drought events (GLDEs), based on estimates of root-zone soil moisture from the SoilClim model and the mesoscale Hydrologic Model (mHM). Using density-based 3D clustering, the catalog delineates 781 GLDEs during the 1980–2025 period and evaluates their severity using an index calculated from four spatiotemporal characteristics. We analyzed the dynamics of each GLDE by tracking individual drought movements and found that some GLDEs are among the longest-lasting extreme weather phenomena, persisting for multiple years, with epicenters moving thousands of kilometers over the course of their lifespan. We found that severe drought events often experience dynamic evolution and are more prone to spatial shifts. On the other hand, less severe droughts are more often static, but in some cases, they can experience a dynamic development too. Moreover, we focused on the events with the highest severity index. In particular, we examined exceptionally severe drought events in South America (starting in 2019) and central Africa (starting in 2020), both of which were still ongoing as of December 2025, as well as a highly dynamic drought event that began in Europe in 2018 and ended in Central Asia in 2024. Our results highlight the importance of investigating drought spatial dynamics and their potential drivers, including modes of climate variability and large-scale atmospheric circulation patterns.
How to cite: Řehoř, J., Trnka, M., Rakovec, O., Hanel, M., Balek, J., Brázdil, R., and Kumar, R.: Dynamics of the Earth’s largest drought events in 1980–2025, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-747, https://doi.org/10.5194/ems2026-747, 2026.
Based on the CN05.1 observation grid data and CMIP6 (Coupled Model Intercomparison Project Phase 6) model simulation data, this study comprehensively evaluated the simulation capability of CMIP6 models for scPDSI (selfcalibrating Palmer Drought Severity Index) of China and selected seven model ensembles with relatively good performance to project the change characteristics of scPDSI, runoff, and soil moisture in China in the 21st century. On this basis, this study analyzed the uncertainty in the CMIP6 future projection. The results show that the simulation capability of CMIP6 models for scPDSI over China still needs improvement and the simulation performance of the multimodel ensemble is better than most individual models, but deficiencies remain in temporal and amplitude trends. The temporal trend of scPDSI shows a slightly increasing trend for the SSP1-2.6 and SSP2-4.5 scenarios, with trend values of 0.03 (10 a)−1 and 0.01 (10 a)−1, respectively, and decreasing for the SSP5-8.5 scenario [−0.05 (10 a)−1]. Soil moisture shows decreasing trends over time: the trend values of the surface soil moisture and total soil moisture are −0.30% (10 a)−1 and −0.26% (10 a)−1 for the SSP5-8.5 scenario, respectively. Runoff shows increasing trends with time: the trend values of the surface runoff and total runoff are 1.76% (10 a)−1 and 3.13% (10 a)−1 for the SSP5-8.5 scenario, respectively. At the end of the 21st century, the annual scPDSI over China generally decreases under SSP5-8.5scenario, changes in soil moisture are generally “high in the North and low in the South”, the downtrend is most significant in the Qinghai–Xizang Plateau region, and the change range of surface soil moisture is bigger than total soil moisture. Runoff tends to rise in most areas, except in Northwest China and Qinghai–Xizang Plateau region, and its change range is bigger with the emission scenarios. The probability density curves of most variables in the 21st century flatten as the emission scenarios increase, so future changes will become more dramatic.
How to cite: Xu, Y. and Lai, Y.: Assessment of Simulation Capability and Projection of Drought over hina Based on CMIP6 Global Climate Models, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-784, https://doi.org/10.5194/ems2026-784, 2026.
The daytime (WD) and nighttime (WN) heat waves are defined as lasting at least three consecutive warm days and warm nights, respectively. These were calculated for late spring and summer (MJJA) from 1966 to 2024, when the 90th percentile, determined using a 15-day window, was exceeded. Temperature data was obtained from the Institute of Meteorology and Water Management National Research Institute (IMWM-NRI). The compound WD and WN were identified when these events overlapped for at least one day. During the study period, the number of WD and WN events increased. In the case of the former, the most significant increase started in the middle of the 90s, and in the latter, in the early 21st century. A notably higher trend is observed for the compound (of 1.2 events per decade) compared to individual events (0.7 events per decade for WN and 0.3 events per decade for WD). Until 2007, individual WD events dominated, especially from 1992 to 2006. Since then, compound events have become more prevalent, mainly due to a significant increase in the number of accompanying WN.
There are important differences in the background of compound and individual WD&WN event formation. To characterise these, we used the ERA5 reanalysis (geopotential height at 850 hPa, latent and sensible heat fluxes, specific humidity, mean surface direct short-wave radiation and mean top net long-wave radiation fluxes, total cloud cover, maximum and minimum temperature), for two terms, 03UTC and 15UTC, which correspond to WD and WN, respectively. In the afternoon, the compound WD&WN events occurred when the high-pressure system was located much closer to the northeastern border, associated with much higher direct short-wave and top net long-wave radiation flux and less cloud cover than during individual events. These conditions lead to considerably higher temperatures and lower latent heat flux anomalies. The specific humidity is above normal but still lower than in the case of individual WD events. At night, for individual events, the high-pressure center occupied eastern Poland and is associated with much lower cloud cover and higher top-of-atmosphere long-wave radiation flux. The minimum temperature and specific humidity increase, but not to the extent seen during compound heat waves. There are no notable differences between sensible and latent heat fluxes, both of which are slightly above average.
This study is funded by the National Science Center (NCN) (grant number 2023/51/B/ST10/01926).
How to cite: Jędruszkiewicz, J. and Wibig, J.: Daytime and Nighttime Heat Waves in Poland — Compound and Individual Events, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-105, https://doi.org/10.5194/ems2026-105, 2026.
The purpose of the present study is to quantify the compound events and persistent events (e.g., heat waves) from probability perspectives. Notably, the compound events are quantified by a joint frequency distribution of the two variables that are used to identify those compound events. For example, the tendency of having simultaneously warm and dry (i.e., less rains) states on the same day can be identified in the joint distribution of temperature and precipitation. If such a tendency exists, it is identified as a local peak in the joint distribution, located at positive temperature and negative precipitation anomalies. In this manner, we objectively demonstrate the tendency of compound warm-dry events over Poland in the summer season, which has been empirically known, but not clearly quantified. In winter the opposite is true and the precipitation distribution for high positive anomalies is clearly skewed in the direction of positive anomalies of temperature confirming higher precipitation on warmer days due to the atmosphere's greater capacity for water vapor.
Joint distributions are not necessarily between two variables of the same day. A lag can be introduced, and in this manner, it can be demonstrated that the tendency of warm days over Poland are frequently followed by high precipitation few days after. A simple lag correlation suggests that such an event is most likely to happen with 5-day lag. However, in this case, there is no shift of the peak to a positive side of precipitation anomaly, but the tendency is merely identified by a long tail towards the positive precipitation anomaly in joint distribution.
The persistent events are quantified by a conditional probability: for example, a persistence of a warm state can be quantified by the conditional probability of having the same warm state a day after when this warm event has happened.
For these demonstrations, daily mean temperatures and precipitation (1966- 2024) from 48 meteorological stations obtained from the Institute of Meteorology and Water Management, National Research Institute are used.
This research is funded by the National Science Center, Poland (NCN) (grant number 2023/51/B/ST10/01926)
How to cite: Yano, J.-I., Jędruszkiewicz, J., and Wibig, J.: Compound Events over Poland : Probabilistic Perspective, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-26, https://doi.org/10.5194/ems2026-26, 2026.
The expected future warming in Europe carries major implications for climate and weather extremes, such as more frequent, prolonged, and severe events. The impacts of extreme weather events are often exacerbated, when these events do not occur in isolation, but when two or more extreme events occurr simultaneously or successively. They are called compund extreme events. In the recent decades, an ongoing increase in maximum temperature during summer has been observed in Poland, especially in the central-southern and southeastern areas. This raises the vulnerability of these regions not only to heat waves and drought but also to floods. The potential effect of compound heat waves and extreme rainfall events may be more serious than the effects of these events occurring separately. This research is the first attempt in Poland to investigate whether the presence of a heat wave increases the likelihood of extreme rainfall events, if so, by how much, and whether this changes with warming. For this purpose, we used daily maximum temperature values and 6 h precipitation datasets from 44 meteorological stations in Poland for the 1966–2024 period. Heat waves were identified and the cases of precipitation in a few days just after heat wave were analysed. It was proven that compound heat wave and extreme rainfall events occurred in Poland with spatially differentiated frequency. They appeared the least frequently on the coast and the most frequently in southwestern, southeastern, and northeastern Poland. The extreme rainfall occurred most often between noon and midnight on the last heat wave day. During these hours, the likelihood of extreme rainfall is, on average, 3.5 times higher than that expected according to climatology norms. With warming, the frequency of days with these compound events increases at the rate of 1.22 days per decade, and the frequency of compound events increases at a rate of 3.75 events per decade. Although a detailed analysis of the mechanisms responsible for such events is planned for further research, the preliminary study revealed that in most cases, the approach of a cold front with a mesoscale thundercloud system was responsible for heat wave termination with extreme rainfall. Since we cannot prevent the growing number of heat waves or heavy precipitation events that terminate the heat wave events in Poland, the adaptation strategy needs to be implemented to meet the sustainable development goals regarding climate actions. This refers primarily to urban planning, agriculture (agroecosystems), social health, and well-being.
This research was funded by the National Science Center (NCN) (grant number 2023/51/B/ST10/01926).
How to cite: Wibig, J. and Jędruszkiewicz, J.: Has Climate Change Affected the Occurrence of Compound Heat Wave and Heavy Rainfall Events in Poland?, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-275, https://doi.org/10.5194/ems2026-275, 2026.
Compound hot and dry events represent a major class of climate extremes with substantial impacts on ecosystems, agriculture, and water resources. Their occurrence is driven not only by individual extremes in temperature and precipitation, but also by the structural dependence between these variables. Traditional approaches often rely on univariate statistics or simple threshold analyses, which may fail to capture the joint behavior of temperature and precipitation during extreme events. In this study, we applied copula-based methods to quantify the joint probability of compound hot and dry events across multiple meteorological stations in Poland.
We analyzed long-term observational records (1966-2025) of temperature and precipitation during the warm season. Hot and dry conditions were defined using percentile-based thresholds derived from the full observational period to ensure consistent comparison across time. The dependence between temperature and precipitation was modeled using bivariate copulas, with particular attention given to tail behavior relevant for extreme conditions. Model selection was performed using information criteria and goodness-of-fit statistics, and the selected copulas were subsequently used to estimate joint probabilities and return periods of compound events. To assess potential temporal changes, the dataset was divided into two sub-periods: 1966-1995 and 1996-2025. The comparison of joint probabilities between these periods provides insight into possible shifts in the frequency of compound hot and dry events. Additionally, spatial variability across stations was examined to identify regional differences in both dependence structure and event likelihood.
Preliminary results indicate clear spatial variability in the joint probability of compound hot and dry events across Poland, with some regions exhibiting consistently higher likelihoods than others. The dependence between temperature and precipitation is predominantly negative, reflecting the tendency for high-temperature conditions to co-occur with reduced precipitation. In most locations, the dependence structure suggests stronger association in the upper tail, highlighting an increased likelihood of concurrent extreme conditions rather than independent occurrences of hot and dry events. An analysis of the two sub-periods indicates that the joint probability of hot and dry periods occurring simultaneously has increased over the last thirty years.
Acknowledgements: Funding for this research was provided by the National Science Centre, Poland under project no. 2023/51/B/ST10/01926.
How to cite: Górowski, J., Jędruszkiewicz, J., and Wibig, J.: Joint probability of compound hot and dry events using the concepts of copulas, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-288, https://doi.org/10.5194/ems2026-288, 2026.
Future climate projections suitable for local impact and adaptation studies require the use of regional climate models (RCMs) to downscale global climate models (GCMs). In the process of preparing the Eta RCM to produce projections using the CMIP6 GCMs, the Eta model has been integrated to produce a climate run. The objective of this work is to evaluate the Eta RCM simulation of the South American climate driven by ERA5 reanalysis. The model is set up at 20-km horizontal resolution with 38 vertical layers, covering the entire South American continent and parts of the adjacent oceans. The 30-year integration starts at 0000 UTC on January 1st, 1984, and ends on the same date in 2015. The climatology is assessed in four trimesters corresponding to the austral seasons: DJF (summer), MAM (autumn), JJA (winter), and SON (spring). The maximum precipitation is simulated in DJF over the Northern South America (NSA), extending into the South America Monsoon Region (SAM) and Southeast South America (SES), corresponding to the position of the South Atlantic Convergence Zone (SACZ). The minimum precipitation (< 1mm/day) is correctly simulated in JJA, mainly over SAM. Although the major features of the precipitation seasonal variation in the continent are reproduced by the simulation, there is a large overestimation over the Northwestern South America (NWS), a lack of precipitation band in the Intertropical Convergence Zone near the northern coast over the equatorial Atlantic Ocean, and an underestimation over SAM and SES. The seasonal variation of the 2-m temperature is well simulated over the continent; however, there is an overestimation in the region around Paraguay, Bolivia, northern Argentina, and western Brazil, and an underestimation in the eastern part of Brazil and southern Argentina. Climate extreme indices are calculated on a seasonal basis. The model correctly simulates the mean patterns of consecutive dry days (CDD), heavy precipitation days (R30mm), and total precipitation from very wet days (R95p). The CDD and R30mm trends are generally well simulated across seasons, but the positive R95p trend observed is not captured by the simulations. Similarly, the model correctly simulates the mean patterns of temperature extremes, including the warmest day (TXx) and warmest night (TNx). While the simulation shows an increasing trend in TXx across much of SAM in all seasons, the observations show greater spatial and seasonal variability in areas with a positive trend in TXx. The warm spell duration index (WSDI) shows a positive trend across the entire continent in both observations and simulations. The evaluation of extreme drought and rainy years in three major river basins will be presented.
How to cite: Chou, S. C., Lyra, A. D. A., Medeiros, G. S., Gomes, J. L., Chagas, D. J., Rodrigues, D. C., Campos, D. D. A., Tavares, P. D. S., Dereczynski, C. P., Tavares, M. G., Hao, H., and Jiang, J.: Eta Model simulation of the South American Climate, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-141, https://doi.org/10.5194/ems2026-141, 2026.
The Black Sea Basin (BSB) is a climate change hotspot where complex orography and air–sea interactions determine regional climate. Since these intricate dynamics are not fully represented in coarse-resolution models, we used the WRF model to perform ERA5-driven, 3 km convection-permitting climate simulations for the 2000–2025 period over the BSB. In the study, the model's performance is assessed by comparing simulation outputs with an ensemble of gridded observations and reanalyses, as well as daily station data from the GHCN. To this end, we utilized ERA5-Land and TerraClimate datasets to evaluate temperature patterns, while ERA5-Land, CHIRPS, and MSWEP were employed to analyze precipitation regimes. Additionally, we used ESACCI and CCMP satellite-based gridded observations for soil moisture and marine wind evaluations. The results indicate that the WRF model successfully captures the monthly cycles of maximum and minimum temperatures, with a warm bias in the range of 1–3°C. We found that a significant portion of the temperature bias stems from differences in model and station elevations. Applying a lapse-rate correction substantially reduces these discrepancies for both ERA5 and WRF outputs. Specifically, we identified a warm bias of 2°C in minimum temperatures at stations between 1000 and 2000 m in winter, which can be linked to a positive soil moisture bias of about 0.15 m3/m3. This bias is attributed to the model's tendency to produce precipitation amounts 2–3 mm/day higher than observations in winter in high-altitude regions, driven by enhanced orographic forcing at the convection-permitting scale. Notably, the results demonstrate the added value of WRF simulations over ERA5 in simulating extreme precipitation events and capturing the diurnal cycle of precipitation. The model successfully reproduces daily extreme precipitation thresholds exceeding 100 mm, specifically at the 99th and 99.9th percentiles, and peak afternoon precipitation when compared to observations. Furthermore, the model exhibits high skill in reproducing both the magnitude and direction of offshore wind over Black Sea, the Marmara Sea, and the northern Aegean Sea with a mean bias of 0.5–1 m/s. These results validate the performance of the high-resolution WRF configuration, which explicitly resolves fine-scale processes, positioning it as a reliable atmospheric driver for future studies focusing on climate extremes and coupled atmosphere-ocean modeling in the BSB.
Acknowledgment: The numerical calculations reported in this paper were fully performed using the EuroHPC Joint Undertaking (EuroHPC JU) supercomputer MareNostrum 5, hosted by the Barcelona Supercomputing Center (BSC). Access to MareNostrum 5 was provided through a national access call coordinated by the Scientific and Technological Research Council of Turkey (TÜBİTAK). We gratefully acknowledge BSC, TÜBİTAK, and the EuroHPC JU for providing access to these resources and supporting this research.
How to cite: Kelebek, M. B. and Önol, B.: Evaluation of 25-Year ERA5-driven Convection-permitting Climate Simulations over the Black Sea Basin, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-400, https://doi.org/10.5194/ems2026-400, 2026.
Climate classifications are useful tools for assessing climate variability and change, as they aggregate multiple variables into discrete climate types representing regions with homogeneous characteristics, often corresponding to vegetation zones or eco-regions. The Köppen–Trewartha classification (KTC) defines climate regimes using temperature- and precipitation-based thresholds, synthesising conditions into discrete and comparable units for analysing their spatial distribution and temporal evolution. In this study, we assess how well the new generation of EURO-CORDEX regional climate simulations driven by ERA5 reanalysis within the CMIP6 framework reproduces the observed distribution of KTC climate types across Europe.
As part of the coordinated EURO-CORDEX evaluation effort, individual model simulations are compared against observational reference data representing observed climate conditions and their evolution. This enables an assessment of how well each simulation reproduces the distribution of major European climate types and their boundaries. We further investigate how these patterns evolve over time, focusing on shifts in climate regimes and their spatial structure. The analysis is complemented by time series diagnostics of climate type occurrence and spatial extent. Particular attention is given to systematic biases in the extent and boundaries of selected climate types, which provide a physically meaningful indication of model performance.
The analysis includes the full set of available ERA5-driven EURO-CORDEX CMIP6 simulations and contributes to the ongoing evaluation of the new model generation, supporting the interpretation of regional climate change signals and their emergence from natural variability. The KTC framework also enables assessment of how differences between simulations influence the representation of variability and conditions associated with climate extremes under different model configurations.
How to cite: Holtanova, E., Szabó, A. I., and Belda, M.: Evaluating Climate Regimes and Their Temporal Evolution in ERA5-Driven EURO-CORDEX CMIP6 Simulations , EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-512, https://doi.org/10.5194/ems2026-512, 2026.
Croatia’s location, complex coastal orography and strong thermal contrasts with the Adriatic Sea in autumn make this region particularly prone to extreme mesoscale phenomena, including downslope windstorms, thunderstorms, mesoscale convective systems, orographic precipitation and waterspouts. Numerous studies have shown the benefits of convection‑permitting climate models for simulating such extreme events, especially heavy precipitation events. The HARMONIE‑Climate (HCLIM) regional climate model, a state‑of‑the‑art convection‑permitting model, has proven applicable across many regions, providing satisfactory evaluation results and realistically reproducing sub‑daily precipitation statistics and mesoscale precipitation structures. This study aims to assess whether HCLIM can realistically simulate the climatology over Croatia, with a particular focus on precipitation and precipitation extremes.
HCLIM is run for a ten-year period, from 2010 to 2020, with a one-year spin-up time and two nested domains with horizontal grid spacings of 12 km and 3 km. The 12 km simulations are driven at the lateral boundaries by the ERA5 reanalysis. We utilise the flexibility of HCLIM by analysing the performance of two different model configurations. First, we run the 12 km simulations using both the ALADIN physics (hydrostatic dynamical core and parametrised deep convection) and the AROME physics (non-hydrostatic dynamical core without deep convection parameterisation). Second, these two simulations provide the input for two corresponding AROME simulations at 3 km. As observational references, we use E-OBS, a daily gridded dataset at 0.1° horizontal resolution, the sub-daily regional reanalysis CERRA at 5.5 km resolution, and hourly precipitation observations from approximately 40 automatic weather stations in Croatia. We evaluate daily precipitation, temperature, wind, relative humidity and mean sea level pressure, and, given our focus on precipitation, several heavy and extreme precipitation indices, with particular emphasis on hourly precipitation over several specific subregions. Generally, HCLIM simulations realistically reproduce the spatial patterns of precipitation across Croatia. The finer-scale runs at 3 km outperform the coarser 12 km runs by exhibiting smaller biases and better capturing precipitation intensities, frequencies and mesoscale structures.
How to cite: Ivušić, S., Ivasić, S., Jureša, P., Srnec, L., Belušić, D., Keresturi, E., and Horvath, K.: Evaluation of HCLIM convection-permitting climate simulations over Croatia, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-584, https://doi.org/10.5194/ems2026-584, 2026.
Understanding how changes in regional climate scale with global warming is essential for national climate assessments and adaptation planning. Here, we analyse projected changes in Estonia’s climate using a Global Warming Level framework and a CMIP6 multi-model ensemble. The approach expresses regional climate responses as functions of global warming, rather than functions of scenario-specific time horizons.
We analyse annual and seasonal temperature, precipitation, and wind-related indicators, including indicators of extremes, and express their responses as linear scaling relationships per one degree of global warming. Estonia shows clear regional amplification of global warming, with annual mean temperature increasing by about 1.5 °C per 1 °C of global warming. The amplification is strongest in winter (+1.9 °C/°C) and is weaker in summer (+1.3 °C/°C). Cold extremes respond even more strongly: the annual coldest daily minimum temperature rises by about 3.6 °C/°C, indicating a substantial reduction in cold-season severity. Annual precipitation increases by about 31 mm (4.6%) per 1 °C of global warming, and heavy precipitation intensifies across most models. In contrast, changes in summer precipitation show large inter-model spread, while projected wind changes are generally weak and inconsistent.
A central element of the scaling analysis is the assessment of robustness. Trends are calculated separately for each model and then summarised using the ensemble median together with the 10th and 90th empirical percentiles (P10–P90), representing the central 80% model range. A change is classified as robust when the full P10–P90 interval remains on the same side of zero as the median trend, indicating that at least 90% of models agree on the sign of the change. If the P10–P90 interval crosses zero, the signal is considered non-robust because of substantial inter-model disagreement.
The results highlight a clear contrast between changes dominated by thermodynamic controls and those more strongly influenced by changes in atmospheric circulation. Changes in temperature-related indicators and extreme precipitation show high inter-model agreement and robust scaling with global warming, whereas summer precipitation and wind-related changes remain much more uncertain. This indicates that uncertainties are smaller for thermodynamically driven changes than for such changes, where the future behaviour depends more strongly on circulation responses to global warming and internal variability.
How to cite: Jakobson, E., Jakobson, L., Keernik, H., Luhamaa, A., Post, P., Aun, M., and Toll, V.: Scalability of projected climate change in Estonia in relation to global warming, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-722, https://doi.org/10.5194/ems2026-722, 2026.
Long-term homogeneous records of Earth observations are essential for monitoring climate change, its variability, and the frequency and intensity of extremes. EUMETSAT and it's Satellite Application Facilities (SAFs) generate consistent Climate Data Records (CDRs) and Interim Climate Data Records (ICDRs) for a wide range of geophysical variables based on satellite observations. From these data records, climate anomalies and normals are routinely derived to place past and current climate conditions into the robust historical context of WMO defined climate normals.
While the computation of climate anomalies and normals may appear straightforward, a scientifically rigorous implementation must carefully consider potential issues in the observational records such as spatiotemporal gaps or varying sampling frequencies due to the use of different instruments over time. To support the assessments of climate variability and extremes, EUMETSAT is developing a web-based platform providing maps and timeseries of climate anomalies and normals called the Climate Anomalies and Normals (CAN) Service. It is based on precomputed climate anomalies and normals from existing CDRs and interim continuations (ICDRs) of them to ensure timely delivery of climate information. The CAN-Service provides user-friendly access to maps and the underlying data for further analysis, while the full (I)CDRs are available via the EUMETSAT Data Store. By this it provides strong support to national climate services and the public, including media.
The CAN-Service enables users to interpret current conditions in the context of historical variability, supporting the quantification of extremes and monitoring changes. The presentation will address the development status and methodological approach of the CAN-Service and will discuss examples from the climate data records contained. It will also address future evolution of EUMETSAT’s CAN-Service.
How to cite: Traeger-Chatterjee, C., Roebeling, R., Kaspar, F., Schulz, J., and Doutriaux-Boucher, M.: EUMETSAT’s Climate Anomaly and Normals Service: a tool to support Climate Analysis using Satellite based Climate Data Records , EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-412, https://doi.org/10.5194/ems2026-412, 2026.
Taking the three typical river basins of Liaohe, Huaihe and Pearl River as the study areas, based on the precipitation observation data of national meteorological stations from 1961 to 2024, and using hydrological regionalization of the basins as the basic unit, the Standardized Precipitation Index (SPI) was adopted to construct an annual waterlogging intensity index of the basin considering monthly precipitation anomalies. On this basis, waterlogging grades were classified. Combined with the Precipitation Concentration Index (PCI) characterizing the temporal distribution of precipitation, the spatiotemporal characteristics of waterlogging and the trend of hazard risk in the three basins were analyzed. The results show that: (1) The annual mean waterlogging intensity of the Pearl River is higher than that of the Huaihe River and Liaohe River, making it more prone to waterlogging.However, the latter two basins experience more frequent occurrences of severe and extreme waterlogging. The spatial differences in waterlogging intensity index and severe/extreme waterlogging frequency among hydrological regions are small for the Liaohe River, but significant for the Huaihe River and Pearl River. (2)The waterlogging intensity of the three basins all shows significant interannual oscillation and periodic differences during the historical period. The Liaohe and Huaihe Rivers exhibit an increasing trend, while the Pearl River displays a decreasing trend. However, there is no statistically significant step changes or abrupt change points were detected. Since 2020, the waterlogging intensity of the Liaohe and Huaihe Rivers has reached a record high, characterized by a shift toward synchronized, high-frequency waterlogging extreme events. (3)The coverage range of severe and extreme waterlogging in the Liao River Basin exhibits the most pronounced interannual variability, with the highest frequency of years exceeding 70% of the total basin area, followed by the Huai River Basin. Both basins demonstrate distinct decadal clustering characteristics in basin-wide severe and extreme waterlogging events, entering a new high-incidence period after 2020. The Pearl River Basin shows the lowest frequency of basin-wide severe and extreme waterlogging occurrences.（4）A significant upward trend in summer precipitation concentration characterizes both the Liao River and Huai River basins. The concentration degree of summer precipitation in the Liaohe and Huaihe River basins exhibits a significant upward trend. When combined with the enhanced intensity of waterlogging, increased frequency and expanded coverage of severe/extreme waterlogging since 2020, the disaster-inducing risk of waterlogging has been notably elevated. This waterlogging assessment method, integrated with the analysis of precipitation concentration index, can effectively captures the interannual variation patterns and disaster risks of basin-scale waterlogging, offering important reference value for basin-scale climate risk management and disaster prevention and mitigation.
How to cite: Hao, Y., Li, J., Wang, H., Wang, K., Yin, H., and Lu, J.: Waterlogging Assessment and Characteristic Analysis of Three Typical River Basins in China during 1961–2024, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-103, https://doi.org/10.5194/ems2026-103, 2026.
West Africa is a region highly vulnerable to global change, where hydro-climatic extremes become increasingly frequent and intense.
While previous floods studies have been limited to few river basins with scattered observational data, the availability of a recent regional hydrometric in-situ database offers the opportunity for studying hydrological extremes at the west African scale. This study investigates trends in hydrological extremes using annual maximum streamflow (AMAX) over 80 West African catchments from 1950 to 2018.
A rigorous flood frequency framework based on Extreme Value Theory is used for trends detection in return levels, comparing a wide variety of non stationary models. In order to synthesize the regional patterns, an objective typology of flood evolution trajectories is developed using k-means clustering. The results reveal widespread non-stationarity in flood extremes, affecting 85\% of the catchments, with contrasted trajectories of extremes. The clustering reveals 6 main types of trends in hydrological extremes.
While most catchments exhibit a general decline in flood magnitude until the major droughts affecting the region (1970s-1990s), recent decades show divergent evolutions, ranging from stabilization to moderate or strong increase. At the regional scale, a north–south gradient emerges. The Sahelian catchments display trajectories ranging from persistent decreases to weak flood intensification, whereas the Sudano-Guinean basins are predominantly characterized by decreasing trends, with additional nuances related to the shape and magnitude of these declines.
Overall, these results challenge the assumption of an homogeneous signal of hydrological intensification over West Africa and provide a more nuanced depiction of typical Sahelian and Sudano-Guinean flood evolution patterns. Furthermore the contrasted trends identified are only weakly explained by catchment physical or hydrological characteristics, underscoring the complexity of non-stationary hydrological dynamics in the region.
By documenting the diversity of long-term flood trajectories over 1950–2018, this study refines the regional narrative of hydrological changes in West Africa and has important implications for anticipating future hydro-climatic extremes and for supporting the strengthening of resilience of ecosystems and societies.
How to cite: Sorini, G., Blanchet, J., Panthou, G., Vischel, T., and Tramblay, Y.: Typology of flood trends across West Africa, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-332, https://doi.org/10.5194/ems2026-332, 2026.
This study uses the regime shift index to detect the interdecadal shift of the summertime intraseasonal oscillation (ISO) in the East Asian monsoon region during July-September from 1979 to 2021. A regime shift index was found to specify three distinct epochs: 1979-1993, 1994-2004, and 2005-2021. The middle epoch yields a westward extension of the subtropical anticyclonic circulation and maximal intensity in the westerly phase of the northward-propagating ISO, and his is apparently different from other epochs. These circulation anomalies intensify southeasterly winds south of Japan, which block tropical cyclones (TCs) from east of this strong wind zone. The circulation anomalies therefore result in more contracented TC tracks between Taiwan and Japan as well as increased TC frequency and duration. The findings yield a concentration of TCs can lead to more rainfall in the westerly phase of the northward propagating ISO or the middle epoch. The present work shows that ISO variability itself, especially the connection between the subtropical anticyclone and ISO cyclonic anomalies, directly influence TC genesis, clustering, and intensity. The resulting changes in TC characteristics, particularly in frequency and intensity, could have significant implications for regional disaster preparedness and climate adaptation strategies. This highlights the critical need to consider the interdecadal ISO variability in long-term climate projections and TC prediction models, ensuring more accurate forecasts and informed decision-making in the face of evolving climate patterns. As we know that global warming is taking place, the present climate pattern change such as decadal variability of the ISO can also be part of the results of the climate change under global warming. This study could be a hint of representing changes in the future. In other words, the climate pattern change in the future might also undergo the decadal change as in the present study. These insights can be useful for improving TC rainfall prediction under changing climate patterns.
How to cite: Ko, K.-C. and Chen, J.-Y.: Changes of the Subtropical Intraseasonal Oscillations and the associated Tropical Cyclones on the interdecadal time scales in East Asia, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-13, https://doi.org/10.5194/ems2026-13, 2026.
Off‑season hot extremes have emerged as a distinct and insufficiently studied component of European climate variability. Recent unprecedented episodes, such as the major April 2023 pre‑season heat wave in Spain and the early‑April 2024 hot spell in Central Europe with temperatures exceeding 30 °C nearly two months before the conventional summer season, highlight their growing relevance. While summer heat waves are well documented, systematic assessments of pre‑ and post‑season hot events remain scarce. We introduce a new framework for identifying these episodes (days) across Europe for 1961–2024, based on an off-season heat threshold that incorporates local annual maximum temperature, temperature amplitude, and the sharpness of the seasonal cycle. The framework also provides an objective definition of transitional seasons, including their timing and length, enabling consistent detection of hot extremes outside the core summer period. Using ECA&D station data, ERA5 reanalysis, and the E‑OBS dataset, we map the climatology of off‑season hot events by characterising their frequency and intensity. We also quantify regional differences in the off‑season heat‑threshold values and in the timing and length of transitional seasons. Last but not least, we investigate long‑term changes in the frequency and intensity of such events.
How to cite: Krauskopf, T. and Lhotka, O.: Emerging off-season heat events in Europe, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-69, https://doi.org/10.5194/ems2026-69, 2026.
How to cite: Olmo, M., Duzenli, E., Soret, A., and Doblas-Reyes, F.: AI-based downscaling in the Mediterranean for improved understanding of observed and projected climate change, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-80, https://doi.org/10.5194/ems2026-80, 2026.
Every year, the UK is impacted by major storms brought by the jet stream and associated Atlantic storm track. Exceptionally severe storms are well remembered by the public, including the ‘Burns’ Day Storm’ of January 1990, the ‘Boxing Day Storm’ of December 1998, and the ‘Great Storm’ of October 1987, all of which had impacts from extreme wind gusts. More recently, the UK experienced an exceptionally long period of stormy weather over the winter of 2013/2014 that has been described as the stormiest season in the UK since 1871.
Since 2015, impactful storms have been named in the UK by a storm naming group made up of the UK Met Office, the Dutch weather service KNMI, and the Irish weather service Met Éireann. The decision to name a storm is based on its forecast impact, not meteorological conditions, to allow for clear messaging around public warnings. This contributes to the complexity in analysing storms, as there are no definitive criteria for classifying a weather event as a storm. Additionally, trends in the frequency of storms in the UK can not be robustly examined because the record of named storms does not extend far enough back in time.
Climatological analysis and comparison of storms is complex due to the number of variables involved: mean wind speed, maximum wind gust, wind direction, storm duration, spatial extent and storm track, all of which could have a bearing on how one storm could be judged to be “worse” than another.
This work aims to address that by examining the historical record with machine learning techniques. I explore the use of supervised classification models for identifying storms in the historical record pre-2015 based on station observation data and using the named storms as a guide. The model uses patterns in daily windspeed, rainfall, and MSLP across the UK to probabilistically classify each day in the test period as having a storm or not. This expands the catalogue of known storm dates in the UK, allowing further analysis of how storm frequency and severity have changed through time.
How to cite: Carlisle, E.: Identification of impactful storms in the UK using machine learning, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-213, https://doi.org/10.5194/ems2026-213, 2026.
Since 2021, Slovakia has experienced several precipitation periods characterized by markedly divergent totals. Atmospheric precipitation exhibits substantial temporal and spatial variability, yet a novel pattern has emerged: prolonged dry spells (spanning several months or up to a year) alternating with extraordinary to extreme precipitation surpluses of much shorter duration.
This contribution presents longterm dry spells with sewere precipitation deficit folowed up by the heavy or extreme precipitation episodes overcoming historical maximum on records. The spatial distribution of precipitation from selected periods are visualized as gridded fields/layers.
At Bratislava-Letisko station, this phenomenon was recorded at the end of winter and the beginning of spring in the years 2021, 2022, and 2023. The 12-month period from September 2021 to August 2022 represented one phase of this disproportionately prolonged interval characterized by a precipitation deficit, especially in the lowland areas of Slovakia. In Nitra, only 463 mm of precipitation was recorded during the same period (September 2021–August 2022).
In contrast, an example of a pronounced precipitation surplus was observed in Nitra over a similarly long period from December 2022 to December 2023, when a total of 855 mm of precipitation was recorded. The alternation between precipitation-rich and precipitation-deficient periods has become particularly evident in recent years. For instance, following a precipitation-abundant June (231 mm recorded in Nitra) and September 2024 (132 mm recorded in Nitra), a subsequent 9-month period from October 2024 to June 2025 was characterized by a precipitation deficit, during which only 281 mm of precipitation was recorded in Nitra.
In September 2024, much of Central Europe experienced above-average precipitation. In mid-September, Storm Boris brought heavy rainfall, flooding, and significant damage to Central and Eastern Europe. The event is placed in a historical context by comparing its maximum, multi-day, and cumulative precipitation totals recorded between September 11 and September 16, 2024, with previous extreme precipitation occurrences. The results indicate that the highest-ever recorded 2-day (267.3 mm in Borinka) and 5-day (379.8 mm in Pernek) precipitation totals in Slovakia occurred during this event. More than 20% of stations with available data recorded new maximum 2-day or 5-day precipitation totals, with multi-day totals surpassing the 100-year and 200-year quantiles.
How to cite: Garaj, M., Holec, J., Faško, P., Markovič, L., and Kajaba, P.: Remarkable sequence of exceptionally wet and dry situations in Slovakia during the 3rd decade of the 21st Century, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-236, https://doi.org/10.5194/ems2026-236, 2026.
In this study, the impacts of natural and anthropogenic forcings on historical changes and future projections in global-land surface air temperature (GLSAT) are investigated using climate model simulations from the Detection and Attribution Model Intercomparison Project (DAMIP) in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The results show that the increase in GLSAT can be largely attributed to human activities. The effect of anthropogenic forcing (ANT) can be robustly detected and separated from the response to the natural external forcing (NAT) since about 1970–1990s. Well-mixed greenhouse gases is the primary contributor to anthropogenic climate warming. ANT contributes a robust warming trend of 0.1–0.2 °C per decade for global landmass during 1951–2020, along with a stronger warming in 2011–2020 (relative to 1901–1930) of 1.0–1.6 °C. These attributable warming largely encompass the observed warming trend of ~0.18 °C per decade in 1951–2012 and the observed warming of 1.59 °C in 2011–2020 (relative to 1850–1900) for global landmass reported in IPCC AR5 and AR6, respectively. The observed warming changes since 1951 or recent decade are primarily attributed to the GHG-forcing. The anthropogenic warming is projected to increase by 3–6 °C for most of global landmass under the SSP2-4.5 scenario, especially in the high latitudes of the Northern Hemisphere by the late of 21st century, along with an increase in the mean and widespread flattening of the probability distribution functions (PDFs) of temperature anomalies. In contrast a cooling effect of ~0.7°C in 2011–2020, the anthropogenic aerosols (AA) forcing is projected to cool the global land by around 0.6°C by the late of the 21st century.
How to cite: Zhao, T.: Impacts of natural and anthropogenic forcings on historical and future changes in global-land surface air temperature in CMIP6–DAMIP simulations, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-259, https://doi.org/10.5194/ems2026-259, 2026.
Climate projections for regions with complex topography, such as Slovenia, typically rely on high-resolution Regional Climate Models (RCMs) such as the EURO-CORDEX ensemble. However, the added value of dynamical downscaling in representing recent historical trends remains a subject of ongoing evaluation. We compare the performance of various climate model ensembles – CMIP5 and CMIP6 Global Climate Models (GCMs), CMIP5 EURO-CORDEX RCMs and bias-corrected subselection of CMIP5 EURO-CORDEX RCMs – against gridded observations over Slovenia.
The analysis focuses on ten-year moving average of temperature and precipitation anomalies since 1950 (relative to the 1981–2020 baseline) and linear trend estimates for the period 1981–2025. Our results indicate a significant discrepancy: the EURO-CORDEX RCMs underestimate the accelerated warming observed in recent decades while GCMs align more closely with observed trends. Almost all RCM ensemble members fall outside the two standard error range of the observed trend at 0.47–0.71 °C per decade. In contrast, GCM ensembles reflect the magnitude of recent observed temperature increase over Slovenia more accurately, especially the latest CMIP6 generation with approximately half of the ensemble members falling within two standard error range of the observed trend, while for CMIP5 this ratio is approximately one fifth (depending on the underlying emission scenario). Due to high interannual precipitation variability, resulting in less pronounced trends in precipitation, differences between the RCM and GCM ensembles in capturing observed precipitation trends are less significant. Some differences appear on a seasonal scale for spring and summer, where GCMs slightly outperform RCMs.
Our findings suggest that while RCMs provide necessary spatial detail, they may fail to capture certain large-scale drivers of recent rapid warming. Many RCMs in the EURO-CORDEX ensemble use constant aerosol distributions or simplified versions that do not decrease over time, despite the observed decrease in aerosol pollution in recent decades. In addition, many CMIP6 models are set at higher equilibrium climate sensitivity, resulting in more warming than CMIP5 generation and associated EURO-CORDEX models driven by respective boundary conditions. The results highlight the importance of model selection, consideration of model physics and potential limitations of relying solely on RCM ensembles for assessing climate change impacts in the sub-Alpine and sub-Mediterranean transition zones.
How to cite: Vlahović, Ž.: Evaluating the performance of CMIP5, CMIP6 and EURO-CORDEX ensembles in capturing recent climate trends in Slovenia, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-270, https://doi.org/10.5194/ems2026-270, 2026.
Long-term changes in precipitation occurrence and short-term variability influence drought and flood risk and therefore represent an important aspect of climate change assessment. In this study, we analyse trends in wet-day probability and precipitation persistence across Europe and evaluate their consistency across three widely used datasets: station observations (ECA&D), gridded observations (E-OBS), and the ERA5 reanalysis. Wet-day probability is defined as the seasonal probability of daily precipitation exceeding 1 mm. Short-term variability is characterized by (i) transition probabilities between dry and wet days (dry-to-wet and wet-to-wet), assuming a two-state first-order Markov process, and (ii) persistence of precipitation quantified as the lag-1 autocorrelation of this process.
The analysis covers the period 1961–2020 and is conducted separately for seasons, with particular focus on winter and summer. Trends are estimated using non-parametric (Mann-Kendall test, Kendall statistic). To interpret spatial patterns and assess potential drivers, precipitation characteristics are related to atmospheric circulation types derived from sea-level pressure using the Jenkinson–Collison classification, which describes daily flow direction, strength, and vorticity. Circulation types are further categorized as conducive or non-conducive to wet days based on their relative wet-day frequency within each region (e.g., Central, Southern, and Northern Europe).
The results reveal a pronounced north–south gradient in winter, with increasing wet-day probability in northern Europe. Positive trends in both wet-to-wet and dry-to-wet transition probabilities also prevail in northern Europe. In contrast, southern regions show weaker or negative trends. In summer, trends are generally weaker and exhibit no clear large-scale spatial pattern. Differences among datasets highlight the sensitivity of trend estimates to data source, particularly in regions with sparse station coverage.
How to cite: Beranova, R. and Stryhal, J.: Trends in short-term precipitation variability and their connection to atmospheric circulation, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-287, https://doi.org/10.5194/ems2026-287, 2026.
Regional climate models reproduce many large-scale characteristics of daily precipitation, but substantial uncertainty remains in simulating heavy precipitation, especially in summer and over complex terrain. Previous evaluations of the historical ALADIN-CLIMATE/CZ simulation over the Czech Republic showed that standard diagnostics based on mean fields, bias, correlations, and percentile characteristics are useful for assessing overall performance, but provide only limited information on whether the model reproduces the correct spatial organization of precipitation events. This is a key issue for heavy precipitation, whose impacts depend not only on event magnitude but also on where precipitation is concentrated within the domain.
This study evaluates daily precipitation over 1995–2014 using recurrent spatial precipitation regimes derived from a Self-Organizing Map. The analysis is based on a historical model run that provides an appropriate baseline for identifying model biases relevant to interpreting future climate simulations. Observed and modeled daily fields are classified in a common regime space, allowing direct comparison of the frequency, intensity, and spatial structure of characteristic precipitation patterns. This framework is particularly suitable for heavy precipitation because it helps distinguish between errors in the occurrence of particular regimes, errors in precipitation intensity within those regimes, and errors in the representation of terrain- and season-dependent rainfall structures.
The results are consistent with previous evaluations, but provide a more process-oriented interpretation of model error. The historical run reproduces the main characteristics of daily precipitation reasonably well, yet important deficiencies persist in reproducing extreme events. In particular, the model simulates a reduced diversity of precipitation regimes, with wet days concentrated into a relatively small subset of recurrent patterns. It also overproduces annual exceedances of the observational extreme threshold, while the largest deficiencies occur in summer extreme regimes, especially those linked to complex terrain, where conditional intensities are generally too weak. Overall, the regime-based analysis complements conventional validation by showing that uncertainty in simulated heavy precipitation arises not only from bulk bias, but also from imperfect representation of the diversity, frequency, and spatial structure of daily precipitation regimes.
How to cite: Martinkova, M.: Spatial Regimes of Heavy Precipitation over the Czech Republic: A Regime-Based Evaluation of Observed and Historical Model Daily Precipitation, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-316, https://doi.org/10.5194/ems2026-316, 2026.
The downscaling of climate change projections is crucial for impact and adaptation studies, as such studies require higher spatial resolution data than those provided by global CMIP6 models. EC-Earth3 is therefore used as a driving model for dynamic downscaling with the Eta/INPE regional model over SA. In this study, we analyze projected trends under the SSP5-8.5 scenario, focusing on the 2-m air temperature (2 m) and precipitation until the end of the 21st century. Changes are evaluated from 2015 onwards relative to the 1985–2014 climatology and analyzed seasonally (DJF, MAM, JJA, SON). In the near future period, an increasing trend in precipitation is projected over the South Atlantic Convergence Zone (SACZ) during DJF, as well as over northern SA during MAM, while a reduction in precipitation is projected over most of the domain, particularly over the Amazon region. From 2025 onwards, precipitation reductions over the Amazon are projected to predominate in nearly all seasons, while positive changes are projected over parts of northeastern, southeastern, and central SA. This pattern persists in subsequent decades. From 2060 onwards, precipitation reduction over the SACZ exceeds 300 mm per season in SON and DJF. By the end of the century, a strong negative change is projected across the entire SACZ region. In contrast, a persistent positive change is projected over southern Brazil, likely associated with an increase in extreme precipitation events. This contrast tends to enhance the spatial variability of climate over SA and suggests changes in the South American monsoon system and the continental hydrological cycle. Regarding temperature, initial chances do not exceed ±1 °C over most of central SA. From 2025 onwards, positive changes range from +1 to +3 °C across most of the domain. The warming signal intensifies over time, exceeding +4 °C from 2035 onwards during SON. From the 2040s onward, positive temperature changes dominate across the model domain under the SSP5-8.5 scenario. Projected mean temperature increases exceed +6 °C over the central region from the 2050s onwards. By the end of the century, temperature increase range from +6 to +8 °C over most of Brazil. The main agricultural production region in Central Brazil exhibits the highest warming rates. The SON season presents the largest temperature increases and precipitation anomalies.
How to cite: Rodrigues, D. C., Chou, S. C., Chagas, D., Lyra, A., Haarsma, R., and Reerink, T.: Assessment of EC-Earth3 climate change projections over South America, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-432, https://doi.org/10.5194/ems2026-432, 2026.
One of the most severe consequences of climate change is the increase of extreme weather events, both their intensity and frequency. A particularly high risk to agriculture is posed by complex extreme weather events, so-called multivariate compound events. An example of this type of compound event is either simultaneous or consecutive heat wave and drought. Since Europe’s food safety is highly dependent on crop yields, it is essential to precisely map the climate vulnerability of agricultural regions.
The purpose of this study is to conduct spatial and temporal analyses of hot and dry compound events in five European plain regions with different climatic conditions, between 1971 and 2025. The selected regions (Svealand – Sweden; Finnish Lakeland – Finland, Russia; Pannonian Plain – Hungary, Romania, Croatia, Slovenia, Slovakia, Ukraine; Paris Basin – France; Po Valley – Italy) enable the comparison of humid continental, subarctic, oceanic, and humid subtropical climatic conditions. The study focuses on the vegetation period from April to October, which is critical for agriculture, in order to obtain a more accurate picture of the impacts on major field crops (e.g., wheat, maize, barley).
In this study, we used high-resolution, gridded daily data from E-OBS, more specifically, maximum temperature and precipitation time series to analyse the frequency of days exceeding/below various threshold values (e.g., Tmax > 30 °C and daily precipitation < 1 mm), as well as Consecutive Dry Days (CDD). The simultaneous occurrence of the lack of precipitation and extreme temperatures across the European plains is analysed using inter- and intra-variability of the selected European regions.
How to cite: Fritz, P., Kis, A., and Pongrácz, R.: Co-occurrence of hot and dry extreme events in European plain regions, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-535, https://doi.org/10.5194/ems2026-535, 2026.
Anthropogenic activity has altered Earth’s climate at a rate unprecedented in millennia. Whether this rate itself has increased in recent decades remains uncertain, partly because natural variability obscures acceleration signals over short timescales. Here, we show that commonly used detection methods can yield different acceleration estimates, helping to explain divergent conclusions in the literature. We then examine whether acceleration emerges more clearly at regional than at global scales using observational, reanalysis, and simulation datasets. We find that large areas of the planet show significant acceleration of surface temperature. Densely populated regions, biodiversity hotspots, and Key Biodiversity Areas are particularly affected, with roughly half of the world’s population already living in areas undergoing accelerating warming. We show that this regional signal is correlated with the emergence of a global acceleration signal, indicating that a detectable global signal is expected around the present decade. We further demonstrate that regional aerosol forcing modulates the timing of acceleration emergence, delaying detection in heavily polluted regions while hastening it where aerosol emissions have declined. Finally, we assess when a deceleration signal is expected to emerge under different emissions pathways over the twenty-first century. Under a stringent mitigation pathway (SSP1-2.6), a deceleration signal in global warming is projected to emerge near mid-century, whereas under a moderate emissions pathway (SSP2-4.5) it is delayed by about three decades, emerging around 2080. These results indicate that the climate system is not only warming, but doing so at an increasing rate in many inhabited regions, underscoring the urgency of rapid mitigation and adaptation.
How to cite: Shmuel, ., Gottlieb, A. R., and Mankin, J. S.: Regional acceleration of climate change, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-543, https://doi.org/10.5194/ems2026-543, 2026.
Heat waves are among the most relevant manifestations of ongoing climate change in Central Europe, with an increasing frequency of hot days and tropical nights, especially in urban areas. This study synthesizes and updates observational evidence on the intensification of heat waves and heat stress in Poland over the last five decades (1976-2025), with particular attention to changes in frequency, duration, and thermal severity, as well as to differences between temperature-based extremes and human-perceived heat stress. The analysis is based on ERA5 Copernicus data (for background maps), the database of the Polish Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB), records from the University Meteorological Station in the city centre of Lublin, and urban measurements from HOBO sensors.
The intensification of heat stress is reflected in the increasing number of days with strong heat stress according to different biometeorological indices. The fastest increase is observed in southern Poland, especially in the upland region, including Kraków and Rzeszów. Seasonally, the highest frequency of such days occurs in July, followed by August, while June remains the least affected month.
During one of the most intense heat-wave episodes in Poland - the August 2015 mega-heatwave, which produced prolonged heat stress in many Polish cities - the number of hours with strong heat stress (UTCI > 32°C) exceeded 110 in Wrocław (south-western Poland).
Another city in southern Poland characterized by high heat stress is Lublin, which in this study serves as a representative mid-sized Central European city with a heterogeneous urban structure typical of many cities in the region. In Lublin, the observed rise in minimum and maximum air temperature (0.067 and 0.083°C per decade, respectively) has been accompanied by increasing numbers of heat days and tropical nights, a pronounced urban-rural contrast, especially at night, and stronger heat stress in densely built-up districts than in greener or more open urban areas. In the long-term record, the city centre experiences an average of 7.2 heat days per year, compared with 5.6 in the city outskirts. The record values were 26 in 2024 in the city centre and 22 in 2015 in the outskirts. Tropical nights are also much more frequent in the city centre than in the outskirts, averaging 2.1 nights per year in Lublin and 0.2 in the surrounding area.
By combining long-term trends with selected urban case studies, this study shows that changes in extreme heat in Poland are clearly detectable in observational records and should be assessed not only by air temperature, but also by biometeorological indices that better capture the actual human heat burden.
How to cite: Krzyżewska, A.: Observed Intensification of Heat Waves and Heat Stress in Poland: Long-Term Context and Selected Case Studies, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-769, https://doi.org/10.5194/ems2026-769, 2026.
Precipitation projections over the Guiana region in northern South America are hampered by dry biases over that region in CMIP6 models. These biases are partly due to the wrong position of the inter tropical convergence zone (ITCZ) that is generally located too far to the south and unresolved mesoscale processes that are important for convective precipitation prevailing in that region. To account for that pseudo global warming (PGW) experiments with a regional climate model have been performed. In these experiments a perturbation derived from global climate models is imposed on present day simulations that are forced by reanalyses boundary conditions. The higher spatial resolution of regional climate models allows for a better simulation of mesoscale processes and using reanalyses as boundary conditions for the present climate induces an improved position of the ITCZ. For the present climate, the RACMO regional climate model with a resolution of about 12 KM, driven by ERA5 reanalyses boundary conditions, reveals a strong reduction of the dry bias. For the future climate the PGW experiments, perturbed by an ensemble mean of CMIP6 models, indicate a strong increase in precipitation, in particular during the wet season. This contrasts with CMIP6 models that indicate a drying for that region. This has strong implications for climate adaptation measures as presently this region is already affected by large floods induced by heavy rainfall. Present research is focused on changes in extreme precipitation and on different processes explaining these differences, such the position of the ITCZ, the role of orography and the simulation of mesoscale processes.
How to cite: Haarsma, R., Keizer, I., Koole, E., de Vries, H., Chou, S. C., and Lima de Melo, D.: Climate projections for the Guiana region, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-603, https://doi.org/10.5194/ems2026-603, 2026.
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