Extreme weather events such as heavy precipitation and droughts are key indicators of climate
change, yet their variability and underlying drivers remain challenging to assess. This study
investigates trends in extreme precipitation over Europe and the Mediterranean from 1981 to 2022
using CHAPTER (Computational Hydrometeorology with Advanced Performance to Enhanced
Realism), a high-resolution (3 km × 3 km). CHAPTER is a convection-permitting dynamical
downscaling of the ERA5 global reanalysis, performed with the WRF numerical model. The high
spatial resolution of CHAPTER enables a detailed analysis of convective processes that global
climate models cannot directly represent. A robust physical scaling diagnostic is applied to
decompose changes in hourly extreme precipitation into thermodynamic and dynamic contributions.
Results indicate an overall increase in extreme precipitation intensity of 2.5% per degree of
warming, with significant regional variations. The strongest increases are observed over the eastern
Mediterranean, particularly in the Ionian Sea, while slight decreases appear over the Iberian
Peninsula and the western French coasts. These spatial patterns strongly correlate with
thermodynamic scaling, suggesting that precipitation changes at a regional scale are primarily
driven by increasing atmospheric moisture content, consistent with global-scale findings. More
specifically, these spatial trends in extreme precipitation closely align with surface changes in
specific humidity.
Conversely, the dynamic contribution exhibits significant spatial variability, suggesting a strong
influence of natural variability over the 42-year period studied. A statistical significance test
confirms that most observed trends in extreme precipitation are not robust at a 95% confidence
level, reinforcing the hypothesis that natural variability plays a dominant role.

How to cite: Bernini, L., Pfahl, S., Parodi, A., Pasquero, C., and Parodi, A.: Thermodynamic and Dynamic Contribution in Precipitation Extremes over Europe and theMediterranean Basin., EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-17, https://doi.org/10.5194/ems2025-17, 2025.

Our previous research on trends in summer day-to-day mean temperature difference in Europe indicates
inhomogeneities to occur at climate stations in Germany. In most cases, they produce an unrealistic decreasing trend. It is
suggested that these discontinuities are caused by the change in daily mean temperature calculation in April 2001, from averaging
the temperature at 7, 14, and two times 21 to averaging all 24-hourly values. Our current analysis demonstrates this inhomogeneity
and uncovers the difference in climatology and trends of summer temperature variability between aforesaid
definitions of daily mean temperature at 13 stations in Germany. It is revealed that the choice of definition is crucial for
seasonal temperature variability while for seasonal mean temperature itself no difference between definitions is noticed.
The first definition [(T₇ + T₁₄ + 2 x T₂₁)/4] shows days after warming warmer and days after cooling colder than if averaging
all 24 observations, which is the reason for overestimated intraseasonal temperature variability before 2001 and for its
artificial decreasing trends.

How to cite: Krauskopf, T. and Huth, R.: Intraseasonal air temperature variability and its trends are sensitive to the definition of daily mean temperature: Germany as a case study, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-55, https://doi.org/10.5194/ems2025-55, 2025.

Montenegro is located on the Balkan Peninsula. Near the coast and valleys, Mediterranean conditions have allowed Montenegro to develop a vinicultural heritage, which is currently threatened by climate change. This study aimed to expose the impacts of climate change on Montenegrin viticulture, using a high-resolution CHELSA database (≈ 1 km). Climate data was analysed for the historical period 1981-2010 and the future period of 2071-2100. The projections included 5 Global Climate Models (GCM) and 3 Shared Socioeconomic Pathway (SSP) scenarios: SSP1-2.6, SSP3-7.0, and SSP5-8.5. The selected indices for this analysis were GDD10, Winkler Index, Mean annual temperature, Growing season average temperature, Total annual precipitation and Total growing season precipitation. Across the different scenarios, the results show distinct differences concerning the Lake Skadar basin and the Montenegrin Coast, the warmest regions of Montenegro. The mean annual temperature increase will be from 2 °C to 5 °C, and the total annual precipitation might decrease to 250 mm per year (12%). For traditional viticulture, the maximum Climate normal of the Winkler index value is 2700 °C per year. For Montenegro, the Winkler Index will reach from 2800 to 3600 °C per year and is also predicted to expand the growing season, with an increasing number of days with an average temperature above 10°C. These results show that climate change is threatening Montenegrin viticulture, and so the application of adaptation measures in the sector is mandatory to preserve its legacy.  However, the results depict the emergence of new areas suitable for viticulture. Acknowledgements/Funding: This research was supported by FCT –Portuguese Foundation for Science and Technology, under the projects UID/04033: Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas and LA/P/0126/2020 (https://doi.org/10.54499/LA/P/0126/2020), and by the MONTEVITIS project “Integrating a comprehensive Europe-an approach for climate change mitigation and adaptation in Montenegro viticulture”, funded by the European Union’s Horizon Europe, the Framework Programme for Research and Innovation (2021–2027), under grant agreement nº 101059461.

How to cite: Fernandes, A., Kovač, N., Fraga, H., Fonseca, A., Šućur Radonjić, S., Simeunović, M., Ratković, K., Menz, C., Costafreda-Aumedes, S., and Santos, J. A.: Climate change projections for Montenegro and potential impacts on viticulture, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-87, https://doi.org/10.5194/ems2025-87, 2025.

The Pacific Walker Circulation (PWC) is an important part of the global atmospheric circulation. Its strength is changing constantly due to internal variability, such as ENSO, IPO, and multi-decadal climate variability, as well as the forced response to increasing greenhouse gas concentrations. Despite the observational studies showing strengthening of the PWC, modelling studies predominantly predict its weakening with the reason for this discrepancy still unknown. Generally, results of different studies are difficult to compare, due to different datasets, different time intervals and different indices used. However, any change in PWC strength may have vastly different effects on the global climate, which underlines the importance of proper simulation of its trends in the changing climate. 

The main aim of our study is to assess the consistency of different PWC indices across reanalyses.  We compared nine different PWC indices between six different reanalyses (ERA5, ERA-Interim, JRA-55, MERRA-2, NCEP and NOAA 20CRv3), both over their respective time spans and over the common period from 1981 to 2011. The comparison was performed for the trends of different lengths, as well as correlations between indices for each reanalysis and between reanalyses for each index. 

On average, time series of indices in reanalyses verify well compared to pure observation-based indices. They are able to capture the strongest El Niño years and distinguish between El Niño and La Niña states. As expected, the spread of indices is larger in the surface-based reanalyses than in the full atmospheric reanalyses, as the the lack of observations in the free atmosphere in the former make them less constrained by observations. The spread is generally the largest during the strongest El Niño events. Correlations between the indices are stronger for the indices based on physically related processes, such as indices based on surface pressure and surface wind or 500-hPa vertical velocity and upper tropospheric humidity. Indices based on surface variables are more strongly correlated between reanalyses than indices based on data in the upper-atmosphere.  

Trends of different lengths show mixed results, depending on the reanalyses and indices. The 20-year trends ending at about 2020 are mostly negative but not statistically significant. Ultimately, this raises a key question: Are the traditional PWC indices still suitable for capturing changes in today’s rapidly changing global climate? 

How to cite: Kosovelj, K., Pikovnik, M., and Zaplotnik, Ž.: Variability and trends of the Pacific Walker circulation indices in multiple reanalyses , EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-134, https://doi.org/10.5194/ems2025-134, 2025.

In the last two decades, several severe to extreme droughts have been recorded in parts of the Slovenian pre-Alpine region, with the most pronounced events occurring in the summers of 2003, 2013 and 2022, which also affected Slovenia on the scale of a natural disaster. These droughts typically resulted from prolonged periods of below-average precipitation, while on shorter timescales, their development and intensification were strongly influenced by concurrent heatwaves. When droughts and heatwaves occur simultaneously or in close succession, their combined impact to ecosystems and related economic sectors, such as agriculture and forestry, often exceeds the sum of their individual impacts. These compound extreme events can lead to significant crop losses, heightened wildfire risk and cascading disruptions across interconnected systems.

Compound drought and heatwave (CDHW) events can be analysed using various combinations of drought and heatwave indicators. In the framework of the Interreg Alpine Space project X-RISK-CC, we defined CDHW events by combining the Standardized Precipitation-Evapotranspiration Index (SPEI) on a monthly, 2-monthly and 3-monthly timescale with the heatwave index based on daily maximum temperature exceeding a high threshold over three consecutive days. For the case study area in the Slovenian Prealps, we examined past and future characteristics of CDHW events through historical trends from observations and through projections using the global warming level (GWL) approach for warming scenarios of 2 °C, 3 °C and 4 °C relative to the pre-industrial period 1850–1900.

Several CDHW events have been observed in the case study area in recent decades, with trends indicating an increase in both frequency and magnitude since 1970 at certain locations. Future projections suggest that the annual frequency of CDHW events could increase by 1 to 5 events per year relative to the current climate. These events are also expected to intensify under all global warming levels, with the increase in annual maximum magnitude ranging from 40 % to 150 %. The probability of occurrence of individual droughts and heatwaves, as well as the probability of CDHW events is projected to rise. A CDHW event as extreme as the 1-in-50-year event in the current climate is expected to become up to 8 times as likely under a global warming of 3 °C and up to 13.5 times as likely under a global warming of 4 °C.

How to cite: Vlahović, Ž., Lokošek, N., and Žun, M.: Compound drought and heatwave events: A case study on historical and future perspective in the Slovenian pre-Alpine region, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-145, https://doi.org/10.5194/ems2025-145, 2025.

We present a new methodology for modeling the intensities of extreme sub-daily precipitation events aimed at generating spatially continuous return level maps with associated uncertainties. This supports a comprehensive understanding of extreme precipitation events, which is important for climate adaptation planning. Our approach is built within a Bayesian generalized additive modeling framework designed to capture complex trends in marginal extremes over space.

The modeling strategy follows a two-step procedure. In the first step, the frequency of exceedances over a threshold is modeled using a spatially varying Negative Binomial distribution. In the second step, the magnitudes of these exceedances are modeled using the Generalized Pareto distribution. Here, the scale parameter is allowed to vary across space while the shape parameter is assumed to remain constant over the spatial domain.

The latent random effects are modeled using Gaussian process priors, which provide high flexibility and interpretability. Inference is performed using the Integrated Nested Laplace Approximation (the INLA system), which provides a fast and accurate alternative to traditional Markov chain Monte Carlo methods, making the framework computationally feasible for high-resolution spatial modeling.

We apply the proposed methodology to a dataset of sub-daily precipitation time series with >25 years of operational service at 50 stations across Denmark. The model successfully captures spatial variation in both the rate and magnitude of extreme events and efficiently produces high-resolution maps of return levels along with credible intervals that quantify uncertainty.

Our two-step Bayesian model offers a robust alternative to the current state-of-the-art method used in Denmark for estimating the intensities of extreme sub-daily precipitation events. The results are consistent with existing approaches but show a more detailed uncertainty quantification. By explicitly modeling spatial variation, the framework enables predictions at unsampled locations, enhancing the understanding of extreme precipitation patterns.

How to cite: Antoniadou, N., Wied Pedersen, J., Stockmarr, A., Jomo Danielsen Sørup, H., Schmith, T., and Steen Mikkelsen, P.: A Bayesian spatial framework for modeling extreme sub-daily precipitation in Denmark, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-158, https://doi.org/10.5194/ems2025-158, 2025.

Precipitation in Central Europe occurs in diverse forms, with significant hydrological and societal impacts depending on its character and intensity. Two dominant types—convective and stratiform precipitation—differ not only in their spatial and temporal development but also in their association with atmospheric circulation patterns. Convective precipitation is often linked to rapid, localized storms capable of causing flash floods, whereas stratiform precipitation is typically associated with widespread, prolonged rainfall events that may lead to regional flooding.

We analyze heavy and extreme precipitation in both the recent climate and under two future climate scenarios: SSP5-8.5 and SSP2-4.5. For the recent climate, we use observational time series from 19 meteorological stations across the Czech Republic, covering the period 1982–2021. Precipitation events are classified as convective or stratiform using an automated algorithm based on SYNOP weather reports. To assess projected changes throughout the 21st century, we utilize the ALADIN-CLIMATE/CZ regional climate model, operated by the Czech Hydrometeorological Institute, which provides simulations at a high horizontal resolution of 2.3 km. Heavy precipitation events are defined as those exceeding the 90th percentile threshold. To further quantify extremes, we estimate 50-year and 100-year return values for convective and stratiform precipitation using a Generalized Extreme Value (GEV) distribution fitted to annual maxima.

To investigate the driving mechanisms behind heavy precipitation events, we will assign circulation types using the Jenkinson & Collins (1977) classification scheme. This approach is based on three key indices: direction, flow strength, and vorticity. This method distinguishes 27 distinct circulation types. Our results indicate a pronounced seasonal and spatial variability in the relationship between circulation patterns and precipitation types. Heavy stratiform precipitation events are most associated with cyclonic circulation and directional flows from the west and north. During summer, however, heavy convective precipitation also frequently occurs under anticyclonic and unclassified conditions, highlighting the role of localized atmospheric instability and mesoscale processes in triggering intense rainfall during warmer months. An important question is how the relationship between heavy precipitation and atmospheric circulation will evolve under future climate conditions.

How to cite: Beranova, R. and Rulfová, Z.: Convective and stratiform heavy and extreme precipitation in a changing climate: Insights from Central Europe, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-201, https://doi.org/10.5194/ems2025-201, 2025.

Since the maximum temperature increased in Poland significantly, more prolonged heat waves are expected in summer. Long-lasting heat waves create high thermal stress not only in the human body but also in the agriculture and energy systems. Far more dangerous is the case when very high temperature during the day is followed by high temperature during the night. This may pose a real challenge for the human thermoregulation system, which can not fully recover even at night after daytime heat stress. It is proven that hot day and night events are more harmful to the human body when they occur as compound events, but most of the studies considered warm daytime or nighttime events separately. The main issue of this study is to detect trends in the occurrence of warm spells during the day and night either separately or inseparable. Furthermore, these events are also investigated under different mechanisms that can favour their appearance. First of all, the circulation patterns under each event are analysed. Then, the humidity and radiation conditions are described for warm daytime or nighttime events and compound events. To distinguish the daytime and nighttime warm-spell, the maximum and minimum temperature is used. These events are selected based on the 90^th percentile threshold in the 15-day window. All datasets used in the study were acquired from the Institute of Meteorology and Water Management—National Research Institute (IMWM-NRI) and ERA5 Reanalysis for the period from 1966 to 2024.

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.: Compound daytime and nighttime high-temperature extremes in Poland, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-308, https://doi.org/10.5194/ems2025-308, 2025.

Recent global warming has intensified the urban heat island (UHI) effect and related temperature impacts in cities. The capital of the Czech Republic, Prague (c. 1.385 million inhabitants in 2023), with its long history of meteorological observations and dense network of meteorological stations, was analysed to assess changes in UHI and related temperature variables over the period 1921–2023. Long-term changes in mean (TAVG), maximum (TMAX), and minimum (TMIN) temperatures, along with temperature characteristics derived from them, showed predominantly significant increasing trends, except for the number of frost and ice days, which exhibited a decreasing tendency. Accelerated warming was particularly evident in the past two decades. During 1961–2023, the mean annual magnitude of Prague’s UHI was highest for TMIN and TAVG (1.8°C and 1.5°C respectively for the Klementinum station, and 1.7°C and 1.1°C respectively for the Karlov station), while it was relatively negligible for TMAX. Based on mean series from urban, suburban, and rural stations, the strongest intensification of UHI during the study period was observed in the summer and for TMIN. The daily UHI structure was characterised by the highest nocturnal positive and statistically significant temperature differences compared to rural surroundings, particularly on days with long sunshine duration and lower wind speeds, conditions conducive to intensified sensible heat flux. The highest TAVG and TMIN differences between Prague and its rural surroundings were recorded during anticyclonic circulation types, as opposed to directional and cyclonic types. Urban warming was generally more pronounced during circulation types with eastern and southeastern airflow compared to other airflow directions. 

Acknowledgements:  This research was supported by the Technology Agency of the Czech Republic for its financial support under the grant no. SS02030040 (Prediction, Evaluation and Research for Understanding National sensitivity and impacts of drought and climate change for Czechia, PERUN)

How to cite: Zahradníček, P., Brázdil, R., Řehoř, J., Dobrovolný, P., Šanda, R., and Štěpánek, P.: Increasing vulnerability of urban climate to recent climate change, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-476, https://doi.org/10.5194/ems2025-476, 2025.

The seasonal snowpack in the Alps and Carpathians is undergoing rapid transformation due to climate change, but the implications of these shifts for snow avalanche activity remain insufficiently understood. This study investigates both observed and projected changes in climate indicators relevant to snow avalanche activity, analyzing current conditions (1984–2021, based on the CERRA dataset) and future scenarios (up to 2100, under RCP4.5 and RCP8.5, using EURO-CORDEX simulations). Our objective is to assess how climate conditions favorable for dry- and wet-snow avalanche occurrences may evolve throughout the 21st century in the Alps and Carpathians. Avalanche activity is inferred from climatic pre-conditions identified in historical avalanche records sourced from the European Avalanche Warning Services and the mountain rescue databases, calibrated to the unique climatic and topographic features of the Alps and Carpathians. In addition, terrain and land cover characteristics are integrated into the analysis to delineate areas of high and very high susceptibility to snow avalanches across the region. Findings reveal a complex pattern of change in climatic conditions associated with both dry- and wet-snow avalanche activity. Depending on elevation and the emission scenario, future projections suggest an overall reduction in total avalanche activity by the end of the century compared to present-day baselines. This study represents one of the first comprehensive assessments of climate change impacts on snow avalanche dynamics in the Alps and Carpathian Mountains and provides a valuable reference point for further investigations into mountain hazards under evolving climate conditions.

This research received funds from the project “Cross-sectoral framework for socio-economic resilience to climate change and extreme events in Europe (CROSSEU)” funded by the European Union Horizon Europe programme, under Grant agreement n°101081377.

How to cite: Micu, D., Amihaesei, V., Bothe, O., Bowyer, P., Cheval, S., Ontel, I., and Paraschiv, M.: Climate-driven conditions for snow avalanche activity in the Alps and Carpathian Mountains under climate change, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-498, https://doi.org/10.5194/ems2025-498, 2025.

Climatological normal periods are used to describe the typical climate conditions that can be expected in a given location. These climate normals – statistical values such as means or totals for specific climate elements – are calculated for non-overlapping 30-year periods. The 1961–1990 period was probably the most widely used reference baseline in modern climatology, as it was recommended by the World Meteorological Organization for long-term climate change assessments. Now that 2020 has passed, a new climatological normal period (1991–2020) can be adopted. This raises an important question: how will this updated baseline affect the way we define anomalies and extremes, given that climate warming has already shifted what is now considered “normal” in many regions? With ongoing climate change, the statistical definition of “normal” itself is evolving – potentially influencing climate assessments and regional comparisons.

The main aim of this study is to assess how the selection of the reference period (1961–1990 vs. 1991–2020) influences how extremes are defined and distributed across Central Europe, based on a new high-resolution dataset. First, we compared how the choice of baseline period affects spatial and seasonal patterns of air temperature and precipitation indices. These indices include mean values and counts of extreme days defined by absolute thresholds. Next, we assessed how standard percentile thresholds used to define extremes (such as the 90th percentile) vary depending on the baseline period, and how these differences impact the spatial distribution of corresponding extremes. The analyses are based on a newly developed, high-resolution gridded daily dataset for Central Europe (1 × 1 km), covering the years 1961–2020, which includes daily maximum and minimum temperatures and precipitation totals. The dataset is based on in-situ measurements covering Poland, Czechia, Slovakia, and the border regions of Germany and Austria.

The results show large differences in temperature and precipitation patterns between indices computed using the two baseline periods, demonstrating that the 1991–2020 reference is strongly affected by recent climate change. The selection of a more recent baseline can significantly understate the extent of ongoing warming, especially when extremes are defined using percentile thresholds. Precipitation indices appear less sensitive to baseline changes, although differences still exist. The 1961–1990 period may offer a more stable reference for climate studies, and careful consideration is needed when communicating changing baselines to decision-makers.

How to cite: Sulikowska, A., Wypych, A., Štěpánek, P., and Zahradníček, P.: New baselines, new extremes? Assessing the impact of reference periods on climate extremes in Central Europe, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-601, https://doi.org/10.5194/ems2025-601, 2025.

Western Asia, with its diverse and complex geographical and environmental conditions, is one of the world's most vulnerable regions to climate change making it particularly susceptible to extreme precipitation events (EPE). This study develops a probabilistic risk assessment for EPEs across the region, identifying high-risk zones for heavy rainfall and flash floods through analysis of 160 years of daily precipitation data, including ERA5 reanalysis data (1941–2020) and 7 CMIP6 models under two scenarios of SSP2-4.5 and the most pessimistic one, SSP5-8.5 (2021–2100). By considering the trends of 10 certain indices (EPIs) based on both historical precipitation data and future projections, The findings categorize areas into four distinct risk levels, ranging from no risk to high risk. The statistical significance of EPIs was assessed using the nonparametric Mann–Kendall test on the significance levels of 5%. For each grid cell, trends in all EPIs were calculated, and grids exhibiting statistically significant upward trends were classified as susceptible to extreme precipitation. This criterion - positive and significant trends across indices - was systematically applied to all grids in the study area, generating a spatially explicit risk classification. Regions with overlapping susceptibility signals from multiple indices were prioritized as high-risk zones.

The same methodological framework was applied to the future climate projections derived from the selected CMIP6 models. To combine the results across the different models and enhance the reliability of the classification, a machine learning technique was employed. Specifically, the Random Forest (RF) algorithm was used to integrate the spatial outputs of all models based on the "most agreed-upon risk level" for each grid cell. The goal was to produce a unified classification map that reflects the most probable future risk zones for extreme precipitation.

The outcome of this analysis shows that although the "high-risk" area decreases from 10% to 2% under the SSP2-4.5 scenario, this percentage increases significantly to 25% under the SSP5-8.5 scenario. In other words, 25% of the region is classified as high-risk in the pessimistic scenario and indicate a pronounced shift, with a majority of previously moderate-risk areas transitioning to high-risk categories by 2100. Overall, the "no-risk" area decreases from 55% to 46% under SSP5-8.5, indicating a general increase in the area susceptible to extreme rainfall. Notably, northwestern Iran and central Turkey consistently appear as high-risk zones across all analyses, from historical part through both future scenarios, highlighting their persistent vulnerability.

These findings give confidence to the potential impacts of flooding and infrastructure challenges in regions unfamiliar to dealing with heavy rainfall. This information is important for water management strategies that are part of preparing for climate change impacts, which clearly emphasize the rise in extreme weather patterns across the Middle East.

How to cite: Fakour, P. and Ustrnul, Z.: A 160-Year Analysis of Extreme Precipitation Hazard Shifts in Western Asia: Perspectives from Historical Trends and AR6 Projections, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-596, https://doi.org/10.5194/ems2025-596, 2025.