Honey bees (Apis mellifera L.) are one of the most important pollinators worldwide, primarily managed by beekeepers. Beyond their role in pollination, they produce a range of valuable products, including honey, bee bread, pollen, propolis, royal jelly, venom, apilarnil and wax. It is a well-known fact that the weight is a good indicator of the health, strength, food and foraging capabilities of the colony despite its complex structure. Various external and internal factors could influence these variations, yet until today, this is the most popular way of observing bees. Nowadays, the use of digital hive scales is becoming more widespread, offering precise and high temporal resolution monitoring of bee activity.

Our study aims to forecast honey bee foraging behaviour during a heavy, monocultural nectar flow (Robinia pseudoacacia L.) in the period between April 15 and June 15 in a Hungarian active apiary, incorporating meteorological factors as exogenous variables. To achieve this, we deployed hive scales under two hives from 2021 to 2024, recording weight data at 1-hour and 30-minute intervals. After pre-processing the data, we applied time-series models using a 24-hour rolling forecast method and defined four cases: 1) without the exogenous variables, 2) with meteorological variables, 3) with diurnal patterns, and 4) combining all factors. Linear and non-linear models were tested with and without the seasonal component, utilizing ARIMAX (AutoRegressive Integrated Moving Average with eXogenous variables), SARIMAX (Seasonal ARIMAX) and additional LSTM (Long Short-Term Memory) approaches. Beyond model development, we seek to quantify the impact of weather conditions on hive weight fluctuations and explore the biological responses of honey bees to environmental changes.

These insights are crucial for advancing modern precision apiculture, optimizing hive management strategies and preparing for climate-driven challenges in beekeeping.

This work has been implemented by the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014) project within the framework of Hungary's National Recovery and Resilience Plan supported by the Recovery and Resilience Facility of the European Union.

How to cite: Ilyés-Vincze, C., Varga-Balogh, A., Leelőssy, Á., and Mészáros, R.: Hive weight time series prediction using meteorological factors during R. pseudoacacia nectar flow  , EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-16, https://doi.org/10.5194/ems2025-16, 2025.

Assessing drought and aridity risks can help olive growers make informed decisions and plan effective management strategies to mitigate climate-related challenges. Portugal is a major producer of olive oil, with six regions designated as Protected Denomination of Origin (PDO), each characterized by varying olive orchard (OR) densities, ranging from traditional rainfed to superintensive irrigated systems. This study aimed to evaluate future drought and aridity trends and their potential effects on ORs within these PDO regions. To achieve this, drought and aridity indicators were analyzed for both historical (ERA5: 1981–2000) and projected future periods (2041–2060; 2081–2100) under two climate scenarios (RCP4.5 and RCP8.5), using a 7-member ensemble of global climate models. Spearman’s correlation analysis identified Annual Mean Aridity (AIA) as the most representative climate indicator influencing ORs. Readily Available Soil Water (RAW, mm) was used to assess the soil’s capacity to retain moisture for olive trees. Additionally, the Olive Drought and Aridity Risk Index (ODAR) was developed to estimate future risks for each OR by weighting AIA and RAW based on orchard density. Projections indicate that southern Portugal will experience greater aridity (0.69) compared to central and northern regions (0.60). Moreover, southern PDOs are expected to have lower RAW levels (<60 mm), whereas central and northern areas will retain higher soil water content (>90 mm). These findings suggest that southern ORs will be more vulnerable to water stress than those in the north. According to ODAR, ORs in central PDOs will face both low and high risks, while northern regions will mostly experience moderate to high risk. However, in the south, very high risk levels are expected, which could adversely impact olive tree growth, fruit production, and olive oil quality. To enhance the resilience of the sector, targeted adaptation strategies will be necessary. This work is supported by National Funds by FCT –Portuguese Foundation for Science and Technology, under the projects UID/04033 and LA/P/0126/2020 (https://doi.org/10.54499/LA/P/0126/2020).

How to cite: Fraga, H., Freitas, T., Paredes, P., and Santos, J.: Future aridity and Drought Risks for Traditional and Super-Intensive Olive Orchards in Portugal, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-57, https://doi.org/10.5194/ems2025-57, 2025.

Tropical regions are home for 45% of the world’s forested landmasses, which comprises approximately 15% of global land areas. Among them tropical rainforest encompasses around 25% of all the ecological zones, which are spread largely in South America, Central America, Africa, and Southeast Asia. They are the home for two-thirds of the terrestrial biomass and act as natural carbon sinks by exchanging more carbon fluxes with the atmosphere compare to any other biomes in the world. Carbon sinks in the tropical rainforests are restricting the global warming to attain unprecedented heights. The carbon content of soil is about three times higher than that of atmosphere or vegetation, which makes soil respiration as the largest contributor of carbon efflux into the atmosphere through root (autotrophic) and microbial (heterotrophic) respiration. However, deforestation and climate change is switching them to a net carbon source at some of the deforested patches. Using machine learning algorithm we predict that more than 50% of the tropical rainforests will undergo rapid “Savannisation”/transformation by the end of 21^st century under high emission scenarios. Climate change projects ‘El Niño-like’ warming condition, which decreases precipitation in the rainforests and favors atmospheric dryness. These transformations in vegetation morphology underpins the higher probability of occurrences of Net ecosystem production (NEP) i.e. the differences between Gross Primary Productivity (GPP) and Respiration (RE) less than 0, due to increasing microbial activity in the degraded patches of Central Amazonia, Central America (Nicaragua, Honduras, Mexico), Western Africa (coastal Ghana, Benin, Togo, Nigeria) and South East Asian (Greater Sunda islands) rainforests, and thereby transform the traditional carbon sinks into a net source of carbon to the atmosphere. These transformations are more acute in the Amazonian and Central American sectors of the rainforests, which is expected to accelerate by the middle of 21^st century. This is due to faster degradation of rainforests if global mean temperature warms beyond 2.3^◦K (by late 2050’s) and will undergo total transformation if warming exceeds 3.8^◦K (by ~2075). In Central Amazonia vegetation degradation saturates the carbon sink and more than 25% of the rainforests will transform into a net carbon source due to increase in soil microbial respiration. This alteration will exacerbate global warming and has consequences for policies that are intended to stabilize Earth’s climate.

How to cite: Nath, D.: Faster dieback of rainforests altering tropical carbon sinks under climate change, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-95, https://doi.org/10.5194/ems2025-95, 2025.

Fire-prone ecosystems — including savannas, boreal forests, and Mediterranean regions — are experiencing increasingly intense wildfires, with climate change identified as a key driver. Changes in temperature, precipitation, and vegetation dynamics are altering fuel availability and dryness, leading to shifts in fire behaviour. However, as fuel remains poorly represented and constrained in global models, our ability to predict these shifts is still limited.

In this study, we present a long-term record of key fuel state variables — specifically fuel load and moisture content — derived from remote sensing. Creating long-term records of these essential climate variables can serve as indicators of climate variability and ecosystem vulnerability. Funded by ESA-FUELITY project, this work integrates multiple satellite datasets into the SPARKY-Fuel Characteristics dataset, covering the period from 2019 to 2021. It combines L-band vegetation optical depth (VOD) from SMOS and solar-induced fluorescence (SIF) from Sentinel-5P. A hybrid approach is employed, leveraging supervised machine learning to improve the connection between satellite observations and modelled fuel variables, enabling more accurate updates to vegetation conditions.

This dataset can be used in studies related to vegetation productivity, water stress, and carbon cycling, providing a valuable resource for detecting environmental change. Constraining these variables with satellite observations offers significant potential to capture climate-driven shifts in ecosystem flammability and drought response, particularly in fire-prone regions where traditional vegetation indices often lack sensitivity.

Here, we analyse the capability of this dataset to detect fire activity globally and identify regions of shifting fire behaviour. We will demonstrate how this dataset can help refine our understanding of fuel–fire interactions, providing a powerful lens for identifying possible tipping points in vulnerable environments.

Our work reflects a growing need for cross-disciplinary approaches that combine physical modelling, remote sensing, and artificial intelligence to track biosphere responses in a changing climate.

How to cite: El Garroussi, S., Di Giuseppe, F., McNorton, J., de Rosnay, P., Garrigues, S., and Fairbairn, D.: Tracking extreme fire behaviour through assimilated fuel variables: A lens on climate change impact, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-113, https://doi.org/10.5194/ems2025-113, 2025.

Tropospheric ozone is an important greenhouse gas, furthermore, it has a harmful effect on the health of humans, animals and plants. Elevated levels of near surface ozone can lead to various negative impacts on plants, including premature aging, reduction in flower numbers and biomass, altered tolerance to biotic and abiotic stresses and yield loss. In this study different stress-functions are analysed for crops that play a key role in regulating stomatal conductance of ozone. Factors, such as temperature, soil moisture and humidity are particularly important, especially during hot and dry periods in the Carpathian Basin.

Our analysis is based on hourly meteorological and ozone concentration data for the period 2004–2022. The selected station is K-Puszta EMEP monitoring station, located in the central region of Hungary, in the Great Hungarian Plain. The temporal variability of each meteorological and phenological factor was investigated for wheat and potato. Furthermore, AOT40 values (a common metric for ozone exposure) were also calculated for the period 1992–2021 for K-Puszta station. According to our results, in the case of wheat, the critical level of AOT40 is reached later within the year by 6 days on average if we compare the years before and after 2006. Moreover, the critical level of AOT40 related to maize was exceeded only in two years after 2006, while in the period 1992–2005 six occurrences were found.

Acknowledgements. This work has been implemented by the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014) project within the framework of Hungary's National Recovery and Resilience Plan supported by the Recovery and Resilience Facility of the European Union.

How to cite: Kis, A., Kocsis, B., and Mészáros, R.: Temporal analysis of ozone exposure and environmental factors for different agricultural crops based on data from a Carpathian Basin monitoring site, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-304, https://doi.org/10.5194/ems2025-304, 2025.

Droughts are a recurring climatic hazard with significant ecological and socioeconomic consequences. Their frequency and severity have intensified under global warming, driven by rising evapotranspiration, declining soil moisture, and intensified hydrological cycles. Even historically water-rich regions like northern Italy are increasingly affected.

To monitor and understand drought events and their impacts, drought indices are essential. The Standardized Precipitation Evaporation Index (SPEI) is a widely used drought indicator representing the deviations in water balance, i.e., the difference between precipitation and potential evapotranspiration (PET), thus allowing the temperature effects to be considered. As a standardized indicator, it facilitates the result comparison across different environments and climate conditions and enables analysis across different time scales, from short-term agricultural droughts to longer-term hydrological or physiological droughts.

Drought indices are generally defined at monthly resolution. However, for specific applications, such as the comparison of meteorological conditions with soil moisture dynamics or with the response of vegetation, daily indices might be preferable since they enable a more detailed description of the onset and end time of deficit conditions and of short-term variations. This study assesses the methods for the calculation of SPEI at daily scale and evaluates its suitability with respect to monthly SPEI to capture drought episodes and represent the spatio-temporal relationship with vegetation conditions in forest ecosystems. The analysis was conducted in Mazia valley, an inner-alpine dry valley in the eastern Italian Alps (Trentino-South Tyrol), and SPEI values were derived from a daily gridded observational dataset (250 m resolution) of temperature and precipitation covering the study area from 1980 to 2024.

For the calculation of daily SPEI, several probability distributions and fitting strategies for water balance values (precipitation minus PET) were tested. The use of a moving window centred on each day was found to be the best choice reducing result variability and reflecting seasonality.

Daily SPEI time series were calculated at various aggregation scales (15 days to 6 months) and drought events were defined at each grid-cell level as periods of at least 30 consecutive days with negative SPEI values, starting when the index dropped below a certain threshold depending on the drought class considered (moderate to extreme). Comparing daily and monthly SPEI in terms of drought detection confirmed that the higher temporal resolution better captures the short-term yet intense droughts and the inter-monthly variability of water balance. When daily SPEI was compared to vegetation water stress indicators, including remotely sensed spectral indices and tree-level measurements collected for alpine forests in Mazia valley, they were found to allow for a better comparability with physiological drought conditions. Preliminary analyses provide insights on the use of daily SPEI for high-resolution monitoring of drought and understanding of drought dynamics and impacts.

How to cite: Maines, E., Crespi, A., Patriarca, E., Obojes, N., Castelli, M., Bartkowiak, P., Notarnicola, C., and Fonti, P.: Advancing drought impact assessment with daily SPEI: insights from alpine forest response, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-409, https://doi.org/10.5194/ems2025-409, 2025.

Over the past decade, the Sudoe region (Spain, Portugal, and France) has experienced a significant increase in forest fires, placing this region among the most affected in the EU. This growing threat is linked not only to climate change but also to socio-economic factors such as rural depopulation and the decline of traditional land-use practices. As forests become increasingly unmanaged and climate extremes intensify, the risk of wildfires continues to escalate.

To address this complex issue, the Use4Forest project adopts a proactive approach to wildfire prevention. The initiative is built on three main pillars: understanding local environmental and socio-economic dynamics; designing and testing innovative forest use and management solutions; and promoting the transfer and replication of successful strategies across the region. By working closely with forestry experts and local authorities, the project aims to strengthen institutional capacity and encourage smarter, more sustainable forest management practices.

The project brings together 13 key partners from across the Sudoe area: 3 from France, 3 from Portugal, and 7 from Spain — including 2 from the Basque Country (HAZI and EUSKALMET). HAZI is the public foundation of the Basque Government dedicated to promoting the development of the forestry and agri-food sectors. The Basque Meteorology Agency (EUSKALMET) is a public entity that provides information on weather and climate, including operational fire weather and wildfire risk monitoring and warning at local level.

In this presentation, we provide a brief overview of the general objectives and planned activities of the project Use4Forest, with a particular emphasis on the contribution of the two Basque partners. In this context, we will present our specific goals, planned actions, and some preliminary results. The focus is on advancing the understanding of forest fires at the Basque Country level, not only in terms of weather-climate contributions, but also covering other key factors such as fuel dynamics and forest management practices.

Among other relevant activities, it is worth highlighting the analysis of successful case studies where socio-economic prevention strategies are playing a key role in reducing wildfire risk in Basque Public Utility Forests; the use of LiDAR point clouds and TLS/SLAM laser scanning technologies to analyze territory; the real-time determination of fuel characteristics (fuel moisture sensors, satellite imagery, …); the review and improvement of the Euskalmet wildfire risk index prediction system (dynamic fuel condition, ...); the development and implementation of advanced decision support systems that integrate risk indices, impact assessments, and fire behavior and spread modeling; the operational use of satellite products and other observational data applicable to wildfire emergency response; and the operational validation of local predictive systems, with a focus on end-user needs and the incorporation of impact data from recorded wildfire events.

How to cite: Gaztelumendi, S., Cantero, A., Gerenabarrena, I., and Aranda, J. A.: Interreg Sudoe Use4Forest Project: the Basque partners’ contribution, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-491, https://doi.org/10.5194/ems2025-491, 2025.

Climate change is bringing many changes including higher temperatures, extreme weather, and changes in our agricultural systems. These changes will all have damaging effects to the patterns we currently know including deaths by high temperatures, damages to infrastructure from extreme events, and changes to crop yields. Agricultural models are used to try and understand how climate change will affect crop growth and crop yield.

This research project aims to understand how winter wheat (Triticum aestivum) yields have been impacted historically by excessive rainfall events and to project how yields will be affected by a future increase in precipitation. I use future climate projections (RCP 2.6, 4.5, and 8.5) from the CH2018 dataset (CH2018 Project Team, 2018) and historical rainfall reconstruction data (Imfeld et al., 2022) in a crop model to simulate winter wheat harvest yields for the years of 1763-2100. The files used in the crop model were optimized for the most accurate outcome using Switzerland’s climate. The model used is PCSE (Python Crop Simulation Environment) and the PCSE output yields using historical reconstructions are then compared to observed yields to determine the accuracy of the model in relation to this project. From there, conclusions will be drawn about the future of winter wheat yields under a changing climate that is projected to have an increase in precipitation. 

CH2018 Project Team (2018): CH2018 - Climate Scenarios for Switzerland. National Centre for Climate Services. doi: 10.18751/Climate/Scenarios/CH2018/1.0

Imfeld, Noemi; Pfister, Lucas; Brugnara, Yuri; Brönnimann, Stefan (2022): Daily high-resolution temperature and precipitation fields for Switzerland from 1763 to 2020 [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.950236.

How to cite: Jakobsen, A., Broennimann, S., and Holzkaemper, A.: Determining the historical and future impact of excess water limitation on winter wheat yields in Switzerland, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-506, https://doi.org/10.5194/ems2025-506, 2025.

This study presents a comparative characterization of wildfires in the Basque Country in relation to other regions of the Iberian Peninsula. The primary aim is to understand the patterns and dynamics of wildfires at different spatial scales and the regional-to-local differences between territories. To this end, various statistical techniques are applied to analyze both temporal and spatial aspects of fire activity, considering different aggregation levels such as autonomous community, province, and municipality.

The fire data used come from the National Wildfire Database, provided by the Spanish Ministry for the Ecological Transition and the Demographic Challenge. This database includes more than 30 years of historical wildfire records, with event information on detection dates, burned forested and non-forested areas, causes, geographic location, and other variables.

The methodology combines descriptive statistics, spatial analysis, and some visual data analytics techniques to examine fire frequency, severity, spread, and other characteristics. Clustering is used to identify similarities in terms of fire incidence, seasonality, and size distribution. From the original variables, additional indicators are derived at different spatial and temporal aggregation levels to allow interregional comparisons, including weather factors.

Special attention is given to the comparison between the Basque Country and other Spanish regions, focusing on regional differences in wildfire behavior. For this purpose, different normalizations are applied to the indicators. The results reveal significant spatial and temporal variability in wildfire occurrences, with some areas showing higher fire frequencies associated with specific factors. While the Basque Country experiences far fewer wildfires than neighboring territories, it displays similar patterns in terms of seasonality and fire causes.

Overall, the findings provide valuable insights into forest fire behavior across some territories of the Iberian Peninsula and highlight the importance of considering local conditions at multiple scales when designing forest fire prevention and response strategies. This comparative approach allows for a deeper understanding of wildfire in the Basque Country, emphasizing both similarities and differences with other regions that feature diverse geographical and climatic contexts. The results may contribute to more effective wildfire management policies at the regional and local levels.

How to cite: Gaztelumendi, S. and Aranda, J. A.: Characterization of wildfires in Basque Country and comparison with other Iberian Peninsula Regions., EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-514, https://doi.org/10.5194/ems2025-514, 2025.

Plant phenology is primarily driven by air temperature, although this relationship is complex and not yet fully understood – particularly regarding the influence of temperature extremes on the timing of individual phenophases. In recent decades, observed springtime warming has led to significantly earlier green-up in temperate deciduous forests. Furthermore, spring temperatures in Central Europe are projected to rise by 2–5°C by the end of the century, depending on the scenario. Such changes are expected to profoundly affect forest structure and functioning, including ecosystem processes such as water, carbon, and nutrient cycling. These shifts may, in turn, have far-reaching consequences for ecosystem productivity, food webs, and species interactions.

To improve our understanding of deciduous trees responses to temperature changes – and how such shifts may affect ecosystems – we examined the relationship between the onset of spring activity in silver birch (Betula pendula) and recent springtime temperature anomalies in Poland (2018–2024). This period includes several extreme spring seasons (e.g. 2018, one of the warmest on record), offering a unique empirical basis for evaluating how future climate conditions may influence temperate forest phenology.

The phenological data used in this study included both ground-based observations of leaf unfolding and satellite-derived estimates of the start of season (SOS) for silver birch, one of the most abundant deciduous tree species in Poland. Ground-based data were obtained from the Institute of Meteorology and Water Management – National Research Institute. The SOS metric was derived from Sentinel-2 imagery (10 × 10 m resolution), based on derivatives of the Enhanced Vegetation Index. Temperature conditions for individual seasons were assessed using in-situ measurements and a newly developed high-resolution gridded dataset (1 × 1 km) for Central Europe. The relationship between air temperature and the onset of the season was explored using both temperature anomalies and the Growing Degree Days index.

The study provides empirical evidence of the sensitivity of spring phenology in deciduous trees to temperature conditions in Central Europe, offering valuable insights into potential future shifts under ongoing climate change. Our findings show a significant advancement in silver birch phenology during exceptionally warm springs and notable delays during colder ones. Most importantly, the results suggest that not only the magnitude, but also the timing of temperature anomalies within the season plays a crucial role in shaping spring phenological responses.

How to cite: Sulikowska, A., Grabska-Szwagrzyk, E., Chmist-Sikorska, J., and Wypych, A.: Leaf-out in a warming climate: linking air temperature anomalies and silver birch phenology in Poland using ground and satellite data, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-588, https://doi.org/10.5194/ems2025-588, 2025.

Frost occurs almost every year in Slovenia and usually affects smaller, exposed areas, but sometimes also larger areas. Hoarfrost is a hydrometeor in the form of ice crystals that form by direct deposition on objects such as tree branches, plant stems, leaves or branches. It forms when air with a dewpoint temperature below freezing is saturated by cooling and is a major risk factor for agriculture, especially when it occurs during sensitive phenophases, particularly in late spring or early autumn. Although a spring frost risk assessment was carried out for several apple, sweet cherry and grapevine varieties in relation to their phenophases, a broader analysis of hoarfrost-susceptible locations and conditions has not yet been done for Slovenia. To determine the periods and locations with higher frost susceptibility, we first analyzed the frequency of cold days (days with a minimum temperature < 0°C), as the occurrence of temperatures below 0°C is not sufficient to guarantee the formation of hoar frost.

For the occurrence of hoarfrost and cold days, we analyzed the average annual and monthly values and their long-term variation as well as the extreme data over a period of 55 years (1971-2024). To analyse the spatial variability, we selected meteorological stations of the Slovenian national weather network that represent the variability of the climate in Slovenia and belong to different climate regions: Submediterranean climate region, Moderate climate of the hilly region, Subcontinental climate region and Subalpine climate region, with altitude ranging from 55 m to 864 m. The average multi-year number of days with hoarfrost is about 50 days/year at most locations, and the number of cold days exceeds the number of days with hoarfrost at a single station by twenty percent to three times the value. It is therefore important to monitor both parameters in order to assess the frost risk. The probability of cold days and hoarfrost days varies greatly between years and locations. Very often cold days and hoarfrost occur late in May and in the autumn as early as September, especially at higher elevations, and in extreme cases such events have been recorded even in June and August.

Monitoring and analyzing long-term values of hoarfrost and cold days and their temporal and spatial variability can help in frost forecasting so that farmers can take various measures against frost risk to prevent damage. A comprehensive frost management strategy should consider the early and main season as part of the farm's annual agrometeorological planning.

How to cite: Črepinšek, Z., Pantar, P., Žnidaršič, Z., and Pogačar, T.: Analysis of hoarfrost and cold days over the period 1971-2024 in Slovenia, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-636, https://doi.org/10.5194/ems2025-636, 2025.

Local environmental conditions fundamentally influence both the yield and quality of grapes, therefore wine regions have traditionally optimised these conditions through strategic varietal selection and viticultural practices. However, the sustainability of viticulture, especially in Portugal, faces a growing threat from climate change, with escalating temperatures, changing patterns of precipitation, and more frequent extreme weather events. Due to the significant impact of climate, particularly air temperature, on the growth, productivity, and life cycle stages of grapevines, many Portuguese wine regions are currently reaching or surpassing their ideal climate conditions for optimal grape production. This study assesses climate risks in Portugal's Wine Protected Denomination of Origin (PDO) regions by analysing climate extreme indices for historical (1981-2010) and future (2041-2070 and 2071-2100) periods under the high emissions Representative Concentration Pathway (RCP) 8.5 scenario. The results show a significant increase in temperature extremes, particularly in western regions, coupled with a decrease in precipitation and an intensification of drought extremes, increasing the risk of severe droughts. These climatic changes pose a direct threat to vine development, yields, and the typicity of regional wines, particularly in key regions such as Alentejo and Douro. To mitigate these challenges, this study highlights the importance of integrating climate information into viticultural decision-making. To effectively inform winemakers and guide their adaptation strategies, a crucial first step is identifying climate vulnerabilities at a regional scale, which will encompass refined vineyard management practices, selection of resilient grape varietals, and, as a last resort, the potential relocation of vineyards. By providing actionable insights into evolving climate risks, this study contributes to the long-term sustainability of Portuguese viticulture, ensuring the resilience of the Portuguese wine sector in an era of unprecedented environmental change.

Acknowledgments: Research funded by Vine & Wine Portugal—Driving Sustainable Growth Through Smart Innovation, PRR & NextGeneration EU, Agendas Mobilizadoras para a Reindustrialização, Contract Nb. C644866286-011. We acknowledge FCT – Portuguese Foundation for Science and Technology, under the project UIDB/04033 and LA/P/0126/2020 (https://doi.org/10.54499/UIDB/04033/2020).

How to cite: Fonseca, A., Fraga, H., and A. Santos, J.: Climate Change and Extreme Weather Events impacts on the Future of Viticulture in Portugal, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-10, https://doi.org/10.5194/ems2025-10, 2025.