In the past, the wine regions in the northern areas of Hungary represented the northern limit of viticulture due to climatic conditions. However, as a result of global warming, viticulture has expanded to regions significantly further north, such as Poland (Ziernicka-Wojtaszek and Zawora, 2007), the coastal areas of Germany (Schernewski, 2011), and Southern Scandinavia (Gustafsson and Mårtensson, 2005). Hungary is renowned for its diverse and historically significant wine regions, each offering unique terroirs influenced by varied climatic, geological, and topographical conditions. The country is home to 22 official wine regions, including internationally acclaimed areas such as Tokaj, Villány, and Eger.

Other notable wine regions include Sopron, with its proximity to Lake Neusiedl providing a unique microclimate, and Balatonfüred-Csopak, located near Lake Balaton, where the moderating effects of the lake support the production of high-quality whites such as Olaszrizling (Németh et al., 2014).

These regions differ significantly in their microclimates, soil types, and historical viticultural practices, making Hungary an exceptional location for examining the impacts of climate change on grape suitability. Each region’s unique climatic conditions are essential for understanding how temperature shifts may influence grape phenology, yield, and quality (Szenteleki et al., 2012).

The safe cultivation of grapes is typically associated with Mediterranean climate zones, where favorable thermal conditions provide a stable environment for grape growth. Jackson (2008) emphasized that these regions are delimited by 10°C and 20°C isotherms, reflecting the lower and upper bounds of grapevine physiological tolerances. Schultz and Jones (2010) further refined this definition, suggesting that the average temperature during the growing season should range between 12°C and 22°C for optimal viticultural conditions. Similarly, Van Leeuwen and Seguin (2006) highlighted the importance of cumulative heat units above a base temperature of 10°C, proposing a threshold of 1000°C during the growing season for successful grape cultivation.

Temperature is a primary driver of grapevine phenological development, with annual temperature variations exerting a significant influence on the timing of key growth phases (Jones and Davis, 2000; Jones et al., 2005; Cook and Wolkovich, 2016; García de Cortázar-Atauri et al., 2017). Research has consistently demonstrated that temperature not only governs phenological events but also directly affects berry composition and quality. These findings underscore the preeminence of temperature over soil characteristics or varietal factors in determining grape development (Van Leeuwen et al., 2004; Jones, 2006b).

Climatic requirements are critical determinants of both the quantity and quality of grape yields (Santos et al., 2010). Grapes, as heat- and sunlight-demanding crops, require high solar radiation and elevated temperatures during the vegetative period and berry ripening stages (Malheiro et al., 2010). As global temperatures rise, wine regions face increasing challenges, including potential shifts in traditional cultivation zones. Dunn et al. (2019) and Tóth and Végvári (2016) highlighted the prospect of viticultural boundaries extending poleward in both hemispheres, creating new opportunities in countries like Poland (Kunicka-Styczyńska et al., 2016), Sweden (Rauhut Kompaniets, 2022), Canada (Jobin Poirier et al., 2021), and the United Kingdom (Gannon et al., 2023). At the same time, traditional wine-producing regions may confront heightened risks of unsuitability due to excessive heat or reduced cold tolerance (Duchêne et al., 2010).

Temperature is a key factor influencing grapevine development, phenology, and suitability for wine production. Understanding how temperature variables such as the GDD-Winkler Index, Growing Season Temperature, Biologically Effective Degree Days, and Huglin Index change over time is crucial for assessing the future adaptability of grapevine varieties to specific regions. This study examines the past and future distributions of these temperature variables across 22 Hungarian wine regions, following international best practices.

Our study aims to analyse how the distribution of the four essential temperature variables used to assess grape suitability (AGST, GDD, HI, BEDD) will change in the near and distant future. Furthermore, we sought to determine how the suitability of wine grapes can be quantitatively defined if the average temperature during the growing season is known. Based on the studies by Jones et al. (2005) and Hannah et al. (2013), we know the optimal temperature range for the suitability of many wine grape varieties (21 varieties). The cultivation risk increases whenever the average temperature during the growing season deviates from the specified values, either higher or lower. In our investigations, we determined the probability that the average temperature during the growing seasons from 2031 to 2100 would be optimal for the given grape variety, providing a comprehensive assessment of future cultivation conditions. Additionally, we sought to determine how much the cultivation risk for wine grape varieties changes if the average temperatures of the growing seasons increase, i.e., if the temperatures are lower or higher than the optimal temperature requirements of the given wine grape variety. The physiological processes of grapevines occur within the temperature range of 5–35°C (Gladstones, 1992; Mullins et al., 1992). This range provides the theoretical basis for assessing grapevine suitability under varying climatic conditions. Building on the research findings of Jones (2006a); Jones et al. (2012); Jones (2015), and Van Leeuwen and Darriet (2016), we developed an impact function to evaluate the adaptability of wine grape varieties to different growing conditions.

The FORESEE 4.2 database incorporates data from 14 regional climate models of the EURO-CORDEX initiative, which adhere to the RCP4.5 and RCP8.5 scenarios and utilize a uniform bias correction methodology. Despite sharing these characteristics, the models differ in their physical parameterizations and climate projections. For example, IPSL-RCA4 exhibited the smallest bias in temperature and precipitation, while HadGEM2 projected the most significant summer droughts, highlighting the importance of ensemble-based assessments to capture uncertainties.

Additionally, to estimate the past and future climatic suitability of Hungarian wine regions, we utilized multiple datasets from the FORESEE system. The FORESEE-HUN v1.0 database (1971–2022) provided interpolated daily meteorological data at a 0.1° x 0.1° resolution, created using data from the Hungarian Meteorological Service (HUCLIM). Future projections were derived from FORESEE 4.0, which integrates 28 bias-corrected climate models, including the 14 models of the CORDEX experiment under the RCP4.5 and RCP8.5 scenarios (Kern et al., 2024). Using these datasets, we analyzed the distribution of four temperature indices (AGST, GDD-Winkler index, HI, BEDD index) across 22 Hungarian wine regions.The database covers the entire territory of Hungary and contains 2070 pixel data points per variable and model. The database specific to the 22 wine regions includes 300 pixels. The geographical location of Hungary and its 22 wine regions is illustrated in Figure 1 , providing a visual representation of the study area and the spatial distribution of the wine regions analyzed in this study.

To evaluate the climatic suitability of grape cultivation in Hungarian wine regions, we focused on four temperature indices widely used in viticultural studies. These indices provide a quantitative framework for assessing the thermal conditions necessary for grapevine development, yield, and quality, and in this case, for quantitatively evaluating the suitability of viticulture. Below, we define these indices and explain their significance in the context of this study.

AGST (Average Growing Season Temperature):

GDD-WI (Growing Degree Days - Winkler Index):

HI (Huglin Index):

BEDD (Biologically Effective Degree Days):

In this study, we examined the climatic suitability of grape cultivation across 22 official Hungarian wine regions, each characterized by distinct climatic, geological, and topographical conditions. Below, we provide an overview of the key grape varieties and their unique adaptations in the major wine regions.

To quantitatively evaluate the climatic suitability of Hungarian wine regions for different grape varieties, we developed a temperature-based suitability function. This approach allows us to assess how well the average growing season temperature (AGST) aligns with the optimal temperature requirements of each grape variety. Below, we present the methodology for calculating suitability values, which provides a numerical framework for comparing climatic conditions across regions and time periods.

The suitability values (S) were calculated using a temperature-based suitability function that evaluates the average growing season temperature (AGST) relative to the optimal temperature range of each grape variety. The suitability function S(T) is defined as follows:

Where:

This index provides a numerical value between 0 and 1, representing the degree of climatic suitability for a specific grape variety.

This study examined the climatic suitability of 22 official Hungarian wine regions, each characterized by distinct climatic, geological, and topographical conditions. The regions represent a wide range of viticultural diversity, including unique grape varieties that have adapted to local conditions over centuries. Below is a detailed overview of the main grape varieties cultivated in the major wine regions included in the analysis:

Tokaj Wine Region:

o Key Grape Varieties: Furmint, Hárslevelű, Sárgamuskotály (Muscat Lunel)

o Description: Tokaj, located in northeastern Hungary, is world-renowned for its Aszú wines, primarily made from Furmint and Hárslevelű grapes affected by noble rot. These varieties thrive in volcanic soils and a microclimate characterized by warm summers and cool autumns, which are ideal for the slow ripening required for high-quality dessert wines (Fazekas et al., 2022).

Villány Wine Region:

o Key Grape Varieties: Kékfrankos, Cabernet Franc, Merlot, Cabernet Sauvignon

o Description: Villány, in southern Hungary, is the country’s warmest wine region. It specializes in red wines, with Cabernet Franc becoming the flagship variety. Long, hot summers and mild winters provide excellent conditions for full-bodied red grape varieties (Mód and Simon, 2012).

Eger Wine Region:

o Key Grape Varieties: Kékfrankos, Leányka, Hárslevelű, Olaszrizling

o Description: Situated in northern Hungary, Eger is celebrated for Egri Bikavér (Bull’s Blood), a red wine blend often based on Kékfrankos, and increasingly for its white varietals such as Leányka and Hárslevelű. The region’s diverse soils and temperate continental climate allow for a wide range of grape cultivation (Bálo et al., 2014).

Sopron Wine Region:

o Key Grape Varieties: Kékfrankos, Zweigelt, Pinot Noir

o Description: Located near Lake Neusiedl, Sopron benefits from a unique microclimate with relatively mild winters and cool summers. Kékfrankos dominates the region, producing vibrant, fruit-forward red wines (Németh et al., 2014).

Balatonfüred-Csopak Wine Region:

o Key Grape Varieties: Olaszrizling, Szürkebarát (Pinot Gris), Sauvignon Blanc

o Description: Positioned along the northern shore of Lake Balaton, this region is known for its high-quality white wines, particularly Olaszrizling. The lake’s moderating effects create a favorable climate for producing crisp, aromatic wines (Szabó and Závodi, 2018).

Other Notable Regions:

o Mátra: Known for its aromatic whites, such as Muscat Ottonel and Tramini.

o Szekszárd: Specializes in red blends similar to Eger, with Kadarka and Kékfrankos playing prominent roles.

o Badacsony: Famous for Olaszrizling and Kéknyelű, a unique variety found almost exclusively in this region (Hlédik and Harsányi, 2019).

Grape Variety Adaptation and Climatic Considerations

The grape varieties cultivated in these regions reflect the diverse climatic conditions of Hungary, ranging from the cool, continental climate of Tokaj to the Mediterranean-influenced climate of Villány (Hajdu, 2018; Czigány et al., 2020). This diversity makes Hungary an ideal study area for assessing how temperature shifts may impact grape phenology, yield, and quality ( (Fraga et al., 2012).Each grape variety has specific temperature thresholds for optimal ripening, which were factored into our analysis to evaluate future cultivation risks and opportunities (Van Leeuwen and Seguin, 2006).

We determined the values and distributions of the examined unique temperature indices, which are the Averege Growing Season Temperature (AGST), Growing Degree Days (GDD), Huglin Index (HI), Biologically Effective Degree Days (BEDD), and.

These indices were used to assess the suitability of wine grape varieties under different climatic scenarios.

The results are presented for three time periods used in the IPCC reports (IPCC, 2014). The reference values are characterized by the period from 1986 to 2005. Future changes relative to this period are presented for two time periods: the near future (2016-2035) and the distant future (2081-2100). In our analyses, we consistently follow these time scales. Additionally, we examine in detail how the heat requirements for 21 wine grape varieties will be met in the future. These are presented for 10-year periods, showing the probability that the average temperatures during the growing seasons fall within the specified optimum interval. Furthermore, we determined the probabilities of average temperatures falling below or above the optimum interval. Finally, based on previous research findings, we developed an impact function that allows us to estimate the cultivation suitability of wine grapes within the temperature range of 5-35°C.

The equations, class intervals, and names of the temperature indices used in the study are presented in Table 1 .

A problem with using the GDD-Winkler index is that the Region I-V classification is not used in every wine-producing country. Therefore, it may be more appropriate to classify different growing regions into the following climate classes, as shown in Table 2 .

To illustrate temporal changes in AGST, we introduced the Dynamic AGST function or DAGST function. This method allows us to track decade-by-decade how the average temperature of the growing season will change in the future and how this relates to the optimal temperature requirements of the 21 examined grape varieties. By considering the most pessimistic case for the 22 Hungarian wine regions and the 14 examined models, using data from the two climate scenarios (RCP4.5 and RCP8.5), we can assess whether all Hungarian growing sites will remain suitable for cultivating the main grape varieties in the future.

For 21 wine grape varieties, optimal temperature ranges were determined using the functional approach of Jones et al. (2005) and the numerical values provided by Hannah et al. (2013). These ranges were used to create class intervals for each variety, allowing for the analysis of the likelihood that the average temperatures during the growing seasons fall within the specified optimum intervals.

We analysed the frequencies of the four climatic variables studied over three periods. The class intervals with the highest frequencies show a clear shift towards warmer intervals in the future ( Table 3 ). Based on AGST, Hungarian wine regions have predominantly belonged to the “warm” range in the past; however, in the future, we can expect the most frequent occurrences to be classified as “hot” vintages. This indicates a significant impact on the thermal suitability of grape varieties across Hungarian wine regions, emphasizing the necessity for adaptive strategies. The GDD-Winkler index shows a similar warming trend, with historical “intermediate” conditions (Region II) transitioning to “warm” vintages (Region III) in the near future and predominantly “hot” vintages (Region IV) by the end of the century.

The Huglin index supports these findings, showing that historically “temperate” regions will shift to “warm temperate” or even “warm” conditions in the future, reflecting global warming’s impact on viticulture. Similarly, BEDD values are projected to increase, with the most frequent range shifting from 1200–1400°C in the past to 1400–1600°C in both the near future and the distant future. In the near future, and even more so in the distant future, we can expect the BEDD sums during the growing season to range between 1400–1600°C.

We analysed the distribution of the studied temperature variables that will change in the near and distant future compared to the recent past (1986-2005) as a reference period. The following observations can be made:

For AGST, the occurrence frequencies of the “intermediate” and “warm” climatic class intervals will decrease in the near future. However, the decrease will not exceed 15%. However, in the distant future, the decrease will exceed 30%. The frequency of “hot” climatic vintages will increase by more than 15% in the near future. In contrast, in the distant future, the “hot” climatic class interval will occur 50% more frequently than in the past. Additionally, in the distant future, the frequency of “very hot” vintages will increase by more than 20% compared to historical data ( Figure 2A ).

The GDD-Winkler index also supports the prediction of definite future warming. In Hungarian wine regions, the occurrence frequency of “intermediate” climatic conditions, characteristic of Region II, will decrease by more than 25% in the near future. In contrast, the frequency of “hot” climatic vintages, characteristic of Region IV, will increase by more than 15%. These changes will significantly intensify in the distant future compared to historical data. The probability of “intermediate” climatic vintages, characteristic of Region II, will decrease by more than 50%.

In contrast, the occurrence of “warm” vintages, characteristic of Region III, will decrease by 15%. Conversely, the occurrence of “hot” climatic vintages, characteristic of Region IV, will increase by more than 35%. The occurrence of “very hot” climatic vintages, characteristic of Region V, will increase by 30% in the distant future ( Figure 2B ).

In the near future, the frequency of HI values characteristic of “temperate” climatic areas will decrease by more than 20%. Compared to past values, “warm” climatic effects will increase by more than 15%. In the distant future, the frequency of “temperate” climatic vintages will decrease by more than 40%, and the probability of “warm temperate” vintages will decrease by more than 20%. Meanwhile, the likelihood of “warm” vintages will increase by more than 30%, “very warm” vintages by more than 25%, and the probability of “too hot” vintages will increase by more than 10% in the distant future ( Figure 2C ).

In the near future, the occurrence frequency of vintages with a BEDD between 1200 and 1400 will decrease by more than 25%, while the probability of vintages with a BEDD between 1400 and 1600 will increase by more than 25%. In the distant future, these changes will intensify: the occurrence frequency of vintages with a BEDD between 1200 and 1400 will decrease by more than 60%, while the probability of vintages with a BEDD between 1400 and 1600 will increase by more than 40%, and the likelihood of vintages with a BEDD between 1600 and 1800 will increase by more than 25% ( Figure 2D ).

In the following, we will provide a detailed analysis of how the spatial patterns of the four examined temperature variables (AGST, GDD, HI, and BEDD) have changed in Hungary’s wine regions compared to the 1986–2005 baseline period. The changes are presented for a near future period (2016–2035) and a distant future period (2081–2100) ( Figure 3 ).

The exploration of spatial differences can play a crucial role not only in shaping the future viticultural strategies of the wine regions but also in influencing the economic and cultural development trajectories of these areas. These data help us better understand how individual wine regions will be able to adapt to the new conditions brought about by climate change and to what extent they will be able to do so.”

Figure 3A illustrates the regional distribution of changes in temperature indices (AGST, GDD, HI, BEDD) across Hungary’s wine regions compared to the reference period 1986–2005.

Overall, the data suggest that changes in temperature indices tend to increase more significantly in eastern wine regions compared to western regions.

Figure 3B illustrates the regional distribution of changes in temperature indices (AGST, GDD, HI, BEDD) across Hungary’s wine regions compared to the reference period 1986–2005 for the distant future.

Unlike the near future (2016–2035), where regional differences were more pronounced, the distant future (2081–2100) shows a tendency for decreased regional disparities in AGST, GDD, and HI. However, BEDD exhibits a contrasting trend, with its differences increasing between regions. Northern wine regions also tend to experience stronger warming compared to southern ones.

For the 22 Hungarian wine regions, we produced projections for seven decades, covering the period from 1931 to 2100, showing how the AGST values will change in the future based on the most pessimistic, optimal, and average of the 14 models. The most pessimistic change refers to the model result that shows the highest temperature increase over the seven decades across the 22 wine regions. The most optimal change refers to the model result that shows the smallest temperature increase from 1931 to 2100 across the 22 wine regions. Under the RCP4.5 scenario, this could even mean a decrease.

For the RCP4.5 scenario, the HadGEM2-CCLM model was the most pessimistic for the Hajós-Baja wine region. At the same time, the most optimistic change was seen with the NCC-HIRHAM5 model in the Kunság wine region. In this case, the most optimal change represents a decrease, with the AAGST value during the growing season decreasing by 0.8°C over seven decades. The observed differences in AGST projections between the most optimistic, the most pessimistic, and the ensemble average models during the 2031–2040 period can be attributed to several factors. Firstly, the early projection period is particularly sensitive to systematic biases caused by the transition from observation-based historical data to modeled projections. Secondly, internal climate variability has a stronger influence on shorter periods, such as a single decade, amplifying model differences. Additionally, variations in regional parameterization and model sensitivity to greenhouse gas emissions contribute to these deviations. These factors emphasize the importance of ensemble averages for providing balanced and robust projections.”

However, even under the RCP4.5 scenario, the most pessimistic model shows an increase of nearly 2.0°C ( Figure 4A ).

Under the RCP8.5 scenario, the HadGEM2-RACMO22E model was the most pessimistic for the Sopron wine region. In contrast, the MPI-REMO2009 r1 model showed the most optimistic AGST change in the Balatonfüred-Csopak wine region. For the most optimistic change, the average AGST value during the growing season increases by 1.0°C over seven decades. However, the most pessimistic model indicates an increase of more than 4.0°C ( Figure 4B ).

The studies by Jones (2006a), Van Leeuwen et al. (2013), and Hannah et al. (2013) predominantly describe a static correlation between the Averege Growing Season Temperature (AGST) and the suitability of grapevine varieties. These studies highlight the AGST values for specific locations over a defined period, juxtaposed with the average heat requirement ranges of key grapevine varieties. Each grapevine variety is optimally cultivated within a defined temperature range, beyond which its viability is compromised. Specifically, if the mean AGST at a given location falls below or exceeds the temperature range required by a particular grape variety, the cultivation of that variety is deemed unsuitable for the site.”

The Dynamic Average Growing Season Temperature (DAGST) calculation method allows us to track decade-by-decade changes in the average temperature of the growing season in the future and assess how these relate to the optimal temperature requirements of the 21 examined grapevine varieties. Using data from 22 Hungarian wine regions and 14 climate models, along with two radiative forcing scenarios (RCP4.5 and RCP8.5), we can analyze how the average temperature of the growing season evolves under the most optimistic and most pessimistic scenarios. Furthermore, we can evaluate whether, according to the 14 model results, all Hungarian growing sites will remain suitable for cultivating the main grapevine varieties in the future. Based on the three scenario types (most optimistic, most pessimistic, and the 14 climate model results) and the two radiative forcing scenarios (RCP4.5 and RCP8.5), we can illustrate the progression of six DAGST functions for the period 2031–2100, alongside the optimal temperature ranges of 21 grapevine varieties ( Figure 5 ).

The results highlight the following:

Knowing the optimal temperature requirements of the 21 examined wine grape varieties, we calculated the probability that the average temperatures during the growing seasons will fall within the optimal intervals specified for each variety over 10-year periods. Additionally, we determined the probabilities of average temperatures falling below or above the optimal intervals ( Figure 6A ). These probabilities were calculated for three different temperature class intervals from 2031 to 2100 under two emission scenarios (RCP 4.5 and RCP 8.5).

However, claiming that these grape varieties could not be cultivated in such years would be an exaggeration. In practice, grape varieties are often cultivated beyond their optimal temperature ranges, even when the long-term average temperature of the growing season exceeds their preferred range. We also cultivate grape varieties whose optimal temperature range is lower than the current long-term average temperature of the growing season.”

The probability of occurrence within the optimal temperature interval generally decreases for most of the 21 examined grape varieties from the near future (2031-2040) to the distant future (2091-2100) ( Table 4 ). However, for the high heat-demanding varieties such as Carignane, Zinfandel, and Nebbiolo, there is an observed increase in the frequency of optimal temperatures towards the distant future under the optimistic RCP 4.5 scenario.

The physiological processes of grapevines occur within the temperature range of 5–35°C (Gladstones, 1992; Mullins et al., 1992). Utilizing and further developing the research findings published by Jones (2006c); Keller (2010); Jones et al. (2012); Jones (2015), and Van Leeuwen and Darriet (2016), we created an impact function. This function calculates a value between 0 and 1 within the 5–35°C range, based on the average temperature during the growing season (AGST), to quantitatively assess the suitability of wine grape varieties ( Figure 6B ).

The calculated suitability values S(T) provide a quantitative measure of climatic suitability for grape varieties under varying temperature conditions. Historical data show that most varieties in Hungarian wine regions exhibit S-values within the optimal range, consistent with current viticultural practices. For future scenarios, high S-values (above 0.8) align with observations from other regions, where successful grape cultivation persists despite average growing season temperatures exceeding the optimal range (e.g., Burgundy and the Rhone Valley) (Van Leeuwen et al., 2013). It should be noted that the suitability index does not explicitly define what specific S-values (e.g., 0.95, 0.9, 0.85) correspond to in terms of cultivation security or yield quality. These interpretations require additional empirical data and validation, which were beyond the scope of the current study. Future research could focus on linking S-values to specific levels of production risk or quality assurance.The decadal changes in suitability values calculated by the introduced temperature impact function for grape varieties are shown in Table 5 . The results indicate that for lower heat-requirement grape varieties, such as Muller-Thurgau, the suitability value does not drop below 0.71 from the current 0.83 by the end of the century, even under the pessimistic RCP 8.5 scenario. Under optimistic scenarios, the decrease in suitability values for lower heat-requirement grape varieties is a maximum of 3-4%, representing a relatively small change. Meanwhile, for higher heat-requirement varieties, such as Zinfandel or Nebbiolo, the temperature suitability for cultivation may improve by 1-2%.

According to the more optimistic RCP 4.5 scenario, the average temperature during the vegetation period in Hungarian wine regions could rise by approximately 0.6-0.7°C over the next seven decades. The most significant increase in AGST (Average Growing Season Temperature) is expected in the Csongrád wine region. At the same time, the slightest change is anticipated in the Sopron wine region ( Figure 7A ). Under the more pessimistic RCP 8.5 scenario, the average temperature increase over the next seven decades is expected to exceed 2.0°C across Hungarian wine regions. The most significant growth, over 2.5°C, is expected in the Csongrád wine region. In contrast, the slightest change, 2.3°C, is expected in the Pannonhalma wine region ( Figure 7B ).

The temperature differences due to the nature of specific climate models are significantly higher when considering regional differences. Under the RCP 4.5 scenario, the temperature differences between the models can reach up to 3°C. The highest average temperature during the vegetation period for the period 2031-2100 (2.2°C) is projected by the HadGEM2-CCLM model, while the EC-EARTH-HIRHAM5 model suggests a decrease in the average temperature during the vegetation period by 0.8°C over the next seven decades ( Figure 7C ). Under the RCP 8.5 scenario, the HadGEM2-RACMO22E model projects an average temperature increase of 3.8°C, whereas the MPI-REMO2009 r1 model projects that the average temperature during the vegetation period over the next seven decades will barely exceed 1.0°C ( Figure 7D ).

According to our study’s climate model results, certain Hungarian wine regions might experience vintages with average growing season temperatures exceeding 21°C in the future. This highlights the potential impacts of global warming on the suitability of winegrape varieties in these regions.The study confirmed that the temperature and heat indexes used to assess the suitability for grapevine cultivation show a definite increase in the near and distant future. The increase compared to historical values is expected to reach 25-50% in the distant future, indicating that ‘warm’ and ‘hot’ climatic conditions will become significantly more common in Hungarian wine regions.

The biologically effective heat sum is expected to increase markedly, which indicates that it will be possible to cultivate grape varieties with higher heat requirements more safely in Hungarian wine regions. In the distant future, there will also be opportunities to cultivate grape varieties that are not currently grown and better tolerate high temperatures and stress, such as Grenache, Syrah, and Tempranillo.

The results show that grape varieties with higher heat requirements, such as Grenache, Carignane, Zinfandel, or Nebbiolo, will be safely cultivable in Hungarian wine regions even under the most optimistic scenarios. However, according to the most pessimistic scenario and models predicting the most significant temperature changes, even the higher heat-requiring grape varieties might experience a slight decrease in suitability by the end of the century in some Hungarian wine regions.