Péter Szabó

Climate change is expected to substantially alter wildfire risk, increasing the need for reliable long-term projections to support disaster risk assessment and climate adaptation planning. However, human-induced fires—particularly agricultural burning—can obscure the relationship between weather conditions and fire occurrence, leading to biased risk estimates.This study develops an empirical-statistical framework to model and project wildfire occurrence risk, explicitly incorporating human influences. The model combines satellite-based fire detections, the Keetch-Byram Drought Index as a meteorological predictor, and land cover information to represent vegetation and land use characteristics. A key innovation is the inclusion of a Human Factor proxy derived from Google Trends data, capturing changes in legislation, public awareness, and fire-related behaviour.The framework is calibrated and evaluated using high-quality, homogenized gridded observations for Hungary at 5 km spatial resolution over the period 2001-2024, providing a robust test case with reliable input data. While the analysis focuses on this region, the methodology is designed to be transferable to other regions with comparable data availability.Results show that accounting for human influences improves model performance, reduces omitted variable bias, and restores the expected positive relationship between drought conditions and wildfire risk. Projections under a high-emission climate scenario indicate that average fire occurrence risk may substantially increase by late-century, with extreme years potentially experiencing several-fold increases, assuming no changes in current human prevention efforts or land cover flammability.The findings highlight the importance of integrating socio-environmental drivers into wildfire risk modelling and provide a framework for long-term disaster risk assessments in climate-sensitive regions.

Precipitation and drought conditions play a key role in agriculture, so the regional and local adaptation strategies for the coming decades need information on how these climatic conditions tend to change due to global warming. For this purpose, the results of regional climate model (RCM) simulations from the EURO-CORDEX initiative are analyzed to estimate the possible future trends until the end of the 21st century. In order to take into account the uncertainty arising from the anthropogenic factors (e.g. greenhouse gas emissions, land use changes, population), three different RCP scenarios (i.e. RCP2.6, RCP4.5, RCP8.5) are taken into consideration representing immediate mitigation, mitigation from 2040, and business-as-usual future pathways, respectively. The study analyzes the changes in seasonal precipitation, seasonal number of dry days, and seasonal maximum of consecutive dry days by mid-century (2041-2060) and late-century (2081-2100) relative to the reference period (2001-2020) in Southeastern Europe, i.e. a major Mediterranean region between the Adriatic and the Black Sea. The difference between the RCM simulations enables us (i) to assess the uncertainty of the projections, and (ii) to identify robust likely changes in the region. Thus, stakeholders and decision-makers are provided with relevant information for future planning.Acknowledgements: Research leading to this study has been supported by the European Climate Fund (G-2309-66801), the Hungarian National Research, Development and Innovation Fund (K-129162), and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014).

Understanding sub-daily temperature variations is crucial in changing climate, especially as the diurnal temperature range (DTR) serves as a sensitive indicator of local and regional climatic shifts. DTR tends to be higher in arid regions, and its amplification directly affects human health – particularly cardiovascular and respiratory conditions – as well as agricultural productivity and energy demand. Rapid temperature changes within a day can stress crops, increase respiratory activity in plants, and result in spikes in heating or cooling requirements. This study investigates sub-daily temperature dynamics over South-East Europe using 3-hourly temperature data from the ERA5-Land reanalysis (1971–2024) and high-resolution (the atmosphere on 25 km) CMIP6 climate model simulations (1971–2050). The focus is on characterising temporal trends and potential climatic drivers behind observed and projected changes of at least 4-10 °C within 3 hours. Preliminary results reveal a notable increase in large positive sub-daily temperature changes – especially during transient months (March, April, September, October) – over the Pannonian Basin, predominantly during warm periods. Furthermore, an increase in large negative temperature shifts is detected from February to September, often associated with warm spells and precipitation events following warm spells. These findings suggest an evolving pattern of intra-day thermal variability, influenced by seasonal warming and atmospheric instability. The analysis highlights the role of cloud cover, soil moisture, relative humidity, and dew-point temperature as contributing factors. Changes in these parameters influence both the magnitude and direction of sub-daily temperature shifts. Understanding these mechanisms is essential for developing adaptation strategies in agriculture, urban planning and public health sectors.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. In addition, this study has been supported by the European Climate Fund (G-2409-68866).

Adapting to climate change is already essential in the near future, thus necessitating a good understanding of expected changes by relevant sectors. For instance, severe thunderstorms pose significant economic risks and threats to human life as well as to critical infrastructure, but their detailed analysis is still quite challenging. Recent advancements in climate models have improved spatial resolution, enabling explicit descriptions of thunderstorm formation and development. However, the number of such high-resolution simulations remains limited. To overcome the resolution limitations, several convective parameters (e.g. convective available potential energy, convective inhibition, bulk wind shear, lapse rate, precipitable water, thunderstorm intensity parameter) are commonly used in weather forecasts and hazard warnings to characterize hazardous weather conditions, but their application on a climate scale is hindered by substantial storage and computational demands.Within the CORDEX (Coordinated Regional Climate Downscaling Experiment) framework, model simulation results are available for the entire European region at a fine resolution of 10 km. The aim of our research is to create the climatology of convective parameters based on an ensemble of regional climate models (RCMs), which can be used to explore changes in convective hazards due to climate change over the century. The study starts with the ERA5 reanalysis, from which we determine whether any trend can be detected in the different European subregions. Also, the RCMs have to be validated for the past from the convective processes’ point of view. Then, the future changes and trends are calculated for the available scenarios until the end of the 21st century.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. We acknowledge the Digital Government Development and Project Management Ltd. for awarding us access to the Komondor HPC facility based in Hungary. In addition, this study has been supported by the European Climate Fund (G-2409-68866).

Although anthropogenic global warming is well-known within the scientific community, the public is still not certain or even misled on how to associate specific local climate events to this global issue. Therefore, it is essential to raise public awareness by providing sound, graphical, interesting, and easily understood scientific information. Our attribution project was initiated in September 2021, and aimed at this task for Hungary. For this purpose, seasonally relevant indicators were calculated and published in each season near the time of a corresponding event occurrence, and the dissemination was done via a national platform aiming for climate awareness (www.masfelfok.hu). In addition, the public is also reached through the republishment of various media platforms, and the social media networks are used as well.The following major issues/indicators were evaluated so far: snow frequency, cold winter anomalies, sleet, fog, vegetation start for cold-resistant and warm-demanding plants, late spring frosts and frost around blooming, heatwaves (using different thresholds), late summer-like conditions in autumn, grape stress factors, drought conditions (e.g. Forest Aridity Index, De Martonne Index, Pálfai Aridity Index, consecutive dry days), fire weather index, human comfort index (UTCI), heating and cooling degree days, precipitation extremes, etc.The analyses were performed using several data sources with at least daily temporal resolution: (1) an ensemble of CMIP6 global climate model simulations of both natural-only forcings and historical runs with around 1° resolution, (2) an ensemble of regional climate model simulations from EURO-CORDEX with 0.11° resolution, including the RCP2.6, RCP4.5, and RCP8.5 scenarios, (3) a fine-resolution (0.1°), homogenized observation-based gridded database (i.e. HuClim) for Hungary updated yearly, (4) a fine-resolution (0.1°), but not homogenized observation-based database (i.e. E-OBS) for Europe, (5) ECMWF Reanalysis data (ERA5 with 0.25° or ERA5-Land with 0.1° resolution) for those variables that are not available in the purely measurement-based HuClim.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. In addition, this activity has been supported by the European Climate Fund (G-2409-68866).

Droughts may severely impact several different sectors, including drinking water availability, agricultural production, and energy supply. Due to climate change (CC), temperature is projected to increase on average, while the temporal distribution of precipitation is estimated to change, i.e. more heavy precipitation events and longer dry periods are likely to occur in Central Europe. In Hungary, which is the target area of this study, drought occurs from time to time, as a natural and CC-induced phenomena. To be prepared for the changes and to make adaptation strategies in time, the quantification of future changes is necessary. For this purpose, the modified Pálfai drought index (PaDI) is calculated for Hungary for the period 1975–2100. In the period 1975–2022, according to the observation-based HuClim dataset, a serious drought occurred in 2022 and heavy droughts in three years (1992, 2003 and 2012) over the Great Hungarian Plain. Future trends were projected using six climate model simulations from the EURO-CORDEX initiative under three RCP scenarios (RCP2.6, RCP4.5, and RCP8.5). According to our results, the difference between the radiative forcing’s change of the different scenarios is smaller in the near future; however, by the end of the 21st century, scenarios play a key role in the projected changes. More specifically, the average spatial fraction of heavy drought by 2081–2100 in the case of RCP2.6, RCP4.5 and RCP8.5 is projected to be 3%, 10% and 17%, respectively, compared to 6% in the 2001–2020 reference period. The most exposed area to heavy drought is the Great Hungarian Plain, especially its southern regions. Mitigation of climate change (e.g. irrigation, shift of sowing time or even shift of crop cultivars) should be the main aim to prevent the increase of frequency and severity of droughts, which may otherwise induce adverse effects on e.g. crop yields and water supply.

Understanding sub-daily scale temperature variability can be used for evaluating the impacts of climate change on human health, agriculture and daily life. In particular, higher temperature fluctuations (within a day, or from one day to another) increase physiological and psychological stress, demanding more frequent adaptation in areas such as clothing choices and energy management. The Pannonian Basin, encompassing Hungary, provides an ideal setting for this analysis due to its distinctive climate, well-defined four seasons, and sensitivity to global warming, which amplify the effects of temperature variability.This study focuses on diurnal temperature range (DTR), inter-day temperature variability, and intra-day temperature changes using various thresholds. These metrics are analyzed on monthly and seasonal scales. Historical (1971-2024) DTR and inter-day variability were derived from the homogenized, high-resolution HuClim database using daily mean, maximum and minimum temperatures. For intra-day changes, we utilize hourly temperature data from ERA5-Land, a reanalysis product. Future projections are derived from an ensemble of EURO-CORDEX regional climate model simulations, encompassing multiple scenarios: RCP2.6 (limiting global warming to 2 °C), RCP4.5 (moderate mitigation), and RCP8.5 (business-as-usual).Preliminary results indicate an increase in DTR and inter-day temperature variability across all months, especially in spring and late summer. Intra-day temperature changes show substantial increases during spring and minor changes during winter. Positive intra-day temperature changes peak in spring, while negative changes are more frequent in summer. These findings highlight the growing temperature volatility in the region, emphasizing the need for adaptive strategies in agriculture and human health to moderate the impacts of climate change.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. In addition, this study has been supported by the European Climate Fund (G-2409-68866).

Winter phenomena such as fog and freezing rain can significantly impact our daily lives by creating hazardous conditions for transportation and other outdoor activities. Dense fog reduces visibility, leading to traffic disruptions and potential accidents on roads, while freezing rain leaves surfaces with a layer of ice with high risks of falls and slide resulting in personal injuries, in addition, both can disrupt air travel as well. The Carpathian Basin can experience an increased occurrence and persistence of fog due to its unique geographical features, such as low-lying areas, lower wind speed, and river valleys that facilitate temperature inversions. Freezing rain is also prevalent in the Carpathian Basin when raindrops of warmer air masses from the Mediterranean fall through a sub-freezing, inversional layer of air before reaching the ground.To assess these impacts, we created a methodology based on daily, gridded data sets: we analyzed daily minimum and mean temperature, mean relative humidity, and wind speed for the fog from the best available, homogenized, high-resolution HuClim observational database. For the freezing rain, we collected hourly variables of temperature, total precipitation, and snow from the high-resolution, observation-based but modeled reanalysis of ERA5-Land. For the future, we assessed corrected, daily variables from an ensemble of EURO-CORDEX regional climate model simulations. Several scenarios were taken into account for the effects of human activity: RCP2.6 is a scenario aiming at 2 °C global warming by 2100, RCP4.5 urges strong mitigation from 2040, while RCP8.5 is a non-mitigation scenario.Results suggest that the number of foggy days slightly decreased over parts of the area of interest in the last few decades, but freezing rain did not change remarkably. Regarding the future, the days with fog would decrease significantly following the RCP8.5 scenario, especially by the end of the 21st century, while they would not change much with the RCP2.6. These are one of the rare positive impacts of regional climate change, however, it does not compensate for the adverse effects of anthropogenic climate change.

In addition to the historically sensitive Mediterranean regions, northern parts of Southeast Europe are increasingly vulnerable to forest fires exacerbated by climate change. Higher temperatures, more frequent heat waves, and erratic rainfall patterns in the region foster conditions conducive to swift wildfire ignition and propagation. Human-induced factors further exacerbate the risk, while the ecological consequences of these fires are far-reaching, affecting biodiversity and human lives.The Forest Fire Danger Index is a tool for assessing wildfire risk under very dry soil conditions. It incorporates factors besides soil dryness such as daily wind speed, mean temperature, and humidity to assess the potential risk for wildfires. Elevated wind speed can hasten fire propagation, while low humidity and high temperatures increase the likelihood of ignition and accelerate spread in arid regions. To calculate soil dryness specifically developed for fire controls, we analyzed the widely-used Keetch-Byram Drought Index, which relies on daily precipitation, maximum temperature, and effectively captures the soil's evaporation-precipitation balance.For the calculations, we assessed E-OBS version 29, a state-of-the-art, quality-controlled and interpolated observational dataset on 0.1° horizontal resolution for the reference period of 1971–2023. For the future, we used an ensemble of regional climate model simulations from the Euro-CORDEX initiative, which takes into account future anthropogenic activity through three distinct RCP scenarios until 2100 (RCP2.6, RCP4.5, and RCP8.5).Results indicate that regions historically experiencing infrequent severe compound wildfire events, such as most of the northern lowland areas in Romania, Bulgaria, Serbia, Hungary, or Croatia, are exposed to significant changes with global warming. Particularly after 2060 in the case of the non-mitigation scenario of RCP8.5 compared to the immediate mitigation of RCP2.6. Consequently, these possibly high impacts require a substantial investment in fire monitoring, education, and a warning system in these countries as well.Acknowledgments: Research leading to this study has been supported by the European Climate Foundation (G-2309-66801), the Hungarian National Research, Development and Innovation Fund (K-129162), and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014).