Analysis of hot and dry compound events in Hungary in 1971-2025

The Carpathian Basin is identified as one of the climate change hotspots in Europe. According to the latest data from the Copernicus Climate Change Service (C3S), the European continent – including Hungary – has already warmed by approximately 2.4 °C compared to the pre-industrial period (1850-1900), accompanied by more frequent extreme weather events. This substantial warming justifies the aim to focus on the detailed analysis of summer heat waves and droughts, especially their simultaneous occurrence. As demonstrated by the exceptionally hot and dry summer of 2022 in Hungary, the cumulative impact of these events poses severe consequences for agriculture, water management, and public health.

The main goal of our research is to explore the relationship between hot and dry periods in Hungary using homogenised, gridded daily maximum temperature and precipitation data from the HuClim database (0.1° spatial resolution) for the period 1971-2025. To investigate the spatial behaviour of the dependence strength between the monthly extremes of the base variables, a detailed cross-correlation analysis was completed. First, we analysed the spatial structure of monthly extreme temperature and precipitation fields separately using cross-correlation matrices based on different percentile values often used as extreme thresholds (i.e. the 75th, 90th, 95th, and 99th percentiles). In addition, we used anomaly maps to identify regions where extreme heat occurs with precipitation deficit at the same time. To investigate the duration of dry periods, we selected the Consecutive Dry Days (CDD) index calculated from daily precipitation data.

Our preliminary results indicate substantial differences in the spatial structure of the monthly variables. The analysis of the cross-correlation matrices demonstrates that while temperature fields follow a quite uniform, homogeneous pattern even in extremes, precipitation fields show a more heterogeneous structure. The joint evaluation of spatial anomalies (calculated as the difference between grid-point values and the regional mean) revealed substantial spatial heterogeneity. While mountainous regions show lower values due to orographic effects, the Great Hungarian Plain emerges as the most vulnerable 'hotspot' regarding the combined impact of heat waves and droughts, where the most pronounced positive temperature anomalies coincide with the greatest precipitation deficits. This is especially important due to the dominance of agriculture in the region, and suggests a clear necessity of adaptation strategies depending on further future climatic changes.

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.