Martin Gera

Precipitation in high mountain areas is of critical importance as these regions are major sources of freshwater, supporting river basins, ecosystems, and downstream communities. Changes in precipitation regimes in these regions can have cascading impacts on water availability, agriculture, hydropower, and biodiversity. The present study aims to give new information about precipitation variability in high mountain regions of Bulgaria (Musala, Botev Peak, and Cherni Vrah) and to assess the role of large-scale atmospheric circulation patterns for the occurrence of extreme precipitation months. The study period is 1937–2024, and the classification of extreme precipitation months is based on the 10th and 90th percentiles of precipitation distribution. The temporal distribution of extreme precipitation months was analyzed by comparison of two periods (1937–1980 and 1981–2024). The impact of atmospheric circulation was evaluated by correlation between the number of extreme precipitation months and indices for the North Atlantic Oscillation (NAO) and Western Mediterranean Oscillation (WeMO). Results show a statistically significant decrease in winter and spring precipitation at Musala and Cherni Vrah, and a persistent drying tendency at Cherni Vrah across all seasons. The frequency of extremely wet months in winter and autumn has sharply declined since 1981, whereas extremely dry months have become more common, particularly during the cold season. Precipitation erosivity also exhibits station-specific responses, with Musala and Cherni Vrah showing reduced monthly concentration, while Botev Peak retains pronounced warm-season erosive rainfall. Circulation analysis indicates that positive NAOI phases favor dry extremes, while positive WeMOI phases enhance wet extremes. These findings reveal a shift toward drier and more seasonally uneven conditions in Bulgaria’s alpine zone, increasing hydrological risks related to drought, water scarcity, and soil erosion. The identified shifts in precipitation seasonality and intensity offer essential guidance for forecasting hydrological risks and mitigating soil erosion in vulnerable mountain ecosystems. The study underscores the need for adaptive water-resource strategies and enhanced monitoring in high-mountain areas.

Birds often return to the same locations where they have previously bred successfully or survived the winter, demonstrating site fidelity. This behaviour extends beyond breeding sites to include roosting and feeding areas, with individuals frequently recaptured at the same locations across years. In this study, we investigated the winter site fidelity of Great Tits and analysed how various factors (winter temperature, sex, age, site, date of first capture, and winter season) influence recaptures within and between winters. We monitored individuals roosting in nest boxes at two sites within Bratislava city, western Slovakia. Within-winter site fidelity was observed in 45.89% of birds (N = 146), meaning these individuals were recaptured at least once during the same winter at the same site. Among the tested variables, age and date of first capture in the season significantly influenced within-winter site fidelity. Older birds and those captured earlier in the season were more likely to be recaptured in the same winter. Between-winter site fidelity, defined as birds ringed and later recaptured in a different winter, was observed in 12.92% of 178 Great Tits. Age was a significant factor, with older individuals being more likely to be recaptured in subsequent winters. Furthermore, birds that were recaptured more often during their first winter had a higher likelihood of being recaptured in later winters, suggesting consistent long-term site use.

This study presents the research of thunderstorms in Slovakia using records of thunderstorm days from weather observation stations from 1965 to 2023, as well as radar data, and data from lightning detection systems from 2010 to 2023. An algorithm was developed to identify thunderstorms using radar and lightning data. The temporal distribution of thunderstorms is examined across annual, seasonal, daily, and hourly timescales. Additionally, we focus on the spatial distribution of thunderstorms, where lightning data according to a proposed algorithm were used. The occurrence of thunderstorms is also analyzed in the light of macrosynoptic types, according to a 28-class classification of the Slovak Hydrometeorological Institute. The results show that close thunderstorms (within 3 km of a given location) in Slovakia occur on average on 15 days a year, most frequently in the summer months of June and July, and primarily in the late afternoon between 3 and 5 p.m. Central European Summer Time (CEST). The spatial distribution of thunderstorms in Slovakia is non-homogeneous, with an increased occurrence in Central Slovakia, particularly in the area of Muránska Planina, Stolické, and Volovské Vrchy Mts. Conversely, the fewest thunderstorms occur in the westernmost part of the territory. Severe thunderstorms are most numerous in the Gemer region. The occurrence of thunderstorms is significantly influenced by synoptic types, with the most favorable conditions associated with types B (trough over Central Europe), Bp (traveling trough), C (cyclone over Central Europe), and Cv (upper cyclone). In recent decades, significant decrease in the number of thunderstorm days per year has been observed. This may be due to the observed decreasing trend of cyclonic synoptic situations in Europe, where a substantial number of thunderstorms occur.

Long-term data on the phytoplankton of the Bulgarian Black Sea (BBS) coast describe three states for the ecosystem: a “pristine” reference phase (1954–1970 years); an intensive anthropogenic eutrophication (1970–1992 years) phase; and a post-eutrophication phase after the early 1990s of the 20th century. The eutrophication period is characterised by ecosystem degradation and intense phytoplankton blooms, some of which were formed by the potentially toxic species Lingulodinium polyedra. This warm-water species is a red tide former that is associated with fish and shellfish mortality events. In the 1980s, L. polyedra reached the highest biomass of 84.4 g·m⁻³ in Varna Bay, BBS. The aim of this study (1992–2022) was to provide an overview of the development of L. polyedra in the phytoplankton biocenosis in the Bulgarian part of the Black Sea, taking into account the influence of anthropogenic stress and the climatic variables NAO and SST on the development of the species population. An analysis of the distribution of the dinoflagellate L. polyedra is based on a total of 5126 phytoplankton samples collected during the period between 1992 and 2022 under projects led by the Institute of Fish Resources, Varna. The samples were analyzed using standard methods validated for the Black Sea, and phytoplankton abundance and biomass were determined. The species are most abundant in summer in the coastal marine areas exposed to anthropogenic influence. During the analyzed period, a decrease in the abundance and biomass of L. polyedra in Bulgarian Black Sea waters were observed. It was found that the influence of climatic factors such as NAO and SST on the species population is from weak to moderate, and the correlation with NAO cycles is better expressed.

The atmospheric circulation, not only near the surface but also at high altitudes, is probably the main factor determining the weather and climate of a given area, along with its latitude, altitude, the shape of the relief of the area and its surroundings, and the proximity of water basins of different sizes. The main objective of this study is to investigate the relationship between anticyclonic circulation types in the middle troposphere at the 500 hPa level and the seasonal summer temperature over the region of the central Balkan Peninsula, particularly Bulgaria. A previously compiled classification of atmospheric circulation is used, and the frequencies of the circulation types are correlated with the mean seasonal (monthly) temperature, where the extreme seasons and months are defined as the 10th percentile for cold summer seasons and months and the 90th percentile for warm ones. A positive and statistically significant correlation was found for the anticyclones located southwest of Bulgaria and a negative one for those located southeast of it. A comparison between the last two 30-year climatological periods (1961–1990 and 1991–2020) was also made, and an irrefutable decrease in the number of cold summer seasons from 257 to just 17 was found in the last 30 years, respectively, as well as a rapid increase in the number of extreme warm summer seasons from 26 to 263, encompassing all 15 meteorological stations studied.

In the conditions of rising air temperature and changing precipitation regimes in Central Europe and Slovakia over the last two decades, it is necessary to analyse drought, develop high-quality tools for drought detection, and understand its reactions to the emerging drought situation. One of the frequently used meteorological drought indices is the Standardized Precipitation and Evapotranspiration Index (SPEI). Several parameters can be modified in different steps of the calculation process of SPEI. In the article, we analyse the influence of selected adjustable parameters on the index results. Our research has shown that the choice of a statistical distribution (Log-logistic, Pearson III, or Generalized Extreme Value) for fitting water balance can affect the feasibility of calculating distribution parameters (and thus the index) from the provided input data, as well as lead to either underestimation or overestimation of the index. The normality test of SPEI can be used as a tool for the detection and elimination of highly skewed indices and cases when the indices were not well determined by the distribution function. This study demonstrated improved results when using the GEV distribution, despite the common use of the Log-logistic distribution. With the Pearson III distribution, unusually high or low SPEI values (|SPEI| > 6) were detected.

During the last decades, a decrease in the nutrients and an increase in marine temperature on the surface of the Varna Bay of the Black Sea have been registered. The main aim of this study was to establish the influence of some environmental factors (SST, TP, DIN) on the structure of the phytoplankton and to define what part of these dynamics results from the changes in temperature. Bivariate correlation and Nonlinear regression analyses were used to establish the connection between factors of the environment and the quality parameters of different size and taxonomic groups of phytoplankton. The rising SST proved to statistically significantly influence the decrease in the abundance of nano-phytoplankton (50.9%), the abundance and biomass of micro-phytoplankton (53%; 33.2%), the Bacillariophyceae (49.5%; 35.6%), and the biomass of the species of group “Other” (51.4%). The decreasing TP has a significant influence on the decrease in the abundance and biomass of the diatoms and the biomass of group “Other”. The decreasing DIN significantly affects the decrease in the abundance and biomass of Dinophyceae. The analyses showed that rising temperatures had a leading role in the changes in the taxonomic and size structure of phytoplankton during the period 1992–2019.

The article examines the occurrence of extremely cold and extremely warm days as an indicator of environmental changes in the Pirin Mountain (Bulgaria). The study is based on hourly air temperature data recorded by an automatic weather station. By averaging the hourly data, daily values are calculated. The occurrence of extremely cold and extremely warm days during the period 2015–2018 for January, April, July and October are analyzed. Extreme temperature days are determined by threshold values for the 10th and 90th percentiles. Characteristic synoptic situations related to the manifestation of extreme temperatures are presented. As a result of the research it was established that the advections of air masses are the leading factor for the occurrence of extreme temperatures. In addition very important for the extremely low temperatures is the high air pressure over the Balkan Peninsula.

This paper presents the development of technologies to support the decision-making of local government executives and smart city concept managers in selecting and evaluating the competencies of new members for advisory groups for solving problems that are implemented in safe times in individual areas or in crises, such as pandemics. The reason for developing effective urban transformation strategies and for the transparent selection of independent experts (non-politicians) for policymaking, decision-making, and implementation teams is not only the heterogeneity of smart city dimensions together with the necessary complexity and systems approach, but also the nature of the capacities and tools needed for smart city concepts. The innovative hybrid competency assessment model is based on fuzzy logic and a network for neuro-fuzzy assessment. It is a technological model for evaluating the competencies of specialists, taking into account the influence of human factors on the processes of personnel selection and system management. An innovative web platform named “Smart City Concept Personnel Selection” has been designed, which can be adapted to various users of municipalities or regional institutions for the transparent selection of qualified personnel for effective decision-making and the use of public funds during safe times or emergencies, such as the COVID-19 pandemic.

Radar measurements are inherently affected by various meteorological and non-meteorological factors that may lead to a degradation of their quality, and the unwanted effects are also transferred into composites, i.e., overlapping images from different radars. The paper was aimed at answering the research question whether we could create ‘cleaner’ radar composites without disturbing features, and if yes, how the operational practice could take advantage of the improved results. To achieve these goals, the qRad and qPrec software packages, based on the concept of quality indices, were used. The qRad package estimates the true quality of the C-band radar volume data using various quality indices and attempts to correct some of the adverse effects on the measurements. The qPrec package uses a probabilistic approach to estimate precipitation intensity, based on heterogeneous input data and quality-based outputs of the qRad software. The advantages of the qRad software are improved radar composites, which offer benefits, among others, for aviation meteorology. At the same time, the advantages of the qPrec software are manifested through improved quantitative precipitation estimation, which can be translated into hydrological modeling or climatological precipitation mapping. Beyond this, the developed software indirectly contributes to sustainability and environmental protection—for instance, by enabling fuel savings due to the more effective planning of flight routes or avoiding runway excursions due to information on the increased risk of aquaplaning.