Vol. 124, No. 3 * Pages 311–426 * July - September 2020

Nowadays, the use of probabilistic modeling for the design of engineering structures is becoming more and more widespread due to the advances in computer technology. In order to have a comprehensive picture about a meteorological phenomenon, e.g., wind actions on structures, uncertainties must be taken into account. From structural engineering and practical points of view, the effect of the length of short time series available for the analysis on the final results can be interesting to define a minimum observation-length. In this way, the real condition at the site can be utilized to assess wind loading effects on the structure.
This paper deals with the effect of uncertainties associated with the parameter estimation and threshold selection. A four-year record of wind speed data of Sződliget is analyzed, and these results are compared with the results of neighboring sites, Penc, and Budapest. The peak over threshold (POT) method with maximum likelihood estimation are selected to obtain the basic wind velocity. The suitable threshold is chosen using an automatic threshold selection approach.
According to our results, the applied automated threshold selection method provide reliable results, and it is simple and computationally inexpensive. This method may reduce associate errors of threshold selection in the future. It was found that at least approximately 100 realizations should exceed the specified threshold to earn reliable results. It means that 1–1.5-year and 4-year records of wind speeds are necessary for statistical inference in case of weakly dependent observations and for statistically independent events, respectively.

The dependence of the influence of extreme climate conditions on the variability of forest fires in the Timočka Krajina region of northeastern Serbia was studied. The impact of extreme conditions was investigated with extreme climate indices using air temperature, relative humidity, and precipitation measured at three meteorological stations in northeastern Serbia. The De Martonne index was used to analyze climate conditions as a measure for aridity. The study analyzes trends in extreme climate indices with an emphasis on the two contrasting years, 2012 and 2014, and compares them to the baseline period 1961–1990. The year 2012 was very warm and dry, while 2014 was one of the wettest recorded in Serbia. There was an increase (decrease) in warm (cold) temperature indices. Non-significant increases in extreme precipitation indices were observed, while the number of precipitation events greater than 1 mm decreased, as did relative humidity.
Ångström index values were used as an index for assessing the risk of forest fires. These indices were analyzed and a correlation between them and forest fires in northeastern Serbia was established. The aridity index was low during the years 2012, 2011, and 2017, correlating with the large number of forest fires. High values of the Ångström index in 2013 and 2014 were associated with a minimum number of registered forest fires. As an improved indicator for the number of forest fires, the modified Ångström index using daily maximum temperature is proposed.

Temperature changes are in the focus of climate research. There are many analyses available, but they rarely apply rigorous mathematics for assessing the results.
The main approach of this paper is the dependent weighted bootstrap. It is a simulation method, where both the fitted regression and the dependency among the data are taken into account. We present a simulation study showing that for serially dependent data it is the most accurate in case of estimating the coefficient in a linear regression.
This paper shows an analysis of the gridded European temperature data. We have used the 0.5° × 0.5° grid of daily temperatures for 68 years (from 1950 to 2017), created by the European Climate Assessment. We investigated the speed of the global warming by changing the starting point of the linear regression. The significance of the differences between the coefficients was tested by the dependent weighted bootstrap. We have shown that the acceleration was significant for large regions of Europe, especially the central, northern and western parts.
The vast amount of results is summarized by a Gaussian model-based clustering, which is the suitable approach if we intend to have clusters that are spatially compact. The number of clusters was chosen as 13, by a suitably modified "elbow rule". This approach allows to compare the speed and acceleration of warming for different regions. The quickest warming in the last 40 years was observed in Central and Southwestern Europe, but the acceleration is more pronounced in Central Europe.

Climate is one of the most important factors of tourism development. Tourism trends and activities are largely determined by climatic conditions, as well as potential tourist investments. South Serbia is characterized by climate diversity on a relatively small territory. This region is characterized by heterogeneity and richness in geomorphological, hydrological, and cultural tourism resources. However, more intensive tourism development is limited by a weak financial tourism base. The aims of the work are to evaluate climatic conditions in the main tourism centers of South Serbia and to determine the impact of climate change on the development of tourism in the region. Bioclimatic indicators, primarily the tourism climatic index, were used as a statistical and qualitative method for the evaluation of climatological data for the needs of tourism. The results of the research will point to the advantages, but also to the deficiencies of the climate as a tourism resource of South Serbia.

Recent climate change has been caused by interaction of natural processes and the anthropogenic factor. In turn, it incites the pronounced natural and socio-economic changes. It is the air temperature that plays a pertinent role in understanding the climate change problem. Southeast Europe, including Bosnia and Herzegovina (B&H), is highly relevant for the observations of regional differences in changes of air temperature regime. From the regional-geographical point of view, South and Southeast B&H cover 26.5% (13.568 km²) of B&H territory (51.209 km²). It is from south and southeast that the Mediterranean impacts from the Adriatic Sea penetrate into the defined region, which further affects the variability of climate conditions in B&H. The paper presents trends in three parameter categories: mean annual, mean maximum, and mean minimum air temperatures in the territory of South and Southeast B&H. The aim of the paper is to demonstrate the likely climate change based on air temperature trends. Methodologically, temperature trends were processed by using the Mann-Kendall trend test. For the purpose of the analysis, available data from four meteorological stations in South and Southeast B&H for a 56-year period were used. Based on the obtained results, a statistically relevant positive trend was observed in all twelve time series. According to the analyzed trends, the increase of air temperature was dominant in the target area. The application of Geographical Information System (GIS) tools indicated the presence of regional differences in air temperature distribution. An evident phenomenon is the combined impact of the orography of the region and the maritime influence. The occurring climate change affects specific social sectors, so the problem must be addressed properly. Another pertinent fact is that the climate change problem has not been adequately analyzed in the strategic documents in B&H.

The 11 km regional ensemble ALADIN-LAEF (Aire Limitée Adaption Dynamique Développment InterNational – Limited Area Ensemble Forecasting) is evaluated by comparison with the 5 km deterministic model ALARO (ALADIN and AROME combined model – Application of Research to Operations at Mesoscale), in order to investigate the advantages and disadvantages facing short-range ensemble and high-resolution forecasts. To make rational decisions about the benefits or challenges of both systems, the forecast skill was measured through probabilistic and deterministic approaches over a 2-month period from late spring to summer season of 2013. The verification uses observations from 1219 SYNOP stations and 1 km × 1 km precipitation analysis from INCA (Integrated Nowcasting through Comprehensive Analysis) nowcasting system. The evaluation was carried out for three essential meteorological variables: 2 m temperature, 10 m wind speed, and 6-hour cumulated precipitation. From the probabilistic point of view, the results show that ALADIN-LAEF outperforms ALARO-LAGGED ensemble system, being statistically more reliable. From the deterministic point of view, the high-resolution deterministic system simulates better the precipitation forecast structure with respect to the observations. Compared to the ensemble system, the deterministic system cannot provide guidance concerning the forecast uncertainties or probabilities, making the ensemble products a powerful tool for risk assessment and decision making.

The short historical outline describes the significance of Dénes Berényi's textbook “Mikroklimatologie” (Microclimatology, 1967, in German) for the present day. Despite its limited distribution, it is an important document of the transition from the phenomenological to the physical based description of local climatological processes. In any case, it remains an important reference for climatology before 1960.