Vol. 126, No. 1 * Pages 1–157 * January - March 2022

Climate studies, particularly those that are related to climate change, require long, high-quality controlled data sets, which are representative both spatially and temporally. Changing the conditions of measurements, for example relocating the station, or changing the frequency and timing of measurements, or changing the instruments used can cause breaks in the time series. To avoid these problems, data errors and inhomogeneities are eliminated and the data gaps are filled by using the MASH (Multiple Analysis of Series for Homogenization, Szentimrey, 1999, 2008) homogenization procedure. The Hungarian meteorological observation network was upgraded significantly in the last decades. Homogenization of the data series raises the question of how to homogenize long and short data series together within the same process. It is possible to solve this with the MASH method due it has solid mathematical foundations, which make it suitable for such purposes. The solution includes the synchronization of the common parts’ inhomogeneities within three (or more) different MASH processing of the three (or more) datasets with different lengths depending on the time periods and elements. After the homogenization process, the station data series were interpolated to a 0.1 degree regular grid covering the whole area of Hungary. The MISH (Meteorological Interpolation based on Surface Homogenized Data Basis; Szentimrey and Bihari, 2007) program system was used for this purpose. The MISH procedure was developed specifically for the interpolation of various meteorological elements. In the case of mean temperature, we also renewed the MISH modeling, as compared to previous years, the number of homogenized stations doubled due to the new work, so it was expedient to model the climate statistical parameters with this extended station system. Time series of daily mean temperature and precipitation sum for the period 1870–2020 for Hungary were used in this study. As a result, the longest ever homogenized, gridded daily data sets became available for Hungary. The method described here can also be applied to produce representative datasets for other meteorological elements.

The aim of this work was the regionalization of low flow for chosen catchments located in the upper Vistula river basin using non-hierarchical cluster analysis. Next, with such creative clusters, the regional relationships were determined between the specific low flow discharge q₉₅ and the meteorological and physiographic parameters of the catchment. The study evaluated regional regression models for low flow (specific q₉₅ discharge) in selected, 30 catchments located in the upper Vistula river basin. The data for calculations were a series of observations of daily discharge from the multiannual period of 1963–2016 and were obtained from the Institute of Meteorology and Water Management – National Research Institute in Warsaw. The study showed, that the k-means method can be used for regional regression determination. The parameters which influenced the catchments grouping in clusters were the specific low flow discharge q₉₅, precipitation, median catchment altitude, mean catchment slope, soil, and land use. The study indicated that k-means method may be an effective tool for evaluating low flow in rivers of the southern parts of Poland.

Climate change is one of the largest environmental issues causing hydroclimatological extremes such as floods, droughts, and aridity. The aim of this study is to assess the observed and projected climate changes in Bačka (Serbia). Detailed trend analyses and possible climate scenarios over Bačka has not been presented up to now. In this paper, four data sets were extracted and calculated: mean annual air temperature, mean air temperatures during the vegetation period, mean annual precipitation and total precipitation during the vegetation period. The presented parameters were obtained from the annual meteorological reports of the Republic Hydrometeorological Service of Serbia. Trend equation based on linear regression, trend magnitude according to the trend equation, and Mann-Kendall statistics have been used for trend analysis of climatic parameters. A GIS modeling of the possible climate scenario was created according to the Beijing Climate Center Climate System Model (BCC-CSM2-MR). Based on the trend equations, positive trends related to air temperature and precipitation variables are dominant. The trend magnitude shows the largest mean increase in all time series related to air temperature during the vegetation period. The highest mean precipitation increase occurs only in two time series. The Mann-Kendall statistics showed significantly positive trends in 11 cases and no changes in 9 cases. According to BCC-CSM2-MR, changes will be especially dominant in case of air temperatures. The expected changes in the total precipitation during the vegetation period show a tendency towards semiarid conditions. The presented results of observed and projected climate changes demand adaptation measures, especially from the aspect of sustainable agriculture.

Aggressive behavior in psychiatric care is a serious problem. The causes of aggression may be ambiguous, including behaviors gender, age, or atmosphere on the ward. Other risk factors, usually not mentioned, include meteorological conditions, such as air temperature and humidity, pressure or wind. The available literature suggests a link between meteorological conditions and the use of coercive interventions in psychiatric care. In this study, we examined meteorological conditions that correlated with an increased number of cases of aggressive behavior leading to coercive interventions. The relationships between the studied variables were determined using linear correlation tests and cluster analysis. The study draws on coercive intervention records from The Józef Babiánski Psychiatric Hospital in Krakow, spanning 27 months. The hospital’s seventeen in-patient treatment wards, six day-care centers, nine community treatment teams, and six outpatient clinics have a capacity of 790 patients. Among patients who were susceptible to weather changes, specific weather types were identified as being related to more cases of aggressive behavior.

The geographical position of the Arctic front and two branches of the Polar front over Europe was determined during the period 1995–2015 using calculated grid fields of the thermal frontal parameter in the troposphere layer of 850–700 hPa. It was revealed that the geographical position of climatological fronts changed both in the cold and warm periods of the year in comparison with climate data. The most recent standard reference period of 1961–1990 recommended by WMO (WMO, 2017) was used for comparison. It is shown that in January there was a shift of the northern and southern branches of the Polar front to the north compared to the reference climate period, and in July the convergence of both branches of the Polar front in the middle latitudes was observed. The Arctic front was characterized by a northern location compared to the climate in both January and July. It is revealed that the main areas of frontogenesis in the cold period of the year were the sea surface, namely, the southern regions of the Norwegian Sea, the central part of the Baltic Sea, and the western half of the Mediterranean Sea. In the summer, more active atmospheric fronts were over the continent in the area of the mountain systems such as the south of the Scandinavian mountains, the north of the Alps and Pyrenees, the Urals, and the lower Volga region. The Arctic front intensified over the Barents and Norwegian Seas in all seasons of the year.

The aim of this article was to investigate the effect of macroscale circulation types on total cloud cover in Poznań-Ławica (western Poland) in years 1951–2015. The analysis was preceded by the characteristics of the long-term, annual, and seasonal changes in total cloud cover and cloud genera (data regarding observations of cloud genera covered the period of 1971–2015). The effect of six macroscale circulation types (Arctic oscillation, North Atlantic Oscillation, East Atlantic, East Atlantic/West Russian, Scandinavian, and Polar/Eurasian Types) on the total cloud cover was examined. The amount of cloud cover in Poznań was influenced by the macroscale circulation types, mainly in the warm part of the year. The North Atlantic Oscillation, Arctic Oscillation and Scandinavian types had the strongest impact there.

In this research, changes in annual and seasonal trends of mean temperatures were analyzed on the territory of the Rasina River basin (central Serbia). We used data from four meteorological stations during three periods: 1961–1989, 1990–2018, and 1979–2013. The change detection analysis has been conceded using the Pettitt’s test, von Neumann ratio test, Buishand’s range test, and standard normal homogeneity (SNH) test, while the linear regression, Mann-Kendall, and Sen's slope tests have been applied for trend analysis. The results show that the change in summer temperatures occurred shortly after 1980. The analysis results showed that inhomogeneous structures are generally observed between 1976 and 1984, between 1997 and 1998, and in 2006. The trend of all the data on annual basis showed positive increasing trend. The analysis indicated that the average annual, winter, and summer temperatures show significant increasing trend both in the longer period (1961–2018) and in the second part of the period (1990–2018). In the first part of the period (1961–1989), autumn temperatures in Kruševac, summer and autumn temperatures in Blace, as well as winter and autumn temperatures in Goč showed significant decreasing trend. The significant rising trend in the summer and winter months in the last 30 years may affect water availability and water demands in the region.