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The aim of the paper is to characterize the trends of sunshine duration (SDU) and air temperature in Poland, which may help understand the mechanism of contemporary climate change. The daily totals of SDU and daily data on air temperature from the years 1971-2020, from 25 synoptic stations in Poland are the basic source data. The series of records of the two variables showed that the points of change in the level of stabilization of the value of SDU and air temperature are close to each other, and confirm known in the literature "global dimming" and "global brightening" periods. The linear regression model confirmed that sunshine duration explains well the variability of, and increase in day-time air temperature in Poland in the warm part of the year. [ABSTRACT FROM AUTHOR]

This paper presents changes in the ice regime of lakes located in the northern part of Poland. It has been established that in the period 1960–2019, there was a successive decline in the ice extent of lakes, clearly visible in individual parameters; formation of ice cover is delayed by 3.0 days/decade (on average for all lakes), its decline occurred earlier by 3.8 days/decade, and the length of ice cover is shorter by 6.8 days/decade. Moreover, the maximum thickness of the ice cover is becoming thinner, and this process has progressed at an average rate of 2.3 cm/decade. The aforementioned situation shows strong relations with air temperature. It was particularly evident in the late 1980s, when a change in the thermal regime took place, which was documented in most of the analysed parameters, as demonstrated in the study. It has been established that from that period up to now, the decline of ice cover tends to start 19 days earlier, the duration of ice cover is shorter by 22 days, and the ice cover is 8 cm thinner, on average. The observed transformation affects the imbalance of the existing equilibrium in lakes, which can be related to both biotic and abiotic processes. [ABSTRACT FROM AUTHOR]

Our study examines the role of auxiliary variables in the process of spatial modelling and mapping of climatological elements, with air temperature in Poland used as an example. The multivariable algorithms are the most frequently applied for spatialization of air temperature, and their results in many studies are proved to be better in comparison to those obtained by various one-dimensional techniques. In most of the previous studies, two main strategies were used to perform multidimensional spatial interpolation of air temperature. First, it was accepted that all variables significantly correlated with air temperature should be incorporated into the model. Second, it was assumed that the more spatial variation of air temperature was deterministically explained, the better was the quality of spatial interpolation. The main goal of the paper was to examine both above-mentioned assumptions. The analysis was performed using data from 250 meteorological stations and for 69 air temperature cases aggregated on different levels: from daily means to 10-year annual mean. Two cases were considered for detailed analysis. The set of potential auxiliary variables covered 11 environmental predictors of air temperature. Another purpose of the study was to compare the results of interpolation given by various multivariable methods using the same set of explanatory variables. Two regression models: multiple linear (MLR) and geographically weighted (GWR) method, as well as their extensions to the regression-kriging form, MLRK and GWRK, respectively, were examined. Stepwise regression was used to select variables for the individual models and the cross-validation method was used to validate the results with a special attention paid to statistically significant improvement of the model using the mean absolute error (MAE) criterion. The main results of this study led to rejection of both assumptions considered. Usually, including more than two or three of the most significantly correlated auxiliary variables does not improve the quality of the spatial model. The effects of introduction of certain variables into the model were not climatologically justified and were seen on maps as unexpected and undesired artefacts. The results confirm, in accordance with previous studies, that in the case of air temperature distribution, the spatial process is non-stationary; thus, the local GWR model performs better than the global MLR if they are specified using the same set of auxiliary variables. If only GWR residuals are autocorrelated, the geographically weighted regression-kriging (GWRK) model seems to be optimal for air temperature spatial interpolation. [ABSTRACT FROM AUTHOR]

The paper discusses the circulation and thermal conditions over Poland and their dependence on the sign and values of the North Atlantic Oscillation (NAO) index (hereinafter NAO+ and NAO-). The input data used in the research consisted of average monthly values of air temperature in Warsaw, NAO index values, and a calendar of atmospheric circulation types according to Lityński (1969). The study comprised the three winter months (December, January,February) from the period 1951-2015. The dependence between the circulatory and thermal conditions was investigated on the basis of 10 months representing each of the winter months with the highest NAO+ and NAOvalues and 10 months with the greatest positive and negative temperature deviations from the long-term average (Δt+, Δt-), based on the assumption, that they should largely be the same months. In general, the analysis confirmed these assumptions, but it also showed that there are deviations from previously known regularities as regards the effect of the positive or negative phases of the NAO on the thermal conditions in Poland. [ABSTRACT FROM AUTHOR]

This paper concerns the relationships between selected circulation indices and air temperature over Southeast Poland between 1871-2010. The geostrophic wind speed and the resultant vorticity were computed based on daily gridded fields of mean sea-level pressure over an area defined from 5°20' to 40°20'E and from 41°15' to 61°15'N. The highest daily mean geostrophic wind speed over Southeast Poland is observed from December to February. In turn, the maximum (positive) values of the resultant vorticity occur in April and May, while the minimum (negative) values are observed in January. Mean air temperature from November to February has a strong positive correlation with the geostrophic wind speed. Moreover, the occurrence of the highest coefficients regarding the correlation between the geostrophic wind speed and air temperature in winter as well as the NAO index was recorded at the beginning of the 21st century. This suggests that the range of impact of sea-level pressure distribution over the North Atlantic on the winter air temperature over Southeast Poland may have increased over the last decades. One of the causes may be an eastward shift of the position of the center of the Icelandic Low and the Azores High in the period from December to February. [ABSTRACT FROM AUTHOR]

The objective of the paper was the determination of the effect of teleconnection patterns (North Atlantic Oscillation (NAO), Arctic Oscillation (AO), East Atlantic pattern (EA), East Atlantic/Western Russia (EAWR), and Scandinavian pattern (SCAND)) on changes in air and water temperature in Polish lakes. Correlations of circulation indices with air and lake water temperature were analysed in the monthly cycle. Deviations of values of such components in different phases of the analysed atmospheric circulations types from mean average from the years 1971 to 2015 were also determined. The research showed a variable effect of the atmospheric circulations types. The strongest effect on water temperature was observed in winter, when AO and NAO circulation showed particularly evident influence. Deviations of water temperature from mean values from the analysed multi-annual period generally oscillated around 1.0 °C, reaching a maximum value of 1.4 °C. The presented research shows the complexity of processes determining changes in lake water temperature, the course of which depends on many factors with both regional (e.g., ice cover on lakes) and local range (conditions of water exchange, human pressure). [ABSTRACT FROM AUTHOR]

This paper presents the application of the high-resolution WRF model data for the automatic classification of the atmospheric circulation types and the evaluation of the model results for daily rainfall and air temperatures. The WRF model evaluation is performed by comparison with measurements and gridded data (E-OBS). The study is focused on the area of Poland and covers the 1981-2010 period, for which the WRF model has been run using three nested domains with spatial resolution of 45 km × 45 km, 15 km × 15 km and 5 km × 5 km. For the model evaluation, we have used the data from the innermost domain, and data from the second domain were used for circulation typology. According to the circulation type analysis, the anticyclonic types (AAD and AAW) are the most frequent. The WRF model is able to reproduce the daily air temperatures and the error statistics are better, compared with the interpolation-based gridded dataset. The high-resolution WRF model shows a higher spatial variability of both air temperature and rainfall, compared with the E-OBS dataset. For the rainfall, the WRF model, in general, overestimates the measured values. The model performance shows a seasonal pattern and is also dependent on the atmospheric circulation type, especially for daily rainfall. [ABSTRACT FROM AUTHOR]

In the changing climate, exceptionally warm (EWMs) and dry spring months are increasingly observed. At the same time, exceptionally cold months (ECMs) are less frequent, although their impact on a warming climate becomes significant. Due to the role that such climatic anomalies play in the environment and their effects on human activity, it is very important to explain the causes of their occurrence. For this reason, in this study, the authors have attempted to determine the circulation conditions favourable to the occurrence of extremely cold (ECM) and warm (EWM) spring months in Kraków in the years 1874–2022. The study used the average temperature of individual spring months (March–May), as well as types of atmospheric circulation and air masses from the daily Calendar of Atmospheric Circulation Types for southern Poland. A distinct increase in spring air temperature (0.181 °C/10 years) and its individual months (0.162–0.191 °C/10 years) was confirmed. It was accompanied by a significant increase in the occurrence of EWM and a decrease in ECM. It was also found that the direction of air advection and the related temperature characteristics of air masses have the greatest impact on the occurrence of exceptionally cold or warm months. A slight positive effect of zonal circulation on the temperature increase at the beginning of the spring season and the advection of air from the south in April and east in May was found. In the case of the coldest months (ECMs), low temperatures most often developed in the presence of advection from the NW-N-NE directions. [ABSTRACT FROM AUTHOR]

The primary objective of the paper was to characterize the climatic conditions in the winter season in Poland in the years 1966/67–2019/20. The study was based on daily values of minimum (Tmin) and maximum air temperature (Tmax), and daily values of snow cover depth. The study showed an increase in both Tmin and Tmax in winter. The most intensive changes were recorded in north-eastern and northern regions. The coldest winters were recorded in the first half of the analyzed multiannual period, exceptionally cold being winters 1969/70 and 1984/85. The warmest winters occurred in the second half of the analyzed period and among seasons with the highest mean Tmax, particularly winters 2019/20 and 1989/90 stood out. In the study period, a decrease in snow cover depth statistically significant in the majority of stations in Poland was determined, as well as its variability both within the winter season and multiannual. [ABSTRACT FROM AUTHOR]

The aim of the study was to determine changes in maximum air temperature (Tmax) in summer, and occurrence of hot days in the period 1966–2020, as well as to forecast the direction and rate of changes in near and far future. The research showed an increase in Tmax in the summer season. In the analysed period, the changes intensified over the last 20 years, as suggested by, among others, the occurrence of the 10 warmest years in the study period, mostly after 2000. According to model projections, an increase in Tmax will be recorded both in the near and far future. The consequence of the current increase in Tmax has been an increase in the frequency of hot days. Further increase in the number of hot days in Poland is projected for the upcoming decades. The smallest changes are projected for areas with most intensive changes in Tmax, and the largest in areas with moderate changes in the Tmax. [ABSTRACT FROM AUTHOR]

Progressive climate changes are the most important challenges for modern agriculture. Permanent grassland represents around 70% of all agricultural land. In comparison with other agroecosystems, grasslands are more sensitive to climate change. The aim of this study was to create deterministic models based on artificial neural networks to identify highly significant factors influencing the yield and digestibility of grassland sward in the climatic conditions of central Poland. The models were based on data from a grassland experiment conducted between 2014 and 2016. Phytophenological data (harvest date and botanical composition of sward) and meteorological data (average temperatures, total rainfall, and total effective temperatures) were used as independent variables, whereas qualitative and quantitative parameters of the feed made from the grassland sward (dry matter digestibility, dry matter yield, and protein yield) were used as dependent variables. Nine deterministic models were proposed Y_G, DIG_G, P_G, Y_GB, DIG_GB, P_GB, Y_GC, DIG_GC, and P_GC, which differed in the input variable and the main factor from the grassland experiment. The analysis of the sensitivity of the neural networks in the models enabled the identification of the independent variables with the greatest influence on the yield of dry matter and protein as well as the digestibility of the dry matter of the first regrowth of grassland sward, taking its diverse botanical composition into account. The results showed that the following factors were the most significant (rank 1): the average daily air temperature, total rainfall, and the percentage of legume plants. This research will be continued on a larger group of factors influencing the output variables and it will involve an attempt to optimise these factors. [ABSTRACT FROM AUTHOR]

Lake Śniardwy is the largest among more than 7000 Polish lakes. So far, it has not been a subject of detailed investigations concerning long-term changes in water temperature or ice regime. A considerable change in thermal and ice conditions has been observed in the period 1972-2019. Mean annual water temperature increased by 0.44°C dec-1 on average, and was higher than an increase in air temperature (0.33°C dec-1). In the monthly cycle, the most dynamic changes occurred in April (0.77°C dec-1). In the case of ice cover, it appeared increasingly later (5.3 days dec-1), and disappeared earlier (3.0 days dec-1). The thickness of ice cover also decreased (2.4 cm dec-1). Statistical analysis by means of a Pettitt test showed that the critical moment for the transformations of the thermal and ice regime was the end of the 1980's. In addition to the obvious relations with air temperature for both characteristics, it was evidenced that the occurrence of ice cover depended on wind speed and snow cover. The recorded changes in the case of Lake Śniardwy are considered unfavourable, and their consequences will affect the course of physical, chemical, and biological processes in the largest lake in Poland. [ABSTRACT FROM AUTHOR]

The main purpose of the research was to determine the conditions affecting ice phenomena, including the three-phase cycle of ice: expansion, retention and decay of the ice cover on selected rivers of the Baltic coastal zone in the Northern Poland (Przymorze region). The analysis has been elaborated for the years 1951–2010 against the backdrop of currently occurring climatic changes, with particular emphasis on the development and phase variability of the NAO. The article presents the impact of the variability in atmospheric circulation which has manifested in an increase in air temperature, over the last 20 years, on thermal conditions during winter periods in the South Baltic Coastal Strip. The increase in air temperature has contributed to an increase in the temperature of river waters, thus leading to a shortening of the duration of ice phenomena on rivers in the Przymorze region. The article also brings to light an increased occurrence of winter seasons classified as cool, and a disruption in the occurrence of periods classified as normal over the last 30 observed years. The research has demonstrated a significant dependence between the seasonal change in air temperature and the variability of thermal conditions of water, which has a direct impact on the variability of the icing cycle of rivers in the Przymorze region. The authors also show that the variability in forms of ice phenomena for individual river sections is determined by the local factors, i.e. anthropogenic activity, impact of urbanized areas or inflow of pollutants. [ABSTRACT FROM AUTHOR]

Drought reduces crop yields not only in areas of arid climate. The impact of droughts depends on the crop growth stage and soil properties. The frequency of droughts will increase due to climate change. It is important to determine the environmental variables that have the strongest effect on wheat yields in dry years. The effect of soil and weather on wheat yield was evaluated in 2018, which was considered a very dry year in Europe. The winter wheat yield data from 19 trial locations of the Research Center of Cultivar Testing (COBORU), Poland, were used. Soil data from the trial locations, mean air temperature (T) and precipitation (P) were considered as environmental factors, as well as the climatic water balance (CWB). The hydrothermal coefficient (HTC), which is based on P and T, was also used. The effect of these factors on winter wheat yield was related to the weather conditions at particular growth stages. The soil had a greater effect than the weather conditions. CWB, P, T and HTC showed a clear relationship with winter wheat yield. Soil data and HTC are the factors most recommended for models predicting crop yields. In the selection of drought-tolerant genotypes, the plants should be subjected to stress especially during the heading and grain filling growth stages. [ABSTRACT FROM AUTHOR]

The major aim of the research is to analyze the variability of thermal seasons characteristics (onset and length), at 7 stations in Poland during the 40-year-long period of 1971-2010. The analysis comprised the selection of the optimal method for season onset identification and the statistical analysis of the season onset and length characteristics, which was augmented with the interdecadal comparison of statistics using one-way analysis of variance (ANOVA). Also, it was investigated if the season onset type (late/normal/early) induces the season length distribution characteristics. The results show that the variability of the onset of thermal seasons is most pronounced in the case of summer and early spring. Summer also shows the tendency to occur faster, whereas autumn tends to start later. The interdecadal change of the thermal seasons length is clearly visible in the case of summer which length systematically increases and winter where the trend is reversed at most of the stations. The research also confirmed that for winter, early spring, and summer, the onset type clearly determines the distribution of the season length. Other seasons either show little variability or the differences appear only at some stations. [ABSTRACT FROM AUTHOR]

A unique, highly time-resolved, and synchronous three-year dataset of near-surface atmospheric radon-222 as well as soil heat flux and air temperature measurements at two sites (rural and urban) in Central Poland are investigated. The recognition of temporal variability of Rn-222 and selected meteorological variables in the urban and rural areas served to create two statistical models for estimation of this radionuclide concentration at 2 m a.g.l. The description of the relationships between the variables for individual months was established on the basis of an exponential function and an exponential function with time derivative of predictor to account for the hysteresis issue. The model with time derivative provided better results. The weakest fitting of modelled data to empirical ones is observed for the winter months. During subsequent seasons, air temperature as well as QG-driven (soil heat flux) models exhibited very high agreement with the empirical data (MBE, RMSE, MAE, and 'index of agreement' by Willmott were used to evaluate the models). A restriction in the use of QG for Rn-222 concentration was observed only in winter in the case of snow cover occurrence, which reduces the daily QG variability. [ABSTRACT FROM AUTHOR]

The main source of information about future climate changes are the results of numerical simulations performed in scientific institutions around the world. Present projections from global circulation models (GCMs) are too coarse and are only usefulness for the world, hemisphere or continent spatial analysis. The low horizontal resolution of global models (100-200 km), does not allow to assess climate changes at regional or local scales. Therefore it is necessary to lead studies concerning how to detail the GCMs information. The problem of information transfer from the GCMs to higher spatial scale solve: dynamical and statistical downscaling. The dynamical downscaling method based on 'nesting' global information in a regional models (RCMs), which solve the equations of motion and the thermodynamic laws in a small spatial scale (10-50 km). However, the statistical downscaling models (SDMs) identify the relationship between large-scale variable (predictor) and small-scale variable (predictand) implementing linear regression. The main goal of the study was to compare the global model scenarios of thermal condition in Poland in XXI century with the more accurate statistical and dynamical regional models outcomes. Generally studies confirmed usefulness of statistical downscaling to detail information from GCMs. Basic results present that regional models captured local aspects of thermal conditions variability especially in coastal zone. [ABSTRACT FROM AUTHOR]

Altricial birds nesting in places with a favourable microclimate would be able to maintain the proper temperature of eggs or nestlings with less effort and thus reproduce more successfully. Tree cavities provide relatively safe nesting sites, but their microclimate is hardly known. Here we present the first data on air temperature and humidity in natural cavities used by Great Tits nesting in protected primeval forest in the Białowie a National Park (Eastern Poland). We checked what microclimatic conditions existed in cavities selected by Great Tits, how the construction of a nest changed the microclimate in a cavity and to what extent cavity localisation and cavity dimensions modified the microclimate of the breeding cavities. Great Tits used cavities in the living trees which were characterised by cool but relatively stable temperatures and very high relative humidity. Such conditions appear to be typical for cavities in living trees in general. Cavities with Great Tit broods were warmer and drier that the unused ones. The microclimate did not appear to constitute the major factor determining Great Tit usage of cavities in living trees, but it could exert a modifying effect on the pattern of cavity use by them. By choosing cavities of appropriate dimensions and placing the nest at an appropriate distance from the entrance, Great Tits could modify the cavity microclimate. However, their options were probably constrained by necessity to meet other important requirements, such as nest safety and illumination. [ABSTRACT FROM AUTHOR]

Atmospheric drought is an extremely important issue on a global, regional and local scale, especially in the context of climate change. The aim of the study was to assess the spatiotemporal variation of atmospheric (meteorological) drought in agricultural areas of east-central Poland, represented by the Lublin Voivodeship (Lublin region) in 1971–2015. Average monthly air temperatures and monthly precipitation totals recorded over the 45-year period at 25 weather stations were used in the study. The assessment of spatiotemporal variation in atmospheric drought in the study area was based on calculations of the aridity index. The analysis showed an increase in the severity of atmospheric drought in the Lublin region, with intensification of this phenomenon in the last two decades, especially in the warmer half of the year (April, June–August). The main cause of drought in the Lublin region was identified as a statistically significant increase in air temperature (on average, from 0.4 °C to 0.7 °C/10 years in April, July and August, and from 0.2 °C to 0.5 °C/10 years in June) together with the absence of changes in precipitation in the warmer half of the year. This may be linked to some increase in the frequency of high-pressure circulation types, both non-directional and advection from the south. Due to the worsening problem of drought in Poland in recent years, especially in agriculture, there is a need for further research on this subject and for solutions aimed at optimizing agricultural use of the productive environment. [ABSTRACT FROM AUTHOR]

The recognition of changes in the course of agricultural thermal periods is vital when it comes to determining appropriate measures for adapting agriculture to climate change. The present study examined changes in air temperature between 1951 and 2014 in the area of south-western Poland. A statistically significant, positive linear trend was confirmed for the annual average temperature, seasonal averages, and monthly averages in the periods spanning February–May and July–August. From the beginning of the 21st century, the period of winter dormancy of plants started increasingly later; farming and plant vegetation periods started increasingly earlier, and the period of active plant growth was prolonged. Among the considered agricultural periods, the growing season was the most prolonged. The duration of the farming period was also significantly longer, but the winter dormancy period was shortened. The negative linear trend of days when the temperature stood at <0 °C was statistically confirmed for temperature in the entire region and most of the stations. In terms of predicting the consequences of the changes that were observed today over the next decades, this is not an easy task. However, the nature of these changes suggests that further cultivation of winter crops may require far-reaching adaptation measures. [ABSTRACT FROM AUTHOR]