Search

The aim of this paper was to characterize the warm and dry compound events (WD days) in Poland during the period of 1966–2023, focusing on assessing the frequency and intensity of such events and their spatial and temporal variability, as well as on the driving factors of warm and dry compound events. WD days are those days that have a maximum temperature equal to or higher than the 90th percentile and the precipitation on that day and the 14 preceding days are equal to or less than the 25 percentile. During 1966–2023, the frequency of WD days increased significantly, mainly in April, the summer months, and December. Higher temperatures favored the occurrence of WD days from March to November, but, in winter months, the heat did not favor the occurrence of WD days. The exception was December, when high temperatures in the first part of the analyzed period did not favor the occurrence of a dry day, whereas, in the second part, it did. The strongest influence on the frequency of WD days had the East Atlantic pattern, where air flowed over Poland from the southwest. Warm and humid air flowing from the Atlantic Ocean must overcome the mountain barrier; therefore, it flows to Poland as warm and dry air. From spring to autumn, the WD days were related to an increase in the geopotential height in central Eastern Europe, and, in the winter, they were related with blocking over the Balkans.

This article presents the results of several attempts to statistically characterize the short-term (year-to-year) and long-term (>10-year) variability of the NAO Hurrell index in the period 1864 – 2019 and is a complementary continuation of their description presented in the study by Kożuchowski and Wibig (2021). The study used a time series of seasonal averages (DJFM) of the NAO index values according to Hurrell from the period 1864-2019. It was shown that the distribution of the NAO index and changes in the index from year to year do not differ significantly from the normal distribution and the observed frequency of increases or decreases of the index in relation to this value shows good convergence with adequate normal distribution probability (Fig. 2). The symmetry of the normal distribution means that the numbers of year-to-year increases and decreases in the index are equal in the entire index set. The NAO time series shows an above-average association of changes with opposite signs, which constitute more than 2/3 of the total number of all changes and form a negative, significant autocorrelation of the Δ variable (r1= -0.47). As a result, there is a tendency to prefer the change index sequences: decrease/increase and increase/decrease. Such associations of multi-directional changes develop most strongly in the range of the lowest and highest index values, which is confirmed by the significant negative autocovariance of changes. When examining the sequence of successive NAO indices in the time series, the association of the NAOi and NAOi+1 indices was found to be basically random. Frequency distributions of NAOi+1 values depending on NAOi are random – they do not differ significantly from the binomial distribution. However, in the statistics describing the volatility of NAO indices, signals were found that disturbed the symmetrical distribution of the observed changes in the index. They include e.g., repeated in the time series cases of difference between decreases and increases in the index – after significant decreases in the value of the index, its significant increases are characteristic and above average, but after large increases – decreases are not so great and frequent (Fig. 6 and 7). A special peculiarity is the form of volatility c, which means an increase in the index following its decrease and is associated with almost all cases of the index in the range of the 1st decile of the NAO value (Fig. 3). The volatility of the lowest indices (especially in the range of the 1st decile NAO) is much larger than the volatility of higher indices representing the positive NAO phases, the reason for the formation of such volatility asymmetry are different circulation conditions, corresponding to extremely low and moderately high and high NAO indices, i.e., the domination of meridional circulation or zonal circulation. The most significant signs of deviation from the stochastic nature of NAO volatility are revealed in the long-term course of the index. The observed concentration of extremely low and extremely high NAO indices in some decades of the multiannual period (Table 9) is characterized by a negligible probability of occurrence in a random series.

Changes in air humidity in Łódź in the years 1966–2020 in the light of selected indicators The aim of the study is to present changes in air humidity in central Poland in the years 1966–2000 in Łódź as an example. The values of air temperature, relative humidity and atmospheric pressure from four observation terms, 00, 06, 12 and 18 UTC, were used. On this basis, the saturated vapour pressure, the current vapour pressure, and the saturation deficit were calculated. Then, the variability of these three indicators and relative humidity was examined. The variability of monthly and seasonal average values of humidity indices in four observation periods was presented, the trends in seasonal variability of humidity indices were calculated and the distribution functions of their distributions were compared in the midday period in three 15-year periods: 1966–1980, 1986–2000 and 2006–2020. It has been shown that the pressure of saturated water vapour is the highest in summer, the lowest in winter, and slightly higher in spring than in autumn at all times, except for the night. It increased significantly in the studied period as a result of the increase in air temperature. A comparison of the distributions in three 15-year periods shows a significant increase in the probability of occurrence of high values of saturation vapour pressure, even above 30hPa. The water vapour pressure in the air is highest in summer and lowest in winter, but in spring it is lower than in autumn. All trend coefficients are positive, but only less than half are statistically significant. A comparison of the distributions over three 15-year periods show a slight increase in the probability of higher values of the actual vapour pressure. The saturation deficit, as the difference between the previous two indicators, increases significantly. Its value in spring is significantly higher than in autumn. The trend is positive, especially in spring and summer, and the comparison of distributions shows that in the last 15 years the probability of high values of saturation deficit increased significantly. The course of relative humidity is the opposite of saturation deficit. In autumn, the relative humidity is definitely higher than in spring. The trend is down. To sum up, warming brings an increase in the capacity of the atmosphere for water vapour, a slight increase in the amount of water vapour in the air, but also a significant increase in saturation deficit and a decrease in relative humidity, which is particularly strong in spring in the first half of the growing season. Keywords: water vapour pressure, saturation deficit, relative humidity, linear trend, probability distribution Zarys treści: Celem opracowania jest ocena zmian wilgotności powietrza w środkowej Polsce w latach 1966–2000 na przykładzie Łodzi. Wykorzystano wartości temperatury powietrza, wilgotności względnej i ciśnienia atmosferycznego z czterech terminów obserwacyjnych, godzin 00, 06, 12 i 18 UTC. Na tej podstawie policzono ciśnienie pary wodnej nasyconej, aktualne ciśnienie pary wodnej i niedosyt wilgotności. Następnie zbadano zmienność tych trzech wskaźników oraz wilgotności względnej. Przedstawiono zmienność średnich miesięcznych i sezonowych wartości wskaźników wilgotności w czterech terminach obserwacyjnych, policzono trendy sezonowych wartości wskaźników wilgotności i porównano dystrybuanty ich rozkładów w terminie południowym w trzech 15-letnich okresach: 1966–1980, 1986–2000 i 2006–2020. Pokazano, że ciśnienie pary wodnej nasyconej największe jest latem, najmniejsze zimą, wiosną jest nieco wyższe niż jesienią we wszystkich terminach oprócz nocnego. Ciśnienie pary wodnej nasyconej wzrosło istotnie w badanym okresie z powodu wzrostu temperatury powietrza. Porównanie rozkładów w trzech 15-letnich okresach wskazuje na znaczny wzrost prawdopodobieństwa wystąpienia wysokich wartości ciśnienia pary wodnej nasyconej, nawet powyżej 30 hPa. Ciśnienie pary wodnej w powietrzu największe jest latem, najmniejsze zimą, jednak wiosną jest niższe niż jesienią. Wszystkie współczynniki trendu są dodatnie, ale tylko mniej niż połowa jest statystycznie istotna. Porównanie rozkładów w trzech 15-letnich okresach pokazuje nieznaczny wzrost prawdopodobieństwa wystąpienia wyższych wartości ciśnienia pary wodnej. Niedosyt wilgotności jako różnica poprzednich dwóch wskaźników wzrasta wyraźnie. Jego wartość wiosną jest znacząco wyższa niż jesienią. Trendy są dodatnie, szczególnie wiosną i latem, a porównanie rozkładów wskazuje, że w ostatnim 15-leciu prawdopodobieństwo dużych wartości niedosytu wilgotności znacząco wzrosło. Przebieg wilgotności względnej jest odwrotny do niedosytu wilgotności. Jesienią wilgotność względna jest zdecydowanie wyższa niż wiosną. Trend jest spadkowy. Podsumowując, ocieplenie przynosi wzrost pojemności atmosfery na parę wodną, niewielki wzrost ilości pary wodnej w powietrzu, ale też znaczący wzrost niedosytu wilgotności i spadek wilgotności względnej, szczególnie silny wiosną w pierwszej połowie okresu wegetacyjnego.

The aim of the study is to analyze the occurrence of hot days and heat waves in Poland, their intra-annual distribution, and their long-term variability, and to present the circulation factors favoring the appearance of extensive waves in the country. Hot days were days with Tmax not lower than the threshold value defined by the 95th percentile of summer Tmax in the period 1961–1990. Atmospheric circulation was described using sea level pressure, geopotential of 700 and 500 hPa level, and horizontal and vertical wind on these levels. A statistically significant increase in the number of hot days in the entire study period and a significant acceleration in growth after 1980 were shown. In the entire analyzed period, only 11 waves were found covering at least 25% of the country area and lasting no less than a week. Among them, only one occurred before 1990, and more than half were observed in the last decade. Four circulation patterns favoring the extensive heat waves were distinguished differing the location of main baric center location. Spatial and temporal distribution of vertical velocity anomalies allows distinguishing clear phases of strengthening, stabilization, and weakening of anticyclone accompanying the occurrence of a heat wave.

Snow accumulation and associated synoptic conditions in the Russian Arctic are analysed based on snow depth data from 1950 to 2013 from the All-Russian Research Institute of Hydrometeorological Information—World Data Centre data set. The mean duration of snow coverage in the Russian Arctic is approximately eight to nine months. While the period of snowmelt is usually very short (one or two months), snow accumulates during most of the cold season (October–May). Snow accumulation is associated with negative anomalies of sea level pressure and positive anomalies of air temperature, which means increased cyclonic activity over the analysed region. The cyclones differ in intensity and localization, depending on the area of snowfall. In the western part of the Russian Arctic the cyclones and air masses that bring snowfall may originate from the North Atlantic, while in the eastern part they originate from the Bering Sea, Okhotsk Sea or the North Pacific. The cyclones that bring snowfall may also form locally along the zonal border between two different air masses: the very cold, polar, continental air originating from the Siberian High and the Arctic air from the north, which is often warmer and always more humid than the continental air.

The regional climate model RegCM3 is used to investigate potential future changes of temperature indices in Poland for the period 2011–2030. The model is forced by ECHAM5/MPI-OM GCM data from World Data Centre (WDCC) database for the 1971–1990 reference period and 2011–2030 projection period under SRES B1, A1B and A2 emission scenarios. Model output statistics methods are used to transform simulated minimum and maximum temperature data into realistic data. Selected indices of temperature extremes and their differences between the scenario simulations and the reference were calculated, for all scenarios, for the entire period and for each season. Results show a mean yearly increase in the number of summer and hot days and a decrease in the number of frost and ice days. Highest decline in the number of frost and ice days in autumn and an increase in spring is noticed. An highest increase in the number of summer and hot days is seen in summer. Future projections of these indices are relevant for studies on climate change impact in agriculture, tourism, health, transportation, road and building infrastructure.

Gridded data sets of observations are frequently used for the evaluation of climate extremes in climate models. However, it is necessary to understand how the behaviour of extremes is affected in such data sets. The aim of the paper is to analyse how the smoothing effect is related to the number of stations used for calculating the values in each gridcell. A very dense network of stations with highly correlated records of temperature and precipitation was used. The set of grid points was established and for each grid point all data from stations located in the circles with a radius of 75 km in the case of temperature and of 50 km in the case of precipitation were used. Two distributions were compared. The first one was built of the data averaged from all selected stations. The second one was built of all the data from the same stations. Apart from high correlation of averaged records, the effect of reducing extremes is strong. In the case of temperature in winter, the areal averaging causes the overestimation of temperature in the left tail of distribution for the percentiles below the tenth. In summer, the strongest effect is in the right tail and the temperature in underestimated. In the case of precipitation, the higher the number of stations averaged the lower the number of dry days. At the same time, the highest daily totals are underestimated in the highest 5 percentiles (equal and higher than the 95th percentile). All the effects increase with the increasing number of averaged records.

Cold waves commonly occur in higher latitudes under prevailing high pressure systems especially during winter season which cause serious economical loss and cold related death. Accurate prediction of such severe weather events is important for decision making by administrators and for mitigation planning. An Advanced high resolution Weather Research and Forecasting mesoscale model is used to simulate a severe cold wave event occurred during January 2006 over Europe. The model is integrated for 31 days starting from 00UTC of 1 January 2006 with 30 km horizontal resolution. Comparison of the model derived area averaged daily mean temperatures at 2m height from different zones over the central Europe with observations indicates that the model is able to simulate the occurrence of the cold wave with the observed time lag of 1 to 3days but with lesser intensity. The temperature, winds, surface pressure and the geopential heights at 500 hPa reveal that the cold wave development associates with the southward progression of a high pressure system and cold air advection. The results have good agreement with the analysis fields indicates that the model has the ability to reproduce the time evolution of the cold wave event.