Climate Change and Threats to Public Health in the Kaliningrad Region

Purpose: to carry out a comparative analysis of meteorological characteristics (average monthly precipitation and average monthly air temperature) on Moscow region territory based on the ERA5-Land Copernicus (C3S) reanalysis data and stationary weather stations. Materials and methods. Data obtained from 11 weather stations located in different districts of Moscow region from April to September 2000–2020, as well as data from climate archives based on regular meteorological observations, aerologic and satellite information was used. A comparison of the average monthly air temperature and precipitation for the growing season of main agricultural crops was carried out, the data deviation based on the reanalysis results from the actual data was presented, the correlation coefficients were calculated, the result of calculating the Pearson correlation coefficient was presented, and the advantage of the reanalysis data was shown. Results: the calculations obtained showed that the distribution of average monthly temperature and precipitation differs slightly from the observation data, which can be explained by the peculiarities of determining the coordinates of the weather station relative to the reanalysis grid nodes. Conclusions. ERA5-Land reanalysis data are suitable for determining the main meteorological characteristics in those areas where there are no stationary weather stations or access to their data is difficult. The reanalysis values as a whole reflect the variability of air temperature and precipitation in the study area of Moscow region quite well relative to the indicators obtained by ground-based observations. ERA5-Land data can be supplemented and applied in various fields of research, such as climate forecasting, yield forecasting using agro-climatic indicators, irrigation or drainage planning, etc.

The results of revealing the peculiarities of sweet cherry fruit quality formation of different varieties depending on the weather conditions of the growing year in the southern region of Russia are presented. The study was conducted in the Prikubanskaya horticultural zone of the Krasnodar Territory, characterized by hot and dry summer, abnormally high air temperatures during the period of fruit bud differentiation, mild and low-snow winter with sharp changes in positive and subzero temperatures. The objects of the study were 11 sweet cherry varieties of domestic and foreign selection: Alaya, Dar izobiliya, Sashenka, Chernye glaza, Kavkazskaya, Aelita, Yantarnaya, Krupnoprodnaya, Prestizhnaya, Sputnik, Francis. The purpose of the study was to determine the peculiarities of generation and dynamics of weight, biochemical indices of fruits depending on the genotype of the variety and conditions of the year. The obtained data confirm that a number of factors have a significant effect on the fruit size and weight, and the accumulation of biochemical substances is determined by the characteristics of the variety and differs from year to year within the limits determined by the genotype. Aclose correlation between weight, fruit size and biochemical composition with meteorological indicators: precipitation, average annual and average air temperatures during the period of fruit formation was found. It was found that fruit weight was more influenced (R2 = 0.74) by the average annual air temperature: the higher it was, the larger the fruit size, and vice versa. Significant correlation dependence (R2 = 0.95) was revealed between the amount of precipitation in May and vitamin C accumulation in fruits, i.e. the greater the amount of precipitation, the lower the vitamin C content. A close relationship (R2 = 0.91) was found between the content of anthocyanins and the average monthly air temperature in May, which indicates that the higher the temperature, the less these substances accumulate in fruits. According to the results of the study, several varieties with high fruit quality (weight over 9.0 g, tasting score 4.5–4.7 points) and the best content of various biochemical substances were selected for the creation of new varieties with high flavor and fruit quality. These varieties are Alaya, Kavkazskaya, Krupnoplodnaya, Prestizhnaya and Chernye glaza.

The analysis of the quality of ultra-long-term forecasts with 1-5 year lead time of the monthly and annual precipitation sums, the average monthly and average annual surface air temperature obtained using the INM-CM5 climate model’s outputs is performed. Series of verification forecasts for the period from 1991 to 2023 were used. Forecasts were checked for 12 river basins located in different parts of Russia. To eliminate systematic forecast errors used a method for correcting, which reduces the error of ultra-long-term precipitation forecasts by almost two times, and air temperatures by almost three times. Forecasts of intra-annual precipitation distribution were satisfactory for 8 out of 12 river basins. Forecasts of the intra-annual distribution of air temperature were good for all 12 river basins. Demonstrated, that the INM-CM5 climate model outputs can be used for ultra-long-term forecasting of monthly and annual precipitation, average monthly and average annual air temperature.

Studying the capacity of some plant species to adapt to climate change is essential for ecological research and agricultural policy development. Chinese Torreya (Torreya grandis ‘Merrillii’) has been an important crop tree in subtropical China for over a thousand years. It is necessary to characterize its adaptation to climate change. In this study, the average monthly temperature and precipitation from 1901 to 2017 in the six regions with Chinese Torreya plantations at different provinces were analyzed. The results indicated that the average annual air temperature across these regions had increased by about 2.0 °C, but no general trend in the annual precipitation and incidence of drought was found. The annual air temperature that Chinese Torreya plantations had experienced was 12.96–18.23 °C; the highest and the lowest average monthly air temperatures were 30.1 °C and −0.8 °C, respectively. The lowest and the highest annual precipitation were 874.56 mm and 2501.88 mm, respectively. Chinese Torreya trees endured a severe drought period in the 1920s. The monthly air temperature at Zhuji, which is the central production region, showed a significant correlation with the air temperature in the other five regions. The monthly precipitation in Hunan and Guizhou had no significant correlation with that of Zhuji. Chinese Torreya plantations have been grown in the regions with a similar climate distance index of air temperatures but different precipitation. This tree has a high capacity to adapt to climate change based on the climate dynamics across its range. This approach may provide a way to evaluate climate adaptation in other tree species. These results may provide helpful information for the development of Chinese Torreya plantations.

The aim of this paper is to examine the spatial and temporal variability of the average monthly, seasonal and annual air temperatures in Serbia. Therefore, data from 64 climatologic stations were analyzed in the period from 1961 to 2010. Based on the data, on the position of the stations (their latitude, longitude, altitude), and the characteristics of the terrain in their vicinity (inclination and terrain exposure in a radius of 10 km around the station), a regression model was constructed based on which air temperatures are interpolated for the territory of Serbia. The rootmean-square error (RMSE) of the regression model ranged from 0.2 oC in January, February and November to 1.1 oC in August. Spatial distribution of air temperatures is shown (maps of mean monthly, mean seasonal and mean annual air temperatures are made), and the Sen's procedure was used to calculate trends of air temperatures (maps of average monthly, mean seasonal and mean annual trends of air temperatures). The Mann-Kendall test was used to test the significance of air temperature trends. Apart from the southeast, the whole territory of Serbia has practically experienced a statistically significant rise in the average annual air temperature, with the highest increase in the summer and winter months.

The proposed article is devoted to the study and analysis of changes in the field of average monthly air temperature on the territory of Ukraine over the past fifteen years (2006-2020) of the period 1991-2020 to determine the trends that have emerged as a result of changes in global circulation over the Atlantic-European sector of the Northern Hemisphere and the possible occurrence of frequent drought events on the territory of Ukraine. Тaking into account the drastic climate changes that have occurred during the last decades, there is a problem in adapting a number of branches of the production complex to such changes in order to prevent economic losses and develop a new strategy in this direction. Connection with research tasks. The presented study is related to the implementation of a number of state-ordered research works dedicated to the study of the peculiarities of modern climate changes in Ukraine and the identification of climate-vulnerable areas on its territory. Problems to be solved in the article. Taking into account the accumulated material regarding the features of the distribution of the air temperature field in Ukraine and the probabilistic scenarios for its change under the influence of general warming in the Northern Hemisphere, for the territory of Ukraine it is necessary to find out the mechanism of its current changes and determine their direction on a temporal and territorial scale. The main purpose of the presented article was to investigate and establish the main trends in the current field of average monthly air temperature in Ukraine over the past 15 years (2006-2020) and show the nature of the spatial and temporal distribution of these changes. Materials and methods. The data of the average monthly air temperature at 55 stations of Ukraine during all months of the year for the fifteen-year periods 1991-2005 and 2006-2020 served as the research materials. The main research methods were physical and statistical to determine the deviations of two 15-year periods and cartographic to determine spatio-temporal differentiation of detected cells. Main results. It was established that on the territory of Ukraine in January 2006-2020 there was a certain decrease in the average monthly air temperature due to lower temperatures. In the rest of the winter months, its growth is observed, especially in the territory of the northwestern, northern, and northeastern regions and in some central and southern regions.. In the spring, the increase in the average monthly air temperature in 2006-2020 occurred more intensively in the northern regions and in a number of regions of the western region (Peredkarpattia). In the summer, the increase in air temperature was observed throughout the territory of Ukraine, but most intensively in July. Territorially, the greatest increase in the average monthly air temperature was expressed in the north, northeast and south. In autumn, the increase in the average monthly air temperature was most intense in November 2006-2020 in the regions of the northern and central regions, as well as in the Carpathian region. In the last 15 years, the average monthly air temperature in Ukraine has increased, but in January it decreased in the north, northeast, in some places in the center and south. This trend is new for today's climate. The results of the study for the territory of Ukraine are presented for the first time and can be used for planning agricultural works.

The relevance of the chosen topic is based on the goals and objectives of the Water Strategy of Ukraine until 2050 that provides for promotion of studies on the impact of climate change on the water content of Ukrainian rivers. The Dniester River is a transboundary river. It supplies water to Moldova and several regions of Ukraine. Predicting possible changes in the Dniester River's runoff due to global warming will help our society adapt to new climate conditions and take preventive measures. The research of the mountainous part of the watershed is of particular importance, as it is the area of runoff formation. Warming can change contribution of the snow component to the river's feed pattern and affect the total river flow. The object of the study: changes in air temperature due to global warming. The subject of the study: assessment of changes in the temperature regime within the Dniester watershed and impact of such changes on formation of its mountainous part's runoff. The study is aimed at assessing the changes in the air temperature regime within the Dniester River watershed at the beginning of the 21st century and assessing the impact of warming during winter season on formation of mountain rivers' spring floods. The main research methods include the method of difference integral curves and the method of regression analysis. The research materials include average monthly and annual air temperatures at 13 meteorological stations located within the Dniester watershed for the period of 1947-2021. The research indicated that the Dniester watershed is subject to warming. Statistically significant changes in air temperature began in 1988. Fluctuations in average annual air temperatures occur synchronously. Positive statistically significant trends over the entire observation period (1947-2021) were found for average annual air temperatures, average monthly temperatures of both warm and cold periods, and for the winter season. When considering two measurement periods (before 1989 and after), it was found that no statistically significant trends were observed before 1989. They were formed after 1989. It was also discovered that mountainous watersheds of the Ukrainian Carpathians respond to warming by forming negative trends in the fluctuations of average monthly runoff of spring floods.

The mountainous relief of the terrain has a significant effect especially on the temperature and precipitation characteristics. They mainly occur on windward slopes (mainly south-west to west), in the summer months, under conditions for convective weather manifestations, often accompanied by the formation of massive storm clouds, the appearance of intense precipitation and also storms. The relief of the Jeseníky Mountains, with high hills and narrow valleys, results in frequent occurrence of ground temperature inversions. Under suitable conditions, especially with clear night sky in spring and autumn, valley fogs arise resulting in lowering significantly air temperature before dawn. In most of the territory of Hrubý Jeseník Mountains and the massif of the Králický Sněžník climatological characteristics are dominantly influenced in relation to the altitude. For climatological processing and climate characteristics, we have defined the Jeseníky Mountain area, which is primarily based on geomorphological units. The area of the defined territory of the Jeseníky Mountains is approximately 3,251 square kilometres, which is approximately 4% of the territory of the Czech Republic. The average altitude is 613.1 meters above sea level. We calculated the area monthly and annual characteristics for the Jeseníky Mountains for the main processed meteorological elements, i.e. average monthly air temperature, monthly precipitation, monthly sunshine duration and in winter also for the monthly amount of new snow. Time series included air temperature and precipitation since 1875, new snow since 1896, and sunshine duration since 1932. The average annual air temperature for the normal period, or normal 1991–2020, is 7.2 °C. The highest average annual air temperature in the Jeseníky Mountain was 8.4 °C in 2019. According to the average annual air temperature (4.4 °C) in the Jeseníky Mountains, the year 1875 and 1940 were the coldest. Based on the evaluation of the linear trend, the average temperature has increased over the last 150 years annual air temperature in the Jeseníky Mountains by 1.5 °C. On average, the air temperature increases the most in November, by almost 2.2 °C in 150 years, and the least in September (by 0.7 °C). The average annual precipitation total for the defined area of the Jeseníky Mountains is 848.7mm. The highest annual precipitation total, 1,217.8mm, was recorded in 1890. The year 2015 was the lowest in terms of precipitation, with only 590mm of precipitation. In almost 150 years, the annual precipitation has decreased by around 77mm. The largest long-term decrease in precipitation is evident in October, almost 23mm in 150 years, and the lowest in February, August and December (between 2–3 mm). In the top parts of the Jeseníky Mountains, if the snow has not been blown, around 540cm snow cover occurs on an annual average. At the altitude of 1,300m above sea level, the annual total is around 460cm. Altitude zones around 1,100m above sea level have an average annual depth of new snow approximately 390cm. In areas around 1,000m above sea level, an average of 350cm of new snow cover appears in the Jeseníky Mountains. In the published literature, we searched for significant episodes related to the weather and climate of the Jeseníky Mountains, which we supplemented with data on the values of individual meteorological elements from local stations.

The long-term dynamics of the average annual and seasonal air temperature on the territory of the Moscow region is considered. To assess the significance of linear trends in annual and seasonal air temperature, the criterion “trend-to-noise ratio” was used, calculated according to the method of V.E. Chuba. In addition, statistical criteria were used the Spearman criterion and the correlation coefficient. It has been established that the highest value of annual air temperature, falls on the territory of the city of Moscow, where its own special microclimate is created, and the lowest value of the average annual air temperature is observed at the weather station Mozhaisk. When analyzing the trend in the rate of increase in annual air temperature, the following results were obtained. The increase in the average annual air temperature over the period for Moscow is 2,61 °C/74 years, for the southeastern part of the Moscow region (Kolomna) is 2,26 °C/97 years and for the western part of the region from Mozhaisk) is 2,36/90 years. Checking the significance of linear trends showed that in the dynamics of the average annual, seasonal and maximum and minimum air temperatures in the Moscow region, there is a positive statistically significant linear trend.

Climate variability in the Russian Arctic in 1991-2017 is examined based on the mesurements of the air temperature at 19 meteorological stations. The average annual air temperature at the stations fluctuated relative to the climatic baseline of 1961-1990 by 0.5-4°C in 1991-2004. Since 2005, it was higher than the climatic baseline at all stations annually. The increase in the air temperature was most pronounced in the winter months from November to February at all stations (more than 15ºC at some stations in some years). The increase in the air temperature in the summer months was noticeably smaller. The baseline level of the average monthly air temperature from November to February was exceeded most prominently at high latitude meteorological stations located at Wiese Island, Severnaya Zemlya, and Franz Josef Land (16-17ºC in some years, starting with 2005). Stations located at a distance from the ocean, such as Khatanga and Tiksi, are characterized by a smaller temperature increase compared to coastal and island stations, such as Barenzburg, Wrangel Island and others. Smaller deviations of the air temperature from the baseline level are typical in the western sector of the Russian Arctic (Murmansk, Svyatoy Nose). The influence of the Arctic climate variability on the ice regime of arctic lakes is considered according to Flake model (http://www.flake.igb-berlin.de/) for the Lena River Delta lakes.

An N–PLS regression technique was tested as an empirical downscaling method. Average monthly near-ground air temperature (t), specific humidity (q), and sea-level pressure (p) fields across Central and Western Europe were used as predictors for average monthly air temperature (T), dew temperature (D), and precipitation amount (P) at 4 locations in Slovenia. The empirical downscaling models (EM) were developed by means of available predictand data from the ARSO archive and predictor data from the NCEP/NCAR reanalysis project, for the period 1951–2002, separately for single months. Using the combination of t and p as predictors, the EM for T explained from 73% to 95% of predictand variability, for D from 74% to 97% of predictand variability, and for P from 31% to 76% of predictand variability. The use of q as an additional predictor did not improve the quality of the EM considerably. Developed EM using p and t as predictors were applied to the results of 5 general circulation models (GCM): CSIRO/Mk2, CCC/CGCM2, UKMO/HadCM3, DOE-NCAR/PCM, and MPI-DMI/ECHAM4-OPYC3. Only the simulations based on SRES A2 and B2 emission scenarios were considered in our calculations. Available mean monthly values of predictors for the period 1951–2100 were used. All the projections of GCM results indicate an increase in T and D and decrease in P in the 21st century at all 4 locations. The expected range of changes in T, D, and P is wide due to the different response of GCM to identical changes in the atmospheric composition, and represents a source of uncertainty in empirical downscaling results. Another important source of uncertainty in empirical downscaling studies, especially when temperature dependent predictors are used, is the problem of extrapolation. By using the proper mathematical approach for EM development we only reduce a part of the uncertainty related to the quality of empirical models that also strongly depend on the quality of input data and predictor selection. The N–PLS regression seems to be a suitable choice of mathematical method, as the feature selection from a large number of predictor time series is not predictand independent. Finally, any climate change and impact studies for the future are affected by many other uncertainties that we have to be fully aware of, while interpreting their results.

Air temperature is a meteorological variable that influences the climate in the world. The availability of air temperature data is of concern in Brazil, particularly in the State of Mato Grosso do Sul (MS), since most weather stations are concentrated on the country's coast. Thus, the study aimed to develop models to estimate the average monthly and annual air temperatures (maximum and minimum) for the site of the State of MS. The linear multiple regression technique is adopted in this study. Temperature data from 1978 to 2018 were used, corresponding to 78 meteorological stations on the website of the State of MS. Geographical coordinates (latitude, longitude and altitude) were used as predictor variables for the models, and monthly and annual extreme temperatures (Tmax, Tmin) models were fitted. The regression models used in the study were statistically tested (α ≤ 0.01). The models of mean annual Tmin and mean annual Tmax obtained adjusted determination coefficients (R2adj) of 81.2% and 74.9%, respectively. The monthly average temperature models showed adjusted coefficients of determination between 0.69 and 0.90 for Tmax and from 0.71 to 0.86 for Tmin. Another method used to validate our results, the digital elevation model for the State of MS, obtained through a Shuttle Radar Topography Mission radar image. The obtained results fitted well with these of the annual and monthly models for extreme temperatures. The temperature models used in the study are duly suitable to predict air temperature in all sites in the State of MS.

Introduction. For the first time, the problem of global warming was officially announced in 1976 by the World Meteorological Organization. The most complete picture of ongoing climate change, causes, consequences and response strategies can be obtained from the reports of the IPCC (intergovernmental group of experts). There are many works devoted to regional climate changes, including those in the North Caucasus. However, these works do not reflect the modern agro-climatic conditions of the mountainous landscapes of the North Caucasus which occupy 27% of the territory and are actively involved in agriculture. Aim - analysis of modern agro-climatic conditions of the mountain landscapes of the North Caucasus in a changing climate. Materials and research methods. To assess agro-climatic conditions, traditional agro-climatic indicators were used, such as annual and average monthly air temperatures; sums of active temperatures exceeding 5 and 10°С; dates of stable transition of the average daily air temperature through 0, 5 and 10°C in spring and autumn; the duration of the period with an average daily temperature of 0, 5, 10 ° C, the average temperature of the coldest and warmest months of the calendar year, annual precipitation, hydrothermal coefficient. The processing of the material was carried out by methods of mathematical statistics using Excel spreadsheets. Processed data on temperature and precipitation in the period from 1961 to 2020 for six meteorological stations. Research results. For the period from 1961 to 2020, within the mountain landscapes of the North Caucasus, there is an increase in annual air temperature compared to the previous period by an average of 0,5 °C. Against the background of an increase in annual temperature, such agro climatic indicators as the sum of active temperatures increased, exceeding 5o and 10oC by 6 and 13%, respectively. The stable transition of the average daily air temperature through 0, 5, 10°C has also undergone changes. In spring, on average, this happens 5, 1, 6 days earlier. Whereas in autumn, on the contrary, 3, 1, 5 days later. The duration of the period with an average daily temperature of 0, 5, 10 °C increased by an average of 10, 3, 13 days, respectively. Precipitation increased at all meteorological stations, with the exception of the Klukhorsky cross, by an average of 45 mm. The hydrothermal coefficient, which characterizes precipitation during the growing season, remained within the limits of natural fluctuation, except for the Klukhorsky cross, where it decreased due to a decrease in precipitation during the warm period. Discussion. The analysis of the agro-climatic conditions of the mountain landscapes of the North Caucasus for 1961-2020. revealed trends in the growth of annual temperature and precipitation, however, the moisture supply of the active vegetation period, estimated using the HTC, remained unchanged. Our results correlate with the official data of Rosgydromet, published in the Report on the peculiarities of the climate of the Russian Federation for 2021. Conclusion. The study allows us to state that in the mountainous landscapes of the North Caucasus, climatic changes proceed according to the scenario of an increase in air temperature and precipitation. As a result, agro-climatic indicators have changed: the sum of active temperatures has increased, exceeding 5o and 10oC and the duration of the period with an average daily temperature of 0, 5, 10oC, the dates of a stable transition through 0, 5, 10oC have changed, precipitation has increased, but the HTC has remained within the natural fluctuation . The stability of the HTC indicator indicates the stability of landscape boundaries, despite the observed changes in agro-climatic indicators. Resume. The observed climatic changes within the mountain landscapes of the North Caucasus contribute to an increase in the productivity of agricultural production by improving the conditions for heat and moisture supply to the territory. Suggestions for practical application and direction for future research. The results of the study can be useful for updating the schemes of agricultural zoning of the mountainous territories of the North Caucasus, as well as for developing land use schemes based on contour farming, which reduces the risks of adverse natural phenomena, including those caused by climate change.

Purpose: The suburban rail transport operation requires taking into account seasonal irregularities in passenger flows. Although a strong correlation between monthly passenger flows and average monthly air temperature was revealed earlier, it is less pronounced on some routes than on others. The study has been carried out to find out what causes the weak correlation on certain suburban routes and to define the weather impact areas on monthly traffic volumes. Methods: The research is based on the statistical reports of transportation companies such as JSC "North-Western Suburban Passenger Company" and LLC "Southern Suburban Passenger Company". The possible relationship between monthly passenger flows and the average monthly air temperature are investigated. Correlation analysis methods and MS Excel tools are used for data processing. The correlation coefficients are considered in combination with the coefficients of monthly unevenness. Results: The dependence of the monthly traffic irregularities on the correlation intensity between monthly passenger flows and the average monthly air temperature during the year has been established. The application area of the correlation between the average monthly air temperature and monthly passenger flows has been specified. The suburban routes classification has been proposed based on the factors effecting traffic volumes strongly. Practical significance: With a view to predicting, passenger flow changes are more advisable to describe based on a smaller number of factors, so as the prediction errors shall be fewer. For this purpose, the routes are categorised into ‘working’ and ‘recreational’ ones, as for each of them a different set of factors should be taken into consideration when making predictive equations or models. The correlation analysis between average monthly air temperature and monthly passenger flows can be useful when a geographical location makes it difficult to determine the type of destination

As the backland of the Qinghai-Tibet Plateau, the river source region is highly sensitive to changes in global climate. Air temperature estimation using remote sensing satellite provides a new way of conducting studies in the field of climate change study. A geographically weighted regression model was applied to estimate synchronic air temperature from 2001 to 2015 using Moderate-Resolution Imaging Spectroradiometry (MODIS) data. The results were R2 = 0.913 and RMSE = 2.47°C, which confirmed the feasibility of the estimation. The spatial distribution and variation characteristics of the average annual and seasonal air temperature were analyzed. The findings are as follows: (1) the distribution of average annual air temperature has significant terrain characteristics. The reduction in average annual air temperature along the elevation of the region is 0.19°C/km, whereas the reduction in the average annual air temperature along the latitude is 0.04°C/degree. (2) The average annual air temperature increase in the region is 0.37°C/decade. The average air temperature increase could be arranged in the following decreasing order: Yangtze River Basin > Mekong River Basin > Nujiang River Basin > Yarlung Zangbo River Basin > Yellow River Basin. The fastest, namely, Yangtze River Basin, is 0.47°C/decade. (3) The average air temperature rise in spring, summer, and winter generally increases with higher altitude. The average annual air temperature in different types of lands following a decreasing order is as follows: wetland > construction land > bare land glacier > shrub grassland > arable land > forest land > water body and that of the fastest one, wetland, is 0.13°C/year.