Climate and Bioclimatic Conditions of Kolguyev Island (Barents Sea)

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The analysis is based on data from the Kolguev Severny meteorological station for the period 1941–2024 and on field observations conducted during June–July of 2023 and 2025. Trends in air temperature and precipitation, as well as the duration of the frost-free and growing seasons, were calculated. The Universal Thermal Climate Index (UTCI) was used to assess bioclimatic conditions. A persistent increase in air temperature has been observed on Kolguev Island throughout the observation period in all seasons, with a marked intensification during the second decade of the 21st century. The dates of the spring transition of air temperature across 0°C have shifted to earlier dates, while the autumn transition has shifted to later dates, resulting in a lengthening of the growing season and an increase in the sum of positive temperatures. During the second decade of the 21st century, a tendency toward decreasing moisture availability on the island has also been observed. Throughout the year, bioclimatic conditions on Kolguev Island are dominated by cold stress of varying intensity according to the UTCI classification, ranging from extreme to slight cold stress. In summer (July–August), about 4% of days fall into the “no thermal stress” category according to UTCI. In the 21st century (2001–2022), the proportion of such days has increased. Field observations on Kolguev Island in June–July 2023 and 2025 indicate the predominance of strong and moderate cold stress conditions. Conditions corresponding to “no thermal stress” occur mainly during the morning and evening hours. climate bioclimate Universal Thermal Climate Index (UTCI) cold stress Kolguev Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Over the past two decades, the air temperature in the Arctic has increased at rates that are more than twice the global average (IPCC 2019 ; Notz and Stroeve 2016 ; Richter-Menge et al. 2017 ). This acceleration has been driven by feedback mechanisms associated with the reduction of sea ice and snow cover, which further increase warming. During each of the five years from 2014 to 2018, the annual mean near-surface air temperature in the Arctic has exceeded that of any year since 1900 (Overland et al. 2018 ). In the winters of 2016 and 2018, near-surface air temperatures in the central Arctic were 6°C higher than the average from 1981–2010, which is contributing to a reduction in sea ice in the region. In Russia, the highest air temperature trends for the period of 1960–2020 have occurred in Yamal, Taimyr, and along the coast of the East Siberian Sea (0.5–0.6°C per decade) (Third… 2022). In 1994–2010, warming in the Russian Arctic has mainly been associated with winter conditions, but the highest rates of increase in mean annual air temperature have occurred along the Arctic coast (Climate… 2025). In the Arctic-seas region, temperatures have increased by about 4°C in winter and 2°C in summer from the 1990s to the 2020s. Meteorological observations from coastal and island stations indicate an increase in winter air temperature since the 1970s by about 6°C and nearly 3°C in summer (Climate… 2025). The warming climate has also disrupted the traditional nature-use practices of the Indigenous peoples of the North. Higher temperatures and an increased number of freeze–thaw cycles in winter have led to a rise in transportation accidents among Indigenous communities due to weaker ice on routes crossing lakes, rivers, and seas, as well as changes in snow-cover conditions. The warming climate has also been identified as one of the causes of the sharp increase in wildfires in Yakutia (Revich 2023 ). In the context of ongoing global warming, there is an increasing need to assess the impacts of changing climatic conditions on humans, and bioclimatic indices are often used. The impact depends on numerous climatic parameters, including air temperature, wind speed, humidity, and solar radiation, as well as levels of human activity, clothing, and overall physical condition. The interaction of these factors can be evaluated using various bioclimatic indices (de Freitas and Grigorieva 2017 ). The Universal Thermal Climate Index (UTCI) is one of the most advanced indices and accounts for the combined effects of air temperature, wind speed, solar radiation, and humidity on the human body. This index is widely used to assess human thermal comfort in relation to climate and weather (Bröde et al. 2012 ; Potchter et al. 2018 ; Bröde 2021 ). Staiger et al. ( 2019 ) and Katavoutas et al. ( 2022 ) have shown that UTCI is among the most suitable indices for use in various areas of human biometeorology for both assessing short-term weather impacts and evaluating the consequences of long-term climate change. It is also applied in epidemiology, medical research, biometeorological forecasting, tourism and recreation studies, and bioclimate assessments at different spatial scales. The applications of the UTCI also include daily forecasting and warning systems, urban and regional planning, environmental epidemiology, and research on climate impacts on humans (Pappenberger et al. 2015 ). A major advantage of the UTCI compared with other indices is its universal assessment scale and its wide range of applicability from below − 50°C to above + 50°C. These features allow it to be used in all climatic conditions while ensuring full comparability of results obtained in different regions (Błażejczyk and Błażejczyk 2014 ażejczyk et al. 2012; de Freitas and Grigorieva 2017 ażejczyk and Kuchcik 2021 ). Unlike other bioclimatic indices that are closely linked to air temperature, the UTCI uses a more advanced model of clothing insulation (Havenith et al. 2012 ). The index has been used to assess thermal stress both at the global scale (Pappenberger et al. 2015 ) and in studies focusing on Europe (Di Napoli et al. 2018 ; Pappenberger and Hannah 2018 ), Africa (Boko et al. 2013 ), and Russia (Shartova et al. 2019 ; Konstantinov et al. 2020 ; Vinogradova 2019 , 2021 ). Bioclimatic studies in the Arctic have covered a substantial time spanning from the early 20th century to the present. For example, Araźny et al. ( 2019 ) assessed bioclimatic conditions in Franz Josef Land in the early 20th century. Based on expedition data, they showed that biometeorological conditions in the early 20th century were more severe than in 1981–2010. But in the early 1930s (during the early 20th-century warming period), conditions were more favorable and comparable to those observed in the current warming phase (Araźny et al. 2019 ). Research conducted in the current warming period shows that there have been improvements in bioclimatic conditions in Arctic regions. A comparative analysis of bioclimatic conditions in Chukotka and Alaska showed that the coldest UTCI categories are most common in coastal areas of Northern Alaska and Chukotka and are associated with strong winds and low winter temperatures (Grigorieva et al. 2023 ). The category of “slight heat stress” may occasionally occur in inland areas of these peninsulas. A decrease in extreme cold stress according to the UTCI has been accompanied by an expansion of the comfort range in both Alaska and Chukotka (Grigorieva et al. 2023 ). A steady increase in air temperature has also been observed across the Arctic, with stronger warming in winter than in summer (Climate… 2025). This has manifested as changes in the frequency and intensity of temperature extremes, particularly with a tendency toward decreasing winter cold extremes and increasing summer warm extremes (Sulikowska et al. 2019 ). In Northern Europe, cold stress remains common but is showing a decreasing trend of 8–12 hours per year. In the northern cities of Reykjavik in Iceland and Rovaniemi in Finland, the reduction in cold stress is about 10 hours per year (Mărmureanu et al. 2025 ). A gradual transition toward milder conditions has been observed, and the number of hours without or with moderate heat stress according to the UTCI has increased by 0.6% per decade (Mărmureanu et al. 2025 ). Data on Arkhangelsk for the period of 1999–2016 show that very strong and extreme cold stress did not occur there, which may possibly be due to the warming influence of the Atlantic Ocean. During the coldest months—January and February—the UTCI ranged from − 13 to − 27°C, which corresponds to strong cold stress (Shartova et al. 2019 ). In Arkhangelsk, Kandalaksha, Salekhard, and Naryan-Mar, the Physiological Equivalent Temperature (PET) index and UTCI increased 1.5–3.0 times faster than the air temperature (Semenova et al. 2019 ). With increasing summer temperatures in the Arctic, the UTCI has also increased at a rate of 0.457°C per decade in the period of 1979–2019 (Huang et al. 2021 ). The increase in the number of comfortable days in the Arctic has mainly been observed in Central Eastern Russia (66.5°–70° N), Greenland, and Ellesmere Island north of 80° N (Huang et al. 2021 ). The aim of the present study was to assess the changes in climatic and bioclimatic conditions on Kolguev Island from the mid-20th century to the present using various characteristics of the climatic regime and the UTCI. Study Area Most of Kolguev Island is occupied by flat landscapes of the typical and southern tundra zones. Thermokarst lakes and depressions are widespread, and deflation hollows occur in areas of exposed sands (Zinchenko, 2014 ). The surfaces of marine terraces feature peatlands with permafrost at depths of about 30 cm. The flora is largely characteristic of Arctic and sub-Arctic regions. The tundra vegetation is dominated by shrubs and grasses, with northern tundra landscapes prevailing mainly in the northern and western parts of the island, whereas southern tundra occurs in the southern and eastern sectors. The shrub layer consists of dwarf birch and several species of willow ( https://en.wikipedia.org/wiki/Kolguyev_Island ). Economic activity on Kolguyev Island is characterized by oil production (concentrated in the eastern part of the island) and the traditional indigenous livelihood of reindeer herding (Shmatova et al., 2023 ). The settlements are Bugrino and Severny ( https://en.wikipedia.org/wiki/Kolguyev_Island ). Materials and methods Climate change on Kolguev Island was assessed using data from the Kolguev Severny meteorological station (69.53° N, 49.08° E, 23 m a.s.l.; observation period 1941–2024). The analysis used daily mean, maximum, and minimum air temperatures, daily precipitation totals, wind speed, air humidity, and atmospheric pressure obtained from the website of the All-Russian Research Institute of Hydrometeorological Information – World Data Center (VNIIGMI-MCD) ( http://meteo.ru ). The bioclimatic conditions of the island were also evaluated through field observations conducted in 2023 and 2025 using an automatic meteorological station (Davis Vantage Pro2 Weather Station). Measurements were taken every half hour. Trends and changes in the mean annual, summer, and winter air temperatures and precipitation totals were recorded, as were the dates of air-temperature transitions across 0°C in spring and autumn. The statistical significance of the trends and changes was assessed at the 95% confidence level using Student’s t-test. Estimates were obtained for the duration of the frost-free period and the growing season (the number of days with mean daily temperature above + 5°C), as well as the sums of mean daily temperatures above 0°C and above + 5°C for the entire observation period and separately for 30-year periods (1961–1990 and 1981–2010) and 10-year intervals. Long-term fluctuations in climatic parameters were assessed using time series of air temperature and precipitation, corresponding linear trends for the entire observation period and for 2000–2024, and decadal moving averages. The calculations were performed using Excel and programs written in Python. The thermal state of the environment can be characterized in terms of bioclimatic indices that reflect its impact on humans, and the UTCI was used to assess changes in the bioclimate. The UTCI is based on the multi-node human heat balance model developed by Fiala (Fiala et al. 2012 ), which represents the thermal stress of the environment affecting the human body (de Freitas and Grigorieva 2017 ). The index describes the thermal conditions of the environment and is widely applied in various fields of human biometeorology (Błażejczyk et al. 2010 , 2013 ; Bröde et al. 2010 , 2012 ; Jendritzky et al. 2009, 2012). The UTCI can be interpreted as an equivalent environmental temperature (°C) that produces the same physiological response in the human body as the actual environmental conditions (Bröde et al. 2012 ). The deviation of the UTCI from air temperature ( T a ) depends on the actual values of air temperature, mean radiant temperature ( T mrt ), wind speed ( v a ), and humidity, which is expressed either as water vapor pressure ( e ) or relative humidity ( R ) (Błażejczyk et al. 2013 ). UTCI = f ( T a ; T mrt ; v a ; е ) = T a + Δ( T a ; T mrt ; v a ; е ) The sensitivity of the UTCI to temperature, humidity, and wind speed makes it applicable in both hot and cold conditions. The UTCI thermal stress categories are defined as follows (Błażejczyk et al. 2013 ; Bröde et al. 2012 ; Fiala et al. 2012 ): above + 46°C: extreme heat stress; +38 to + 46°C: very strong heat stress; +32 to + 38°C: strong heat stress; +26 to + 32°C: moderate heat stress; +9 to + 26°C: no thermal stress; 0 to + 9°C: slight cold stress; −13 to 0°C: moderate cold stress; −27 to − 13°C: strong cold stress; −40 to − 27°C: very strong cold stress; below − 40°C: extreme cold stress. The range of 18 to 26°C is considered the “thermal comfort zone.” Due to substantial data gaps in earlier periods, the mean daily UTCI values were calculated for 1966–2022. All bioclimatic index calculations were performed using the software package BioKlima © 2.6 ( https://www.igipz.pan.pl/bioklima.html ). The percentage of days characterized by different categories of heat and cold stress on the Island was assessed for the period of 1966–2022, for individual decades, and for June–July 2023 and 2025 (expedition-based observations). Linear trends in the UTCI were also calculated. Results and Discussions Characteristics of the Climatic Regime Climate change on Kolguev Island was assessed using linear trend coefficients that characterize the average rate of change in temperature, precipitation, and other parameters during the study period. Figure 2 shows the variations in mean annual, winter, and summer temperatures and precipitation, as well as their linear trends and 10-year moving averages, which illustrate medium-term climatic fluctuations. The mean annual temperatures ranged from − 6.5 to + 1°C. The highest values were recorded in the early 1940s and the 2020s, and positive average annual temperatures have been increasingly observed in the modern climate. Over the entire observation period, a warming trend can be identified, which became more pronounced at the beginning of the 21st century (Fig. 2a). The rate of increase in mean annual temperature showed a linear trend over the entire observation period at + 0.25°C per decade and was statistically significant. In the period of 2000–2024, the increase in mean annual temperature accelerated substantially and significantly, reaching 0.85°C per decade. Similar tendencies have been reported in many parts of the Arctic, including Alaska (Sulikowska et al., 2019 ) and the western sector of the Russian Arctic (Semenova et al. 2019 ; Climate…, 2025). Figure 2 Changes in average annual (a, d), winter (b, e), summer (c, f), temperatures (a-c) and precipitation (d-f), decadal moving averages (yellow) and trends according to data from the Kolguev Severny weather station for 1941–2024 Decadal moving averages allow assessment of medium-term cyclical variations in temperature and precipitation. The graphs clearly show quasi-decadal fluctuations in the mean annual temperature in the 20th century, including the warming of the 1930s to the early 1940s, which was also noted by Araźny et al. ( 2019 ), as well as the cooling of the 1970s. Since the early 2000s, the temperature has persistently increased. The mean summer temperatures range from 2.5 to 11°C (Fig. 2c), and the highest values occurred in the 2010s and 2020s. Over the entire observation period, the summer temperature exhibited a significant increasing trend of 0.26°C per decade. At the beginning of the 21st century, the rate of warming increased significantly to 0.68°C per decade. The mean winter temperatures range from − 18 to − 5°C (Fig. 2b). However, in the more eastern parts of the Russian Arctic, they may reach much lower values as low as − 40 to − 45°C in Severnaya Zemlya, the Laptev Sea, and the New Siberian Islands (Alexeev, 2014 ). The entire period showed a weak, positive, but statistically insignificant trend in winter temperature of 0.2°C per decade. Since the beginning of the 21st century, this trend increased to 1.05°C per decade, but it still remained statistically insignificant. The long-term average annual precipitation at the Kolguev Severny meteorological station is approximately 330 mm, and most precipitation occurs in the warm season. A slight increase occurred in the mean annual precipitation totals, but the trend was not statistically significant. In the context of interannual variability, the wettest periods occurred in the 1960s and 1970s and at the very beginning of the 2000s. The trends in both annual and seasonal precipitation totals for the entire observation period are slightly positive but not significant. In the subsequent period of 2000–2024, however, a decrease in precipitation occurred. Winter precipitation showed statistically significant negative trends (− 20.1 mm per decade) (Fig. 2e). Total precipitation also showed decreases in the annual levels (trend − 44.5 mm per decade) and in the summer (trend − 8.5 mm per decade), although these trends were not statistically significant (Fig. 2d, f). According to the long-term average climatic conditions of 1961–1990, the mean precipitation amount in periods with positive temperatures was 175 mm (Table 1 ). In the first decade of the 21st century (2000–2010), precipitation in the warm period increased to 210 mm, while in the second decade (2011–2021), it decreased to 172 mm, which is even lower than the long-term average. The precipitation trend for the warm period in 2000–2021 was − 31.8 mm per decade but was not statistically significant. The total precipitation for the cold period was 164 mm according to the long-term average conditions. In the 21st century, a substantial and consistent decline has been observed, and in 2011–2021, it decreased nearly twofold to 80 mm (Table 1 ). In northern regions, temperature is the principal factor that governs the development of vegetation, particularly thermal availability in the growing season. The most important characteristics of this factor are the duration of the frost-free period (the interval between the dates when air temperature crosses 0°C in spring and autumn) and the duration of the growing season (the number of days with temperatures above + 5°C) (Table 1 ). There was a tendency toward earlier spring transitions of mean daily air temperature across 0°C with a statistically significant trend of − 1 day per decade. In contrast, the dates of the autumn transition of mean daily air temperature across 0°C have been shifting toward later dates. At the Kolguev Severny meteorological station, the trend was weakly negative (− 0.3 days per decade). Table 1 Characteristics of heat and precipitation (Pr) supply and their changes*. (our research) Indicator Period Changes (differences) 1961–1990 1981–2010 2000–2010 2011–2021 3–1 3–2 4–1 4–2 4–3 1 2 3 4 Frost-free period, days 146 149 153 172 7 4 26 23 19 ∑ T > 0, °С 758 786 848 1058 90 63 300 273 210 Number of days with T > 5°С 69 75 82 101 13 7 32 26 19 ∑ T ≥ 5, °С 576 613 692 896 117 79 320 282 203 ∑ Pr (T ≥ 0°С) 175 190 210 172 35 20 –3 –18 –38 ∑ Pr (T < 0°С) 164 156 152 80 –12 –4 – 84 – 76 – 72 * Significant changes are highlighted in bold. According to the long-term average conditions of 1961–1990, the frost-free period on Kolguev Island lasted 146 days. In 2000–2010, it increased by 7 days, and in 2011–2021, it increased further by 19 days, reaching 172 days in the second decade of the 21st century, which is almost one month longer than in the 20th century. Notably, the most substantial and statistically significant increase occurred between the first and second decades of the 21st century. The sum of positive temperatures for the long-term average period (1961–1990) was 758°C. A substantial and statistically significant increase of 300°C was observed in 2011–2021, when the sum of positive temperatures reached 1058°C (Table 1 ). The period of active vegetation is associated with the number of days and the sum of temperatures above + 5°C. As noted by Titkova and Vinogradova ( 2015 ), the correlation coefficient between the sum of temperatures above + 5°C and the Normalized Difference Vegetation Index (NDVI) in the north of the European part of Russia is 0.85. On Kolguev Island, the period of active vegetation has increased by about one month (32 days), and the number of days when a mean daily temperature above + 5°C occurred increased from 69 days in 1961–1990 to 101 days in the second decade of the 21st century (Table 1 ). Characteristics of Bioclimatic Conditions Bioclimatic conditions on Kolguev Island are characterized by various degrees of cold stress for almost the entire year. Figure 3 shows the duration of different categories of the UTCI for the entire period (1966–2022) and for individual decades (categories: extreme, very strong, and strong cold stress). The average proportion of severe cold stress was 73% of the days per year, which corresponds to approximately 9 months. Moderate cold stress occurred on 22% of days, while days without thermal stress accounted for only 4%, or about 15 days. The highest percentage of days with the most severe cold stress categories was 76% and occurred in the 1970s. During this period, the proportion of days with extreme cold stress reached 18%. By the second decade of the 21st century (2011–2022), the proportion of days with extreme cold stress decreased twofold to 9%, which has also been reported for cities in the north of the European part of Russia (Semenova et al. 2019 ; Shartova et al. 2019 ). A reduction in the frequency of extreme cold stress has also been reported in other Arctic regions. For example, Grigorieva et al. ( 2023 ) demonstrated a decline in extreme cold-stress frequency in 1979–2020, particularly in Northern Alaska and along the Chukotka coast. A decrease in cold stress has also been reported for Iceland and Finland (Mărmureanu et al., 2025 ). At the same time, the number of days with very strong and strong cold stress changed only slightly and accounted for 29–32% of days, although the proportion of less severe conditions increased somewhat. The percentage of days classified as having no thermal stress remained almost unchanged and only increased to 6% in 2011–2022, which has also been noted by Huang et al. ( 2021 ). Figure 4 presents the seasonal variability in the duration of different UTCI categories for decadal periods. From December to March, bioclimatic conditions on Kolguev Island can be characterized by extreme, very strong, and strong cold stress. The most severe conditions occur in January and February. The proportion of days with extreme cold stress has gradually decreased from 55% (January) and 64% (February) in the 1970s (Fig. 4a) to 25% and 31% in the 2010s, respectively (Fig. 4e). February is the most severe month on the island. Since the 1980s (Fig. 4b), very strong cold stress has become the dominant winter condition and occurred on more than 50% of days in all periods, while the proportion of days with strong cold stress has gradually increased. During the transitional seasons (spring and autumn), the proportion of days with less severe cold-stress categories correspondingly increases or decreases. From May onward, conditions of strong and moderate cold stress become dominant, and under warming conditions, the percentage of such days has increased, while the percentage of days with very strong cold stress has decreased (Fig. 4). The warmest period on Kolguev is in July and August, and during these months, a small proportion of days fall into the “no thermal stress” category, ranging from 4% in the 1970s to 7% in the 2010s. Huang et al. ( 2021 ) have also reported an increase in the number of days without thermal stress in the Arctic. In these months, moderate and slight cold-stress conditions dominate, and by the 2010s, the proportion of days with slight cold stress increased, while the proportion with moderate cold stress decreased (Fig. 4). Figure 4 Seasonal duration of UTCI gradations based on data from the Kolguev Severny weather station for the periods: (a) 1971–1980; (b) 1981–1990; (c) 1991–2000; (d) 2001–2010; (e) 2011–2020 The diurnal variation of the UTCI was analyzed based on expedition observations conducted in June and July of 2023 and 2025 (Fig. 5 ). The results show that conditions on the island in this period were dominated by strong, moderate, and slight cold stress. In 2023, conditions were colder than in 2025, and very strong cold stress was recorded in 3–10% of observations (Fig. 5 a). Under polar day conditions, the diurnal cycle of the UTCI is weakly expressed, but moderate cold stress occurs more frequently in daytime hours. Table 2 Climatic and bioclimatic parameters for the periods of expeditionary observations. Air temperature, °C Wind speed, m/s UTCI, °C 2023 2025 2023 2025 2023 2025 Mean 6.8 7.2 5.5 4.7 –12.6 –6.2 Minimum 1.1 0.6 0.0 0.0 –37.7 –27.4 Maximum 18.9 18.4 14.3 12.5 12.4 13.2 Standard Deviation 3.2 3.2 2.5 2.9 9.4 8.5 Early in the morning and late in the evening, conditions are more favorable than in the day, with slight cold stress occurring more often. In 3% of cases in 2023 and in 5–7% of cases in 2025, conditions corresponded to the category of “no thermal stress.” During this period, the reduction in the severity of conditions appeared to be associated with a weakening of the wind. The wind is typically strong on the island because the main branch of the Arctic Front passes near it, which makes cyclonic activity more intense and increases wind speeds in the Barents Sea (Titkova et al., 2014 ). Table 2 presents the climatic and bioclimatic parameters from the expedition observations. The mean air temperature in June–July was about 7°C, the minimum was about 1°C, and the maximum was 18.9°C. The average wind speed was 4.7–5.5 m/s, with maximum values reaching 14.5 m/s. The mean UTCI values for the entire field observation period corresponded to the category of moderate cold stress, while minimum values reached very strong cold stress, and maximum values corresponded to the “no thermal stress” category. Figure 6 shows the variations in air temperature, wind speed, and UTCI during the observation periods in 2023 (Fig. 6 a) and 2025 (Fig. 6 b). The lowest UTCI values occurred at wind speeds of 10 m/s or higher, and even in summer, they could correspond to the category of very strong cold stress. Such conditions were observed on June 14–16, 2023, and on June 30, 2025. When the wind weakened during the nights of June 14–15, 2023, the UTCI increased to the category of moderate cold stress (Fig. 6 a). During the field observation periods, the UTCI reached the “no thermal stress” category only when wind speeds weakened and air temperatures were relatively high at around 12–14°C (June 25 and July 4, 2023; July 3 and 11, 2025). However, when winds remained strong at similar temperatures, bioclimatic conditions still corresponded to cold stress categories (July 5 and 10, 2023) (Fig. 6 ). Grigorieva et al. ( 2023 ) also emphasize that the coldest UTCI categories in Chukotka and Alaska are associated with strong winds and low temperatures. Conclusions The assessment of climatic changes on Kolguev Island indicated a persistent increase in air temperature in all seasons with a pronounced increase in intensity in the second decade of the 21st century. There was a shift toward earlier dates of the spring transition of air temperature across 0°C and toward later dates of the autumn transition, along with an increase in the duration of the growing season and the sum of positive temperatures. In the context of long-term increases in precipitation in the region, tendencies toward decreasing moisture availability have emerged on Kolguev Island in the second decade of the 21st century. Under conditions of global warming, the number of days with the most severe cold stress categories (extreme cold stress) decreased by half from 18% to 9%. In recent decades, bioclimatic conditions corresponding to less severe stress categories have begun to prevail. In the summer months, the proportion of days with “no thermal stress” increased from 4% in the 1970s to 7% in the 2010s, and the proportion of days with slight cold stress has also increased. Field observations in June–July 2023 and 2025 showed a predominance of strong and moderate cold-stress conditions. In the morning and evening hours, conditions of “no thermal stress” may occur, which are associated with a weakening of the wind. However, even in summer, conditions corresponding to very strong cold stress may occur with sufficiently low temperatures and wind speeds of 10 m/s or higher. Expedition observations made it possible to investigate the interdiurnal and intradiurnal fluctuations of climatic and bioclimatic parameters and to assess the range of variation in bioclimatic conditions in the summer months. During this time, the island’s population (who practice reindeer herding and traditional subsistence activities) and visiting people (for expeditions, tourism, or fishing) spend the maximum amount of time outdoors. When wind speeds decreased, bioclimatic conditions on the island can change substantially within a few hours, from very strong to moderate cold stress. Continued field studies on Arctic islands will make it possible to expand the detailed datasets available on the climatic and bioclimatic conditions of the Arctic. Declarations Competing interests. The author has declared that there are no conflicts of interest concerning this study. Funding. This work was supported by Russian Science Foundation (RSF) grant no. 22-17-00168-P, P “Biogeographic consequences of climate change in the Russian Arctic.” Acknowledgement. This research was supported by Russian Science Foundation (RSF) grant “Biogeographic consequences of climate change in the Russian Arctic.” Data availability. The raw data from the Kolguev Severny meteorological station are available at http://meteo.ru ; expedition observation data are available upon request. References Alexeev GV (2014) Impact of climatic and hydro-meteorological factors on the development of resource exploitations in the marine part of Russian Arctic. Strategic priorities for the development of the Russian Arctic: Collection of scientific papers. St. Petersburg State Polytechnic University. 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Springer, Cham. https://doi.org/10.1007/978-3-030- 76716-7_2 Bröde P, Jendritzky G, Fiala D, Havenith G (2010) The universal thermal climate index UTCI in operational use. Proceedings of conference: adapting to change: new thinking on comfort Cumberland Lodge, Windsor, UK, 9–11 April 2010 Bröde P, Fiala D, Błażejczyk K, Holmér I, Jendritzky G, Kampmann B et al (2012) Deriving the operational procedure for the universal thermal climate index (UTCI). Int J Biometeorol 56(3):481–494. https://doi.org/10.1007/s00484-011-0454-1 Climate Report for the Russian Federation for 2024 (2025) Rosgidromet. Moscow, 135 p. (In Russ) de Freitas CR, Grigorieva EA (2017) A comparison and appraisal of a comprehensive range of human thermal climate indices. Int J Biometeorol 61:487–512. https://doi.org/10.1007/s00484-016-1228-6 Di Napoli C, Pappenberger F, Cloke HL (2018) Assessing heatrelated health risk in Europe via the Universal Thermal Climate Index (UTCI). Int J Biometeorol 62:1155–1165. https://doi.org/10.1007/s00484-018-1518-2 Fiala D, Havenith G, Bröde P, Kampmann B, Jendritzky G (2012) UTCI Fiala multinode model human heat transfer and thermal comfort. Int J Biometeorol 56:429–441 Grigorieva EA, Alexeev VA, Walsh JE (2023) Universal thermal climate index in the Arctic in an era of climate change: Alaska and Chukotka as a case study. Int J Biometeorol 67:1703–1721. https://doi.org/10.1007/s00484-023-02531-2 Havenith G, Fiala D, Błazejczyk K, Richards M, Bröde P, Holmér I, Rintamaki H, Benshabat Y, Jendritzky G (2012) The UTCI-clothing model. Int J Biometeorol 56:461–470. 10.1007/s00484-011-0451-4 Huang Y, Zhang X, Zhang D, Zhang L, Zhang W, Ren C, Pan T, Chu Z, Chen Y (2021) Spatial-Temporal Characteristics of Arctic Summer Climate Comfort Level in the Context of Regional Tourism Resources from 1979 to 2019. Sustainability 13:13056. https://doi.org/10.3390/su132313056 https:// en.wikipedia.org/wiki/Kolguyev_Island (11.02.2026) IPCC (2019) : Meredith, M., M. Sommerkorn, S. Cassotta, C. Derksen, A. Ekaykin, A. Hollowed, G. Kofinas, A. Mackintosh, J. Melbourne-Thomas, M.M.C. Muelbert, G. Ottersen, H. Pritchard, and E.A.G. Schuur, 2019: Polar Regions. In: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate [H.-O. Pörtner, D.C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, N.M. Weyer (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp. 203–320. https://doi.org/10.1017/9781009157964.005 Katavoutas G, Founda D, Varotsos KV, Giannakopoulos C (2022) Climate change impacts on thermal stress in four climatically diverse European cities. Int J Biometeorol 66:2339–2355. https://doi.org/10.1007/s00484-022-02361-8 Konstantinov P, Shartova N, Varentsov M, Revich B (2020) Evaluation of outdoor thermal comfort conditions in Northern Russia over 30-year period (Arkhangelsk Region). Geogr Pannonica 24(4). https://doi.org/10.5937/gp24- 24738 Notz D, Stroeve J (2016) Observed Arctic sea-ice loss directly follows anthropogenic CO 2 emission. Science 354(6313):747–750. 10.1126/science.aag2345 Mărmureanu L, Antonescu B, Ene D, Andrei S, Turcu R (2025) Changes in the thermal stress across Europe between 1940–2023. Int J Biometeorol 69:3569–3586. https://doi.org/10.1007/s00484-025-03043-x Overland JE, Hanna E, Hanssen-Bauer I, Kim S-J, Walsh JE, Wang M, Bhatt US, Thoman RL (2018) Surface air temperature. in Arctic Report Card 2018 https://arctic.noaa.gov/Report-Card/Report-Card-2018/ArtMID/7878/ArticleID/783/Surface-Air-Temperature Pappenberger F, Jendritzky G, Staiger H, Dutra E, Di Giuseppe F, Richardson DS, Cloke HL (2015) Global forecasting of thermal health hazards: The skill of probabilistic predictions of the Universal Thermal Climate Index (UTCI). Int J Biometeorol 59(3):311–323. http://dx.doi.org/10.1007/s00484-014-0843-3 Pappenberger F, Hannah LC (2018) Assessing heat-related health risk in Europe via the Universal Thermal Climate Index (UTCI). Int J Biometeorol. https://doi.org/10.1007/s00484-018-1518-2 Potchter O, Cohen P, Lin TP, Matzarakis A (2018) Outdoor human thermal perception in various climates: a comprehensive review of approaches, methods and quantification. Sci Total Environ 631:390–406. https://doi.org/10. 1016/j. scito tenv. 2018. 02. 276 Revich ВА (2023) Changing climate and puЫic health: proЫems of adaptation: scientific report. ed. B.N. Porfiryev. Dynamic Print, Мoscow. 168 р. (In Russ) Richter-Menge J, Overland JE, Mathis JT, Osborne EE (2017) Arctic Report Card 2017. Semenova AA, Konstantinov PI, Varentsov MI, Samsonov TE (2019) Modeling the dynamics of comfort thermal conditions in Arctic cities under regional climate change. IOP Conf Series: Earth Environ Sci 386:012017. 10.1088/1755-1315/386/1/012017 Shartova N, Shaposhnikov DA, Konstantinov PI, Revich BA (2019) Universal Thermal Climate Index (UTCI) applied to determine thresholds for temperature-related mortality. Health Risk Analysis 3:83–93. https://doi.org/10.21668/health. risk/ 2019.3. 10. eng Shmatova AG, Loshchagina JA, Glazov PM (2023) Analysis of Landsat time series to identify climate-inducedland cover changes on Kolguev Island. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa 20(4):149–164 (In Russ) Staiger H, Laschewski G, Matzarakis A (2019) Selection of Appropriate Thermal Indices for Applications in Human Biometeorological Studies. Atmosphere 10:18. https://doi.org/10.3390/atmos10010018 Sulikowska A, Walawender JP, Walawender E (2019) Temperature extremes in Alaska: temporal variability and circulation background. Theoret Appl Climatol 136:955–970. https://doi.org/10.1007/s00704-018-2528-z Third Assessment Report on Climate Change and Its Consequences on the Territory of the Russian Federation (2022) St. Petersburg: Naukoemkie technologii Publ. 676 p. (In Russ) Titkova TB, Vinogradova VV (2015) The response of vegetation to climate change in boreal and subarctic landscapes at the beginning of XXI century. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 12(3):75–86 (In Russ) Titkova TB, Mikhailov AY, Vinogradova VV (2014) Arctic Front and Barents Sea ice coverage in winter. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa. 11(3):117–125 (In Russ) Vinogradova VV (2019) Universal index of thermal comfort on the territory of Russia. Izv Akad Nauk Ser Geogr 2:3–19 (In Russ) Vinogradova VV (2021) Using the Universal Thermal Climate Index UTCI) for the assessment of bioclimatic conditions in Russia. Int J Biometeorol 65:1473–1483. https://doi.org/10.1007/s00484-020-01901-4 Zinchenko AG (2014) Geomorphological scheme Scale 1:2 500 000, In: Map of the Pliocene-Quaternary for-mations. Sheet R-39,40. Saint Petersburg: Kartograficheskaya fabrikaVSEGEI 1:8 (In Russ) Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 21 Mar, 2026 Reviewers invited by journal 20 Mar, 2026 Editor assigned by journal 18 Mar, 2026 First submitted to journal 18 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9138286","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":609462885,"identity":"f39e1972-7af4-4760-b11b-a6a472fbe41c","order_by":0,"name":"Vera Vinogradova","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYJCCA0AsB2JIkKTFmDQtIJDYQLQWgxs5hocLKmrTNxw/e/DGxzaGfIMDhLUYHJ5x5njuhjN5yZYzzjBYbiCkRbLnWMJh3rZjuRsO5JhJ81QwGBC0BaYl3eD8GzPpPwZEaOFnbz4A1FKTAHShmTQDMbaAtfCcOWA488YbY8ueMxIGkoS0sDEzNn/mqaiT5zufY3jjZ5uNAR8hLVBwmEEBopL42KxjkG8gWvEoGAWjYBSMNAAAVNpEAldDSWAAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-3036-3705","institution":"Institut geografii RAN","correspondingAuthor":true,"prefix":"","firstName":"Vera","middleName":"","lastName":"Vinogradova","suffix":""}],"badges":[],"createdAt":"2026-03-16 13:09:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9138286/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9138286/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105565631,"identity":"ee319028-0cae-483a-b0ba-9e91279ca4c0","added_by":"auto","created_at":"2026-03-27 12:53:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2550137,"visible":true,"origin":"","legend":"\u003cp\u003eKolguev Island, meteorological station Kolguev Severny, and expedition observation points in 2023 and 2025\u003c/p\u003e","description":"","filename":"VinogradovaFig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9138286/v1/79dbe816e825da7e06841dd4.jpg"},{"id":105565106,"identity":"0c1f65f8-a7ac-477b-98db-3b34014b5b15","added_by":"auto","created_at":"2026-03-27 12:51:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4604972,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in average annual (a, d), winter (b, e), summer (c, f), temperatures (a-c) and precipitation (d-f), decadal moving averages (yellow) and trends according to data from the Kolguev Severny weather station for 1941–2024\u003c/p\u003e","description":"","filename":"VinogradovaFig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9138286/v1/c230c0acb1760b4e3db78b22.jpg"},{"id":105373208,"identity":"df46c6bd-f5f3-4e5b-9cc0-00ac4701f098","added_by":"auto","created_at":"2026-03-25 09:47:01","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":716234,"visible":true,"origin":"","legend":"\u003cp\u003eDuration of the Universal Thermal Climate Index (UTCI) gradations for the period (1966–2022) and ten-year periods based on data from the Kolguev Severny weather station\u003c/p\u003e","description":"","filename":"VinogradovaFig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9138286/v1/a12481e2fc74fcdb0cb0e342.jpg"},{"id":105373207,"identity":"d2870da3-31a3-40ce-a93c-18fad1143a6b","added_by":"auto","created_at":"2026-03-25 09:47:01","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1926492,"visible":true,"origin":"","legend":"\u003cp\u003eSeasonal duration of UTCI gradations based on data from the Kolguev Severny weather station for the periods: (a) 1971–1980; (b) 1981–1990; (c) 1991–2000; (d) 2001–2010; (e) 2011–2020\u003c/p\u003e","description":"","filename":"VinogradovaFig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9138286/v1/e936436135a7f1efa811a002.jpg"},{"id":105373205,"identity":"a8e5605b-97f9-4d47-a541-7faca24c8597","added_by":"auto","created_at":"2026-03-25 09:47:01","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1879996,"visible":true,"origin":"","legend":"\u003cp\u003eDiurnal variations in the duration of UTCI gradations based on expeditionary observations for (a) 2023 and (b) 2025\u003c/p\u003e","description":"","filename":"VinogradovaFig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9138286/v1/f8fe8060532c2e0fbe8956a4.jpg"},{"id":105373202,"identity":"16845161-9961-4a99-a427-c35c7356a983","added_by":"auto","created_at":"2026-03-25 09:47:01","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3001291,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in air temperature, wind speed, and UTCI over the expedition observation period: (a) 2023 and (b) 2025\u003c/p\u003e","description":"","filename":"VinogradovaFig.6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9138286/v1/e4227dd96301bc45e369083d.jpg"},{"id":105570085,"identity":"04676ba0-53c3-4320-8778-13218748628f","added_by":"auto","created_at":"2026-03-27 13:14:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":17510261,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9138286/v1/de4765a6-59da-4884-8159-9996b9e54d07.pdf"}],"financialInterests":"","formattedTitle":"Climate and Bioclimatic Conditions of Kolguyev Island (Barents Sea)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOver the past two decades, the air temperature in the Arctic has increased at rates that are more than twice the global average (IPCC \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Notz and Stroeve \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Richter-Menge et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This acceleration has been driven by feedback mechanisms associated with the reduction of sea ice and snow cover, which further increase warming. During each of the five years from 2014 to 2018, the annual mean near-surface air temperature in the Arctic has exceeded that of any year since 1900 (Overland et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In the winters of 2016 and 2018, near-surface air temperatures in the central Arctic were 6\u0026deg;C higher than the average from 1981\u0026ndash;2010, which is contributing to a reduction in sea ice in the region. In Russia, the highest air temperature trends for the period of 1960\u0026ndash;2020 have occurred in Yamal, Taimyr, and along the coast of the East Siberian Sea (0.5\u0026ndash;0.6\u0026deg;C per decade) (Third\u0026hellip; 2022). In 1994\u0026ndash;2010, warming in the Russian Arctic has mainly been associated with winter conditions, but the highest rates of increase in mean annual air temperature have occurred along the Arctic coast (Climate\u0026hellip; 2025).\u003c/p\u003e \u003cp\u003eIn the Arctic-seas region, temperatures have increased by about 4\u0026deg;C in winter and 2\u0026deg;C in summer from the 1990s to the 2020s. Meteorological observations from coastal and island stations indicate an increase in winter air temperature since the 1970s by about 6\u0026deg;C and nearly 3\u0026deg;C in summer (Climate\u0026hellip; 2025). The warming climate has also disrupted the traditional nature-use practices of the Indigenous peoples of the North. Higher temperatures and an increased number of freeze\u0026ndash;thaw cycles in winter have led to a rise in transportation accidents among Indigenous communities due to weaker ice on routes crossing lakes, rivers, and seas, as well as changes in snow-cover conditions. The warming climate has also been identified as one of the causes of the sharp increase in wildfires in Yakutia (Revich \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the context of ongoing global warming, there is an increasing need to assess the impacts of changing climatic conditions on humans, and bioclimatic indices are often used. The impact depends on numerous climatic parameters, including air temperature, wind speed, humidity, and solar radiation, as well as levels of human activity, clothing, and overall physical condition. The interaction of these factors can be evaluated using various bioclimatic indices (de Freitas and Grigorieva \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Universal Thermal Climate Index (UTCI) is one of the most advanced indices and accounts for the combined effects of air temperature, wind speed, solar radiation, and humidity on the human body. This index is widely used to assess human thermal comfort in relation to climate and weather (Br\u0026ouml;de et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Potchter et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Br\u0026ouml;de \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Staiger et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Katavoutas et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) have shown that UTCI is among the most suitable indices for use in various areas of human biometeorology for both assessing short-term weather impacts and evaluating the consequences of long-term climate change. It is also applied in epidemiology, medical research, biometeorological forecasting, tourism and recreation studies, and bioclimate assessments at different spatial scales. The applications of the UTCI also include daily forecasting and warning systems, urban and regional planning, environmental epidemiology, and research on climate impacts on humans (Pappenberger et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA major advantage of the UTCI compared with other indices is its universal assessment scale and its wide range of applicability from below \u0026minus;\u0026thinsp;50\u0026deg;C to above +\u0026thinsp;50\u0026deg;C. These features allow it to be used in all climatic conditions while ensuring full comparability of results obtained in different regions (Błażejczyk and Błażejczyk \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003eażejczyk et al. 2012; de Freitas and Grigorieva \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003eażejczyk and Kuchcik \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Unlike other bioclimatic indices that are closely linked to air temperature, the UTCI uses a more advanced model of clothing insulation (Havenith et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The index has been used to assess thermal stress both at the global scale (Pappenberger et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and in studies focusing on Europe (Di Napoli et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Pappenberger and Hannah \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Africa (Boko et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and Russia (Shartova et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Konstantinov et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Vinogradova \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBioclimatic studies in the Arctic have covered a substantial time spanning from the early 20th century to the present. For example, Araźny et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) assessed bioclimatic conditions in Franz Josef Land in the early 20th century. Based on expedition data, they showed that biometeorological conditions in the early 20th century were more severe than in 1981\u0026ndash;2010. But in the early 1930s (during the early 20th-century warming period), conditions were more favorable and comparable to those observed in the current warming phase (Araźny et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearch conducted in the current warming period shows that there have been improvements in bioclimatic conditions in Arctic regions. A comparative analysis of bioclimatic conditions in Chukotka and Alaska showed that the coldest UTCI categories are most common in coastal areas of Northern Alaska and Chukotka and are associated with strong winds and low winter temperatures (Grigorieva et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The category of \u0026ldquo;slight heat stress\u0026rdquo; may occasionally occur in inland areas of these peninsulas. A decrease in extreme cold stress according to the UTCI has been accompanied by an expansion of the comfort range in both Alaska and Chukotka (Grigorieva et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA steady increase in air temperature has also been observed across the Arctic, with stronger warming in winter than in summer (Climate\u0026hellip; 2025). This has manifested as changes in the frequency and intensity of temperature extremes, particularly with a tendency toward decreasing winter cold extremes and increasing summer warm extremes (Sulikowska et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In Northern Europe, cold stress remains common but is showing a decreasing trend of 8\u0026ndash;12 hours per year. In the northern cities of Reykjavik in Iceland and Rovaniemi in Finland, the reduction in cold stress is about 10 hours per year (Mărmureanu et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). A gradual transition toward milder conditions has been observed, and the number of hours without or with moderate heat stress according to the UTCI has increased by 0.6% per decade (Mărmureanu et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eData on Arkhangelsk for the period of 1999\u0026ndash;2016 show that very strong and extreme cold stress did not occur there, which may possibly be due to the warming influence of the Atlantic Ocean. During the coldest months\u0026mdash;January and February\u0026mdash;the UTCI ranged from \u0026minus;\u0026thinsp;13 to \u0026minus;\u0026thinsp;27\u0026deg;C, which corresponds to strong cold stress (Shartova et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In Arkhangelsk, Kandalaksha, Salekhard, and Naryan-Mar, the Physiological Equivalent Temperature (PET) index and UTCI increased 1.5\u0026ndash;3.0 times faster than the air temperature (Semenova et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWith increasing summer temperatures in the Arctic, the UTCI has also increased at a rate of 0.457\u0026deg;C per decade in the period of 1979\u0026ndash;2019 (Huang et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The increase in the number of comfortable days in the Arctic has mainly been observed in Central Eastern Russia (66.5\u0026deg;\u0026ndash;70\u0026deg; N), Greenland, and Ellesmere Island north of 80\u0026deg; N (Huang et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe aim of the present study was to assess the changes in climatic and bioclimatic conditions on Kolguev Island from the mid-20th century to the present using various characteristics of the climatic regime and the UTCI.\u003c/p\u003e\n\u003ch3\u003eStudy Area\u003c/h3\u003e\n\u003cp\u003e \u003c/p\u003e \u003cp\u003eMost of Kolguev Island is occupied by flat landscapes of the typical and southern tundra zones. Thermokarst lakes and depressions are widespread, and deflation hollows occur in areas of exposed sands (Zinchenko, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The surfaces of marine terraces feature peatlands with permafrost at depths of about 30 cm. The flora is largely characteristic of Arctic and sub-Arctic regions. The tundra vegetation is dominated by shrubs and grasses, with northern tundra landscapes prevailing mainly in the northern and western parts of the island, whereas southern tundra occurs in the southern and eastern sectors. The shrub layer consists of dwarf birch and several species of willow (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://en.wikipedia.org/wiki/Kolguyev_Island\u003c/span\u003e\u003cspan address=\"https://en.wikipedia.org/wiki/Kolguyev_Island\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEconomic activity on Kolguyev Island is characterized by oil production (concentrated in the eastern part of the island) and the traditional indigenous livelihood of reindeer herding (Shmatova et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The settlements are Bugrino and Severny (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://en.wikipedia.org/wiki/Kolguyev_Island\u003c/span\u003e\u003cspan address=\"https://en.wikipedia.org/wiki/Kolguyev_Island\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eClimate change on Kolguev Island was assessed using data from the Kolguev Severny meteorological station (69.53\u0026deg; N, 49.08\u0026deg; E, 23 m a.s.l.; observation period 1941\u0026ndash;2024). The analysis used daily mean, maximum, and minimum air temperatures, daily precipitation totals, wind speed, air humidity, and atmospheric pressure obtained from the website of the All-Russian Research Institute of Hydrometeorological Information \u0026ndash; World Data Center (VNIIGMI-MCD) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://meteo.ru\u003c/span\u003e\u003cspan address=\"http://meteo.ru\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The bioclimatic conditions of the island were also evaluated through field observations conducted in 2023 and 2025 using an automatic meteorological station (Davis Vantage Pro2 Weather Station). Measurements were taken every half hour.\u003c/p\u003e \u003cp\u003eTrends and changes in the mean annual, summer, and winter air temperatures and precipitation totals were recorded, as were the dates of air-temperature transitions across 0\u0026deg;C in spring and autumn. The statistical significance of the trends and changes was assessed at the 95% confidence level using Student\u0026rsquo;s t-test. Estimates were obtained for the duration of the frost-free period and the growing season (the number of days with mean daily temperature above +\u0026thinsp;5\u0026deg;C), as well as the sums of mean daily temperatures above 0\u0026deg;C and above +\u0026thinsp;5\u0026deg;C for the entire observation period and separately for 30-year periods (1961\u0026ndash;1990 and 1981\u0026ndash;2010) and 10-year intervals. Long-term fluctuations in climatic parameters were assessed using time series of air temperature and precipitation, corresponding linear trends for the entire observation period and for 2000\u0026ndash;2024, and decadal moving averages. The calculations were performed using Excel and programs written in Python.\u003c/p\u003e \u003cp\u003eThe thermal state of the environment can be characterized in terms of bioclimatic indices that reflect its impact on humans, and the UTCI was used to assess changes in the bioclimate. The UTCI is based on the multi-node human heat balance model developed by Fiala (Fiala et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), which represents the thermal stress of the environment affecting the human body (de Freitas and Grigorieva \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The index describes the thermal conditions of the environment and is widely applied in various fields of human biometeorology (Błażejczyk et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Br\u0026ouml;de et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Jendritzky et al. 2009, 2012). The UTCI can be interpreted as an equivalent environmental temperature (\u0026deg;C) that produces the same physiological response in the human body as the actual environmental conditions (Br\u0026ouml;de et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The deviation of the UTCI from air temperature (\u003cem\u003eT\u003c/em\u003e\u003csub\u003ea\u003c/sub\u003e) depends on the actual values of air temperature, mean radiant temperature (\u003cem\u003eT\u003c/em\u003e\u003csub\u003emrt\u003c/sub\u003e), wind speed (\u003cem\u003ev\u003c/em\u003e\u003csub\u003ea\u003c/sub\u003e), and humidity, which is expressed either as water vapor pressure (\u003cem\u003ee\u003c/em\u003e) or relative humidity (\u003cem\u003eR\u003c/em\u003e) (Błażejczyk et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUTCI\u0026thinsp;=\u0026thinsp;\u003cem\u003ef\u003c/em\u003e (\u003cem\u003eT\u003c/em\u003e\u003csub\u003ea\u003c/sub\u003e; \u003cem\u003eT\u003c/em\u003e\u003csub\u003emrt\u003c/sub\u003e; \u003cem\u003ev\u003c/em\u003e\u003csub\u003ea\u003c/sub\u003e; \u003cem\u003eе\u003c/em\u003e) = \u003cem\u003eT\u003c/em\u003e\u003csub\u003ea\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;Δ(\u003cem\u003eT\u003c/em\u003e\u003csub\u003ea\u003c/sub\u003e; \u003cem\u003eT\u003c/em\u003e\u003csub\u003emrt\u003c/sub\u003e; \u003cem\u003ev\u003c/em\u003e\u003csub\u003ea\u003c/sub\u003e; \u003cem\u003eе\u003c/em\u003e)\u003c/p\u003e \u003cp\u003eThe sensitivity of the UTCI to temperature, humidity, and wind speed makes it applicable in both hot and cold conditions. The UTCI thermal stress categories are defined as follows (Błażejczyk et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Br\u0026ouml;de et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Fiala et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e): above +\u0026thinsp;46\u0026deg;C: extreme heat stress; +38 to +\u0026thinsp;46\u0026deg;C: very strong heat stress; +32 to +\u0026thinsp;38\u0026deg;C: strong heat stress; +26 to +\u0026thinsp;32\u0026deg;C: moderate heat stress; +9 to +\u0026thinsp;26\u0026deg;C: no thermal stress; 0 to +\u0026thinsp;9\u0026deg;C: slight cold stress; \u0026minus;13 to 0\u0026deg;C: moderate cold stress; \u0026minus;27 to \u0026minus;\u0026thinsp;13\u0026deg;C: strong cold stress; \u0026minus;40 to \u0026minus;\u0026thinsp;27\u0026deg;C: very strong cold stress; below \u0026minus;\u0026thinsp;40\u0026deg;C: extreme cold stress. The range of 18 to 26\u0026deg;C is considered the \u0026ldquo;thermal comfort zone.\u0026rdquo;\u003c/p\u003e \u003cp\u003eDue to substantial data gaps in earlier periods, the mean daily UTCI values were calculated for 1966\u0026ndash;2022. All bioclimatic index calculations were performed using the software package BioKlima \u0026copy; 2.6 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.igipz.pan.pl/bioklima.html\u003c/span\u003e\u003cspan address=\"https://www.igipz.pan.pl/bioklima.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The percentage of days characterized by different categories of heat and cold stress on the Island was assessed for the period of 1966\u0026ndash;2022, for individual decades, and for June\u0026ndash;July 2023 and 2025 (expedition-based observations). Linear trends in the UTCI were also calculated.\u003c/p\u003e"},{"header":"Results and Discussions","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of the Climatic Regime\u003c/h2\u003e \u003cp\u003eClimate change on Kolguev Island was assessed using linear trend coefficients that characterize the average rate of change in temperature, precipitation, and other parameters during the study period. Figure\u0026nbsp;2 shows the variations in mean annual, winter, and summer temperatures and precipitation, as well as their linear trends and 10-year moving averages, which illustrate medium-term climatic fluctuations.\u003c/p\u003e \u003cp\u003eThe mean annual temperatures ranged from \u0026minus;\u0026thinsp;6.5 to +\u0026thinsp;1\u0026deg;C. The highest values were recorded in the early 1940s and the 2020s, and positive average annual temperatures have been increasingly observed in the modern climate. Over the entire observation period, a warming trend can be identified, which became more pronounced at the beginning of the 21st century (Fig.\u0026nbsp;2a). The rate of increase in mean annual temperature showed a linear trend over the entire observation period at +\u0026thinsp;0.25\u0026deg;C per decade and was statistically significant. In the period of 2000\u0026ndash;2024, the increase in mean annual temperature accelerated substantially and significantly, reaching 0.85\u0026deg;C per decade. Similar tendencies have been reported in many parts of the Arctic, including Alaska (Sulikowska et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and the western sector of the Russian Arctic (Semenova et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Climate\u0026hellip;, 2025).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;2\u003c/b\u003e Changes in average annual (a, d), winter (b, e), summer (c, f), temperatures (a-c) and precipitation (d-f), decadal moving averages (yellow) and trends according to data from the Kolguev Severny weather station for 1941\u0026ndash;2024\u003c/p\u003e \u003cp\u003eDecadal moving averages allow assessment of medium-term cyclical variations in temperature and precipitation. The graphs clearly show quasi-decadal fluctuations in the mean annual temperature in the 20th century, including the warming of the 1930s to the early 1940s, which was also noted by Araźny et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), as well as the cooling of the 1970s. Since the early 2000s, the temperature has persistently increased. The mean summer temperatures range from 2.5 to 11\u0026deg;C (Fig.\u0026nbsp;2c), and the highest values occurred in the 2010s and 2020s. Over the entire observation period, the summer temperature exhibited a significant increasing trend of 0.26\u0026deg;C per decade. At the beginning of the 21st century, the rate of warming increased significantly to 0.68\u0026deg;C per decade.\u003c/p\u003e \u003cp\u003eThe mean winter temperatures range from \u0026minus;\u0026thinsp;18 to \u0026minus;\u0026thinsp;5\u0026deg;C (Fig.\u0026nbsp;2b). However, in the more eastern parts of the Russian Arctic, they may reach much lower values as low as \u0026minus;\u0026thinsp;40 to \u0026minus;\u0026thinsp;45\u0026deg;C in Severnaya Zemlya, the Laptev Sea, and the New Siberian Islands (Alexeev, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The entire period showed a weak, positive, but statistically insignificant trend in winter temperature of 0.2\u0026deg;C per decade. Since the beginning of the 21st century, this trend increased to 1.05\u0026deg;C per decade, but it still remained statistically insignificant.\u003c/p\u003e \u003cp\u003eThe long-term average annual precipitation at the Kolguev Severny meteorological station is approximately 330 mm, and most precipitation occurs in the warm season. A slight increase occurred in the mean annual precipitation totals, but the trend was not statistically significant. In the context of interannual variability, the wettest periods occurred in the 1960s and 1970s and at the very beginning of the 2000s. The trends in both annual and seasonal precipitation totals for the entire observation period are slightly positive but not significant.\u003c/p\u003e \u003cp\u003eIn the subsequent period of 2000\u0026ndash;2024, however, a decrease in precipitation occurred. Winter precipitation showed statistically significant negative trends (\u0026minus;\u0026thinsp;20.1 mm per decade) (Fig.\u0026nbsp;2e). Total precipitation also showed decreases in the annual levels (trend\u0026thinsp;\u0026minus;\u0026thinsp;44.5 mm per decade) and in the summer (trend\u0026thinsp;\u0026minus;\u0026thinsp;8.5 mm per decade), although these trends were not statistically significant (Fig.\u0026nbsp;2d, f).\u003c/p\u003e \u003cp\u003eAccording to the long-term average climatic conditions of 1961\u0026ndash;1990, the mean precipitation amount in periods with positive temperatures was 175 mm (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the first decade of the 21st century (2000\u0026ndash;2010), precipitation in the warm period increased to 210 mm, while in the second decade (2011\u0026ndash;2021), it decreased to 172 mm, which is even lower than the long-term average. The precipitation trend for the warm period in 2000\u0026ndash;2021 was \u0026minus;\u0026thinsp;31.8 mm per decade but was not statistically significant. The total precipitation for the cold period was 164 mm according to the long-term average conditions. In the 21st century, a substantial and consistent decline has been observed, and in 2011\u0026ndash;2021, it decreased nearly twofold to 80 mm (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn northern regions, temperature is the principal factor that governs the development of vegetation, particularly thermal availability in the growing season. The most important characteristics of this factor are the duration of the frost-free period (the interval between the dates when air temperature crosses 0\u0026deg;C in spring and autumn) and the duration of the growing season (the number of days with temperatures above +\u0026thinsp;5\u0026deg;C) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There was a tendency toward earlier spring transitions of mean daily air temperature across 0\u0026deg;C with a statistically significant trend of \u0026minus;\u0026thinsp;1 day per decade. In contrast, the dates of the autumn transition of mean daily air temperature across 0\u0026deg;C have been shifting toward later dates. At the Kolguev Severny meteorological station, the trend was weakly negative (\u0026minus;\u0026thinsp;0.3 days per decade).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of heat and precipitation (Pr) supply and their changes*. (our research)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eChanges (differences)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1961\u0026ndash;1990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1981\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2000\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2011\u0026ndash;2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrost-free period, days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026sum; T\u0026thinsp;\u0026gt;\u0026thinsp;0, \u0026deg;С\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e273\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e210\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of days with T\u0026thinsp;\u0026gt;\u0026thinsp;5\u0026deg;С\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026sum; T \u0026ge; 5, \u0026deg;С\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e320\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e282\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e203\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026sum; Pr (T \u0026ge; 0\u0026deg;С)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026ndash;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026sum; Pr (T\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026deg;С)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ndash;\u003cb\u003e84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026ndash;\u003cb\u003e76\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;\u003cb\u003e72\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e* Significant changes are highlighted in bold.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAccording to the long-term average conditions of 1961\u0026ndash;1990, the frost-free period on Kolguev Island lasted 146 days. In 2000\u0026ndash;2010, it increased by 7 days, and in 2011\u0026ndash;2021, it increased further by 19 days, reaching 172 days in the second decade of the 21st century, which is almost one month longer than in the 20th century. Notably, the most substantial and statistically significant increase occurred between the first and second decades of the 21st century. The sum of positive temperatures for the long-term average period (1961\u0026ndash;1990) was 758\u0026deg;C. A substantial and statistically significant increase of 300\u0026deg;C was observed in 2011\u0026ndash;2021, when the sum of positive temperatures reached 1058\u0026deg;C (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe period of active vegetation is associated with the number of days and the sum of temperatures above +\u0026thinsp;5\u0026deg;C. As noted by Titkova and Vinogradova (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), the correlation coefficient between the sum of temperatures above +\u0026thinsp;5\u0026deg;C and the Normalized Difference Vegetation Index (NDVI) in the north of the European part of Russia is 0.85. On Kolguev Island, the period of active vegetation has increased by about one month (32 days), and the number of days when a mean daily temperature above +\u0026thinsp;5\u0026deg;C occurred increased from 69 days in 1961\u0026ndash;1990 to 101 days in the second decade of the 21st century (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCharacteristics of Bioclimatic Conditions\u003c/h3\u003e\n\u003cp\u003eBioclimatic conditions on Kolguev Island are characterized by various degrees of cold stress for almost the entire year. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the duration of different categories of the UTCI for the entire period (1966\u0026ndash;2022) and for individual decades (categories: extreme, very strong, and strong cold stress). The average proportion of severe cold stress was 73% of the days per year, which corresponds to approximately 9 months. Moderate cold stress occurred on 22% of days, while days without thermal stress accounted for only 4%, or about 15 days. The highest percentage of days with the most severe cold stress categories was 76% and occurred in the 1970s. During this period, the proportion of days with extreme cold stress reached 18%. By the second decade of the 21st century (2011\u0026ndash;2022), the proportion of days with extreme cold stress decreased twofold to 9%, which has also been reported for cities in the north of the European part of Russia (Semenova et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Shartova et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA reduction in the frequency of extreme cold stress has also been reported in other Arctic regions. For example, Grigorieva et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) demonstrated a decline in extreme cold-stress frequency in 1979\u0026ndash;2020, particularly in Northern Alaska and along the Chukotka coast. A decrease in cold stress has also been reported for Iceland and Finland (Mărmureanu et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). At the same time, the number of days with very strong and strong cold stress changed only slightly and accounted for 29\u0026ndash;32% of days, although the proportion of less severe conditions increased somewhat. The percentage of days classified as having no thermal stress remained almost unchanged and only increased to 6% in 2011\u0026ndash;2022, which has also been noted by Huang et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;4 presents the seasonal variability in the duration of different UTCI categories for decadal periods. From December to March, bioclimatic conditions on Kolguev Island can be characterized by extreme, very strong, and strong cold stress. The most severe conditions occur in January and February. The proportion of days with extreme cold stress has gradually decreased from 55% (January) and 64% (February) in the 1970s (Fig.\u0026nbsp;4a) to 25% and 31% in the 2010s, respectively (Fig.\u0026nbsp;4e). February is the most severe month on the island. Since the 1980s (Fig.\u0026nbsp;4b), very strong cold stress has become the dominant winter condition and occurred on more than 50% of days in all periods, while the proportion of days with strong cold stress has gradually increased.\u003c/p\u003e \u003cp\u003eDuring the transitional seasons (spring and autumn), the proportion of days with less severe cold-stress categories correspondingly increases or decreases. From May onward, conditions of strong and moderate cold stress become dominant, and under warming conditions, the percentage of such days has increased, while the percentage of days with very strong cold stress has decreased (Fig.\u0026nbsp;4). The warmest period on Kolguev is in July and August, and during these months, a small proportion of days fall into the \u0026ldquo;no thermal stress\u0026rdquo; category, ranging from 4% in the 1970s to 7% in the 2010s. Huang et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) have also reported an increase in the number of days without thermal stress in the Arctic. In these months, moderate and slight cold-stress conditions dominate, and by the 2010s, the proportion of days with slight cold stress increased, while the proportion with moderate cold stress decreased (Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;4\u003c/b\u003e Seasonal duration of UTCI gradations based on data from the Kolguev Severny weather station for the periods: (a) 1971\u0026ndash;1980; (b) 1981\u0026ndash;1990; (c) 1991\u0026ndash;2000; (d) 2001\u0026ndash;2010; (e) 2011\u0026ndash;2020\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe diurnal variation of the UTCI was analyzed based on expedition observations conducted in June and July of 2023 and 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The results show that conditions on the island in this period were dominated by strong, moderate, and slight cold stress. In 2023, conditions were colder than in 2025, and very strong cold stress was recorded in 3\u0026ndash;10% of observations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Under polar day conditions, the diurnal cycle of the UTCI is weakly expressed, but moderate cold stress occurs more frequently in daytime hours.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClimatic and bioclimatic parameters for the periods of expeditionary observations.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAir temperature, \u0026deg;C\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eWind speed, m/s\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eUTCI, \u0026deg;C\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026ndash;6.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;37.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026ndash;27.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEarly in the morning and late in the evening, conditions are more favorable than in the day, with slight cold stress occurring more often. In 3% of cases in 2023 and in 5\u0026ndash;7% of cases in 2025, conditions corresponded to the category of \u0026ldquo;no thermal stress.\u0026rdquo; During this period, the reduction in the severity of conditions appeared to be associated with a weakening of the wind. The wind is typically strong on the island because the main branch of the Arctic Front passes near it, which makes cyclonic activity more intense and increases wind speeds in the Barents Sea (Titkova et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the climatic and bioclimatic parameters from the expedition observations. The mean air temperature in June\u0026ndash;July was about 7\u0026deg;C, the minimum was about 1\u0026deg;C, and the maximum was 18.9\u0026deg;C. The average wind speed was 4.7\u0026ndash;5.5 m/s, with maximum values reaching 14.5 m/s. The mean UTCI values for the entire field observation period corresponded to the category of moderate cold stress, while minimum values reached very strong cold stress, and maximum values corresponded to the \u0026ldquo;no thermal stress\u0026rdquo; category.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the variations in air temperature, wind speed, and UTCI during the observation periods in 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003ea) and 2025 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). The lowest UTCI values occurred at wind speeds of 10 m/s or higher, and even in summer, they could correspond to the category of very strong cold stress. Such conditions were observed on June 14\u0026ndash;16, 2023, and on June 30, 2025. When the wind weakened during the nights of June 14\u0026ndash;15, 2023, the UTCI increased to the category of moderate cold stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eDuring the field observation periods, the UTCI reached the \u0026ldquo;no thermal stress\u0026rdquo; category only when wind speeds weakened and air temperatures were relatively high at around 12\u0026ndash;14\u0026deg;C (June 25 and July 4, 2023; July 3 and 11, 2025). However, when winds remained strong at similar temperatures, bioclimatic conditions still corresponded to cold stress categories (July 5 and 10, 2023) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Grigorieva et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) also emphasize that the coldest UTCI categories in Chukotka and Alaska are associated with strong winds and low temperatures.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe assessment of climatic changes on Kolguev Island indicated a persistent increase in air temperature in all seasons with a pronounced increase in intensity in the second decade of the 21st century. There was a shift toward earlier dates of the spring transition of air temperature across 0\u0026deg;C and toward later dates of the autumn transition, along with an increase in the duration of the growing season and the sum of positive temperatures. In the context of long-term increases in precipitation in the region, tendencies toward decreasing moisture availability have emerged on Kolguev Island in the second decade of the 21st century.\u003c/p\u003e \u003cp\u003eUnder conditions of global warming, the number of days with the most severe cold stress categories (extreme cold stress) decreased by half from 18% to 9%. In recent decades, bioclimatic conditions corresponding to less severe stress categories have begun to prevail. In the summer months, the proportion of days with \u0026ldquo;no thermal stress\u0026rdquo; increased from 4% in the 1970s to 7% in the 2010s, and the proportion of days with slight cold stress has also increased.\u003c/p\u003e \u003cp\u003eField observations in June\u0026ndash;July 2023 and 2025 showed a predominance of strong and moderate cold-stress conditions. In the morning and evening hours, conditions of \u0026ldquo;no thermal stress\u0026rdquo; may occur, which are associated with a weakening of the wind. However, even in summer, conditions corresponding to very strong cold stress may occur with sufficiently low temperatures and wind speeds of 10 m/s or higher.\u003c/p\u003e \u003cp\u003eExpedition observations made it possible to investigate the interdiurnal and intradiurnal fluctuations of climatic and bioclimatic parameters and to assess the range of variation in bioclimatic conditions in the summer months. During this time, the island\u0026rsquo;s population (who practice reindeer herding and traditional subsistence activities) and visiting people (for expeditions, tourism, or fishing) spend the maximum amount of time outdoors. When wind speeds decreased, bioclimatic conditions on the island can change substantially within a few hours, from very strong to moderate cold stress. Continued field studies on Arctic islands will make it possible to expand the detailed datasets available on the climatic and bioclimatic conditions of the Arctic.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests.\u003c/h2\u003e \u003cp\u003eThe author has declared that there are no conflicts of interest concerning this study.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding.\u003c/h2\u003e \u003cp\u003eThis work was supported by Russian Science Foundation (RSF) grant no. 22-17-00168-P, P \u0026ldquo;Biogeographic consequences of climate change in the Russian Arctic.\u0026rdquo;\u003c/p\u003e\u003ch2\u003eAcknowledgement.\u003c/h2\u003e \u003cp\u003eThis research was supported by Russian Science Foundation (RSF) grant \u0026ldquo;Biogeographic consequences of climate change in the Russian Arctic.\u0026rdquo;\u003c/p\u003e\u003ch2\u003eData availability.\u003c/h2\u003e \u003cp\u003eThe raw data from the Kolguev Severny meteorological station are available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://meteo.ru\u003c/span\u003e\u003cspan address=\"http://meteo.ru\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; expedition observation data are available upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlexeev GV (2014) Impact of climatic and hydro-meteorological factors on the development of resource exploitations in the marine part of Russian Arctic. 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Saint Petersburg: Kartograficheskaya fabrikaVSEGEI 1:8 (In Russ)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-biometeorology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbm","sideBox":"Learn more about [International Journal of Biometeorology](http://link.springer.com/journal/484)","snPcode":"484","submissionUrl":"https://www.editorialmanager.com/ijbm/default2.aspx","title":"International Journal of Biometeorology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"climate, bioclimate, Universal Thermal Climate Index (UTCI), cold stress, Kolguev","lastPublishedDoi":"10.21203/rs.3.rs-9138286/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9138286/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper presents the variability of climatic and bioclimatic conditions on Kolguev Island, located in the Barents Sea. The analysis is based on data from the Kolguev Severny meteorological station for the period 1941\u0026ndash;2024 and on field observations conducted during June\u0026ndash;July of 2023 and 2025. Trends in air temperature and precipitation, as well as the duration of the frost-free and growing seasons, were calculated. The Universal Thermal Climate Index (UTCI) was used to assess bioclimatic conditions. A persistent increase in air temperature has been observed on Kolguev Island throughout the observation period in all seasons, with a marked intensification during the second decade of the 21st century. The dates of the spring transition of air temperature across 0\u0026deg;C have shifted to earlier dates, while the autumn transition has shifted to later dates, resulting in a lengthening of the growing season and an increase in the sum of positive temperatures. During the second decade of the 21st century, a tendency toward decreasing moisture availability on the island has also been observed. Throughout the year, bioclimatic conditions on Kolguev Island are dominated by cold stress of varying intensity according to the UTCI classification, ranging from extreme to slight cold stress. In summer (July\u0026ndash;August), about 4% of days fall into the \u0026ldquo;no thermal stress\u0026rdquo; category according to UTCI. In the 21st century (2001\u0026ndash;2022), the proportion of such days has increased. Field observations on Kolguev Island in June\u0026ndash;July 2023 and 2025 indicate the predominance of strong and moderate cold stress conditions. Conditions corresponding to \u0026ldquo;no thermal stress\u0026rdquo; occur mainly during the morning and evening hours.\u003c/p\u003e","manuscriptTitle":"Climate and Bioclimatic Conditions of Kolguyev Island (Barents Sea)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-25 09:46:51","doi":"10.21203/rs.3.rs-9138286/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-03-21T12:55:28+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-20T12:24:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-19T03:01:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Biometeorology","date":"2026-03-18T08:52:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-biometeorology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbm","sideBox":"Learn more about [International Journal of Biometeorology](http://link.springer.com/journal/484)","snPcode":"484","submissionUrl":"https://www.editorialmanager.com/ijbm/default2.aspx","title":"International Journal of Biometeorology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f6808c90-0607-44d6-af78-542d7a4f514d","owner":[],"postedDate":"March 25th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-25T09:46:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-25 09:46:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9138286","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9138286","identity":"rs-9138286","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}