Changing Snow Conditions Research Articles

Assessing the Impact of Climate Change on Snowfall Conditions in Poland Based on the Snow Fraction Sensitivity Index

This study focuses on temperature and snowfall conditions in Poland, both of which were analyzed from 1981 to 2020. A 40-year record of daily snow fraction time series values was reconstructed using a unique and global multi-source weighted-ensemble precipitation (MSWEP) product, which provided a spatially and temporally consistent reference for the assessment of meteorological conditions. The average states and trends in snow fraction and temperature were analyzed across several years, focusing on the 6-month cold season (November–April). The impact of temperature on the snow fraction pattern was assessed by introducing a snow fraction sensitivity index. To predict short-term changes in snow conditions, a proxy model was established; it incorporated historical trends in the snow fraction as well as its mean state. This study provides clear evidence that the snow fraction is principally controlled by increases in temperature. A warming climate will thus cause a decline in the snow fraction, as we observed in vast lowland areas. Given the ongoing global warming, by the 2050s, snow-dominated areas may go from covering 86% to only 30% of the country’s surface; they will be converted into transient rain–snow areas. Our results demonstrate that a decline in snow water resources has already occurred, and these resources are expected to diminish further in the near future. New insights into the sensitivity of the snow fraction to climate warming will expand our collective knowledge of the magnitude and spatial extent of snow degradation. Such widespread changes have implications for the timing and availability of soil and groundwater resources as well as the timing and likelihood of floods and droughts. Thus, these findings will provide valuable information that can inform environmental managers of the importance of changing snowfall conditions, guiding them to include this aspect in future climate adaptation strategies.

A 20-Year Ecotone Study of Pacific Northwest Mountain Forest Vulnerability to Changing Snow Conditions

(1) Background: Global climate change is expected to significantly alter growing conditions along mountain gradients. Landscape ecological patterns are likely to shift significantly as species attempt to adapt to these changes. We evaluated the extent to which spatial (elevation and canopy cover) and temporal (decadal trend and El Niño–Southern Oscillation/Pacific Decadal Oscillation) factors impact seasonal snowmelt and forest community dynamics in the Western Hemlock–True Fir ecotone region of the Oregon Western Cascades, USA. (2) Methods: Tsuga heterophylla and Abies amabilis seedling locations were mapped three times over 20 years (2002–2022) on five sample transects strategically placed to cross the ecotone. Additionally, daily ground temperature readings were collected over 10 years for the five transects using 123 data loggers to estimate below-canopy snow metrics. (3) Results: Based on validation using time-lapse cameras, the data loggers proved highly reliable for estimating snow cover. The method reported fewer days of snow cover as compared to meteorological station-based snow products for the region, emphasizing the importance of direct under-canopy field observations of snow. Snow season variability was most significantly impacted temporally by cyclical ENSO/PDO climate patterns and spatially by differences in canopy cover within the ecotone. The associated seedling analysis identified clear sorting of species by elevation within the ecotone but reflected a lack of a long-term trend, as species dominance in the seedling strata did not significantly shift along the elevation gradient over the 20-year study. (4) Conclusions: The data logger-based approach provided estimates of snow cover at ecologically significant locations and fine enough spatial resolutions to allow for the study of forest regeneration dynamics. The results highlight the importance of long-term, understory snow measurements and the influence of climatic oscillations in understanding the vulnerability of mountain areas to the changing climate.

Rapid warming and degradation of mountain permafrost in Norway and Iceland

Abstract. With the EU-funded PACE (Permafrost and Climate in Europe) project at the turn of this century, several deep boreholes (100 m+) were drilled in European mountain sites, including in mainland Norway, Svalbard and Sweden. During other projects from 2004 and the International Polar Year (IPY) period in 2006–2007, several additional boreholes were drilled in different sites in both Norway and Iceland, measuring temperatures along both altitudinal and latitudinal gradients. At most sites, multi-temporal geophysical soundings are available using electrical resistivity tomography (ERT). Here, we study the development of permafrost and ground temperatures in mainland Norway and Iceland based on these data sets. We document that permafrost in Norway and Iceland is warming at a high rate, including the development of taliks in both Norway and Iceland in response to global climate change during the last 20 years. At most sites, ground surface temperature (GST) is apparently increasing more strongly than surface air temperature (SAT). Changing snow conditions appear to be the most important factor for the higher GST rates. Modelling exercises also indicate that the talik development can be explained by both higher air temperatures and increasing snow depth.

Assessing past and future climatic influences on the availability of polar bear maternal denning habitat on Wrangel Island

Long-term changes in environmental conditions resulting from climate change may negatively affect reproductive success and lead to population-level consequences for species, especially those living at higher latitudes. Throughout their range, female polar bears (Ursus maritimus) typically require snowdrifts, either on the ice or land, to excavate maternal dens. In the Chukchi Sea (CS) subpopulation, 84% of dens have been reported to on land and 68% of these on Wrangel Island, Russia. Therefore, availability of suitable den habitat on Wrangel Island is critical for the long-term persistence of the CS subpopulation. We performed a retrospective analysis (1980–2020) of the availability of snowdrifts on Wrangel Island to estimate how the timing and distribution of snowdrifts suitable for denning has changed over this period. We evaluated the spatial distribution and availability of potential denning habitat across Wrangel Island from 1 September until 15 December and documented changes in snow conditions through time. We used sensitivity simulations under variable temperature increases associated with climate change projections to predict how availability of potential denning habitat on Wrangel Island might change in the future. We found no trends in spatial or temporal availability of modeled den habitat over the past 41 years. A projected 7.6 °C rise in temperature relative to current conditions resulted in a ∼50% reduction of denning habitat. If temperatures increase ≥13.6 °C relative to current conditions, 100% of denning habitat would be lost. Despite rising temperatures and sea ice loss, the climate of this area is cold enough that availability of denning habitat is not an immediate limiting factor for the CS subpopulation.

Changing winter climate and snow conditions induce various transcriptional stress responses in Scots pine seedlings.

In northern boreal forests the warming winter climate leads to more frequent snowmelt, rain-on-snow events and freeze-thaw cycles. This may be harmful or even lethal for tree seedlings that spend even a half of the year under snow. We conducted a snow cover manipulation experiment in a natural forest to find out how changing snow conditions affect young Scots pine (Pinus sylvestris L.) seedlings. The ice encasement (IE), absence of snow (NoSNOW) and snow compaction (COMP) treatments affected ground level temperature, ground frost and subnivean gas concentrations compared to the ambient snow cover (AMB) and led to the increased physical damage and mortality of seedlings. The expression responses of 28 genes related to circadian clock, aerobic and anaerobic energy metabolism, carbohydrate metabolism and stress protection revealed that seedlings were exposed to different stresses in a complex way depending on the thickness and quality of the snow cover. The IE treatment caused hypoxic stress and probably affected roots which resulted in reduced water uptake in the beginning of the growing season. Without protective snowpack in NoSNOW seedlings suffered from cold and drought stresses. The combination of hypoxic and cold stresses in COMP evoked unique transcriptional responses including oxidative stress. Snow cover manipulation induced changes in the expression of several circadian clock related genes suggested that photoreceptors and the circadian clock system play an essential role in the adaptation of Scots pine seedlings to stresses under different snow conditions. Our findings show that warming winter climate alters snow conditions and consequently causes Scots pine seedlings various abiotic stresses, whose effects extend from overwintering to the following growing season.

Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events

Abstract. Climate projection studies of future changes in snow conditions and resulting rain-on-snow (ROS) flood events are subject to large uncertainties. Typically, emission scenario uncertainties and climate model uncertainties are included. This is the first study on this topic to also include quantification of natural climate variability, which is the dominant uncertainty for precipitation at local scales with large implications for runoff projections, for example. To quantify natural climate variability, a weather generator was applied to simulate inherently consistent climate variables for multiple realizations of current and future climates at 100 m spatial and hourly temporal resolution over a 12×12 km high-altitude study area in the Swiss Alps. The output of the weather generator was used as input for subsequent simulations with an energy balance snow model. The climate change signal for snow water resources stands out as early as mid-century from the noise originating from the three sources of uncertainty investigated, namely uncertainty in emission scenarios, uncertainty in climate models, and natural climate variability. For ROS events, a climate change signal toward more frequent and intense events was found for an RCP 8.5 scenario at high elevations at the end of the century, consistently with other studies. However, for ROS events with a substantial contribution of snowmelt to runoff (> 20 %), the climate change signal was largely masked by sources of uncertainty. Only those ROS events where snowmelt does not play an important role during the event will occur considerably more frequently in the future, while ROS events with substantial snowmelt contribution will mainly occur earlier in the year but not more frequently. There are two reasons for this: first, although it will rain more frequently in midwinter, the snowpack will typically still be too cold and dry and thus cannot contribute significantly to runoff; second, the very rapid decline in snowpack toward early summer, when conditions typically prevail for substantial contributions from snowmelt, will result in a large decrease in ROS events at that time of the year. Finally, natural climate variability is the primary source of uncertainty in projections of ROS metrics until the end of the century, contributing more than 70 % of the total uncertainty. These results imply that both the inclusion of natural climate variability and the use of a snow model, which includes a physically based process representation of water retention, are important for ROS projections at the local scale.

Changing Snow Conditions and Shifts in American marten (Martes americana) distribution in Michigan's Upper Peninsula

Changing Snow Conditions and Shifts in American marten (Martes americana) distribution in Michigan's Upper Peninsula

Small mammal dynamics in snow-covered forests

AbstractIn seasonal environments, the winter months can drive the structure and dynamics of vertebrate communities. Most ecological studies have focused on species above the snow, overlooking those within the subnivium (below-snow environment). The Great Lakes region of North America is characterized by seasonal snow cover and a diverse assemblage of small mammals, both of which are changing rapidly in response to a changing climate. To study the seasonal dynamics of small mammals, we sampled communities in three forest types (hardwood, hemlock-cedar, and spruce bog) in summer and winter over 2 years. We hypothesized that seasonal differences in communities would be moderated by forest structure in summer and snow in winter. We assessed community dominance via species diversity and the abundances of deer mice (Peromyscus maniculatus), white-footed mice (P. leucopus), and southern red-backed voles (Myodes gapperi). We estimated a Community Temperature Index (CTI; a metric of the balance between warm- and cold-adapted species in a community) and tested seasonal drivers of CTI. Species diversity was highest in spruce bogs in winter due to increased species evenness, but diversity was consistent year-round in hardwood and hemlock-cedar forests due to unchanging species dominance. Spruce bogs supported the coldest CTI in summer, but CTIs converged across forest types in winter. In summer, forest structure drove CTI; in winter, colder CTIs were associated with deeper snow and a warmer subnivium. Our work reveals that snow is a critical habitat and filter for cold-adapted species that ultimately structures small mammal communities. Given rapid changes in snow conditions due to climate change, we predict continued range contractions for subnivium-adapted species.

The Snow-Friction of Freestyle Skis and Snowboards Predicted From Snow Physical Quantities

Previous research has shown that friction between ski and snow can vary substantially due to changes in snow conditions. The variation of friction affects the speed a freestyle skier or snowboarder (athlete) reaches during the in-run of a jump. Athletes risk severe injuries if their take-off speed is not within the right margin to land in the “sweet spot” zone. To reduce the risk of injury, snow park designers and competition managers need to calculate the speed athletes reach during the in-run. However, despite multiple attempts over the last decades, to date no model can predict ski-snow friction from snow physical quantities. Hence, simulations of in-run speeds suffer from insufficient validity. For the first time, this work combines kinematic athlete data and comprehensive snow surface measurements to infer the coefficient of friction of freestyle skis and snowboards across a wide range of snow conditions. Athletes’ point mass kinematics were recorded at more than 200 straight gliding runs with differential global navigation satellite systems. The subjects’ air drag and lift were deployed from wind tunnel measurements. Along with the kinematic data and data from wind measurements, a mechanical model of the athlete was established to solve the equation of motion for the coefficient of friction between ski/snowboard and snow. The friction coefficients for ski (snowboard) ranged from 0.023 ± 0.006 (0.026 ± 0.008) to 0.139 ± 0.018 (0.143 ± 0.017) and could be explained well (Radj2 = 0.77) from the measured snow parameters using a multivariate statistical model. Our results provide a new quantitative tool for practitioners to predict the friction of skis and snowboard on snow of various conditions, which aims to increase athletes’ safety in slopestyle and big air.

Ecological responses to variation in seasonal snow cover.

Seasonal snow is among the most important factors governing the ecology of many terrestrial ecosystems, but rising global temperatures are changing snow regimes and driving widespread declines in the depth and duration of snow cover. Loss of the insulating snow layer will fundamentally change the environment. Understanding how individuals, populations, and communities respond to different snow conditions is thus essential for predicting and managing future ecosystem change. We synthesized 365 studies that examined ecological responses to variation in winter snow conditions. This research encompasses a broad range of methods (experimental manipulations, measurement of natural snow gradients, and long-term monitoring), locations (35 countries), study organisms (plants, mammals, arthropods, birds, fish, lichen, and fungi), and response measures. Earlier snowmelt was consistently associated with advanced spring phenology in plants, mammals, and arthropods. Reduced snow depth often increased mortality or physical injury in plants, although there were few clear effects on animals. Neither snow depth nor snowmelt timing had clear or consistent directional effects on body size of animals or biomass of plants. However, because 96% of studies were from the northern hemisphere, the generality of these trends across ecosystems and localities is also unclear. We identified substantial research gaps for several taxonomic groups and response types; research on wintertime responses was notably scarce. Future research should prioritize examination of the mechanisms underlying responses to changing snow conditions and the consequences of those responses for seasonally snow-covered ecosystems.

Adaptive capacity of ski resorts in Western Norway to projected changes in snow conditions

ABSTRACT Skiing is an important part of Norwegian culture, but as climate change leads to warmer, more variable winters, the ski industry needs to adapt. Despite the growing literature on climate change impacts on ski tourism, adaptation options, particularly beyond snowmaking, barriers and the financial and visitor experience implications remain under-researched. Employing projections for future snow and snowmaking conditions, this paper investigates adaptive capacity among seven Western Norwegian ski resorts. Adaptive capacity is examined in terms of physical situation, technology, economic resources, innovative ability, networks and institutions. We find that smaller resorts make up for poor economic performance by drawing on local community support and by implementing innovative efforts to diversify income. Nonetheless, despite high adaptive capacity with respect to networks, institutions and innovative ability, increased snow production costs will make operations in three low-lying resorts unviable as early as the 2030s, with salient implications for winter tourism patterns, small community economies and future participation in the sport. The results also suggest that studies using snow production model projections that represents physical and technical adaptive capacity only, may be conservative in their estimated impact of future climate change.

Do changes in snow conditions have an impact on snowmaking investments in French Alps ski resorts?

This study investigates the relationship between snow conditions and snowmaking investments for over 100 French Alps ski resorts. Investment trends represent a critical issue in capital-intensive sectors such as the ski industry. The data are based on snow reliability indicators and snowmaking investments covering 1997–2014. Descriptive statistics reveal that snowmaking has been the second investment item for ski resorts regardless of the elevation or ski resort size. The study finds that snowmaking investments are highly negatively correlated to snow conditions of the prior year for small and medium-sized ski resorts. Other factors are also likely to play a significant role in driving snowmaking investment dynamics.

Monitoring recent changes of vegetation in Fildes Peninsula (King George Island, Antarctica) through satellite imagery guided by UAV surveys

Mapping accurately vegetation surfaces in space and time in the ice-free areas of Antarctica can provide important information to quantitatively describe the evolution of their ecosystems. Spaceborne remote sensing is the adequate way to map and evaluate multitemporal changes on the Antarctic vegetation at large but its nature of occurrence, in relatively small and sparse patches, makes the identification very challenging. The inclusion of an intermediate scale of observation between ground and satellite scales, provided by Unmanned Aerial Vehicles (UAV) imagery, is of great help not only for their effective classification, but also for discriminating their main communities (lichens and mosses). Thus, this paper quantifies accurately recent changes of the vegetated areas in Fildes Peninsula (King George Island, Antarctica) through a novel methodology based on the integration of multiplatform data (satellite and UAV). It consists of multiscale imagery (spatial resolution of 2 m and 2 cm) from the same period to create a robust classifier that, after intensive calibration, is adequately used in other dates, where field reference data is scarce or not available at all. The methodology is developed and tested with UAV and satellite data from 2017 showing overall accuracies of 96% and kappa equal to 0.94 with a SVM classifier. These high performances allow the extrapolation to a pair of previous dates, 2006 and 2013, when atmospherically clear very high-resolution satellite imagery are available. The classification allows verifying a loss of the total area of vegetation of 4.5% during the 11-year time period under analysis, which corresponds to a 10.3% reduction for Usnea sp. and 9.8% for moss formations. Nevertheless, the breakdown analysis by time period shows a distinct behaviour for each vegetation type which are evaluated and discussed, namely for Usnea sp. whose decline is likely to be related to changing snow conditions.

Does Climate Change Influence Guest Loyalty at Alpine Winter Destinations?

Research has dealt extensively with different aspects of climate change and winter tourism such as the impact on ski resorts and ski lift operators, adaptation strategies, governance at destinations and reactions of winter sports guests to changing snow conditions. This paper goes deeper into the question of destination choice and examines the role of climate change among the many factors affecting guest loyalty at Alpine winter destinations. The study uses an established destination choice model with choice sets, destination image and dynamic feedback loop. A qualitative online forum identifies factors influencing winter destination choice, followed by a quantitative survey which compares Alpine winter holidaymakers categorised as “loyal”, “disloyal” and “undecided”. The results demonstrate that climate change clearly influences destination choice, but snow sports are not the only affected attractors. Enjoyment of the natural environment and value for money are just as high on the list of guest motivators. This indicates that climate change adaptation measures such as snowmaking can be counterproductive to guest loyalty because they spoil the natural scenery and raise prices. The paper concludes with a recommendation for winter destinations to prioritize conservation of the natural environment and integrate more environmental protection measures into their management strategies.

Snow to Precipitation Ratio Controls Catchment Storage and Summer Flows in Boreal Headwater Catchments

AbstractCatchment storage sustains ecologically important low flows in headwater systems. Understanding the factors controlling storage is essential in analysis of catchment vulnerability to global change. We calculated catchment storage and storage sensitivity of streamflow for 61 boreal headwater catchments in Finland. We also explored the connection between computed storage indices and low flow conditions. The relationships between selected climate, snow, and catchment characteristics and calculated storage properties and low flows were investigated, in order to assess the importance of different factors that render catchments vulnerable to climate and environmental change. We found that the most sensitive areas to climate change were located in the southern boreal coastal zone, with fine‐grained soils and agricultural areas. In contrast, catchments in the middle and northern boreal zone, with till and peatland soils and higher snow water equivalent values, were less sensitive under current conditions. In addition, we found a threshold at a snow to precipitation ratio of 0.35. Above that threshold, summer low flows were generally sensitive to changes in snow conditions, whereas below that threshold catchment characteristics gained importance and the sensitivity was more directly related to changes in temperature and timing of rainfall. These findings suggest that a warming climate will have pronounced impacts on hydrology and catchment sensitivity related to snow quantity and snow cover duration in certain snow to precipitation ratio zones. Moreover, land use activities had an impact on storage properties in agricultural and drained peatland areas, resulting in a negative effect on low flows.

Snow cover trends in Finland over 1961–2014 based on gridded snow depth observations

Snow conditions in high‐latitude regions are changing in response to climate warming, and these changes are likely to accelerate as the warming proceeds. Here, we analyse daily gridded snow depth, temperature and precipitation data from Finland over the period 1961–2014 to discover the ongoing changes in monthly average snow depths (SN) and several snow‐related indices. Our results indicate that regional differences of changes in snow conditions can be relatively large, even within such a small district as Finland. Moreover, the interannual variation of the various snow indices was found to be larger in southern Finland than in northern Finland. The largest decrease in snow depth occurred in the southern, western and central parts of Finland in late winter and early spring. This decrease was driven by increasing mixed and liquid precipitation and, especially in spring, increasing temperature. In northern Finland, the decreasing trend of snow depth was most evident in spring, but no change occurred during winter months, although the amount of solid precipitation was found to increase in December–February. In the same months, temperature and the amount of mixed and liquid precipitation increased, likely counteracting the effects of the increasing solid precipitation on snow depth. The annual maximum snow depth that typically occurs in March was found to decrease in over 85% of Finland's area, most strongly in western coastal areas. In almost half of Finland's area, this decrease occurred despite increasing solid precipitation. Our findings highlight the complexity of the responses of snow conditions to climatic variability in northern Europe.

Critical snow density threshold for Dall’s sheep (Ovis dalli dalli)

Snow cover can significantly impact animal movement and energetics, yet few studies have investigated the link between physical properties of snow and energetic costs. Quantification of thresholds in snow properties that influence animal movement are needed to help address this knowledge gap. Recent population declines of Dall’s sheep (Ovis dalli dalli Nelson, 1884) could be due in part to changing snow conditions. We examined the effect of snow density, snow depth, and snow hardness on sinking depths of Dall’s sheep tracks encountered in Wrangell–St. Elias National Park and Preserve, Alaska. Snow depth was a poor predictor of sinking depths of sheep tracks (R2 = 0.02, p = 0.38), as was mean weighted hardness (R2 = 0.09, p = 0.07). Across competing models, top layer snow density (0–10 cm) and sheep age class were the best predictors of track sink depths (R2 = 0.58). Track sink depth decreased with increasing snow density, and the snowpack supported the mass of a sheep above a density threshold of 329 ± 18 kg/m3 (mean ± SE). This threshold could aid interpretation of winter movement and energetic costs by animals, thus improving our ability to predict consequences of changing snowpack conditions on wildlife.

Range-wide variation in the effect of spring snow phenology on Dall sheep population dynamics

Understanding the underlying mechanisms of species distributions and range limits is critical to predicting species responses to climate change. The relationship between climate factors and population performance is often assumed to be constant across species’ ranges, but factors that limit the persistence and abundance of species may vary spatially. We examined the consistency of climate effects on population performance across the global range of Dall sheep (Ovis dalli dalli) in northwestern North America. Using a linear mixed modeling approach, we evaluated the effects of temperature, precipitation, and snow cover on rates of lamb recruitment, which is a key measure of population performance. We used snow cover products derived from NASA’s moderate resolution imaging spectroradiometer (MODIS) imagery and gridded climate data as predictors. Lamb recruitment rates were estimated using range-wide aerial survey data from 2000–2015. These consisted of 127 833 records of sheep sightings from 1570 surveys conducted in 24 mountain units over an area of 634 271 km2. MODIS-derived spring snow cover had stronger effects on lamb recruitment than did temperature or precipitation. Lamb recruitment increased with higher spring snowline elevations, earlier snow disappearance dates, and fewer snow-covered days per year, while the strength of these effects increased strongly with latitude. Simple population models indicate that, based on elasticity estimates, population growth would be reduced by 2% in years with late snow disappearance dates at intermediate northern latitudes, and by 5% at high latitudes. These results suggest that northern Dall sheep populations are more sensitive to changing snow conditions than their southern counterparts. In addition, variable relationships between climatic factors and population performance should be accounted for when modeling species distributions and projecting climate-induced range shifts.

Assessment of the Barren Ground Caribou Die‐off During Winter 2015–2016 Using Passive Microwave Observations

AbstractIn summer 2016, more than 50 Arctic Barren Ground caribous were found dead on Prince Charles Island (Nunavut, Canada), a species recently classified as threatened. Neither predator nor sign of diseases was observed and reported. The main hypothesis is that caribous were not able to access food due to a very dense snow surface, created by a strong storm system in spring. Using satellite microwave data, a significant increase in brightness temperature polarization ratio at 19 and 37 GHz was observed in spring 2016 (60% higher than previous two winter seasons). Based on microwave radiative transfer simulations, such anomaly can be explained with a very dense snow surface. This is consistent with the succession of storms and strong winds highlighted in ERA‐Interim over Prince Charles Island in spring 2016. Using several sources of data, this study shows that changes in snow conditions explain the caribou die‐off due to restricted foraging.

Impacts of snow on soil temperature observed across the circumpolar north

Climate warming has significant impacts on permafrost, infrastructure and soil organic carbon at the northern high latitudes. These impacts are mainly driven by changes in soil temperature (TS). Snow insulation can cause significant differences between TS and air temperature (TA), and our understanding about this effect through space and time is currently limited. In this study, we compiled soil and air temperature observations (measured at about 0.2 m depth and 2 m height, respectively) at 588 sites from climate stations and boreholes across the northern high latitudes. Analysis of this circumpolar dataset demonstrates the large offset between mean TS and TA in the low arctic and northern boreal regions. The offset decreases both northward and southward due to changes in snow conditions. Correlation analysis shows that the coupling between annual TS and TA is weaker, and the response of annual TS to changes in TA is smaller in boreal regions than in the arctic and the northern temperate regions. Consequently, the inter-annual variation and the increasing trends of annual TS are smaller than that of TA in boreal regions. The systematic and significant differences in the relationship between TS and TA across the circumpolar north is important for understanding and assessing the impacts of climate change and for reconstruction of historical climate based on ground temperature profiles for the northern high latitudes.