Changes In Snow Depth Research Articles

Spatial and temporal characteristics in streamflow-related hydroclimatic variables over western Canada. Part 2: future projections

Much of the freshwater in western Canada originates in the Rocky Mountains as snowpack. Temperature and precipitation patterns throughout the region control the amount of snow accumulated and stored throughout the winter, and the intensity and timing of melt during the spring freshet. Therefore, changes in temperature, precipitation, snow depth, and snowmelt over western Canada are examined through comparison of output from the current and future periods of a series of regional climate models for the time periods 1971–2000 and 2041–2070. Temporal and spatial analyses of these hydroclimatic variables indicate that minimum temperature is likely to increase more than maximum temperature, particularly during the cold season, possibly contributing to earlier spring melt. Precipitation is projected to increase, particularly in the north. In the coldest months of the year snow depth is expected to increase in northern areas and decrease across the rest of study area. Snowmelt results indicate increases in mid-winter melt events and an earlier onset of the spring freshet. This study provides a summary of potential future climate using key hydroclimatic variables across western Canada with regard to the effects these changes may have on streamflow and the spring freshet, and thus water resources, throughout the study area.

Timing and regional patterns of snowmelt on Antarctic sea ice from passive microwave satellite observations

AbstractAn improved understanding of the temporal variability and the spatial distribution of snowmelt on Antarctic sea ice is crucial to better quantify atmosphere‐ice‐ocean interactions, in particular sea‐ice mass and energy budgets. It is therefore important to understand the mechanisms that drive snowmelt, both at different times of the year and in different regions around Antarctica. In this study, we combine diurnal brightness temperature differences (dTB(37 GHz)) and ratios (TB(19 GHz)/TB(37 GHz)) to detect and classify snowmelt processes. We distinguish temporary snowmelt from continuous snowmelt to characterize dominant melt patterns for different Antarctic sea‐ice regions from 1988/1989 to 2014/2015. Our results indicate four characteristic melt types. On average, 38.9 ± 6.0% of all detected melt events are diurnal freeze‐thaw cycles in the surface snow layer, characteristic of temporary melt (Type A). Less than 2% reveal immediate continuous snowmelt throughout the snowpack, i.e., strong melt over a period of several days (Type B). In 11.7 ± 4.0%, Type A and B take place consecutively (Type C), and for 47.8 ± 6.8% no surface melt is observed at all (Type D). Continuous snowmelt is primarily observed in the outflow of the Weddell Gyre and in the northern Ross Sea, usually 17 days after the onset of temporary melt. Comparisons with Snow Buoy data suggest that also the onset of continuous snowmelt does not translate into changes in snow depth for a longer period but might rather affect the internal stratigraphy and density structure of the snowpack. Considering the entire data set, the timing of snowmelt processes does not show significant temporal trends.

The Influence of the MJO on the Intraseasonal Variability of Northern Hemisphere Spring Snow Depth

Abstract Intraseasonal variability in springtime Northern Hemisphere daily snow depth change (ΔSD) by phase of the MJO was explored in this study. Principal findings of the relationship between ΔSD and the MJO included the following: 1) Statistically significant regions of lagged ΔSD anomalies for multiple phases of the MJO were found in March, April, and May in both North America and Eurasia. 2) In each month, lagged ΔSD anomalies were physically supported by corresponding lagged anomalies of 500-hPa height (Z500) and surface air temperature (SAT). Spearman rank correlation coefficients indicated a moderate to strong relationship between both Z500 and ΔSD and SAT and ΔSD in both Eurasia and North America for phases 5 and 7 in March. In April, a moderately strong relationship between Z500 and ΔSD was found over Eurasia for phase 5, but the relationship between SAT and ΔSD was weak. In May, correlations between ΔSD and both Z500 and SAT over a hemisphere-wide latitude band from 60° to 75°N were close to −0.5 and −0.4, respectively. Given the strength of these statistical relationships, the following physical pathway is proposed for intraseasonal variability of spring snow depth changes: poleward-propagating Rossby waves in response to tropical MJO convection interact with Northern Hemisphere background flow, leading to anomalous troughing and ridging. These anomalous circulation centers then impact daily snow depth change via precipitation processes and anomalies in surface air temperature.

Mapping starting zone snow depth with a ground-based lidar to assist avalanche control and forecasting

The distribution of snow depth in avalanche starting zones exerts a strong influence on avalanche potential and character. Extreme depth changes over short distances are common, especially in wind-affected, above-treeline environments. Snow depth also affects the ease of avalanche triggering. Experience shows that avalanche reduction efforts are often more successful when targeting shallow trigger point areas near deeper slabs with explosives or ski cutting. Our paper explores the use of high-resolution (cm scale) snow depth and snow depth change maps from terrestrial laser scanning (TLS) data to quantify loading patterns for use in both pre-control planning and in post-control assessment.We present results from a pilot study in three study areas at the Arapahoe Basin ski area in Colorado, USA. A snow-free reference data set was collected in a summer TLS survey. Mapping multiple times during the snow season allowed us to produce time series maps of snow depth and snow depth change at high resolution to explore depth and slab thickness variations due to wind redistribution. We conducted surveys before and after loading events and control work, allowing the exploration of loading patterns, slab thickness, shot and ski cut locations, bed surfaces, entrainment, and avalanche characteristics. We also evaluate the state of TLS for use in operational avalanche control settings.

Long-term fluctuations of snow cover thickness and maximum snow storage in Gis-Baikal area

The paper describes the variability of snow depth and maximal snow storage at level of biogeographical areas and provinces for the long-term period of 1961–2010. Tendencies of snow depth changes increase in most cases with significant factors of regression, but the changes are rather small, only 0.6–6 cm/10 years. Steady changes of maximal snow storage are positive in the most cases of wood sites. The greatest increase of maximal snow storage on wood sites is noted in the South Siberian mountain and taiga area with 10–21 mm/10 years, and, on the contrary, with 4–8 mm/10 years on field sites of Mid-Siberian taiga area.

Interactions between wind-blown snow redistribution and melt ponds in a coupled ocean–sea ice model

Introducing a parameterization of the interactions between wind-driven snow depth changes and melt pond evolution allows us to improve large scale models. In this paper we have implemented an explicit melt pond scheme and, for the first time, a wind dependant snow redistribution model and new snow thermophysics into a coupled ocean–sea ice model.The comparison of long-term mean statistics of melt pond fractions against observations demonstrates realistic melt pond cover on average over Arctic sea ice, but a clear underestimation of the pond coverage on the multi-year ice (MYI) of the western Arctic Ocean. The latter shortcoming originates from the concealing effect of persistent snow on forming ponds, impeding their growth. Analyzing a second simulation with intensified snow drift enables the identification of two distinct modes of sensitivity in the melt pond formation process. First, the larger proportion of wind-transported snow that is lost in leads directly curtails the late spring snow volume on sea ice and facilitates the early development of melt ponds on MYI. In contrast, a combination of higher air temperatures and thinner snow prior to the onset of melting sometimes make the snow cover switch to a regime where it melts entirely and rapidly. In the latter situation, seemingly more frequent on first-year ice (FYI), a smaller snow volume directly relates to a reduced melt pond cover.Notwithstanding, changes in snow and water accumulation on seasonal sea ice is naturally limited, which lessens the impacts of wind-blown snow redistribution on FYI, as compared to those on MYI. At the basin scale, the overall increased melt pond cover results in decreased ice volume via the ice-albedo feedback in summer, which is experienced almost exclusively by MYI.

Simulations of 21st century snow response to climate change in Switzerland from a set of RCMs

ABSTRACTTwenty‐first century snow depth and snow water equivalent (SWE) changes are assessed for three time periods (2020–2049, 2045–2079 and 2070–2099) at 11 stations in Switzerland with the physics‐based snow model SNOWPACK and meteorological input data perturbed by the output from ten regional climate models (RCMs) through the delta change method. Unlike in previous studies, incoming long‐wave radiation has also been modified for future climatic conditions. We thus show the range of future snow simulations assuming different RCM projections.Model validation yields satisfying results for simulating snow depth and SWE for the reference period with errors in the order of 9% and 15%, respectively. For the end of the century, the stations between 1000–1700 m a.s.l. show no pronounced elevation dependence but surprisingly react quite similarly in terms of the relative magnitude of snow cover decrease, which may reach 90%. The projected small increase in winter precipitation has almost no effect at these stations, but incoming long‐wave radiation has an important effect. At the high‐elevation station Weissfluhjoch (2540 m a.s.l.) however, the precipitation increase is partly able to compensate for the increased temperature. This would imply that the snow cover at mid‐elevation stations becomes temperature and radiation dominated and will react similarly to the spatially small differences in the projected temperature change. The low‐elevation stations already show a strong decrease in the near future, and the inclusion of modified incoming long‐wave radiation has almost no effect on the decrease of future snow depth and SWE because the temperatures are already close to the melting point in the reference period. At the end of the century, mean snow depth/SWE are reduced by 35/32%, 83/86% and 96/97% at high‐, mid‐ and low‐elevations, respectively.

Effect of snow cover on pan-Arctic permafrost thermal regimes

This study quantitatively evaluated how insulation by snow depth (SND) affected the soil thermal regime and permafrost degradation in the pan-Arctic area, and more generally defined the characteristics of soil temperature (TSOIL) and SND from 1901 to 2009. This was achieved through experiments performed with the land surface model CHANGE to assess sensitivity to winter precipitation as well as air temperature. Simulated TSOIL, active layer thickness (ALT), SND, and snow density were generally comparable with in situ or satellite observations at large scales and over long periods. Northernmost regions had snow that remained relatively stable and in a thicker state during the past four decades, generating greater increases in TSOIL. Changes in snow cover have led to changes in the thermal state of the underlying soil, which is strongly dependent on both the magnitude and the timing of changes in snowfall. Simulations of the period 2001–2009 revealed significant differences in the extent of near-surface permafrost, reflecting differences in the model’s treatment of meteorology and the soil bottom boundary. Permafrost loss was greater when SND increased in autumn rather than in winter, due to insulation of the soil resulting from early cooling. Simulations revealed that TSOIL tended to increase over most of the pan-Arctic from 1901 to 2009, and that this increase was significant in northern regions, especially in northeastern Siberia where SND is responsible for 50 % or more of the changes in TSOIL at a depth of 3.6 m. In the same region, ALT also increased at a rate of approximately 2.3 cm per decade. The most sensitive response of ALT to changes in SND appeared in the southern boundary regions of permafrost, in contrast to permafrost temperatures within the 60°N–80°N region, which were more sensitive to changes in snow cover. Finally, our model suggests that snow cover contributes to the warming of permafrost in northern regions and could play a more important role under conditions of future Arctic warming.

A Long-Term Assessment of the Variability in Winter Use of Dense Conifer Cover by Female White-Tailed Deer

BackgoundLong-term studies allow capture of a wide breadth of environmental variability and a broader context within which to maximize our understanding of relationships to specific aspects of wildlife behavior. The goal of our study was to improve our understanding of the biological value of dense conifer cover to deer on winter range relative to snow depth and ambient temperature.Methodology/Principal FindingsWe examined variation among deer in their use of dense conifer cover during a 12-year study period as potentially influenced by winter severity and cover availability. Female deer were fitted with a mixture of very high frequency (VHF, n = 267) and Global Positioning System (GPS, n = 24) collars for monitoring use of specific cover types at the population and individual levels, respectively. We developed habitat composites for four study sites. We fit multinomial response models to VHF (daytime) data to describe population-level use patterns as a function of snow depth, ambient temperature, and cover availability. To develop alternative hypotheses regarding expected spatio-temporal patterns in the use of dense conifer cover, we considered two sets of competing sub-hypotheses. The first set addressed whether or not dense conifer cover was limiting on the four study sites. The second set considered four alternative sub-hypotheses regarding the potential influence of snow depth and ambient temperature on space use patterns. Deer use of dense conifer cover increased the most with increasing snow depth and most abruptly on the two sites where it was most available, suggestive of an energy conservation strategy. Deer use of dense cover decreased the most with decreasing temperatures on the sites where it was most available. At all four sites deer made greater daytime use (55 to >80% probability of use) of open vegetation types at the lowest daily minimum temperatures indicating the importance of thermal benefits afforded from increased exposure to solar radiation. Date-time plots of GPS data (24 hr) allowed us to explore individual diurnal and seasonal patterns of habitat use relative to changes in snow depth. There was significant among-animal variability in their propensity to be found in three density classes of conifer cover and other open types, but little difference between diurnal and nocturnal patterns of habitat use.Conclusions/SignificanceConsistent with our findings reported elsewhere that snow depth has a greater impact on deer survival than ambient temperature, herein our population-level results highlight the importance of dense conifer cover as snow shelter rather than thermal cover. Collectively, our findings suggest that maximizing availability of dense conifer cover in an energetically beneficial arrangement with quality feeding sites should be a prominent component of habitat management for deer.

The effect of spatial variability on the sensitivity of passive microwave measurements to snow water equivalent

Passive microwave (PM) remote sensing measurements are routinely utilized to estimate snow depth and water equivalent (SWE). Both vegetation and physical snowpack variables including snowpack grain size, snow depth, and stratigraphy influence the observed brightness temperature. The natural heterogeneity of snowpack and vegetation states within the microwave footprint occurs at spatial scales shorter than PM observation scales. In this study, we analyze the relationship between PM brightness temperature measurements and the heterogeneity of snowpack and vegetation. Specifically, we explore the question of whether PM observations are sensitive to changes in snow depth even given sub-pixel variability in snow and vegetation. To examine this question, densely sampled, spatially distributed in situ snow properties from multiple study areas made during the NASA Cold Land Processes Experiment (CLPX) are employed in a forward modeling scheme to study the effect of highly variable snow and vegetation properties on the observed PM measurement.In all test cases, this study finds that there exists sensitivity of microwave brightness temperature (Tb) to total snow depth contained within the measurement footprint, regardless of the heterogeneous nature of snow pack properties. Across three study areas, Tb decreases by 23–35K as depth increased up to the signal saturation depth, which ranged from 70 to 120cm. With regard to vegetation sensitivity, forest fractions (F) as little as 0.2 can modify the PM measurement by up to 10K, and F greater than 0.6 mask virtually all of the microwave signal attributable to snow. Finally, with respect to the measurement scale, our results indicate that the scale at which the PM measurement is made does not affect the sensitivity of the Tb to mean snow depth, to the scale (1km) examined herein.

Impacts of long-term snow climate change on a high-elevation cold desert shrubland, California, USA

Ecological responses to 50-year old manipulations of snow depth and melt timing were assessed using snow fences arrayed across 50 km of a shrub–conifer landscape mosaic in eastern California, USA. We compared how increased, decreased, and ambient snow depth affected patterns of vegetation community composition, fire fuel accumulation, and annual tree ring growth. We also tested the effect of snow depth on soil carbon storage based on total C content under the two co-dominant shrub species (Artemisiatridentata and Purshia tridentata) in comparison with open, intershrub sites. Increased snow depth reduced the cover of the N-fixing shrub P. tridentata but not the water-redistributing shrub A. tridentata. Annual ring growth was greater on +snow plots and lower on −snow plots for the conifer Pinus jeffreyi but not for Pinus contorta. Graminoid cover and aboveground biomass indicated higher fire fuel accumulation where snow depth was increased. Dead shrub stem biomass was greater regardless of whether snow depth was increased or decreased. Results demonstrate community shifts, altered tree growth, feedbacks on carbon storage, and altered fire fuel accumulation as a result of changes in snow depth and melt timing for this high-elevation, snow-dominated ecotone under future climate scenarios that envision increased or decreased snow depth.

Future Changes of Snow Depth in a Non-Hydrostatic Regional Climate Model with Bias Correction

Future Changes of Snow Depth in a Non-Hydrostatic Regional Climate Model with Bias Correction

Winter Hydrology and NO3− Concentrations in a Forested Watershed: A Detailed Field Study in the Adirondack Mountains of New York1

Abstract: More than 85% of NO3− losses from watersheds in the northeastern United States are exported during winter months (October 1 to May 30). Interannual variability in NO3− loads to individual streams is closely related to interannual climatic variations, particularly during the winter. The objective of our study was to understand how climatic and hydrogeological factors influence NO3− dynamics in small watersheds during the winter. Physical parameters including snow depth, soil temperature, stream discharge, and water table elevation were monitored during the 2007‐2008 winter in two small catchments in the Adirondack Mountains, New York State. Snowpack persisted from mid‐December to mid‐April, insulating soils such that only two isolated instances of soil frost were observed during the study period. NO3− export during a mid‐winter rain‐on‐snowmelt event comprised between 8 and 16% of the total stream NO3− load for the four‐month winter study period. This can be compared with the NO3− exported during the final spring melt, which comprised between 38 and 45% of the total four‐month winter NO3− load. Our findings indicate that minor melt events were detectable with changes in soil temperature, streamflow, groundwater level, and snow depth. But, based on loading, these events were relatively minor contributors to winter NO3− loss. A warmer climate and fluctuating snowpack may result in more major mid‐winter melt events and greater NO3− export to surface waters.

An evaluation of methods for determining during-storm precipitation phase and the rain/snow transition elevation at the surface in a mountain basin

Determining surface precipitation phase is required to properly correct precipitation gage data for wind effects, to determine the hydrologic response to a precipitation event, and for hydrologic modeling when rain will be treated differently from snow. In this paper we present a comparison of several methods for determining precipitation phase using 12years of hourly precipitation, weather and snow data from a long-term measurement site at Reynolds Mountain East (RME), a headwater catchment within the Reynolds Creek Experimental Watershed (RCEW), in the Owyhee Mountains of Idaho, USA. Methods are based on thresholds of (1) air temperature (Ta) at 0°C, (2) dual Ta threshold, −1 to 3°C, (3) dewpoint temperature (Td) at 0°C, and (4) wet bulb temperature (Tw) at 0°C. The comparison shows that at the RME Grove site, the dual threshold approach predicts too much snow, while Ta, Td and Tw are generally similar predicting equivalent snow volumes over the 12year-period indicating that during storms the cloud level is at or close to the surface at this location. To scale up the evaluation of these methods we evaluate them across a 380m elevation range in RCEW during a large mixed-phase storm event. The event began as snow at all elevations and over the course of 4h transitioned to rain at the lowest through highest elevations. Using 15-minute measurements of precipitation, changes in snow depth (zs), Ta, Td and Tw, at seven sites through this elevation range, we found precipitation phase linked to the during-storm surface humidity. By measuring humidity along an elevation gradient during the storm we are able to track changes in Td to reliably estimate precipitation phase and effectively track the elevation of the rain/snow transition during the event.

Factors influencing permafrost temperatures across tree line in the uplands east of the Mackenzie Delta, 2004–20101This article is one of a series of papers published in this CJES Special Issue on the theme of Fundamental and applied research on permafrost in Canada.2Polar Continental Shelf Contribution 03611.

Air and near-surface ground temperatures, late-winter snow conditions, and characteristics of the vegetation cover and soil were measured across the forest–tundra transition in the uplands east of the Mackenzie Delta, Northwest Territories, in 2004–2010. Mean late-winter snow depth decreased northward from 73 cm in the subarctic boreal forest near Inuvik to 22 cm in low-shrub tundra. Annual near-surface ground temperatures decreased northward by 0.1–0.3 °C/km near the northern limit of trees, in association with an abrupt change in snow depth. The rate decreased to 0.01–0.06 °C/km in the tundra. The freezing season is twice as long as the thawing season in the region, so measured differences in the regional ground thermal regime were dominated by the contrast in winter surface conditions between forest and tundra.

Changes in snow depth in Norway during the period 1961–2010

Observed trends in annual maximum snow depth (SD) in Norway are analyzed and examined in the context of changes in winter climate from 1961 until today. Trends are evaluated for the 50-year period (1961–2010) and for three 30-year periods (1961–1990, 1971–2000, 1981–2010). The analyzed dataset is the most extensive and geographically representative for the country so far, and the analysis gives an up-to-date picture of the recent development in snow accumulation. In regions characterized by colder winter climate long-term trends are found to be positive in general, while short-term trends shift from strongly positive in the first period to predominantly negative in the last period. Variation in SD is here mainly linked to variation in precipitation. In regions of warmer winter climate variation in SD is dominated by temperature, and long-term trends are mainly negative. Short-term trends start out weak overall in the first period but become strongly negative most places in the last period. It is likely that, although more and more regions in Norway will experience declining maximum annual SD in a projected wetter and warmer future climate, some inland and higher mountain regions may still accumulate more snow in the coming decades.

The impacts of the PNA and NAO on annual maximum snowpack over southern Canada during 1979–2009

AbstractThe Pacific/North American pattern (PNA) and North Atlantic Oscillation (NAO) are two of the most important atmospheric low‐frequency variability modes modulating interannual anomalies of snowpacks in North America. However, the quantitative degree to which the PNA and NAO affect the annual maximum snow water equivalent (SWEmax), a quantity directly relevant to the ground snow load calculation in National Building Code of Canada, remains unknown. This study explores the relationship of the winter PNA and NAO to the Canadian SWEmax anomalies and potential changes associated with atmospheric circulation patterns. Significant correlations are identified in eastern and western Canada, where climatological mean values are largest due to the high frequency of snow storm occurrence. The regions in Canada where SWEmax anomalies are influenced by the PNA and NAO experienced a significant change from pre‐1998 to post‐1998. This change is consistent with the observed changes in annual maximum snow depth and the winter atmospheric circulations during 1979–2009. Copyright © 2012 Royal Meteorological Society

Spatio-temporal measurements and analysis of snow depth in a rock face

Abstract. Snow in rock faces plays a key role in the alpine environment for permafrost distribution, snow water storage or runoff in spring. However, a detailed assessment of snow depths in steep rock walls has never been attempted. To understand snow distribution in rock faces a high-resolution terrestrial laser scanner (TLS), including a digital camera, was used to obtain interpolated snow depth (HS) data with a grid resolution of one metre. The mean HS, the snow covered area and their evolution in the rock face were compared to a neighbouring smoother catchment and a flat field station at similar elevation. Further we analyzed the patterns of HS distribution in the rock face after different weather periods and investigated the main factors contributing to those distributions. In a first step we could show that with TLS reliable information on surface data of a steep rocky surface can be obtained. In comparison to the flatter sites in the vicinity, mean HS in the rock face was lower during the entire winter, but trends of snow depth changes were similar. We observed repeating accumulation and ablation patterns in the rock face, while maximum snow depth loss always occurred at those places with maximum snow depth gain. Further analysis of the main factors contributing to the snow depth distribution in the rock face revealed terrain-wind-interaction processes to be dominant. Processes related to slope angle seem to play a role, but no simple relationship between slope angle and snow depth was found. Further analyses should involve measurements in rock faces with other characteristics and higher temporal resolutions to be able to distinguish individual processes better. Additionally, the relation of spatial and temporal distribution of snow depth to terrain – wind interactions should be tested.

Reconstructing historical snow depth surfaces to evaluate changes in critical demographic rates and habitat components of snow‐dependent and snow‐restricted species

Summary1. Climate change models consistently predict snow depth declines across the Northern Hemisphere. Snow depth has been linked to the demography of numerous species, and snow depth reduction is expected to affect the demography of some northern species. As many demographic studies depend on long‐term population data that extend back beyond available sources of spatially continuous snow depth data, reliable hindcasting of snow depth surface maps is needed.2. We developed a two‐stage regression modelling approach to reconstructing historic snow depths using an existing and readily available spatiotemporal data set of daily meteorological variables across a large, heterogeneous landscape in North America from 1982 to 2003. The final model accounted for ecoregional differences and predicted snow depth as a function of elevation and total snowfall accumulation.3. Model validations showed that the estimated snow depths were spatially and temporally accurate.4. We demonstrate how to apply this model with ArcGIS to hindcast monthly and yearly sequences of high‐resolution, spatially continuous surfaces of historic snow depths. We also illustrate the utility of the modelled snow depth surfaces for informing predictions of how changes in snow depth may influence the demography and habitats of snow‐dependent and snow‐restricted species by assessing the spatiotemporal stochasticity of snow conditions that potentially benefit wolverine Gulo gulo and the winter ranges, net energy costs and population growth of mule deer Odocoileus hemionus.5. This model can be used to hindcast snow depth surfaces across similar regions; our simple two‐stage modelling approach can be applied to other regions where equivalent climate data are available. The resulting spatiotemporal snow depth surfaces estimated from this model can be linked to existing long‐term wildlife population data sets to investigate the extent to which snow depth declines may regulate or limit populations.

Long-term changes in annual maximum snow depth and snowfall in Switzerland based on extreme value statistics

Mountain snow cover is an important source of water and essential for winter tourism in Alpine countries. However, large amounts of snow can lead to destructive avalanches, floods, traffic interruptions or even the collapse of buildings. We use annual maximum snow depth and snowfall data from 25 stations (between 200 and 2,500 m) collected during the last 80 winters (1930/31 to 2009/2010) to highlight temporal trends of annual maximum snow depth and 3-day snowfall sum. The generalized extreme value (GEV) distribution with time as a covariate is used to assess such trends. It allows us in particular to infer how return levels and return periods have been modified during the last 80 years. All the stations, even the highest one, show a decrease in extreme snow depth, which is mainly significant at low altitudes (below 800 m). A negative trend is also observed for extreme snowfalls at low and high altitudes but the pattern at mid-altitudes (between 800 and 1,500 m) is less clear. The decreasing trend of extreme snow depth and snowfall at low altitudes seems to be mainly caused by a reduction in the magnitude of the extremes rather than the scale (variability) of the extremes. This may be caused by the observed decrease in the snow/rain ratio due to increasing air temperatures. In contrast, the decreasing trend in extreme snow depth above 1,500 m is caused by a reduction in the scale (variability) of the extremes and not by a reduction in the magnitude of the extremes. However, the decreasing trends are significant for only about half of the stations and can only be seen as an indication that climate change may be already impacting extreme snow depth and extreme snowfall.