Snow Cover Period Research Articles

Experimentally increased snow depth affects high Arctic microarthropods inconsistently over two consecutive winters

Climate change induced alterations to winter conditions may affect decomposer organisms controlling the vast carbon stores in northern soils. Soil microarthropods are particularly abundant decomposers in Arctic ecosystems. We studied whether increased snow depth affected microarthropods, and if effects were consistent over two consecutive winters. We sampled Collembola and soil mites from a snow accumulation experiment at Svalbard in early summer and used soil microclimatic data to explore to which aspects of winter climate microarthropods are most sensitive. Community densities differed substantially between years and increased snow depth had inconsistent effects. Deeper snow hardly affected microarthropods in 2015, but decreased densities and altered relative abundances of microarthropods and Collembola species after a milder winter in 2016. Although increased snow depth increased soil temperatures by 3.2 °C throughout the snow cover periods, the best microclimatic predictors of microarthropod density changes were spring soil temperature and snowmelt day. Our study shows that extrapolation of observations of decomposer responses to altered winter climate conditions to future scenarios should be avoided when communities are only sampled on a single occasion, since effects of longer-term gradual changes in winter climate may be obscured by inter-annual weather variability and natural variability in population sizes.

A camera trap‐based assessment of climate‐driven phenotypic plasticity of seasonal moulting in an endangered carnivore

AbstractFor many species, the ability to rapidly adapt to changes in seasonality is essential for long‐term survival. In the Arctic, seasonal moulting is a key life‐history event that provides year‐round camouflage and thermal protection. However, increased climatic variability of seasonal events can lead to phenological mismatch. In this study, we investigated whether winter‐white (white morph) and winter‐brown (blue morph) Arctic foxes (Vulpes lagopus) could adjust their winter‐to‐summer moult to match local environmental conditions. We used camera trap images spanning an eight‐year period to quantify the timing and rate of fur change in a polymorphic subpopulation in south‐central Norway. Seasonal snow cover duration and temperature governed the phenology of the spring moult. We observed a later onset and longer moulting duration with decreasing temperature and longer snow season. Additionally, white foxes moulted earlier than blue in years with shorter periods of snow cover and warmer temperatures. These results suggest that phenotypic plasticity allows Arctic foxes to modulate the timing and rate of their spring moult as snow conditions and temperatures fluctuate. With the Arctic warming at an unprecedented rate, understanding the capacity of polar species to physiologically adapt to a changing environment is urgently needed in order to develop adaptive conservation efforts. Moreover, we provide the first evidence for variations in the moulting phenology of blue and white Arctic foxes. Our study underlines the different intraspecific selective pressures that can exist in populations where several morphs co‐occur, and illustrates the importance of integrating morph‐based differences in future management strategies of such polymorphic species.

Snow Exclusion Does Not Affect Soil Ammonia-Oxidizing Bacteria and Archaea Communities

Soil ammonia-oxidizing microorganisms play important roles in nitrogen (N) cycling in cold ecosystems, but how changes in snow cover will affect their distribution and associated functional characteristics remains unclear. A snow manipulation experiment was conducted to explore the effects of snow exclusion on soil ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) communities and functional characteristics in a spruce forest in the eastern Tibet Plateau. Results showed that the amoA gene abundance and community composition of AOA and AOB did not differ between snow regimes but varied among winter periods. AOA and AOB gene abundances showed a decreasing trend during the snow cover melting period. During the deep snow cover period, Thaumarchaeota and Crenarchaeota in the AOA community decreased significantly, while Proteobacteria and Nitrosospira in the AOB community increased significantly. The main factors affecting the changes in AOA and AOB community diversity and composition were soil MBN, nitrate nitrogen, and temperature, while AOA and AOB community diversity and composition were also significantly correlated with soil enzyme activities related to N cycling. These results recommend that the season-driven variations strongly affected soil ammonia-oxidizing community and functional characteristics more than momentary snow cover change. Such findings offer new insights into how soil N-cycling processes would respond to reduced snowfall in high-altitude regions.

Utilization of cultivated fruits by Japanese martens and red foxes in a snowy environment: a comparison of feeding habits between rural and forest landscapes

Cultivated fruits can serve as an important winter food resource for medium-sized carnivores in rural areas that experience heavy snowfall. However, studies on the food analysis of medium-sized carnivores in heavy snowfall areas, particularly on the use of cultivated fruits, are limited. We evaluated the use of cultivated fruits by medium-sized carnivores during winter in a heavy snowfall area by comparing their feeding habits in rural and forest landscapes. We conducted faecal analysis of Japanese martens (Martes melampus) and red foxes (Vulpes vulpes) in rural and forest landscapes in north-eastern Japan during periods of snow cover. Based on a faecal analysis in the rural landscape, both Japanese martens and red foxes consumed mammals, birds, fruits, and other plant material. In the forest landscape, mammals and insects were consumed by Japanese martens and mammals, fruits, and other plant material were consumed by red foxes. Our results showed that cultivated fruits, such as persimmons and apples, were a major food source in snowy environments, suggesting a wider range of available resources and overlapping feeding habits. It has been suggested that red foxes in forest landscapes move long distances (several kilometres) to consume cultivated fruits. This study suggests that cultivated fruits may also indirectly feed wildlife, even in areas with heavy snowfall.

Substrate influences foraging selection by Eurasian Green Woodpeckers Picus viridis in autumn and winter: observations in Hungary over a 20-year period

Abstract The foraging behaviour and habitat use of the Eurasian Green Woodpecker Picus viridis at various sites in Hungary over a 20-year period was documented. Detailed observations were recorded on foraging behaviour at hard substrates; in quarries, cliffs and human made structures of brick and stone construction. Using Chi-square tests on the frequency of observations of birds at hard substrates foraging sites, we compared usage during periods of snow cover and those without. Birds were found to be more frequently observed at hard substrates during periods of snow cover because these remained largely free of snow. We supposed that this response was due to invertebrate prey becoming increasingly scarce generally across typical foraging sites, i.e. grasslands and meadows during harsh winter conditions. Accessibility to the alternative sites became important as a source of food because availability of prey was more reliable. Vertical surfaces of hard substrates such as those associated with quarries, cliffs and buildings may be important to sustain Eurasian Green Woodpeckers in periods of snow cover where these provide a valuable foraging resource.

IMPROVED ON SNOW COVER EXTRACTION IN MOUNTAINOUS AREAS BASED ON MULTI-FACTOR NDSI DYNAMIC THRESHOLD

Abstract. Snow cover is one of the most active elements of the cryosphere and plays an important role in the surface radiation budget and water balance. Optical satellite remote sensing has become an important tool for snow identification and monitoring. The Sentinel-2 A/B satellite has become an important data source for snow cover extraction because of its high radiation resolution, which reduces the problem of snow/ice saturation in remote sensing observations. The normalized differential snow cover index (NDSI) and the snow cover index considering the forest cover area (NDFSI) are important methods for snow cover extraction, but due to the strong spatial heterogeneity and fast change speed of snow cover in mountainous areas, using the classical fixed threshold method to extract snow cover will result in a large omission error. In this paper, a dynamic threshold method is constructed by synthesizing the effects of the type of snow cover period, aspect and snow underlying land coverage type on the snow cover NDSI/NDFSI. Compared with the high-resolution GF-2 snow map results, the dynamic threshold method has higher accuracy in extracting snow cover, and the overall classification accuracy, omission error, commission error and Kappa coefficient are 97.70%, 0.20%, 11.17% and 0.93 respectively. The dynamic threshold method is used to extract snow cover in a snow cover period in the Babao River Basin. The snow cover rate in the basin fluctuates greatly with time, and the spatial distribution of snow cover is uneven, with more snow cover in mountainous areas and rapid changes in snow cover in river valleys.

POLLEN OF SAGEBRUSH (ARTEMISIA SP.) IN SOLID PRECIPITATION OF THE ALTAI KRAI AND AREAS OF ITS SUPPLY

The results of microscopic analysis of 207 samples of solid precipitation (snow) collected at three key points located in various natural conditions in the Altai krai during the snow cover period (2019-2020, 2020-2021) are presented. The study focuses on the determination of sagebrush pollen ( Artemisia sp.) as one of the main indicators of the state of geosystems, cryospheric processes during paleoclimatic and paleoecological reconstructions, and the main allergen. Pollen grains of trees and grasses were identified in the third part of the samples taken, and sagebrush was isolated in 20% of this number of samples. To determine the areas of its supply, an integrated approach based on the analysis of backwards trajectories of air masses movement (HYSPLIT model) and synoptic conditions (ERA 5 and NCEP/NCAR reanalysis) was used. Such an integrated approach made it possible to determine that sagebrush pollen was supplied with air masses coming from the territories of the Kazakh Upland (Kazakhskiy Melkosopochnik).

How do snow cover fraction change and respond to climate in Altai Mountains of China?

AbstractInvestigating the spatial and temporal changes in snow cover over mountain areas is significant for understanding the impact of regional climate variability. In this study, using cloud‐removed snow cover data, which are generated based on Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products, the spatiotemporal changes of snow cover fraction (SCF) and its relationship with temperature and precipitation changes from 2002 to 2020 were examined over Altai Mountains, China. The results demonstrate that the distribution and changes of SCF are highly spatiotemporally heterogeneous. Within a year, the maximum SCF occurs in January at 98.6%, and the minimum appears in July at 8.7%. The annual‐mean SCF shows an increasing trend at 0.09%·annum−1, owing to the significantly increasing SCF in the snow accumulation period at 0.5%·annum−1 and the decreasing SCF in the snow melting period at −0.2%·annum−1. The SCF distribution, as well as its interannual change, is greatly influenced by elevation. During the snow cover period, a positive linear correlation between SCF and elevation is found at 0.02%·m−1 (p < .01). The annual‐mean SCF decreases in the area below 1,200 m, whereas it increases in the area above 1,200 m. Accordingly, the elevation‐dependent SCF results in various SCF distributions on different slopes and watersheds. The SCF shows an apparent pattern in different aspects, with similar SCFs between the north and east aspects and between the west and south aspects but a difference between the northeast aspects and the westsouth aspects. The SCF is negatively correlated with air temperature (r = −0.74, p < 0.01) and positively correlated with precipitation (r = 0.74, p < 0.01). In addition, temperature shows a significant and larger correlation with SCF in both the snow accumulation and melting periods, indicating the major factor of temperature for the changes in SCF.

Factors influencing the ground thermal regime in a mid-latitude glacial cirque (Hoyo Empedrado, Cantabrian Mountains, 2006–2020)

Air and near-surface ground temperatures were measured using dataloggers over 14 years (2006–2020) in 10 locations at 2262 to 2471 m.a.s.l. in a glacial cirque of the Cantabrian Mountains. These sites exhibit relevant differences in terms of substrate, solar radiation, orientation, and geomorphology. Basal temperature of snow (BTS) measurements and electrical resistivity tomography of the talus slope were also performed. The mean annual near-surface ground temperatures ranged from 5.1 °C on the sunny slope to 0.2 °C in the rock glacier furrow, while the mean annual air temperature was 2.5 °C. Snow cover was inferred from near-surface ground temperature (GST) data, estimating between 130 and 275 days per year and 0.5 to 7.1 m snow thickness. Temperature and BTS data show that the lowest part of the talus slope and the rock glacier furrow are the coldest places in this cirque, coinciding with a more persistent and thickest snow cover. The highest temperatures coincide with less snow cover, fine-grained soils, and higher solar radiation. Snow cover has a primary role in controlling GST, as the delayed appearance in autumn or delayed disappearance in spring have a cooling effect, but no correlation with mean annual near-surface ground temperatures exists. Heavy rain-over-snow events have an important influence on the GST. In the talus slope, air circulation during the snow-covered period produces a cooling effect in the lower part, especially during the summer. Significant inter-annual GST differences were observed that exhibited BTS limitations. A slight positive temperature trend was detected but without statistically significance and less prominent than nearby reference official meteorological stations, so topoclimatic conditions reduced the more global positive temperature trend. Probable existence of permafrost in the rock glacier furrow and the lowest part of the talus slope is claimed; however, future work is necessary to confirm this aspect.

Unique population dynamics of Japanese field vole: Winter breeding and summer population decline

AbstractIt is common knowledge that winter temperatures influence the life history of small mammals. Cold temperatures necessitate increased energy requirements for survival, and recent studies indicate that snow cover can have both negative and positive influences. With each new observation, we develop a more comprehensive understanding of the mechanisms that influence small mammal populations. Here we report on our recent study on Japanese field vole Microtus montebelli, which reaches its peak in population during the early spring and its low during the autumn. To understand the population dynamics of these voles, we conducted a capture‐mark‐recapture survey, then estimated the seasonal abundance, recruit, capture probabilities, and survival probabilities using the Bayesian hierarchical model. We also analyzed the impact of mammalian generalist predator visits on the survival probabilities. Our data indicates that the early spring peak in population is due to intensive winter breeding and the highest survival probabilities during the periods of deep snow cover. When snow cover reaches a certain depth, the circumstances can combine to raise survival probability and favor breeding. During the breeding season in May and June, on the contrary, the survival probability reached its lowest, resulting in a decrease in population despite breeding. The low survival probability between spring and autumn could be attributed to the impact of generalist predators, and low vegetation may have amplified the effect. In summary, the deep snow cover and generalist predators were considered to be the key factors shaping this unique population dynamics in this orchard area.

Economic Impact of Climate Change in the Midland of Russia

The article discusses the global climate warming impact on the most important agro-climatic parameters of the southern half of the Russian Federation European part. It has been established that in recent years a stable zone of moisture deficiency, stretching as a strip from Bryansk to the border of the Chelyabinsk region with Kazakhstan, has formed. At the same time, the most stable moisture deficit in summer is observed in the Bryansk region. For 2014-2016 the amount of moisture deficit according to the Bryansk State Agrarian University meteorological station was 47%. Due to the increasing climate aridity, the Bryansk region is approaching in agroclimatic parameters to traditionally grain regions. The increase in the amount of active temperatures turns its territory into an agro-climatic analogue of the northwestern part of the United States Corn Belt. A significant warming of winter, as well as a reduction in stable snow cover period, increases the beef cattle breeding competitiveness. At the same time, the cultivation of berries, raspberries in particular, becomes impossible without artificial irrigation.

Seasonal changes in soil properties caused by slash and burn agriculture practice in a humid temperate region of northeast Japan

ABSTRACT We investigated the influence of slash and burn (SBA) practice on selected soil properties and its influence on the dynamics of mineral nutrients in a typical humid temperate climate region of northeast Japan. Soils were sampled from an SBA site and compared to an adjacent original forest site (control) located in Shonai area, Yamagata Prefecture, from August 2018 to August 2019 with monthly intervals for SBA and bi-monthly intervals for control, except the snow cover period. The results showed that SBA could not evidently affect soil pH, electric conductivity, available phosphorus, exchangeable cations (Ca2+, Mg2+ and K+), and effective cation exchange capacity. This was likely due to the low severity of fire in the SBA site. On the other hand, cultivation of turnip affected seasonal changes of soil NH4 + and NO3 − mainly attributed to crop absorption. Soil MBC and MBN were significantly increased after one month of burning due to available soil nutrients from plant biomass burning which stimulated microbial growth. There were no significant changes in SOC and TN between the clear-cut stage (before SBA), and after one year at the end of the study period. This was largely due to the short turnip cultivation period and the quick covering by succession plants. In conclusion, our results showed the SBA practice affected soil properties in this study was not relatively significant.

Snow-Disaster Risk Zoning and Assessment in Heilongjiang Province

Heilongjiang Province is located in the northeast region of China, with the country’s highest latitude. It has long and cold winters, and a temperate monsoon climate. Its unique geographic location and climatic conditions make it the second largest stable snow-covered region in China. The winter snow period starts in October and ends in April of the following year. Therefore, the long-term accumulation of snow causes road obstructions and low-temperature frost damage, which seriously affects local economic development and human safety. This study adopts snow parameters (e.g., snow depth and snow-cover period), natural environmental factors (e.g., elevation and slope), and socioeconomic factors (e.g., gross domestic product and light index). On the basis of the disaster risk assessment theory, we constructed a disaster risk index from four aspects (i.e., disaster risk, susceptibility, vulnerability, and disaster prevention and mitigation). Then, we performed snow-disaster risk zoning and an assessment in Heilongjiang Province. The main findings are as follows: the snow-disaster risk in the northern and eastern regions of Heilongjiang Province was high; the central and northern regions were highly sensitive to disasters; the main urban areas were highly vulnerable; and the economically developed regions had strong disaster prevention and mitigation capabilities. Overall, the spatial distribution of the snow-disaster risk followed a decreasing trend from east to west. High-risk areas were distributed in the east and northwest (covering 34.3% of the entire Heilongjiang Province area); medium-risk areas were distributed in the north and center (accounting for 45.2% of the entire Heilongjiang Province area); and low-risk areas were concentrated in the west (constituting 20.5% of the entire Heilongjiang Province area).

Multilayer observation and estimation of the snowpack cold content in a humid boreal coniferous forest of eastern Canada

Abstract. Cold content (CC) is an internal energy state within a snowpack and is defined by the energy deficit required to attain isothermal snowmelt temperature (0 ∘C). Cold content for a given snowpack thus plays a critical role because it affects both the timing and the rate of snowmelt. Measuring cold content is a labour-intensive task as it requires extracting in situ snow temperature and density. Hence, few studies have focused on characterizing this snowpack variable. This study describes the multilayer cold content of a snowpack and its variability across four sites with contrasting canopy structures within a coniferous boreal forest in southern Québec, Canada, throughout winter 2017–2018. The analysis was divided into two steps. In the first step, the observed CC data from weekly snowpits for 60 % of the snow cover period were examined. During the second step, a reconstructed time series of modelled CC was produced and analyzed to highlight the high-resolution temporal variability of CC for the full snow cover period. To accomplish this, the Canadian Land Surface Scheme (CLASS; featuring a single-layer snow model) was first implemented to obtain simulations of the average snow density at each of the four sites. Next, an empirical procedure was used to produce realistic density profiles, which, when combined with in situ continuous snow temperature measurements from an automatic profiling station, provides a time series of CC estimates at half-hour intervals for the entire winter. At the four sites, snow persisted on the ground for 218 d, with melt events occurring on 42 of those days. Based on snowpit observations, the largest mean CC (−2.62 MJ m−2) was observed at the site with the thickest snow cover. The maximum difference in mean CC between the four study sites was −0.47 MJ m−2, representing a site-to-site variability of 20 %. Before analyzing the reconstructed CC time series, a comparison with snowpit data confirmed that CLASS yielded reasonable bulk estimates of snow water equivalent (SWE) (R2=0.64 and percent bias (Pbias) =-17.1 %), snow density (R2=0.71 and Pbias =1.6 %), and cold content (R2=0.93 and Pbias =-3.3 %). A snow density profile derived by utilizing an empirical formulation also provided reasonable estimates of layered cold content (R2=0.42 and Pbias =5.17 %). Thanks to these encouraging results, the reconstructed and continuous CC series could be analyzed at the four sites, revealing the impact of rain-on-snow and cold air pooling episodes on the variation of CC. The continuous multilayer cold content time series also provided us with information about the effect of stand structure, local topography, and meteorological conditions on cold content variability. Additionally, a weak relationship between canopy structure and CC was identified.

A Cloudier Picture of Ice-Albedo Feedback in CMIP6 Models

Increased solar absorption is an important driver of Arctic Amplification, the interconnected set of processes and feedbacks by which Arctic temperatures respond more rapidly than global temperatures to climate forcing. The amount of sunlight absorbed in the Arctic is strongly modulated by seasonal ice and snow cover. Sea ice declines and shorter periods of seasonal snow cover in recent decades have increased solar absorption, amplifying local warming relative to the planet as a whole. However, this Arctic albedo feedback would be substantially larger in the absence of the ubiquitous cloud cover that exists throughout the region. Clouds have been observed to mask the effects of reduced surface albedo and slow the emergence of secular trends in net solar absorption. Applying analogous metrics to several models from the 6thClimate Model Intercomparison Project (CMIP6), we find that ambiguity in the influence of clouds on predicted Arctic solar absorption trends has increased relative to the previous generation of climate models despite better agreement with the observed albedo sensitivity to sea ice variations. Arctic albedo responses to sea ice loss are stronger in CMIP6 than in CMIP5 in all summer months. This agrees better with observations, but models still slightly underestimate albedo sensitivity to sea ice changes relative to observations. Never-the-less, nearly all CMIP6 models predict that the Arctic is now absorbing more solar radiation than at the start of the century, consistent with recent observations. In fact, many CMIP6 models simulate trends that are too strong relative to internal variability, and spread in predicted Arctic albedo changes has increased since CMIP5. This increased uncertainty can be traced to increased ambiguity in how clouds influence natural and forced variations in Arctic solar absorption. While nearly all CMIP5 models agreed with observations that clouds delay the emergence of forced trends, about half of CMIP6 models suggest that clouds accelerate their emergence from natural variability. Isolating atmospheric contributions to total Arctic reflection suggests that this diverging behavior may be linked to stronger Arctic cloud feedbacks in the latest generation of climate models.

Multi-Dimensional Remote Sensing Analysis Documents Beaver-Induced Permafrost Degradation, Seward Peninsula, Alaska

Beavers have established themselves as a key component of low arctic ecosystems over the past several decades. Beavers are widely recognized as ecosystem engineers, but their effects on permafrost-dominated landscapes in the Arctic remain unclear. In this study, we document the occurrence, reconstruct the timing, and highlight the effects of beaver activity on a small creek valley confined by ice-rich permafrost on the Seward Peninsula, Alaska using multi-dimensional remote sensing analysis of satellite (Landsat-8, Sentinel-2, Planet CubeSat, and DigitalGlobe Inc./MAXAR) and unmanned aircraft systems (UAS) imagery. Beaver activity along the study reach of Swan Lake Creek appeared between 2006 and 2011 with the construction of three dams. Between 2011 and 2017, beaver dam numbers increased, with the peak occurring in 2017 (n = 9). Between 2017 and 2019, the number of dams decreased (n = 6), while the average length of the dams increased from 20 to 33 m. Between 4 and 20 August 2019, following a nine-day period of record rainfall (>125 mm), the well-established dam system failed, triggering the formation of a beaver-induced permafrost degradation feature. During the decade of beaver occupation between 2011 and 2021, the creek valley widened from 33 to 180 m (~450% increase) and the length of the stream channel network increased from ~0.6 km to more than 1.9 km (220% increase) as a result of beaver engineering and beaver-induced permafrost degradation. Comparing vegetation (NDVI) and snow (NDSI) derived indices from Sentinel-2 time-series data acquired between 2017 and 2021 for the beaver-induced permafrost degradation feature and a nearby unaffected control site, showed that peak growing season NDVI was lowered by 23% and that it extended the length of the snow-cover period by 19 days following the permafrost disturbance. Our analysis of multi-dimensional remote sensing data highlights several unique aspects of beaver engineering impacts on ice-rich permafrost landscapes. Our detailed reconstruction of the beaver-induced permafrost degradation event may also prove useful for identifying degradation of ice-rich permafrost in optical time-series datasets across regional scales. Future field- and remote sensing-based observations of this site, and others like it, will provide valuable information for the NSF-funded Arctic Beaver Observation Network (A-BON) and the third phase of the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) Field Campaign.

Trends in seasonal snowpack and their relation to climate variables in mountain catchments in Czechia

ABSTRACT This study investigated trends in snowpack for the period 1965–2014 in 40 catchments located in five mountain regions in Czechia. We analysed daily series of air temperature, precipitation, and snow water equivalent (SWE) that were simulated with a conceptual model. The Mann-Kendall test showed strong increasing trends in air temperature at all elevations, mostly at the end of the cold season. This increase caused a decrease in snowfall fraction and SWE. Maximum SWE decreased mainly in western parts of Czechia (by up to −45 mm/decade). The length of the snow-covered period decreased by up to −6.8 days/decade, mainly due to earlier melt-out. Snowpack was more sensitive to changes in air temperature at elevations below 900 m a.s.l., while precipitation had a larger impact on snowpack at elevations above 1200 m a.s.l. The relative importance of air temperature for snow variability increased at all elevations in the last few decades.

Technical note: Introduction of a superconducting gravimeter as novel hydrological sensor for the Alpine research catchment Zugspitze

Abstract. GFZ (German Research Centre for Geosciences) set up the Zugspitze Geodynamic Observatory Germany with a worldwide unique installation of a superconducting gravimeter at the summit of Mount Zugspitze on top of the Partnach spring catchment. This high alpine catchment is well instrumented, acts as natural lysimeter and has significant importance for water supply to its forelands, with a large mean annual precipitation of 2080 mm and a long seasonal snow cover period of 9 months, while showing a high sensitivity to climate change. However, regarding the majority of alpine regions worldwide, there is only limited knowledge on temporal water storage variations due to sparsely distributed hydrological and meteorological sensors and the large variability and complexity of signals in alpine terrain. This underlines the importance of well-equipped areas such as Mount Zugspitze serving as natural test laboratories for improved monitoring, understanding and prediction of alpine hydrological processes. The observatory superconducting gravimeter, OSG 052, supplements the existing sensor network as a novel hydrological sensor system for the direct observation of the integral gravity effect of total water storage variations in the alpine research catchment at Zugspitze. Besides the experimental set-up and the available data sets, the gravimetric methods and gravity residuals are presented based on the first 27 months of observations from 29 December 2018 to 31 March 2021. The snowpack is identified as being a primary contributor to seasonal water storage variations and, thus, to the gravity residuals with a signal range of up to 750 nm s−2 corresponding to 1957 mm snow water equivalent measured with a snow scale at an altitude of 2420 m at the end of May 2019. Hydro-gravimetric sensitivity analysis reveal a snow–gravimetric footprint of up to 4 km distance around the gravimeter, with a dominant gravity contribution from the snowpack in the Partnach spring catchment. This shows that the hydro-gravimetric approach delivers representative integral insights into the water balance of this high alpine site.

A history of tourism at the Mer de Glace: Adaptations of glacier tourism to glacier fluctuations since 1741

Climate change induces profound changes in mountain territories that affect the activities pursued there. Tourism is one activity that is strongly impacted by these changes. Most research on tourism in mountain regions has focused on winter sports tourism, but glacier tourism, a summer activity, is also severely affected by climate change-induced phenomena, including glacier retreat and other geomorphological processes. Given that Alpine glacier tourism has been pursued since the 18th century and glaciers have been changing throughout this period, this article aims to examine the adaptations implemented by glacier tourism operators since the activity’s beginnings. Through analysis of historical documents, glaciological surveys and semi-structured interviews, this paper reveals how tourism activities around the Mer de Glace (the largest French glacier) have been impacted by glacier fluctuations since the first visit to the area in 1741. The study reveals that these developments have mainly been driven by glacier retreat and associated paraglacial dynamics. More recently, the shortening of the period of snow cover on the glacier has also impacted tourism activities. Most of the adaptation strategies implemented by tourism operators during the period in question are found to be reactive, consisting in the installation of safety equipment, the renovation of access points or the building of new structures to allow tourist activities to continue despite the consequences of glacier retreat. Other strategies, such as the adoption of new activities by workers previously specialised in another, are identified that could be considered transformative strategies, although these were only adopted by workers when their activity was no longer feasible. The analysis of materials from 1741 to the present also reveals that the recent impacts of climate change on glacier tourism are much more significant and diverse than those produced by past fluctuations. Therefore, it is important that stakeholders take suitable measures to ensure the sustainable future of the Mer de Glace and other glacier tourism destinations.

Characteristics of turbulence over the semi‐fixed desert area north of Xinjiang, China

AbstractAs the largest fixed and semi‐fixed desert in China, the Gurbantünggüt Desert undergoes a long period of snow cover in the winter and the rapid growth of ephemeral plants in the spring, presenting obvious seasonal changes in the underlying desert surface type, which can lead to variation in the turbulence of the near‐surface boundary layer turbulence over the desert. In this study, gradient tower data and eddy covariance data from 2017 were analysed to investigate the turbulence characteristics of the different surface boundary layers in the hinterland of the Gurbantünggüt Desert. The results indicate that stable atmospheric conditions in the desert occur exclusively during the early morning and at night in the desert, and the onset and duration of this stable state varies seasonally. Two regimes of intermittent turbulence occur during the night, a weak turbulent regime that occurs when the wind speed is less than the threshold and a strong turbulent regime when the wind speed exceeds the threshold, and different wind speed thresholds were observed at each level. These parameters follow a seasonal pattern of summer (July) > spring (April) > autumn (October) > winter (January) in terms of magnitude. The mean turbulence intensities of the along‐wind, cross‐wind and vertical wind are 0.5, 0.47 and 0.14, respectively, with Iu > Iv > Iw. The normalized standard deviation of the wind velocity components (σu, σv and σw) generally satisfies a 1/3 power‐law relation. Our results show that the night‐time turbulence regime classification for the Gurbantünggüt Desert strongly depends on meteorological and orographic features, and the intermittent turbulent events have the non‐stationarity of the flow in common. The results can contribute to the study of land surface processes, climate change and desertification in inland arid desert areas.