Near-surface Ground Temperatures Research Articles

Spatial variability of near-surface ground temperatures in a discontinuous permafrost area in Mongolia

Spatial variability of near-surface ground temperatures in a discontinuous permafrost area in Mongolia

Multisite evaluation of physics-informed deep learning for permafrost prediction in the Qinghai-Tibet Plateau

Prediction of the permafrost ground temperature is challenging due to its complex nonlinear process. Coupling physical models and machine learning has shown great potential in big data analysis, but its performance in permafrost prediction is still unclear. In this study, we proposed a physics-informed deep learning framework (i.e., PI-LSTM) to predict permafrost ground temperature profiles. The framework combines physical information with a long short-term memory (LSTM) network by two-stage training (pretraining and fine-tuning). The output of a Geophysical Institute Permafrost Laboratory 2 (GIPL2) model was used to pretrain the LSTM model. Borehole ground temperature measurements were used to fine-tune the pretrained LSTM model. Validation at multiple sites in various situations in the Qinghai-Tibet Plateau (QTP) shows that the accuracy and efficiency of the PI-LSTM model are dramatically higher than those of the original LSTM or GIPL2 model. Depending on the fine-tuning data sampling frequencies, the performance of the PI-LSTM model improved by an average of 27% (6–56%) and 69% (64–71%) compared to the LSTM and GIPL2 models, respectively. Even when only one year of observations was used to fine-tune the model, the RMSE of the simulated near-surface ground temperature profiles in the next decade did not substantially decline. The incorporation of physical information also contributes to the simulation efficiency. The PI-LSTM model converges faster than the LSTM model, and the training epochs are reduced by 70% (67–73%) during the fine-tuning step. This study demonstrates that integrating physical information into deep learning is promising for improving permafrost predictions.

The spatial and temporal influence of infrastructure and road dust on seasonal snowmelt, vegetation productivity, and early season surface water cover in the Prudhoe Bay Oilfield

Increased industrial development in the Arctic has led to a rapid expansion of infrastructure in the region. Localized impacts of infrastructure on snow distribution, road dust, and snowmelt timing and duration feeds back into the coupled Arctic system causing a series of cascading effects that remain poorly understood. We quantify spatial and temporal patterns of snow-off dates in the Prudhoe Bay Oilfield, Alaska, using Sentinel-2 data. We derive the Normalized Difference Snow Index to quantify snow persistence in 2019–2020. The Normalized Difference Vegetation Index and Normalized Difference Water Index were used to show linkages of vegetation and surface hydrology, in relationship to patterns of snowmelt. Newly available infrastructure data were used to analyze snowmelt patterns in relation infrastructure. Results show a relationship between snowmelt and distance to infrastructure varying by use and traffic load, and orientation relative to the prevailing wind direction (up to 1 month difference in snow-free dates). Post-snowmelt surface water area showed a strong negative correlation (up to −0.927) with distance to infrastructure. Results from field observations indicate an impact of infrastructure on winter near-surface ground temperature and snow depth. This study highlights the impact of infrastructure on a large area beyond the direct human footprint and the interconnectedness between snow-off timing, vegetation, surface hydrology, and near-surface ground temperatures.

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.

Statistical understanding for snow cover effects on near-surface ground temperature at the margin of maritime Antarctica, King George Island

Snow cover plays an important role in water supply through melting of snow/ice in polar ecosystem and environments, in particular, Antarctica. Although a site access to Antarctica is high-priced, measurements of ground surface temperature (GST) using small self-recording temperature sensors (iButtons) can provide a powerful and relatively inexpensive approach to trace the spatial and temporal distributions of soil temperature and in addition, absence/presence of snow cover. In this study, principal component analysis (PCA) was utilized to explain major patterns of GST from 128 sites at King George Island in maritime Antarctica. Variations of GST were monitored between December 2011 and January 2013. The iButtons were initially installed in snow free areas in the austral summer of 2011. Principal components 1 and 2 were associated with air temperature and snow cover, respectively. Both PCs showed good correlations with the mean GST of JJA (June to August), not with that of DJF (December to January). Based on the results excluding an outlier, PCA divided the 127 GST observations into three groups effectively: absence of snow cover (Group 1), intermittent snow cover (Group 2), and presence of snow cover (Group 3). Snow cover can supply water to the ecosystem and the GST pattern of Group 2 may imply an abundance and high productivity of mosses in the study area. Using approaches suggested by previous studies, snow cover showed up nine days (days 317–326), and the melt-out date was day 326 (KG125 in Group 2). The GST data and statistical approaches used in this study can be useful in other GST studies, particularly, for both polar regions.

Thermomechanical characteristics of an energy pile-raft foundation under heating operations

This study aims to comprehensively explore the thermomechanical characteristics of energy pile-raft foundations through in situ full-scale field tests. The foundation of interest was subjected to the joint effect of building loading and cooling thermal loading. The temperature, strain, and stress variability in both the employed pile and raft were measured and analysed. The basement of the building acted as an insulator, and the near-surface ground temperatures under the basement were affected less by seasonal changes in the air temperature. The stabilized heat exchange rate of the energy pile was approximately 75.0 W/m. The overlying raft and building at the pile head and the expanded foot and sandstone at the pile toe imposed greater restraints than those observed at other parts of the pile. The thermally induced stress per centigrade near the pile head and toe was approximately −0.160 MPa/°C and −0.202 MPa/°C, respectively. The thermally induced stresses of this kind of pile were mostly stabilized after 16 days of heating operation. When the pile was under thermomechanical loading, the axial tensile stress was mobilized along the lower half of the pile, and the maximum measured tensile stress was approximately 0.25 MPa, which did not exceed the tensile strength of the employed concrete. The cooling (contracting) of the energy pile also influenced the nearby raft. The raft temperature decreased by 6.2 °C, and the additional tensile stress was approximately 0.88 MPa (40.0% of the upper bound).

Simulation of observed temperature field below a building in Bologna, Italy

Urban settlements, whether single buildings or apartment blocks, influence near-surface ground temperatures. Heat transfer by buildings to the ground must therefore be considered when designing both vertical probes and energy geostructures in urban areas. However, assessment of ground temperature variability in urban areas is still uncommon for shallow geothermal energy purposes, the standard temperature gradient based on climatic conditions usually being employed during the design phase. Yet precise assessment of the heat transfer between buildings, infrastructures and the underground could improve the planning of geothermal systems. This work presents a numerical simulation of a finite-element model of heat transfer to the underground due to both a single building and climate conditions with the aim of reproducing the temperature waves at each depth. An isolated building in Bologna (Italy) was chosen since it allowed exact quantification of its influence on the ground temperature without external interferences. For this purpose, different boundary and initial conditions were applied to the ground thermal model and results were compared with historical data recorded over several years. The idea proposed in the paper for a single building can be considered as the baseline for further ground temperature assessment of wider urban settlements.

Elevational ground/air thermal gradients in the Swiss inner Alpine Valais

ABSTRACT The dependence of air temperature on elevation (i.e., its elevational gradient) in the mountains is well known. However, the elevational gradient of near-surface ground temperatures and derived thermal parameters is much less understood. In this study, we investigated how these parameters depend on elevation by one-year temperature measurements along a transect in the Valais Alps (Switzerland) between 700 and 2,600 m a.s.l. In addition, we studied the effect of differences in slope aspect (north/south) and land cover (open field/forest). Air temperatures were measured as a reference. The results show that the ground thermal regime distinctly differs from that of the air. These differences could mainly be attributed to radiation, snow cover, and ground heat transfer. Our findings have far-reaching implications for ecosystems, agriculture, and forestry in mountains because a large portion of the living biomass is underground and thus affected by ground thermal processes.

High spatial density ground thermal measurements in a warming permafrost region, Beiluhe Basin, Qinghai-Tibet Plateau

Air, ground surface, and permafrost surface temperatures are important components of the permafrost thermal regime. However, ground temperatures from one or two boreholes are commonly considered representative of site conditions in permafrost studies despite significant variations in local surface conditions. This makes the evaluation of site-scale temperature variations important for improving the accuracy of permafrost modelling efforts. In this study we analyzed the variability in near-surface ground temperatures in a warming permafrost region using high spatial density borehole measurements to capture variations in surface conditions. Ground temperatures were collected from 72 boreholes drilled to 5 m depth at 8 sites in Beiluhe Basin, Qinghai-Tibet Plateau. Six sites straddled an alpine meadow ecotone between well- and sparsely-vegetated ground, and two sites were located on slopes with opposing aspects. Air temperatures at the 8 sites were similar with annual mean values ranging from −2.6 to −3.0 °C in 2016–18. In contrast, annual mean surface temperatures exhibited greater variation between sites, so that surface offsets were also variable. Ground surface temperatures were highest at a sloping sunny site, and lowest at a north-facing shady site. The results indicated that surface temperatures were strongly controlled by slope aspect. In contrast, the expected effect of vegetation cover shading was not distinguishable because of variations in soil moisture content between sites. Deeper temperatures at the permafrost surface and at 5 m depth exhibited a similar trend among sites except in an unusual warm transitional area where eolian erosion disturbed the surface vegetation cover. The detailed ground temperature records characterizing within- and between-site variations could be used in future to support the calibration and validation of numerical models of permafrost distribution.

Variações paleoclimáticas e impacto na recarga de águas subterrâneas em sistemas aquíferos multicamadas usando uma abordagem multitraçador (bacia setentrional da Aquitânia, França)

The northern Aquitaine basin (southwest France) is a large multi-layer aquifer system that contains groundwater with strong residence-time variability ranging from years to tens of thousands of years. This system constitutes an archive of paleoclimate variations. A multi-parameter approach involving isotopic tracers (14C, 18O, 2H) was used to determine the residence time of groundwater and to document climate fluctuations, while dissolved noble gases were used to estimate mean annual temperatures (noble gas recharge temperatures, NGRT) at the water table. Near-surface ground temperature reconstruction from 40 ka cal BP to the present was made using data collected from five aquifers. The coldest temperatures are recorded for late Marine Isotopic Stage (MIS) 3 and MIS 2, i.e. between 36 and 18 ka cal BP. The mean NGRT for the period 27–18 ka cal BP is estimated at 5.9 ± 0.9 °C, and a strong increase towards modern values (11–13 °C) is observed after 15 ka cal BP. The temperature change between the Holocene and the Last Glacial ranges from 5 to 7 °C, in agreement with previous NGRT studies in Europe. Since mean near-surface ground temperatures during the glacial were well above 0 °C, long-term presence of permafrost in northern Aquitaine is unlikely. However, a possible warm bias in reconstructed temperatures during the coldest events lies in the fact that NGRTs in cold regions do not reflect annual means but rather the ground temperature during the thaw months.

Microtopographic control on the ground thermal regime in ice wedge polygons

Abstract. The goal of this research is to constrain the influence of ice wedge polygon microtopography on near-surface ground temperatures. Ice wedge polygon microtopography is prone to rapid deformation in a changing climate, and cracking in the ice wedge depends on thermal conditions at the top of the permafrost; therefore, feedbacks between microtopography and ground temperature can shed light on the potential for future ice wedge cracking in the Arctic. We first report on a year of sub-daily ground temperature observations at 5 depths and 9 locations throughout a cluster of low-centered polygons near Prudhoe Bay, Alaska, and demonstrate that the rims become the coldest zone of the polygon during winter, due to thinner snowpack. We then calibrate a polygon-scale numerical model of coupled thermal and hydrologic processes against this dataset, achieving an RMSE of less than 1.1 ∘C between observed and simulated ground temperature. Finally, we conduct a sensitivity analysis of the model by systematically manipulating the height of the rims and the depth of the troughs and tracking the effects on ice wedge temperature. The results indicate that winter temperatures in the ice wedge are sensitive to both rim height and trough depth, but more sensitive to rim height. Rims act as preferential outlets of subsurface heat; increasing rim size decreases winter temperatures in the ice wedge. Deeper troughs lead to increased snow entrapment, promoting insulation of the ice wedge. The potential for ice wedge cracking is therefore reduced if rims are destroyed or if troughs subside, due to warmer conditions in the ice wedge. These findings can help explain the origins of secondary ice wedges in modern and ancient polygons. The findings also imply that the potential for re-establishing rims in modern thermokarst-affected terrain will be limited by reduced cracking activity in the ice wedges, even if regional air temperatures stabilize.

Contemporary sand wedge development in seasonally frozen ground and paleoenvironmental implications

Contemporary sand wedges and sand veins are active in seasonally frozen ground within the extensive discontinuous permafrost zone in Northwest Territories, Canada. The region has a subarctic continental climate with 291 mm a−1 precipitation, −4.1 °C mean annual air temperature, warm summers (July mean 17.0 °C), and cold winters (January mean −26.6 °C). Five years of continuous observations indicate that interannual variation of the ground thermal regime is dominantly controlled by winter air temperature and snow cover conditions. At sandy sites, thin snow cover and high thermal conductivity promote rapid freezing, high rates of ground cooling, and low near-surface ground temperatures (−15 to −25 °C), resulting in thermal contraction cracking to depths of 1.2 m. Cracking potentials are high in sandy soils when air temperatures are <−30 °C on successive days, mean freezing season air temperatures are ≤−17 °C, and snow cover is <0.15 m thick. In contrast, surface conditions in peatlands maintain permafrost, but thermal contraction cracking does not occur because thicker snow cover and the thermal properties of peat prolong freezeback and maintain higher winter ground temperatures. A combination of radiocarbon dating, optical dating, and stratigraphic observations were used to differentiate sand wedge types and formation histories. Thermal contraction cracks that develop in the sandy terrain are filled by surface (allochthonous) and/or host (autochthonous) material during the thaw season. Epigenetic sand wedges infilled with allochthonous sand develop within former beach sediments beneath an active eolian sand sheet. Narrower and deeper syngenetic wedges developed within aggrading eolian sand sheets, whereas wider and shallower antisyngenetic wedges developed in areas of active erosion. Thermal contraction cracking beneath vegetation-stabilized surfaces leads to crack infilling by autochthonous host and overlying organic material, with resultant downturning and subsidence of adjacent strata. Sand wedge development in seasonally frozen ground with limited surface sediment supply can result in stratigraphy similar to ice-wedge and composite-wedge pseudomorphs. Therefore, caution must be exercised when interpreting this suite of forms and inferring paleoenvironments.

A Multi-Methodological Approach to Determine Permafrost Occurrence and Ground Surface Subsidence in Mountain Terrain, Tyrol, Austria

This study evaluates the potential of using high-resolution remote sensing data to detect permafrost patterns in a recently deglaciated alpine area on the mountain ridge of ‘Rofenberg’, Tyrol, Austria. Here, small but continuous settling of the surface was detected in differential digital terrain models throughout an annual airborne laser scanning (ALS) data series (2001–11). The settling is hypothesised to result from thawing of perennially frozen ground. To test this hypothesis, we applied a combination of established methods –geomorphological observations, permafrost modelling, near-surface ground temperature measurements (bottom of the winter snowpack and temperature logging) and geophysical surveys (electrical resistivity tomography, ground penetrating radar, seismic refraction) – that revealed the occurrence of permafrost in recently deglaciated terrain (above 3100 m asl). Consequently, the surface changes detected in the ALS data series are attributed to permafrost thaw and serve as a possible indicator of permafrost occurrence. The applied geophysical measurements also elucidate the recent development of permafrost after glacier recession since the Little Ice Age. However, to prove the existence of permafrost and its possible degradation, ALS data alone are insufficient and a combination of methods is recommended. Copyright © 2016 John Wiley & Sons, Ltd.

Small-scale variation of snow in a regional permafrost model

Abstract. The strong winds prevalent in high altitude and arctic environments heavily redistribute the snow cover, causing a small-scale pattern of highly variable snow depths. This has profound implications for the ground thermal regime, resulting in highly variable near-surface ground temperatures on the metre scale. Due to asymmetric snow distributions combined with the nonlinear insulating effect of snow, the spatial average ground temperature in a 1 km2 area cannot be determined based on the average snow cover for that area. Land surface or permafrost models employing a coarsely classified average snow depth will therefore not yield a realistic representation of ground temperatures. In this study we employ statistically derived snow distributions within 1 km2 grid cells as input to a regional permafrost model in order to represent sub-grid variability of ground temperatures. This improves the representation of both the average and the total range of ground temperatures. The model reproduces observed sub-grid ground temperature variations of up to 6 °C, and 98 % of borehole observations match the modelled temperature range. The mean modelled temperature of the grid cell reproduces the observations with an accuracy of 1.5 °C or better. The observed sub-grid variations in ground surface temperatures from two field sites are very well reproduced, with estimated fractions of sub-zero mean annual ground surface temperatures within &amp;amp;pm;10 %. We also find that snow distributions within areas of 1 km2 in Norwegian mountain environments are closer to a gamma than to a lognormal theoretical distribution. The modelled permafrost distribution seems to be more sensitive to the choice of distribution function than to the fine-tuning of the coefficient of variation. When incorporating the small-scale variation of snow, the modelled total permafrost area of mainland Norway is nearly twice as large compared to the area obtained with grid-cell average snow depths without a sub-grid approach.

Using Near-Surface Ground Temperature Data to Derive Snow Insulation and Melt Indices for Mountain Permafrost Applications

The timing and duration of snow cover in areas of mountain permafrost affect the ground thermal regime by thermally insulating the ground from the atmosphere and modifying the radiation balance at the surface. Snow depth records, however, are sparse in high-mountain terrains. Here, we present data processing techniques to approximate the thermal insulation effect of snow cover. We propose some simple ‘snow thermal insulation indices’ using daily and weekly variations in ground surface temperatures (GSTs), as well as a ‘snow melt index’ that approximates the snow melt rate using a degree-day approach with air temperature during the zero curtain period. The indices consider point-specific characteristics and allow the reconstruction of past snow thermal conditions and snow melt rates using long GST time series. The application of these indices to GST monitoring data from the Swiss Alps revealed large spatial and temporal variability in the start and duration of the high-insulation period by snow and in the snow melt rate. Copyright © 2016 John Wiley & Sons, Ltd.

An ecoregional assessment of freezing season air and ground surface temperature in the Mackenzie Valley corridor, NWT, Canada

Data from a network of air and ground surface temperature monitoring sites along a transect from the low arctic tundra to the taiga plains and the midboreal forest were utilized to explore latitudinal and temporal trends in various derived temperature indices. Parameters examined include air and ground surface mean annual temperatures, freezing degree-days, as well as freezing n-factors, and timing of the onset and completion of freezing at the ground surface. Temperature data show an N-S trend of about 0.75°C increase per degree of latitude in the air, while ground surface temperatures increase by 0.9°C per degree of latitude. Local ranges around the regional trend are between about ±1°C to ±2°C in the air and about ±2°C to ±6°C at the ground surface, with the range increasing northward for both sets of data.The appropriateness of using a common air-freezing index threshold value as an indicator of sufficient ground freezing for winter construction and transportation activities was investigated by determining the accumulated surface freezing degree-days (FDDS) on the date the air-freezing index reached 300 degree-days. This FDDS value was highly variable and in 20% of cases was less than 10. These low values reflect a slower rate of the active layer freeze-back, especially for more southerly study sites where the value of the freezing n-factor is low (0.1–0.3) and the active layer is thick (1–1.5m). In the north, analysis shows a substantial range in the freezing n-factor, the greatest range in active layer freeze-back and the highest range in near-surface ground temperatures, suggesting that a single air temperature index is perhaps not appropriate for all sites within the ecoregions examined.

Future permafrost conditions along environmental gradients in Zackenberg, Greenland

Abstract. The future development of ground temperatures in permafrost areas is determined by a number of factors varying on different spatial and temporal scales. For sound projections of impacts of permafrost thaw, scaling procedures are of paramount importance. We present numerical simulations of present and future ground temperatures at 10 m resolution for a 4 km long transect across the lower Zackenberg valley in northeast Greenland. The results are based on stepwise downscaling of future projections derived from general circulation model using observational data, snow redistribution modeling, remote sensing data and a ground thermal model. A comparison to in situ measurements of thaw depths at two CALM sites and near-surface ground temperatures at 17 sites suggests agreement within 0.10 m for the maximum thaw depth and 1 °C for annual average ground temperature. Until 2100, modeled ground temperatures at 10 m depth warm by about 5 °C and the active layer thickness increases by about 30%, in conjunction with a warming of average near-surface summer soil temperatures by 2 °C. While ground temperatures at 10 m depth remain below 0 °C until 2100 in all model grid cells, positive annual average temperatures are modeled at 1 m depth for a few years and grid cells at the end of this century. The ensemble of all 10 m model grid cells highlights the significant spatial variability of the ground thermal regime which is not accessible in traditional coarse-scale modeling approaches.

Ground temperature variations in a talus slope influenced by permafrost: a comparison of field observations and model simulations

Abstract. Variations in surface and near-surface ground temperatures (GST) dominate the evolution of the ground thermal regime over time and represent the upper boundary condition for the subsurface. Focusing on the Lapires talus slope in the south-western part of the Swiss Alps, which partly contains massive ground ice, and using a joint observational and modelling approach, this study compares and combines observed and simulated GST in the proximity of a borehole. The aim was to determine the applicability of the physically based subsurface model COUP to accurately reproduce spatially heterogeneous GST data and to enhance its reliability for long-term simulations. The reconstruction of GST variations revealed very promising results, even though two-dimensional processes like the convection within the coarse-blocky sediments close to the surface or ascending air circulation throughout the landform ("chimney effect") are not included in the model. For most simulations, the model bias revealed a distinct seasonal pattern mainly related to the simulation of the snow cover. The study shows that, by means of a detailed comparison of GST simulations with ground truth data, the calibration of the upper boundary conditions – which are crucial for modelling the subsurface – could be enhanced.

Cumulative Impacts and Feedbacks of a Gravel Road on Shrub Tundra Ecosystems in the Peel Plateau, Northwest Territories, Canada

Gravel highways in the continuous permafrost zone provide critical transportation links that are increasingly vulnerable to the impacts of climate warming and permafrost thaw. To examine if the physical effects associated with the construction, maintenance, and use of gravel roads alter vegetation and permafrost conditions, we measured vegetation, soils, and near-surface ground temperatures at tall and dwarf shrub tundra sites adjacent to and distant from the Dempster Highway in the Northwest Territories of Canada. We found that alder growth and recruitment were significantly enhanced adjacent to the highway. Where alder shrubs had formed closed canopies, we observed dramatic alterations to plant community composition, soil properties, and ground temperatures. Tall shrub sites adjacent to the road exhibited less understory vegetation, greater litter and organic layer thickness, higher nutrient availability, and thicker snowpack than all other site types. Our results show that in shrub tundra ecosystems the conditions generated by the maintenance and use of a gravel road can drive ecological feedbacks that magnify changes to vegetation communities and soils. We found that where the road facilitated shrub dominance, feedbacks were initiated that enhanced snow accumulation and altered ground temperatures and soil chemistry. In turn, these changes likely promoted enhanced shrub recruitment and growth. Shrub proliferation adjacent to highways is an important consideration for the planning and maintenance of this form of infrastructure. To improve our understanding of the spatial heterogeneity of shrub proliferation, research exploring the relationships between biophysical landscape features and shrub development is also needed.

Inferring snowpack ripening and melt-out from distributed measurements of near-surface ground temperatures

Abstract. Seasonal snow cover and its melt regime are heterogeneous both in time and space. Describing and modelling this variability is important because it affects diverse phenomena such as runoff, ground temperatures or slope movements. This study presents the derivation of melting characteristics based on spatial clusters of ground surface temperature (GST) measurements. Results are based on data from Switzerland where ground surface temperatures were measured with miniature loggers (iButtons) at 40 locations referred to as footprints. At each footprint, up to ten iButtons have been distributed randomly over an area of 10 m × 10 m, placed a few cm below the ground surface. Footprints span elevations of 2100–3300 m a.s.l. and slope angles of 0–55°, as well as diverse slope expositions and types of surface cover and ground material. Based on two years of temperature data, the basal ripening date and the melt-out date are determined for each iButton, aggregated to the footprint level and further analysed. The melt-out date could be derived for nearly all iButtons; the ripening date could be extracted for only approximately half of them because its detection based on GST requires ground freezing below the snowpack. The variability within a footprint is often considerable and one to three weeks difference between melting or ripening of the points in one footprint is not uncommon. The correlation of mean annual ground surface temperatures, ripening date and melt-out date is moderate, suggesting that these metrics are useful for model evaluation.