Despite a number of studies reporting glacier extent changes and their response to climate change over the eastern Tien Shan, glacier mass-balance changes over multiple decades are still not well reconstructed. Here, glacier mass budgets on the Karlik Range, easternmost Tien Shan during the time spans of 1972–2000 and 2000–2015 are quantified using digital elevation models reconstructed from topographic maps, SRTM X-band radar data and ASTER images. The results exhibit significant glacier mass loss in the Karlik Range for the two time spans, with a mean mass loss of −0.19 ± 0.08 m w.e. a−1 for the 1972–2000 period and −0.45 ± 0.17 m w.e. a−1 for the 2000–2015 period. The doubling of mass loss over the latter period suggests an acceleration of glacier mass loss in the early 21st century. The accelerated mass loss is associated with regional warming whereas the decline in annual precipitation is not significant.

The only complete inventory of New Zealand glaciers was based on aerial photography starting in 1978. While there have been partial updates using 2002 and 2009 satellite data, most glaciers are still represented by the 1978 outlines in contemporary global glacier databases. The objective of this project is to establish an updated glacier inventory for New Zealand. We have used Landsat 8 OLI satellite imagery from February and March 2016 for delineating clean glaciers using a semi-automatic band ratio method and debris-covered glaciers using a maximum likelihood classification. The outlines have been checked against Sentinel-2 MSI data, which have a higher resolution. Manual post processing was necessary due to misclassifications (e.g. lakes, clouds), mapping in shadowed areas, and combining the clean and debris-covered parts into single glaciers. New Zealand glaciers cover an area of 794 ± 34 km2 in 2016 with a debris-covered area of 10%. Of the 2918 glaciers, seven glaciers are >10 km2 while 71% is <0.1 km2. The debris cover on those largest glaciers is >40%. Only 15 glaciers are located on the North Island. For a selection of glaciers, we were able to calculate the area reduction between the 1978 and 2016 inventories.

Close-range (CR) L-band radiometry and quasi-simultaneous in situ snow characterizations were conducted in May 2019 at the Swiss Camp research site in the ablation zone of the western Greenland ice sheet. Snow liquid-water and its melt/refreeze are retrieved from microwave antenna temperatures measured with the ground-based L-band radiometer ELBARA-III. The emission model (EM) used in the retrieval is a two-layer configuration of the ‘L-Band Specific Microwave Emission Model of Layered Snowpack’. Consistent snow wetness retrievals were achieved from both single- and multi-angle CR observations of L-band antenna temperatures. This suggests that multi-angle observation is not a pre-requisite for snow wetness retrieval. Therefore, in addition to soil moisture and ocean salinity (SMOS) multi-angle measurements, snow wetness can be estimated from spaceborne L-band brightness temperatures measured at a single observation angle, such as from NASA's SMAP satellite. Our results provide partial validation of a recently presented snow wetness retrieval approach based on the same EM and applied over Greenland using multi-angle SMOS brightness temperatures. Agreement between measured CR antenna temperatures and SMOS brightness temperatures is found to be within the 95% confidence intervals of ELBARA-III and SMOS measurement uncertainties. Our measurements confirm the modeled response of antenna temperatures to diurnal variations of snow wetness.

In this study, our goal is to track internal ice layers on the Snow Radar data collected by NASA Operation IceBridge. We examine the application of deep learning methods on radar data gathered from polar regions. Artificial intelligence techniques have displayed impressive success in many practical fields. Deep neural networks owe their success to the availability of massive labeled data. However, in many real-world problems, even when a large dataset is available, deep learning methods have shown less success, due to causes such as lack of a large labeled dataset, presence of noise in the data or missing data. In our radar data, the presence of noise is one of the main obstacles in utilizing popular deep learning methods such as transfer learning. Our experiments show that if the neural network is trained to detect contours of objects in electro-optical imagery, it can only track a low percentage of contours in radar data. Fine-tuning and further training do not provide any better results. However, we show that selecting the right model and training it on the radar imagery from the start yields far better results.

Effective snow grain radius (re) is mapped at high resolution using near-infrared hyperspectral imaging (NIR-HSI). The NIR-HSI method can be used to quantify re spatial variability, change in re due to metamorphism, and visualize water percolation in the snowpack. Results are presented for three different laboratory-prepared snow samples (homogeneous, ice lens, fine grains over coarse grains), the sidewalls of which were imaged before and after melt induced by a solar lamp. The spectral reflectance in each ~3 mm pixel was inverted for re using the scaled band area of the ice absorption feature centered at 1030 nm, producing re maps consisting of 54 740 pixels. All snow samples exhibited grain coarsening post-melt as the result of wet snow metamorphism, which is quantified by the change in re distributions from pre- and post-melt images. The NIR-HSI method was compared to re retrievals from a field spectrometer and X-ray computed microtomography (micro-CT), resulting in the spectrometer having the same mean re and micro-CT having 23.9% higher mean re than the hyperspectral imager. As compact hyperspectral imagers become more widely available, this method may be a valuable tool for assessing re spatial variability and snow metamorphism in field and laboratory settings.

Observations of teleseismic earthquakes using broadband seismometers on the Ross Ice Shelf (RIS) must contend with environmental and structural processes that do not exist for land-sited seismometers. Important considerations are: (1) a broadband, multi-mode ambient wavefield excited by ocean gravity wave interactions with the ice shelf; (2) body wave reverberations produced by seismic impedance contrasts at the ice/water and water/seafloor interfaces and (3) decoupling of the solid Earth horizontal wavefield by the sub-shelf water column. We analyze seasonal and geographic variations in signal-to-noise ratios for teleseismic P-wave (0.5–2.0 s), S-wave (10–15 s) and surface wave (13–25 s) arrivals relative to the RIS noise field. We use ice and water layer reverberations generated by teleseismic P-waves to accurately estimate the sub-station thicknesses of these layers. We present observations consistent with the theoretically predicted transition of the water column from compressible to incompressible mechanics, relevant for vertically incident solid Earth waves with periods longer than 3 s. Finally, we observe symmetric-mode Lamb waves generated by teleseismic S-waves incident on the grounding zones. Despite their complexity, we conclude that teleseismic coda can be utilized for passive imaging of sub-shelf Earth structure, although longer deployments relative to conventional land-sited seismometers will be necessary to acquire adequate data.

Subglacial topography is an important feature in numerous ice-sheet analyses and can drive the routing of water at the bed. Bed topography is primarily measured with ice-penetrating radar. Significant gaps, however, remain in data coverage that require interpolation. Topographic interpolations are typically made with kriging, as well as with mass conservation, where ice flow dynamics are used to constrain bed geometry. However, these techniques generate bed topography that is unrealistically smooth at small scales, which biases subglacial water flowpath models and makes it difficult to rigorously quantify uncertainty in subglacial drainage patterns. To address this challenge, we adapt a geostatistical simulation method with probabilistic modeling to stochastically simulate bed topography such that the interpolated topography retains the spatial statistics of the ice-penetrating radar data. We use this method to simulate subglacial topography using mass conservation topography as a secondary constraint. We apply a water routing model to each of these realizations. Our results show that many of the flowpaths significantly change with each topographic realization, demonstrating that geostatistical simulation can be useful for assessing confidence in subglacial flowpaths.

The validity of any glaciological paleo proxy used to interpret climate records is based on the level of understanding of their transfer from the atmosphere into the ice sheet and their recording in the snowpack. Large spatial noise in snow properties is observed, as the wind constantly redistributes the deposited snow at the surface routed by the local topography. To increase the signal-to-noise ratio and getting a representative estimate of snow properties with respect to the high spatial variability, a large number of snow profiles is needed. However, the classical way of obtaining profiles via snow-pits is time and energy-consuming, and thus unfavourable for large surface sampling programs. In response, we present a dual-tube technique to sample the upper metre of the snowpack at a variable depth resolution with high efficiency. The developed device is robust and avoids contact with the samples by exhibiting two tubes attached alongside each other in order to (1) contain the snow core sample and (2) to access the bottom of the sample, respectively. We demonstrate the performance of the technique through two case studies in East Antarctica where we analysed the variability of water isotopes at a 100 m and 5 km spatial scales.

The Tibetan Plateau (TP) lakes are sensitive to climate change due to its seasonal ice cover, but few studies have paid attention to the freeze-thaw process of TP lakes and its key control parameters. By combining 216 simulation experiments using the LAKE2.0 model with the observations, we evaluated the effects of ice and snow albedo, ice (Kdi) and water (Kdw) extinction coefficients on the lake ice phenology, water temperature, sensible and latent heat fluxes. The reference experiment performs well in simulating the lake temperature, with a small positive bias increasing with depth, but it underestimates the ice thickness. The increase of ice albedo, snow albedo and Kdi induce a significant decrease in water temperature. Compared with the latent heat, the sensible heat flux is more sensitive to these three parameters. The ice thickness increases almost linearly with the increase of ice albedo but decreases with the increase of Kdi. The ice thickness and frozen days vary little with Kdw, but increasing Kdw can decrease the water temperature. Compared with the ice albedo, the Kdi and snow albedo have a large effect on the number of frozen days. This study brings to light the necessity to improve the parameterizations of the TP lakes freeze-thaw process.

Photogrammetric reconstructions of the Aldegondabreen glacier on Svalbard from 17 archival terrestrial oblique photographs taken in 1910 and 1911 reveal a past volume of 1373.7 ± 78.2 · 106 m3; almost five times greater than its volume in 2016. Comparisons to elevation data obtained from aerial and satellite imagery indicate a relatively unchanging volume loss rate of − 10.1 ± 1.6 · 106 m3 a−1 over the entire study period, while the rate of elevation change is increasing. At this rate of volume loss, the glacier may be almost non-existent within 30 years. If the changes of Aldegondabreen are regionally representative, it suggests that there was considerable ice loss over the entire 1900s for the low elevation glaciers of western Svalbard. The 1910/11 reconstruction was made from a few of the tens of thousands of archival terrestrial photographs from the early 1900s that cover most of Svalbard. Further analysis of this material would give insight into the recent history and future prospects of the archipelago's glaciers. Photogrammetric reconstructions of this kind of material require extensive manual processing to produce good results; for more extensive use of these archival imagery, a better processing workflow would be required.

The 2007–19 glaciological mass-balance series of Mera Glacier in the Everest Region, East Nepal, is reanalysed using the geodetic mass balance assessed by differencing two DEMs obtained from Pléiades stereo-images acquired in November 2012 and in October 2018. The glaciological glacier-wide annual mass balance of Mera Glacier has to be systematically decreased by 0.11 m w.e. a−1 to match the geodetic mass balance. We attribute part of the positive bias of the glaciological mass balance to an over-estimation of the accumulation above 5520 m a.s.l., likely due to a measurement network unable to capture its spatial variability. Over the period 2007–19, Mera Glacier has lost mass at a rate of −0.41 ± 0.20 m w.e. a−1, in general agreement with regional averages for the central Himalaya. We observe a succession of negative mass-balance years since 2013.

The surface spectral albedo was measured over coastal landfast sea ice in Prydz Bay (off Zhongshan Station), East Antarctica from 5 October to 26 November of 2016. The mean albedo decreased from late-spring to early-summer, mainly responding to the change in surface conditions from dry (phase I) to wet (phase II). The evolution of the albedo was strongly influenced by the surface conditions, with alternation of frequent snowfall events and katabatic wind that induce snow blowing at the surface. The two phases and day-to-day albedo variability were more pronounced in the near-infrared albedo wavelengths than in the visible ones, as the near-infrared photons are more sensitive to snow metamorphism, and to changes in the uppermost millimeters and water content of the surface. The albedo diurnal cycle during clear sky conditions was asymmetric with respect to noon, decreasing from morning to evening over full and patchy snow cover, and decreasing more rapidly in the morning over bare ice. We conclude that snow and ice metamorphism and surface melting dominated over the solar elevation angle dependency in shaping the albedo evolution. However, we realize that more detailed surface observations are needed to clarify and quantify the role of the various surface processes.

Spatio-temporal variability of the winter surface mass balance is a major uncertainty in the modelling of annual surface mass balance. Moreover, its measurement at high spatio-temporal resolution (sub-200 m) is very useful to force, calibrate or validate models. This study presents the results of year-round field campaigns to study the evolution of the surface mass balance in a ~2 km2 portion of the accumulation zone of the Mer de Glace (France). It is based on repeated LiDAR acquisitions, submergence-velocity measurements and meteorological records. The two methods used to quantify submergence velocities show good agreement. They present a linear temporal evolution without significant seasonal changes but display significant spatial variability. We conclude that a dense network of submergence velocity measurements is required to reduce the uncertainties when computing winter and annual surface mass balance from digital elevation model differencing. Finally, a hight spatio-temporal variability of the winter surface mass balance is highlighted (e.g., a std dev. of 0.92 m in April) even though the topography is homogeneous (std dev. of 25 m). Attempts to relate this variability to different morpho-topographic variables and wind-related indexes show the need for studies conducted at the snowfall event scale to obtain a better understanding of the variability in mass balance at the glacier scale.

Ice shelves restrain flow from the Greenland and Antarctic ice sheets. Climate-ocean warming could force thinning or collapse of floating ice shelves and subsequently accelerate flow, increase ice discharge and raise global mean sea levels. Petermann Glacier (PG), northwest Greenland, recently lost large sections of its ice shelf, but its response to total ice shelf loss in the future remains uncertain. Here, we use the ice flow model Úa to assess the sensitivity of PG to changes in ice shelf extent, and to estimate the resultant loss of grounded ice and contribution to sea level rise. Our results have shown that under several scenarios of ice shelf thinning and retreat, removal of the shelf will not contribute substantially to global mean sea level (<1 mm). We hypothesize that grounded ice loss was limited by the stabilization of the grounding line at a topographic high ~12 km inland of its current grounding line position. Further inland, the likelihood of a narrow fjord that slopes seawards suggests that PG is likely to remain insensitive to terminus changes in the near future.

Surface albedo typically dominates the mass balance of mountain glaciers, though long-term trends and patterns of glacier albedo are seldom explored. We calculated broadband shortwave albedo for glaciers in the central Chilean Andes (33–34°S) using end-of-summer Landsat scenes between 1986 and 2020. We found a high inter-annual variability of glacier-wide albedo that is largely a function of the glacier fractional snow-covered area and the total precipitation of the preceding hydrological year (up to 69% of the inter-annual variance explained). Under the 2010–2020 ‘Mega Drought’ period, the mean albedo, regionally averaged ranging from ~0.25–0.5, decreased by −0.05 on average relative to 1986–2009, with the greatest reduction occurring 3500–5000 m a.s.l. In 2020, differences relative to 1986–2009 were −0.14 on average as a result of near-complete absence of late summer snow cover and the driest hydrological year since the Landsat observation period began (~90% reduction of annual precipitation relative to the 1986–2009 period). We found statistically significant, negative trends in glacier ice albedo of up to −0.03 per decade, a trend that would have serious implications for the future water security of the region, because glacier ice melt acts to buffer streamflow shortages under severe drought conditions.

Rock debris covers ~30% of glacier ablation areas in the Central Himalaya and modifies the impact of atmospheric conditions on mass balance. The thermal properties of supraglacial debris are diurnally variable but remain poorly constrained for monsoon-influenced glaciers over the timescale of the ablation season. We measured vertical debris profile temperatures at 12 sites on four glaciers in the Everest region with debris thickness ranging from 0.08 to 2.8 m. Typically, the length of the ice ablation season beneath supraglacial debris was 160 days (15 May to 22 October)—a month longer than the monsoon season. Debris temperature gradients were approximately linear (r2 > 0.83), measured as −40°C m–1 where debris was up to 0.1 m thick, −20°C m–1 for debris 0.1–0.5 m thick, and −4°C m–1 for debris greater than 0.5 m thick. Our results demonstrate that the influence of supraglacial debris on the temperature of the underlying ice surface, and therefore melt, is stable at a seasonal timescale and can be estimated from near-surface temperature. These results have the potential to greatly improve the representation of ablation in calculations of debris-covered glacier mass balance and projections of their response to climate change.

Further to systematic experiments on the flexural strength of laboratory-grown, fresh water ice loaded cyclically, this paper describes results from new experiments of the same kind on lake ice harvested in Svalbard. The experiments were conducted at −12 °C, 0.1 Hz frequency and outer-fiber stress in the range from ~ 0.1 to ~ 0.7 MPa. The results suggest that the flexural strength increases linearly with stress amplitude, similar to the behavior of laboratory-grown ice.

Influenced by the Indian monsoon, the Kangri Karpo Mountains (KKM) of the southeastern Tibetan Plateau is the most humid part of the plateau, and one of the most important regions with numerous monsoon temperate glaciers. Glacier mass balance estimates have been strongly negative in the KKM over recent decades, but the spatiotemporal characteristics of surface velocity are poorly understood. Using phase-correlation feature tracking on Landsat images, this study estimates spatiotemporal variabilities of monsoon temperate glaciers for the period of 1988–2019. Results show that a significant slowdown was observed below an elevation of 4900 m, while an accelerated ice flow was found at an elevation of 4900–5800 m over the past 30 years. The trend of slowdown was −0.1 m a−1 dec−1 during 1988–2000, and then it increased to −0.5 m a−1 dec−1 during 2001–2019.