Search

Many glaciers on the Antarctic Peninsula have retreated and accelerated in recent decades. Here we show that there has been a widespread, quasi-synchronous, and sustained increase in grounding line discharge from glaciers on the west coast of the Antarctic Peninsula since 2018. Overall, the west Antarctic Peninsula discharge trends increased by over a factor of 3, from 50 Mtyr-2 during 2017 to 2020 up to 160 Mtyr-2 in the years following, leading to a 7.4 % increase in grounding line discharge since 2017. The acceleration in discharge was concentrated at glaciers connected to deep, cross-shelf troughs hosting warm-ocean waters, and the acceleration occurred during a period of anomalously high subsurface water temperatures on the continental shelf. Given that many of the affected glaciers have retreated over the past several decades in response to ocean warming, thereby highlighting their sensitivity to ocean forcing, we argue that the recent period of anomalously warm water was likely a key driver of the observed acceleration. However, the acceleration also occurred during a time of anomalously high atmospheric temperatures and glacier surface runoff, which could have contributed to speed-up by directly increasing basal water pressure and, by invigorating near-glacier ocean circulation, increasing submarine melt rates. The spatial pattern of glacier acceleration therefore provides an indication of glaciers that are exposed to warm-ocean water at depth and/or have active surface-to-bed hydrological connections; however, many stages in the chain of events leading to glacier acceleration, and how that response is affected by glacier-specific factors, remain insufficiently understood. Both atmospheric and ocean temperatures in this region and its surroundings are likely to increase further in the coming decades; therefore, there is a pressing need to improve our understanding of recent changes in Antarctic Peninsula glacier dynamics in response atmospheric and oceanic changes in order to improve projections of their behaviour over the coming century. [ABSTRACT FROM AUTHOR]

Snow water equivalent (SWE) is a key variable in climate and hydrology studies. Yet, current SWE products mask out high-topography areas due to the coarse resolution of the satellite sensors used. The snow remote sensing community is hence pushing towards active-microwave approaches for global SWE monitoring. Designing a SWE retrieval algorithm is not trivial, as multiple combinations of snow microstructure representations and SWE can yield the same radar signal. Retrieval algorithm designs are converging towards forward modeling approaches using an educated first guess on the snowpack structure. Snow highly varies in space and time, especially in mountain environments where the complex topography affects atmospheric and snowpack state variables in numerous ways. In Canada, automatic weather stations are too sparse, and high-resolution numerical weather prediction systems have a maximal resolution of 2.5 km × 2.5 km, which is too coarse to capture snow spatial variability in a complex topography. In this study, we designed a subgridding framework for the Canadian High Resolution Deterministic Prediction System (HRDPS). The native 2.5 km × 2.5 km resolution forecast was subgridded to a 100 m × 100 m resolution and used as the input for snow modeling over two winters in Glacier National Park, British Columbia, Canada. Air temperature, relative humidity, precipitation, and wind speed were first parameterized regarding elevation using six automatic weather stations. We then used Alpine3D to spatialize atmospheric parameters and radiation input accounting for terrain reflections, and we performed the snow simulations. We evaluated modeled snowpack state variables relevant for microwave remote sensing against simulated profiles generated with automatic weather station data and compared them to simulated profiles driven by raw HRDPS data. The subgridding framework improves the optical grain size bias by 18 % on average and the modeled SWE by 16 % compared to simulations driven with raw HRDPS forecasts. This work could improve the snowpack radar backscattering modeling by up to 7 dB and serves as a basis for SWE retrieval algorithms using forward modeling in a Bayesian framework. [ABSTRACT FROM AUTHOR]

This paper presents a method for determining the impact of dam reservoirs on the ice cover of rivers downstream of their locations based on a long measurement period (1950–2020) and synthetic-aperture radar (SAR) data. Two rivers and two sets of dam reservoirs located in the Carpathian Mountains (central Europe) were selected for this study. In order to estimate the influence of reservoirs, a logistic regression model was built to describe the relationship between the course of air temperature and the occurrence of ice cover (i.e., total ice cover and border ice) at water gauge cross sections upstream and downstream of the reservoirs. The influence of reservoirs was then defined as the differences between the number of days with ice cover predicted from air temperature and those observed at the water gauge cross sections. Additionally, the extent of the impact of the reservoirs was estimated based on SAR data (Sentinel-1) by identifying river sections downstream of the reservoirs on which total ice cover did not form despite the persistence of very low air temperatures. The study shows that dam reservoirs play an important role in decreasing the incidence of ice cover on rivers. The occurrence of ice cover as a result of reservoir operations could decrease by over 80 % in the sections immediately downstream of the reservoirs. The impact of the reservoir on river ice cover diminishes as the distance from the reservoir increases. Using SAR data, it was estimated that total ice cover did not form in sections 26–60 km downstream of the reservoirs, despite the presence of favorable thermal conditions. Based on the results of the study presented here, it can be assumed that in areas where many dam reservoirs are located, the ice regime of rivers is significantly transformed, which should be taken into account when studying river ice cover. This study also demonstrates that the logistic regression model and SAR data are useful tools for assessing the impact of dam reservoirs on river ice cover. [ABSTRACT FROM AUTHOR]

A detailed understanding of snow cover and its possible feedback on climate change on the Tibetan Plateau (TP) is of great importance. However, spatiotemporal variability in snow phenology (SP) and its influencing factors on the TP remain unclear. Based on the daily gap-free snow cover product (HMRFS-TP) with 500 m resolution, this study investigated the spatiotemporal variability in snow cover days (SCDs), snow onset date (SOD), and snow end date (SED) on the TP from 2002 to 2022. A structural equation model was used to quantify the direct and indirect effects of meteorological factors, geographical location, topography, and vegetation greenness on SP. The results indicate that the spatial distribution of SP on the TP was extremely uneven and exhibited temporal heterogeneity. SP showed vertical zonality influenced by elevation (longer SCD, earlier SOD, and later SED at higher elevations). A total of 4.62 % of the TP area had a significant decrease in SCDs, at a rate of -1.74 d yr -1. The SOD of 2.34 % of the TP area showed a significant delayed trend, at a rate of 2.90 d yr -1 , while the SED of 1.52 % of the TP area had a significant advanced trend, at a rate of at -2.49 d yr -1. We also found a strong elevation dependence for the trend in SCDs (R=-0.73). Air temperature, precipitation, wind speed, and shortwave radiation can directly affect SP as well as indirectly affect it by influencing the growth of vegetation, whereas the direct effect was much greater than the indirect effect. Geographical location (latitude and longitude) and topographic conditions (elevation and slope) indirectly affected SP by modulating meteorological conditions and the growth of vegetation. Vegetation primarily influences SP by intercepting the snow and regulating the balance of the solar radiation budget. Regarding the total effect, air temperature was found to be the dominant factor. This study contributes to the understanding of snow variation in response to global warming over the past 2 decades by providing a basis for predicting future environmental and climate changes and their impacts on the TP. [ABSTRACT FROM AUTHOR]

Glacial meltwater directly influences glacier dynamics. However, in the case of debris-covered glaciers, the drivers of glacier velocity and the influence of supraglacial lakes have not yet been sufficiently analysed and understood. We present a spatio-temporal analysis of key glacier characteristics for Baltoro Glacier in the Karakoram from October 2016 to September 2022 based on Earth observation data and climate parameters extracted from the High Asia Refined analysis (HAR) data set. For the glacier variables, we used surface velocity, supraglacial lake extent, melt of snow and ice, and proglacial run-off index. For climate variables, we focused on air temperature and precipitation. The surface velocity of Baltoro Glacier was characterized by a spring speed-up, summer peak, and fall speed-up with a relative increase in summer of 0.2–0.3 m d -1 (75 %–100 %) in relation to winter velocities, triggered by the onset of or an increase in basal sliding. Snow and ice melt have the largest impact on the spring speed-up, summer velocity peak, and the transition from inefficient to efficient subglacial drainage. The melt covered up to 64 % (353 km 2) of the entirety (debris-covered and debris-free) of Baltoro Glacier and reached up to 4700 m a.s.l. during the first melt peak and up to 5600 m a.s.l. during summer. The temporal delay between the initial peak of seasonal melt and the first relative velocity maximum decreases downglacier. Drainage from supraglacial lakes (3.6–5.9 km 2) contributed to the fall speed-up, which showed a 0.1–0.2 m d -1 (20 %–30 %) lower magnitude compared to the summer velocity peak. Most of the run-off can be attributed to the melt of snow and ice. However, from mid-June onward, the lakes play an increasing role, even though their contribution is estimated to be only about half of that of the melt. The observed increase in summer air temperatures leads to a greater extent of melt, as well as to a rise in the number and total area of supraglacial lakes. This tendency is expected to intensify in a future warming climate. [ABSTRACT FROM AUTHOR]

The ERA5 climate reanalysis dataset plays an important role in applications such as monitoring and modeling climate system changes in polar regions, so the calibration of the reanalysis to ground observations is of great relevance. Here, we compare the 2 m air temperature time series of the ERA5 reanalysis and the near-surface bias-corrected reanalysis to the near-ground air temperature measured at 17 automatic weather stations (AWSs) in the McMurdo Dry Valleys, Antarctica. We find that the reanalysis data have biases that change with the season of the year and do not clearly correlate with elevation. Our results show that future work should rely on secondary observations to calibrate when using the ERA5 reanalysis in polar regions. [ABSTRACT FROM AUTHOR]

The Sentinel-1A/B synthetic aperture radar (SAR) imagery archive between 14 October 2014 and 29 June 2023 was used in combination with a segmentation algorithm to create a series of binary ice/open-water maps of Hornsund fjord, Svalbard, at 50 m resolution for nine seasons (2014/15 to 2022/23). The near-daily (1.57 d mean temporal resolution) maps were used to calculate sea ice coverage for the entire fjord and its parts, namely the main basin and three major bays: Burgerbukta, Brepollen and Samarinvågen. The average length of the sea ice season was 158 d (range: 105–246 d). Drift ice first arrived from the southwest between October and March, and the fast-ice onset was on average 24 d later. The fast ice typically disappeared in June, around 20 d after the last day with drift ice. The average sea ice coverage over the sea ice season was 41 % (range: 23 %–56 %), but it was lower in the main basin (27 %) compared to in the bays (63 %). Of the bays, Samarinvågen had the highest sea ice coverage (69 %), likely due to its narrow opening and its location in southern Hornsund protecting it from the incoming wind-generated waves. Seasonally, the highest sea ice coverage was observed in April for the entire fjord and the bays and in March for the main basin. The 2014/15, 2019/20 and 2021/22 seasons were characterised by the highest sea ice coverage, and these were also the seasons with the largest number of negative air temperature days in October–December. The 2019/20 season was characterised by the lowest mean daily and monthly air temperatures. We observed a remarkable interannual variability in the sea ice coverage, but on a nine-season scale we did not record any gradual trend of decreasing sea ice coverage. These high-resolution data can be used to, e.g. better understand the spatiotemporal trends in the sea ice distribution in Hornsund, facilitate comparison between Svalbard fjords, and improve modelling of nearshore wind wave transformation and coastal erosion. [ABSTRACT FROM AUTHOR]

Beginning in December 2020, a series of small to medium, torrent-like pulses commenced upon a historic debris cone located within the Nupchu Valley, Kanchenjunga Conservation Area (KCA), Nepal. Sometime between 16 and 21 August 2022 a comparatively large ice-debris avalanche event occurred, covering an area of 0.6 km 2 with a total estimated volume of order 10 6 m 3. The area of the debris cone left by the August 2022 event increased the historic debris cone area by 0.2 km 2 (total area 0.6 km 2). Although no human or livestock deaths occurred, the increase in torrent-like pulses of debris upon this historic debris cone since 2020 exemplifies a style of mass movement that may become increasingly common as air temperatures rise in the region. Although the magnitude of this event was small compared to events like the 2021 Chamoli avalanche, the widespread distribution and frequency of comparable events present a substantial, and potentially increasing, hazard across High Mountain Asia. [ABSTRACT FROM AUTHOR]

Winter near-surface air temperatures have important implications for ecosystem functioning such as vegetation dynamics and carbon cycling. In cold environments, the persistence of seasonal snow cover can exert a strong control on the near-surface temperatures. However, the lack of in situ measurements of both snow cover duration and surface temperatures over high latitudes has made it difficult to estimate the spatio-temporal variability in this relationship. Here, we quantified the fine-scale variability in winter near-surface air temperatures (+2 cm) and snow cover duration (calculated from temperature time series) using a total of 441 microclimate loggers in seven study areas across boreal and tundra landscapes in Finland during 2019–2021. We further examined the drivers behind this variation using a structural equation model and the extent to which near-surface air temperatures are buffered from free-air temperatures during winter. Our results show that while average winter near-surface temperatures stay close to 0 ∘ C across the study domain, there are large differences in their fine-scale variability among the study areas. Areas with large topographical variation, as well as areas with shallow snowpacks, showed the greatest variation in near-surface temperatures and in snow cover duration. In the tundra, for example, differences in minimum near-surface temperatures between study sites were close to 30 ∘ C and topography was shown to be an important driver of this variability. In contrast, flat topography and long snow cover duration led to little spatial variation, as well as long periods of decoupling between near-surface and air temperatures. Quantifying and understanding the landscape-wide variation in winter microclimates improves our ability to predict the local effects of climate change in the rapidly warming boreal and tundra regions. [ABSTRACT FROM AUTHOR]

The Svalbard archipelago is particularly sensitive to climate change due to the relatively low altitude of its main ice fields and its geographical location in the higher North Atlantic, where the effect of Arctic amplification is more significant. The largest temperature increases have been observed during winter, but increasing summer temperatures, above the melting point, have led to increased glacier melt. Here, we evaluate the impact of this increased melt on the preservation of the oxygen isotope (δ18 O) signal in firn records. δ18 O is commonly used as a proxy for past atmospheric temperature reconstructions, and, when preserved, it is a crucial parameter to date and align ice cores. By comparing four different firn cores collected in 2012, 2015, 2017 and 2019 at the top of the Holtedahlfonna ice field (1100 m a.s.l.), we show a progressive deterioration of the isotope signal, and we link its degradation to the increased occurrence and intensity of melt events. Our findings indicate that, starting from 2015, there has been an escalation in melting and percolation resulting from changes in the overall atmospheric conditions. This has led to the deterioration of the climate signal preserved within the firn or ice. Our observations correspond with the model's calculations, demonstrating an increase in water percolation since 2014, potentially reaching deeper layers of the firn. Although the δ18 O signal still reflects the interannual temperature trend, more frequent melting events may in the future affect the interpretation of the isotopic signal, compromising the use of Svalbard ice cores. Our findings highlight the impact and the speed at which Arctic amplification is affecting Svalbard's cryosphere. [ABSTRACT FROM AUTHOR]

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

We compare the main atmospheric drivers of the melt season over the Greenland Ice Sheet (GrIS) in ERA5 and ERA-Interim (ERAI) in their overlapping period 1979–2018. In summer, ERA5 differs significantly from ERAI, especially in the melt regions. Small-scale ERA5 - ERAI differences near the ice sheet's margins and over steep slopes can be explained by the different resolution, while the large-scale differences indicate a different representation of physical processes in the two reanalyses: averaged over the lower parts of the GrIS, the mean near-surface air temperature is 1 K lower, while the mean downward shortwave radiation at the surface is on average 15 Wm-2 higher than in ERAI. Comparison with observational weather station data shows a significant warm bias in ERAI and, for ERA5, a significant positive bias in downward shortwave radiation. Consequently, methods that previously estimated the GrIS surface mass balance from the ERAI surface energy balance need to be carefully recalibrated before converting to ERA5 forcing. [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R2) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value -235 mm w.e. yr -1 (original) to -57 mm w.e. yr -1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature. [ABSTRACT FROM AUTHOR]

Winter warm air intrusions entering the Arctic region can strongly modify the microwave emission of the snow-covered sea ice system due to temperature-induced snow metamorphism and ice crust formations, e.g., after melt–refreeze events. Common microwave radiometer satellite sea ice concentration retrievals are based on empirical models using the snow-covered sea ice emissivity and thus can be influenced by strong warm air intrusions. Here, we carry out a long-term study analyzing 41 years of winter sea ice concentration observations from different algorithms to investigate the impact of warm air intrusions on the retrieved ice concentration. Our results show that three out of four algorithms underestimate the sea ice concentration during (and up to 10 d after) warm air intrusions which increase the 2 m air temperature (daily maximum) above - 5 ∘ C. This can lead to sea ice area underestimations in the order of 10 4 to 10 5 km 2. If the 2 m temperature during the warm air intrusions crosses - 2 ∘ C, all algorithms are impacted. Our analysis shows that the strength of these strong warm air intrusions increased in recent years, especially in April. With a further climate change, such warm air intrusions are expected to occur more frequently and earlier in the season, and their influence on sea ice climate data records will become more important. [ABSTRACT FROM AUTHOR]

We investigate sea ice conditions during the 2020 melt season, when warm air temperature anomalies in spring led to early melt onset, an extended melt season, and the second-lowest September minimum Arctic ice extent observed. We focus on the region of the most persistent ice cover and examine melt pond depth retrieved from Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) using two distinct algorithms in concert with a time series of melt pond fraction and ice concentration derived from Sentinel-2 imagery to obtain insights about the melting ice surface in three dimensions. We find the melt pond fraction derived from Sentinel-2 in the study region increased rapidly in June, with the mean melt pond fraction peaking at 16 % ± 6 % on 24 June 2020, followed by a slow decrease to 8 % ± 6 % by 3 July, and remained below 10 % for the remainder of the season through 15 September. Sea ice concentration was consistently high (>95 %) at the beginning of the melt season until 4 July, and as floes disintegrated, it decreased to a minimum of 70 % on 30 July and then became more variable, ranging from 75 % to 90 % for the remainder of the melt season. Pond depth increased steadily from a median depth of 0.40 m ± 0.17 m in early June and peaked at 0.97 m ± 0.51 m on 16 July, even as melt pond fraction had already started to decrease. Our results demonstrate that by combining high-resolution passive and active remote sensing we now have the ability to track evolving melt conditions and observe changes in the sea ice cover throughout the summer season. [ABSTRACT FROM AUTHOR]

Deglaciation in Svalbard was followed by seawater ingression and deposition of marine (deltaic) sediments in fjord valleys, while elastic rebound resulted in fast land uplift and the exposure of these sediments to the atmosphere, whereby the formation of epigenetic permafrost was initiated. This was then followed by the accumulation of aeolian sediments, with syngenetic permafrost formation. Permafrost was studied in the eastern Adventdalen valley, Svalbard, 3–4 km from the maximum up-valley reach of post-deglaciation seawater ingression, and its ground ice was analysed for its chemistry. While ground ice in the syngenetic part is basically fresh, the epigenetic part has a frozen freshwater–saline water interface (FSI), with chloride concentrations increasing from the top of the epigenetic part (at 5.5 m depth) to about 15 % that of seawater at 11 m depth. We applied a one-dimensional freezing model to examine the rate of top-down permafrost formation, which could be accommodated by the observed frozen FSI. The model examined permafrost development under different scenarios of mean average air temperature, water freezing temperature and degree of pore-water freezing. We found that even at the relatively high air temperatures of the Early to mid-Holocene, permafrost could aggrade quite fast down to 20 to 37 m (the whole sediment fill of 25 m at this location) within 200 years. This, in turn, allowed freezing and preservation of the freshwater–saline water interface despite the relatively fast rebound rate, which apparently resulted in an increase in topographic gradients toward the sea. The permafrost aggradation rate could also be enhanced due to non-complete pore-water freezing. We conclude that freezing must have started immediately after the exposure of the marine sediment to atmospheric conditions. [ABSTRACT FROM AUTHOR]

The acceleration of climate warming has led to a faster solid–liquid water cycle and a decrease in solid water storage in cold regions of the Earth. Although snowfall is the most critical input for the cryosphere, the phenology of snowfall, or potential snowfall phenology (PSP), has not been thoroughly studied, and there is a lack of indicators for PSP. For this reason, we have proposed three innovative indicators, namely, the start of potential snowfall season (SPSS), the end of potential snowfall season (EPSS), and the length of potential snowfall season (LPSS), to characterize the PSP. We then explored the spatial–temporal variation in all three PSP indicators in the past, present, and future across the Chinese Tianshan mountainous region (CTMR) based on the observed daily air temperature from 26 meteorological stations during 1961–2017/2020 combined with data from 14 models from CMIP6 (Phase 6 of the Coupled Model Intercomparison Project) under four different scenarios (SSP126, SSP245, SSP370, and SSP585, where SSP represents Shared Socioeconomic Pathway) during 2021–2100. The study showed that the SPSS, EPSS, and LPSS indicators could accurately describe the PSP characteristics across the study area. In the past and present, the potential snowfall season started on 2 November, ended on 18 March, and lasted for about 4.5 months across the CTMR on average. During 1961–2017/2020, the rate of advancing the EPSS (-1.6 d per decade) was faster than that of postponing the SPSS (1.2 d per decade). It was also found that there was a significant delay in the starting time (2–13 d) and advancement in the ending time (1–13 d), respectively, resulting in a reduction of 3–26 d for the LPSS. The potential snowfall season started earlier, ended later, and lasted longer in the north and center compared with the south. Similarly, the SPSS, EPSS, and LPSS indicators are also expected to vary under the four emission scenarios during 2021–2100. Under the highest emission scenario, SSP585, the starting time is expected to be postponed by up to 41 d, while the ending time is expected to be advanced by up to 23 d across the study area. This change is expected to reduce the length of the potential snowfall season by up to 61 d (about 2 months), and the length of the potential snowfall season will only last 2.5 months in the 2100s under the SSP585 scenario. The length of the potential snowfall season in the west and southwest of the CTMR will be compressed by more days due to a more delayed starting time and an advanced ending time under all four scenarios. This suggests that, with constant snowfall intensity, annual total snowfall may decrease, including the amount and frequency, leading to a reduction in snow cover or mass, which will ultimately contribute to more rapid warming through the lower reflectivity to solar radiation. This research provides new insights into capturing the potential snowfall phenology in the alpine region and can be easily extended to other snow-dominated areas worldwide. It can also help inform snowfall monitoring and early warning for solid water resources. [ABSTRACT FROM AUTHOR]

Coastal polynyas around the Antarctic continent are regions of very strong ocean–atmosphere heat and moisture exchange that are important for local and regional weather, sea ice production, and water mass formation. Due to extreme atmospheric conditions (very strong offshore winds, low air temperature, as well as humidity) the surface ocean layer in polynyas is highly turbulent, with mixing due to combined Langmuir, wind-induced, and buoyancy-driven turbulence. One of the visible signs of complex interactions between the mixed-layer dynamics and the forming sea ice are frazil streaks, elongated patches of high ice concentration separated by areas of open water. In spite of their ubiquity, observational and modelling analyses of frazil streaks have been very limited largely due to the fact that their significance for heat flux and ice production is only just becoming apparent. In this study, the first comprehensive analysis of the spatial variability of surface frazil concentration is performed for the Terra Nova Bay Polynya (TNBP). Frazil streaks are identified in high-resolution (pixel size 10–15 m) visible satellite imagery, and their properties (surface area, width, spacing, and orientation) are linked to the meteorological forcing (wind speed and air temperature). This provides a simple statistical tool for estimating the extent and ice coverage of the region of high ice production under given meteorological conditions. It is also shown that the orientation of narrow streaks tends to agree with the wind direction, suggesting the dominating role of the local wind forcing in their formation. Very wide streaks, in turn, deviate from that pattern, as they are presumably influenced by several additional factors, including local water circulation and the associated convergence zones. An analysis of peak wavelengths and directions determined from the images, compared to analogous open-water wavelengths computed with a spectral wave model, demonstrates a significant slow-down in the observed wave growth in TNBP. This suggests an important role of frazil streaks in modifying wind-wave growth and/or dissipation in polynyas. [ABSTRACT FROM AUTHOR]

Temperature-index models have been widely used for glacier-mass projections spanning the 21st century. The ability of temperature-index models to capture non-linear responses of glacier surface mass balance (SMB) to high deviations in air temperature and solid precipitation was recently discussed in the context of mass-balance simulations employing advanced machine-learning techniques. Here, we performed numerical experiments with a classic temperature-index model and confirmed that such models are capable of detecting non-linear responses of glacier SMB to temperature and precipitation changes. Non-linearities derive from the change in the degree-day factor over the ablation season and from the lengthening of the ablation season. [ABSTRACT FROM AUTHOR]

Palsas and peat plateaus are expected to disappear from many regions, including Finnish Lapland. However, detailed long-term monitoring data of the degradation process on palsas are scarce. Here, we present the results of the aerial photography time series analysis (1959–2021), annual real-time kinematic (RTK) GNSS and active layer monitoring (2007–2021), and annual unoccupied aerial system surveys (2016–2021) at two palsa sites (Peera and Laassaniemi, 68 ∘ N) located in north-west Finland. We analysed temporal trends of palsa degradation and their relation to climate using linear regression. At both sites, the decrease in palsa area by -77 % to -90 % since 1959 and height by -16 % to -49 % since 2007 indicate substantial permafrost degradation throughout the study periods. The area loss rates are mainly connected to winter air temperature changes at Peera and winter precipitation changes at Laassaniemi. The active layer thickness (ALT) has varied annually between 2007 and 2021 with no significant trend and is related mainly to the number of very warm days during summer, autumn rainfall of previous year, and snow depths at Peera. At Laassaniemi, the ALT is weakly related to climate and has been decreasing in the middle part of the palsa during the past 8 years despite the continuous decrease in palsa volume. Our findings imply that the ALT in the inner parts of palsas do not necessarily reflect the overall permafrost conditions and underline the importance of surface position monitoring alongside the active layer measurements. The results also showed a negative relationship between the ALT and snow cover onset, indicating the complexity of climate–permafrost feedbacks in palsa mires. [ABSTRACT FROM AUTHOR]

Ice caves are one of the least studied parts of the cryosphere, particularly those located in inaccessible permafrost areas at high altitudes or high latitudes. We characterize the climate dynamics and the geomorphological features of Devaux cave, an outstanding ice cave in the Central Pyrenees on the French–Spanish border. Two distinct cave sectors were identified based on air temperature and geomorphological observations. The first one comprises well-ventilated galleries with large temperature oscillations likely influenced by a cave river. The second sector corresponds to more isolated chambers, where air and rock temperatures stay below 0 ∘ C throughout the year. Seasonal layered ice and hoarfrost occupy the first sector, while transparent, massive perennial ice is present in the isolated chambers. Cryogenic calcite and gypsum are mainly present within the perennial ice. During winter, the cave river freezes at the outlet, resulting in a damming and backflooding of the cave. We suggest that relict ice formations record past damming events with the subsequent formation of congelation ice. δ34 S values of gypsum indicate that the sulfate originated from the oxidation of pyrite present in the bedrock. Several features including air and rock temperatures, the absence of drips, the small loss of ice in the past 7 decades, and the location of ice bodies in the cave indicate that the cave permafrost is the result of a combination of undercooling by ventilation and diffusive heat transfer from the surrounding permafrost, reaching a thickness of ∼ 200 m. [ABSTRACT FROM AUTHOR]

Northern peatlands cover approximately four million km 2 , and about half of these peatlands are estimated to contain permafrost and periglacial landforms, like palsas and peat plateaus. In northeastern Canada, peatland permafrost is predicted to be concentrated in the western interior of Labrador but is assumed to be largely absent along the Labrador Sea coastline. However, the paucity of observations of peatland permafrost in the interior, coupled with traditional and ongoing use of perennially frozen peatlands along the coast by Labrador Inuit and Innu, suggests a need for re-evaluation of the reliability of existing peatland permafrost distribution estimates for the region. In this study, we develop a multi-stage consensus-based point inventory of peatland permafrost complexes in coastal Labrador and adjacent parts of Quebec using high-resolution satellite imagery, and we validate it with extensive field visits and low-altitude aerial photography and videography. A subset of 2092 wetland complexes that potentially contained peatland permafrost were inventoried, of which 1119 were classified as likely containing peatland permafrost. Likely peatland permafrost complexes were mostly found in lowlands within 22 km of the coastline, where mean annual air temperatures often exceed +1 ∘ C. A clear gradient in peatland permafrost distribution exists from the outer coasts, where peatland permafrost is more abundant, to inland peatlands, where permafrost is generally absent. This coastal gradient may be attributed to a combination of climatic and geomorphological influences which lead to lower insolation, thinner snowpacks, and poorly drained, frost-susceptible materials along the coast. The results of this study suggest that existing estimates of permafrost distribution for southeastern Labrador require adjustments to better reflect the abundance of peatland permafrost complexes to the south of the regional sporadic discontinuous permafrost limit. This study constitutes the first dedicated peatland permafrost inventory for Labrador and provides an important baseline for future mapping, modelling, and climate change adaptation strategy development in the region. [ABSTRACT FROM AUTHOR]

Meltwater from mountainous catchments dominated by snow and ice is a valuable source of fresh water in many regions. At mid-latitudes, seasonal snow cover and glaciers act like a natural reservoir by storing precipitation during winter and releasing it in spring and summer. Snowmelt is usually modelled either by energy balance or by temperature-index approaches. The energy balance approach is process-based and more sophisticated but requires extensive input data, while the temperature-index approach uses the degree-day factor (DDF) as a key parameter to estimate melt of snow and ice merely from air temperature. Despite its simplicity, the temperature-index approach has proved to be a powerful tool for simulating the melt process especially in large and data-scarce catchments. The present study attempts to quantify the effects of spatial, temporal, and climatic conditions on the DDF of snow in order to gain a better understanding of which influencing factors are decisive under which conditions. The analysis is based on the individual energy flux components; however, formulas for estimating the DDF are presented to account for situations where observed data are limited. A detailed comparison between field-derived and estimated DDF values yields a fair agreement with bias = 0.14 mm ∘ C -1 d -1 and root mean square error (RMSE) = 1.12 mm ∘ C -1 d -1. The analysis of the energy balance processes controlling snowmelt indicates that cloud cover and snow albedo under clear sky are the most decisive factors for estimating the DDF of snow. The results of this study further underline that the DDF changes as the melt season progresses and thus also with altitude, since melting conditions arrive later at higher elevations. A brief analysis of the DDF under the influence of climate change shows that the DDFs are expected to decrease when comparing periods of similar degree days, as melt will occur earlier in the year when solar radiation is lower, and albedo is then likely to be higher. Therefore, the DDF cannot be treated as a constant parameter especially when using temperature-index models for forecasting present or predicting future water availability. [ABSTRACT FROM AUTHOR]

Several studies identified heterogeneous glacier mass changes in western High Mountain Asia over the last decades. Causes for these mass change patterns are still not fully understood. Modelling the physical interactions between glacier surface and atmosphere over several decades can provide insight into relevant processes. Such model applications, however, have data needs which are usually not met in these data-scarce regions. Exceptionally detailed glaciological and meteorological data exist for the Abramov Glacier in the Pamir Alay range. In this study, we use weather station measurements in combination with downscaled reanalysis data to force a coupled surface energy balance–multilayer subsurface model for Abramov Glacier for 52 years. Available in situ data are used for model calibration and validation. We find an overall negative mass balance of - 0.27 mw.e.a-1 for 1968/1969–2019/2020 and a loss of firn pore space causing a reduction of internal accumulation. Despite increasing air temperatures, we do not find an acceleration of glacier-wide mass loss over time. Such an acceleration is compensated for by increasing precipitation rates (+0.0022 mw.e.a-1 , significant at a 90 % confidence level). Our results indicate a significant correlation between annual mass balance and precipitation (R2 = 0.72). [ABSTRACT FROM AUTHOR]

The thermal regime of glaciers and ice caps represents the internal distribution of ice temperatures. An accurate knowledge of the thermal regime of glaciers and ice caps is important to understand their dynamics and response to climate change and to model their evolution. Although the assumption is that most ice masses in the Tien Shan are polythermal, this has not been examined in appropriate detail so far. In this research, we investigate the thermal regime of the Grigoriev ice cap and the Sary-Tor glacier, both located in the inner Tien Shan in Kyrgyzstan, using a 3D higher-order thermomechanical ice flow model. Input data and boundary conditions are inferred from a surface energy mass balance model, a historical air temperature and precipitation series, ice thickness measurements and reconstructions, and digital elevation models. Calibration and validation of the englacial temperatures are performed using historical borehole measurements on the Grigoriev ice cap and radar measurements for the Sary-Tor glacier. The results of this study reveal a polythermal structure of the Sary-Tor glacier and a cold structure of the Grigoriev ice cap. The difference is related to the larger amount of snow (insulation) and refreezing meltwater (release of latent heat) for the Sary-Tor glacier, resulting in higher surface layer temperature, especially in the accumulation area, which is subsequently advected downstream. Further, ice velocities are much lower for the Grigoriev ice cap, with consequent lower horizontal advection rates. A detailed analysis concerning the influence of temperature and precipitation changes at the surface reveals that the thermal structure of both ice bodies is not constant over time, with recent climate change causing increasing ice temperatures in higher areas. The selected ice masses are representative examples of the (inner) Tien Shan glaciers and ice caps. Therefore, our findings and the calibrated parameters can be generalised, allowing improved understanding of the dynamics and future evolution of other glaciers and ice caps in the region. [ABSTRACT FROM AUTHOR]

Regional climate models (RCMs) and reanalysis datasets provide valuable information for assessing the vulnerability of ice shelves to collapse over Antarctica, which is important for future global sea level rise estimates. Within this context, this paper examines variability in snowfall, near-surface air temperature and melt across products from the Met Office Unified Model (MetUM), Regional Atmospheric Climate Model (RACMO) and Modèle Atmosphérique Régional (MAR) RCMs, as well as the ERA-Interim and ERA5 reanalysis datasets. Seasonal and trend decomposition using LOESS (STL) is applied to split the monthly time series at each model grid cell into trend, seasonal and residual components. Significant systematic differences between outputs are shown for all variables in the mean and in the seasonal and residual standard deviations, occurring at both large and fine spatial scales across Antarctica. Results imply that differences in the atmospheric dynamics, parametrisation, tuning and surface schemes between models together contribute more significantly to large-scale variability than differences in the driving data, resolution, domain specification, ice sheet mask, digital elevation model and boundary conditions. Despite significant systematic differences, high temporal correlations are found for snowfall and near-surface air temperature across all products at fine spatial scales. For melt, only moderate correlation exists at fine spatial scales between different RCMs and low correlation between RCM and reanalysis outputs. Root mean square deviations (RMSDs) between all outputs in the monthly time series for each variable are shown to be significant at fine spatial scales relative to the magnitude of annual deviations. Correcting for systematic differences results in significant reductions in RMSDs, suggesting the importance of observations and further development of bias-correction techniques. [ABSTRACT FROM AUTHOR]

Ice caves are, similar to mountain glaciers, threatened by the warming climate. To better understand the response of perennial ice in caves to a changing climate, we analysed the thermal characteristics of a sag-type ice cave in the Austrian Alps (Hundsalm ice cave), based on long-term temperature measurements for the period 2008–2021. Observations show a warming trend in all parts of the cave as well as a distinct seasonal pattern with two main regimes, i.e. an open (winter) and a closed (summer) period. During the closed period, a persistent stable stratification prevails that largely decouples the cave from the external atmosphere. The open period is characterised by unstable to neutral stratification, which is an effect of convection during episodes when cold air can penetrate into the cave. Criteria to detect corresponding periods are investigated. Vertical temperature profiles also provide hints on corresponding circulation patterns and the spatial temperature variability in the cave. The positive air temperature trend is reflected in a decrease in perennial cave ice, derived from stake measurements. Besides surface melting, we find compelling evidence of basal melting of ice. The observed ablation rates can be well reproduced by applying a modified degree-day model, which, however, is less feasible regarding mass balance. Overall, we conclude that Hundsalm ice cave is highly impacted by regional warming, which will lead to the disappearance of its perennial ice deposits within the next decades. [ABSTRACT FROM AUTHOR]

Clouds are an important component of the climate system, yet our understanding of how they directly and indirectly affect glacier melt in different climates is incomplete. Here we analyse high-quality datasets from 16 mountain glaciers in diverse climates around the globe to better understand how relationships between clouds and near-surface meteorology, radiation and surface energy balance vary. The seasonal cycle of cloud frequency varies markedly between mountain glacier sites. During the main melt season at each site, an increase in cloud cover is associated with increased vapour pressure and relative humidity, but relationships to wind speed are site specific. At colder sites (average near-surface air temperature in the melt season <0 ∘ C), air temperature generally increases with increasing cloudiness, while for warmer sites (average near-surface air temperature in the melt season ≫0 ∘ C), air temperature decreases with increasing cloudiness. At all sites, surface melt is more frequent in cloudy compared to clear-sky conditions. The proportion of melt from temperature-dependent energy fluxes (incoming longwave radiation, turbulent sensible heat and latent heat) also universally increases in cloudy conditions. However, cloud cover does not affect daily total melt in a universal way, with some sites showing increased melt energy during cloudy conditions and others decreased melt energy. The complex association of clouds with melt energy is not amenable to simple relationships due to many interacting physical processes (direct radiative forcing; surface albedo; and co-variance with temperature, humidity and wind) but is most closely related to the effect of clouds on net radiation. These results motivate the use of physics-based surface energy balance models for representing glacier–climate relationships in regional- and global-scale assessments of glacier response to climate change. [ABSTRACT FROM AUTHOR]

Glacier mass balance models are needed at sites with scarce long-term observations to reconstruct past glacier mass balance and assess its sensitivity to future climate change. In this study, North American Regional Reanalysis (NARR) data were used to force a physically based, distributed glacier mass balance model of Saskatchewan Glacier for the historical period 1979–2016 and assess its sensitivity to climate change. A 2-year record (2014–2016) from an on-glacier automatic weather station (AWS) and historical precipitation records from nearby permanent weather stations were used to downscale air temperature, relative humidity, wind speed, incoming solar radiation and precipitation from the NARR to the station sites. The model was run with fixed (1979, 2010) and time-varying (dynamic) geometry using a multitemporal digital elevation model dataset. The model showed a good performance against recent (2012–2016) direct glaciological mass balance observations as well as with cumulative geodetic mass balance estimates. The simulated mass balance was not very sensitive to the NARR spatial interpolation method, as long as station data were used for bias correction. The simulated mass balance was however sensitive to the biases in NARR precipitation and air temperature, as well as to the prescribed precipitation lapse rate and ice aerodynamic roughness lengths, showing the importance of constraining these two parameters with ancillary data. The glacier-wide simulated energy balance regime showed a large contribution (57 %) of turbulent (sensible and latent) heat fluxes to melting in summer, higher than typical mid-latitude glaciers in continental climates, which reflects the local humid "icefield weather" of the Columbia Icefield. The static mass balance sensitivity to climate was assessed for prescribed changes in regional mean air temperature between 0 and 7 ∘ C and precipitation between -20 % and + 20 %, which comprise the spread of ensemble Representative Concentration Pathway (RCP) climate scenarios for the mid (2041–2070) and late (2071–2100) 21st century. The climate sensitivity experiments showed that future changes in precipitation would have a small impact on glacier mass balance, while the temperature sensitivity increases with warming, from -0.65 to -0.93 m w.e. a -1 ∘ C -1. The mass balance response to warming was driven by a positive albedo feedback (44 %), followed by direct atmospheric warming impacts (24 %), a positive air humidity feedback (22 %) and a positive precipitation phase feedback (10 %). Our study underlines the key role of albedo and air humidity in modulating the response of winter-accumulation type mountain glaciers and upland icefield-outlet glacier settings to climate. [ABSTRACT FROM AUTHOR]

Remote sensing data are a crucial tool for monitoring climatological changes and glacier response in areas inaccessible for in situ measurements. The Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product provides temperature data for remote glaciated areas where air temperature measurements from weather stations are sparse or absent, such as the St. Elias Mountains (Yukon, Canada). However, MODIS LSTs in the St. Elias Mountains have been found in prior studies to show an offset from available weather station measurements, the source of which is unknown. Here, we show that the MODIS offset likely results from the occurrence of near-surface temperature inversions rather than from the MODIS sensor's large footprint size or from poorly constrained snow emissivity values used in LST calculations. We find that an offset in remote sensing temperatures is present not only in MODIS LST products but also in Advanced Spaceborne Thermal Emissions Radiometer (ASTER) and Landsat temperature products, both of which have a much smaller footprint (90–120 m) than MODIS (1 km). In all three datasets, the offset was most pronounced in the winter (mean offset >8 ∘C) and least pronounced in the spring and summer (mean offset <2 ∘C). We also find this enhanced seasonal offset in MODIS brightness temperatures, before the incorporation of snow surface emissivity into the LST calculation. Finally, we find the MODIS LST offset to be consistent in magnitude and seasonal distribution with modeled temperature inversions and to be most pronounced under conditions that facilitate near-surface inversions, namely low incoming solar radiation and wind speeds, at study sites Icefield Divide (60.68 ∘ N, 139.78 ∘ W; 2,603 m a.s.l) and Eclipse Icefield (60.84 ∘ N, 139.84 ∘ W; 3017 m a.s.l.). Although these results do not preclude errors in the MODIS sensor or LST algorithm, they demonstrate that efforts to convert MODIS LSTs to an air temperature measurement should focus on understanding near-surface physical processes. In the absence of a conversion from surface to air temperature based on physical principles, we apply a statistical conversion, enabling the use of mean annual MODIS LSTs to qualitatively and quantitatively examine temperatures in the St. Elias Mountains and their relationship to melt and mass balance. [ABSTRACT FROM AUTHOR]

Greenland ice sheet surface runoff is drained through supraglacial stream networks. This evacuation influences surface mass balance as well as ice dynamics. However, in situ observations of meltwater discharge through these stream networks are rare. In this study, we present 46 discrete discharge measurements and continuous water level measurements for 62 d spanning the majority of of the melt season (13 June to 13 August) in 2016 for a 0.6 km 2 supraglacial stream catchment in southwest Greenland. The result is an unprecedentedly long record of supraglacial discharge that captures both diurnal variability and changes over the melt season. A comparison of surface energy fluxes to stream discharge reveals shortwave radiation as the primary driver of melting. However, during high-melt episodes, the contribution of shortwave radiation to melt energy is reduced by ∼40 % (from 1.13 to 0.73 proportion). Instead, the relative contribution of longwave radiation, sensible heat fluxes, and latent heat fluxes to overall melt increases by ∼24 %, 6 %, and 10 % (proportion increased from -0.32 to -0.08 , 0.28 to 0.34, and -0.04 to 0.06) respectively. Our data also identify that the timing of daily maximum discharge during clear-sky days shifts from 16:00 local time (i.e., 2 h 45 min after solar noon) in late June to 14:00 in late July and then rapidly returns to 16:00 in early August. The change in the timing of daily maximum discharge could be attributed to the expansion and contraction of the stream network, caused by skin temperatures that likely fell below freezing at night. The abrupt shift, in early August, in the timing of daily maximum discharge coincides with a drop in air temperature, a drop in the amount of water temporarily stored in weathering crust, and a decreasing covariance between stream velocity and discharge. Further work is needed to investigate if these results can be transferable to larger catchments and uncover if rapid shifts in the timing of peak discharge are widespread across Greenland supraglacial streams and thus have an impact on meltwater delivery to the subglacial system and ice dynamics. [ABSTRACT FROM AUTHOR]

On 22 March 2021, an approximately 50 Mm 3 ice-rock avalanche occurred from 6500 m a.s.l. in the Sedongpu basin, southeastern Tibet. The avalanche transformed into a highly mobile mass flow which temporarily blocked the Yarlung Tsangpo river. The avalanche flow lasted ∼ 5 min and produced substantial geomorphological reworking. This event, and previous ones from the basin, occurred concurrently with, or shortly after, positive seasonal air temperature anomalies. The occurrence of future large mass flows from the basin cannot be ruled out, and their impacts must be carefully considered given implications for sustainable hydropower and associated socioeconomic development in the region. [ABSTRACT FROM AUTHOR]

The regulating role of glaciers in catchment run-off is of fundamental importance in sustaining people living in low-lying areas. The reduction in glacierized areas under the effect of climate change disrupts the distribution and amount of run-off, threatening water supply, agriculture and hydropower. The prediction of these changes requires models that integrate hydrological, nivological and glaciological processes. In this work we propose a local model that combines the nivological and glaciological scales. The model describes the formation and evolution of the snowpack and the firn below it, under the influence of temperature, wind speed and precipitation. The model has been implemented in two versions: (1) a multi-layer one that considers separately each firn layer and (2) a single-layer one that models firn and underlying glacier ice as a single layer. The model was applied at the site of Colle Gnifetti (Monte Rosa massif, 4400–4550 ma.s.l.). We obtained an average reduction in annual snow accumulation due to wind erosion of 2×103 kgm-2yr-1 to be compared with a mean annual precipitation of about 2.7×103 kgm-2yr-1. The conserved accumulation is made up mainly of snow deposited between April and September, when temperatures above the melting point are also observed. End-of-year snow density, instead, increased an average of 65 kgm-3 when the contribution of wind to snow compaction was added. Observations show a high spatial and interannual variability in the characteristics of snow and firn at the site and a correlation of net balance with radiation and the number of melt layers. The computation of snowmelt in the model as a sole function of air temperature may therefore be one of the reasons for the observed mismatch between model and observations. [ABSTRACT FROM AUTHOR]

The phenomenon in which the warming rate of air temperature is amplified with elevation is termed elevation-dependent warming (EDW). It has been clarified that EDW can accelerate the retreat of glaciers and melting of snow, which can have significant impacts on the regional ecological environment. Owing to the lack of high-density ground observations in high mountains, there is widespread controversy regarding the existence of EDW. Current evidence is mainly derived from typical high-mountain regions such as the Swiss Alps, the Colorado Rocky Mountains, the tropical Andes and the Tibetan Plateau–Himalayas. Rare evidence in other mountain ranges has been reported, especially in arid regions. In this study, EDW features (regional warming amplification and altitude warming amplification) in the Chinese Tian Shan (CTM) were detected using a unique high-resolution (1 km , 6-hourly) air temperature dataset (CTMD) from 1979 to 2016. The results showed that there were significant EDW signals at different altitudes on different timescales. The CTM showed significant regional warming amplification in spring, especially in March, and the warming trends were greater than those of continental China with respect to three temperatures (minimum temperature, mean temperature and maximum temperature). The significance values of EDW above different altitude thresholds are distinct for three temperatures in 12 months. The warming rate of the minimum temperature in winter showed a significant elevation dependence (p<0.01), especially above 3000 m. The greatest altitudinal gradient in the warming rate of the maximum temperature was found above 4000 m in April. For the mean temperature, the warming rates in June and August showed prominent altitude warming amplification but with different significance above 4500 m. Within the CTM, the Tolm Mountains, the eastern part of the Borokoonu Mountains, the Bogda Mountains and the Balikun Mountains are representative regions that showed significant altitude warming amplification on different timescales. This new evidence could partly explain the accelerated melting of snow in the CTM, although the mechanisms remain to be explored. [ABSTRACT FROM AUTHOR]

Seasonal snowpack is an essential component in the hydrological cycle and plays a significant role in supplying water resources to downstream users. Yet the snow water equivalent (SWE) in seasonal snowpacks, and its space–time variation, remains highly uncertain, especially over mountainous areas with complex terrain and sparse observations, such as in High Mountain Asia (HMA). In this work, we assessed the spatiotemporal distribution of seasonal SWE, obtained from a new 18-year HMA Snow Reanalysis (HMASR) dataset, as part of the recent NASA High Mountain Asia Team (HiMAT) effort. A Bayesian snow reanalysis scheme previously developed to assimilate satellite-derived fractional snow-covered area (fSCA) products from Landsat and MODIS platforms has been applied to develop the HMASR dataset (at a spatial resolution of 16 arcsec (∼500 m) and daily temporal resolution) over the joint Landsat–MODIS period covering water years (WYs) 2000–2017. Based on the results, the HMA-wide total SWE volume is found to be around 163 km 3 on average and ranges from 114 km 3 (WY2001) to 227 km 3 (WY2005) when assessed over 18 WYs. The most abundant snowpacks are found in the northwestern basins (e.g., Indus, Syr Darya and Amu Darya) that are mainly affected by the westerlies, accounting for around 66 % of total seasonal SWE volume. Seasonal snowpack in HMA is depicted by snow accumulating through October to March and April, typically peaking around April and depleting in July–October, with variations across basins and WYs. When examining the elevational distribution over the HMA domain, seasonal SWE volume peaks at mid-elevations (around 3500 m), with over 50 % of the volume stored above 3500 m. Above-average amounts of precipitation causes significant overall increase in SWE volumes across all elevations, while an increase in air temperature (∼1.5 K) from cooler to normal conditions leads to an redistribution in snow storage from lower elevations to mid-elevations. This work brings new insight into understanding the climatology and variability of seasonal snowpack over HMA, with the regional snow reanalysis constrained by remote-sensing data, providing a new reference dataset for future studies of seasonal snow and how it contributes to the water cycle and climate over the HMA region. [ABSTRACT FROM AUTHOR]

Short-term glacier variations can be important for water supplies or hydropower production, and glaciers are important indicators of climate change. This is why the interest in near-real-time mass balance nowcasting is considerable. Here, we address this interest and provide an evaluation of continuous observations of point mass balance based on online cameras transmitting images every 20 min. The cameras were installed on three Swiss glaciers during summer 2019, provided 352 near-real-time point mass balances in total, and revealed melt rates of up to 0.12 m water equivalent per day (mw.e.d-1) and of more than 5 mw.e. in 81 d. By means of a particle filter, these observations are assimilated into an ensemble of three TI (temperature index) and one simplified energy-balance mass balance models. State augmentation with model parameters is used to assign temporally varying weights to individual models. We analyze model performance over the observation period and find that the probability for a given model to be preferred by our procedure is 39 % for an enhanced TI model, 24 % for a simple TI model, 23 %, for a simplified energy balance model, and 14 % for a model employing both air temperature and potential solar irradiation. When compared to reference forecasts produced with both mean model parameters and parameters tuned on single mass balance observations, the particle filter performs about equally well on the daily scale but outperforms predictions of cumulative mass balance by 95 %–96 %. A leave-one-out cross-validation on the individual glaciers shows that the particle filter is also able to reproduce point observations at locations not used for model calibration. Indeed, the predicted mass balances is always within 9 % of the observations. A comparison with glacier-wide annual mass balances involving additional measurements distributed over the entire glacier mostly shows very good agreement, with deviations of 0.02, 0.07, and 0.24 mw.e. [ABSTRACT FROM AUTHOR]

Rock glaciers are a prominent component of many alpine landscapes and constitute a significant water resource in some arid mountain environments. Here, we employ satellite-based interferometric synthetic aperture radar (InSAR) between 2016 and 2019 to identify and monitor active and transitional rock glaciers in the Uinta Mountains (Utah, USA), an area of ∼3000 km2. We used mean velocity maps to generate an inventory for the Uinta Mountains containing 205 active and transitional rock glaciers. These rock glaciers are 11.9 ha in area on average and located at a mean elevation of 3308 m , where mean annual air temperature is - 0.25 ∘C. The mean downslope velocity for the inventory is 1.94 cmyr-1 , but individual rock glaciers have velocities ranging from 0.35 to 6.04 cmyr-1. To search for relationships with climatic drivers, we investigated the time-dependent motion of three rock glaciers. We found that rock glacier motion has a significant seasonal component, with rates that are more than 5 times faster during the late summer compared to the rest of the year. Rock glacier velocities also appear to be correlated with the snow water equivalent of the previous winter's snowpack. Our results demonstrate the ability to use satellite InSAR to monitor rock glaciers over large areas and provide insight into the environmental factors that control their kinematics. [ABSTRACT FROM AUTHOR]

The Nioghalvfjerdsfjorden glacier (also known as the 79 ∘ North Glacier) drains approximately 8 % of the Greenland Ice Sheet. Supraglacial lakes (SGLs), or surface melt ponds, are a persistent summertime feature and are thought to drain rapidly to the base of the glacier and influence seasonal ice velocity. However, seasonal development and spatial distribution of SGLs in the north-east of Greenland are poorly understood, leaving a substantial error in the estimate of meltwater and its impacts on ice velocity. Using results from an automated detection of melt ponds, atmospheric and surface mass balance modelling, and reanalysis products, we investigate the role of specific climatic conditions in melt onset, extent, and duration from 2016 to 2019. The summers of 2016 and 2019 were characterised by above-average air temperatures, particularly in June, as well as a number of rainfall events, which led to extensive melt ponds to elevations up to 1600 m. Conversely, 2018 was particularly cold, with a large accumulated snowpack, which limited the development of lakes to altitudes less than 800 m. There is evidence of inland expansion and increases in the total area of lakes compared to the early 2000s, as projected by future global warming scenarios. [ABSTRACT FROM AUTHOR]

Atmospheric circulation exerts an important control on a region's snow avalanche activity by broadly determining the mountain weather patterns that influence snowpack development and avalanche release. In central Spitsbergen, the largest island in the High Arctic Svalbard archipelago, avalanches are a common natural hazard throughout the winter months. Previous work has identified a unique snow climate reflecting the region's climatically dynamic environmental setting but has not specifically addressed the synoptic-scale control of atmospheric circulation on avalanche activity here. In this work, we investigate atmospheric circulation's control on snow avalanching in the Nordenskiöld Land region of central Spitsbergen by first constructing a four-season (2016/2017–2019/2020) regional avalanche activity record using observations available on a database used by the Norwegian Water Resources and Energy Directorate (NVE). We then analyze the synoptic atmospheric conditions on days with differing avalanche activity situations. Our results show atmospheric circulation conducive to elevated precipitation, wind speeds, and air temperatures near Svalbard are associated with increased avalanche activity in Nordenskiöld Land, but different synoptic signals exist for days characterized by dry, mixed, and wet avalanche activity. Differing upwind conditions help further explain differences in the frequency and nature of avalanche activity resulting from these various atmospheric circulation patterns. We further employ a daily atmospheric circulation calendar to help contextualize our results in the growing body of literature related to climate change in this location. This work helps expand our understanding of snow avalanches in Svalbard to a broader spatial scale and provides a basis for future work investigating the impacts of climate change on avalanche activity in Svalbard and other locations where avalanche regimes are impacted by changing climatic and synoptic conditions. [ABSTRACT FROM AUTHOR]

Knowing when sea ice will open is crucial, notably for scientific deployments. This was particularly obvious when the Weddell Polynya, a large opening in the winter Southern Ocean sea ice, unexpectedly re-appeared in 2016. As no precursor had been detected, observations were limited to chance autonomous sensors, and the exact cause of the opening could not be determined accurately. We investigate here whether the signature of the vertical ocean motions or that of the leads, which ultimately re-open the polynya, are detectable in spaceborne infrared temperature before the polynya opens. From the full historical sea ice concentration record, we find 30 polynyas starting from 1980. Then, using the full time series of the spaceborne infrared Advanced Very High Resolution Radiometer, we determine that these events can be detected in the 2 weeks before the polynya opens as a reduction in the variance of the data. For the three commonly used infrared brightness temperature bands, the 15 d sum and 15 d standard deviation of their area median and maximum are systematically lower than the climatology when a polynya will open. Moreover, by comparing the infrared brightness temperature to atmospheric reanalysis, hydrographic mooring data, and autonomous profilers, we find that temporal oscillations in one band and the decrease in the difference between bands may be used as proxies for upwelling of warm water and presence of leads, respectively, albeit with caution. Therefore, although infrared data are strongly limited by their horizontal resolution and sensitivity to clouds, they could be used for studying ocean or atmosphere preconditioning of polynyas in the historical record. [ABSTRACT FROM AUTHOR]

The Arctic region is responding heavily to climate change, and yet, the air temperature of ice-covered areas in the Arctic is heavily under-sampled when it comes to in situ measurements, resulting in large uncertainties in existing weather and reanalysis products. This paper presents a method for estimating daily mean clear-sky 2 m air temperatures (T2m) in the Arctic from satellite observations of skin temperature, using the Arctic and Antarctic ice Surface Temperatures from thermal Infrared (AASTI) satellite dataset, providing spatially detailed observations of the Arctic. The method is based on a linear regression model, which has been tuned against in situ observations to estimate daily mean T2m based on clear-sky satellite ice surface skin temperatures. The daily satellite-derived T2m product includes estimated uncertainties and covers the Arctic sea ice and the Greenland Ice Sheet during clear skies for the period 2000–2009, provided on a 0.25 ∘ regular latitude–longitude grid. Comparisons with independent in situ measured T2m show average biases of 0.30 and 0.35 ∘ C and average root-mean-square errors of 3.47 and 3.20 ∘C for land ice and sea ice, respectively. The associated uncertainties are verified to be very realistic for both land ice and sea ice, using in situ observations. The reconstruction provides a much better spatial coverage than the sparse in situ observations of T2m in the Arctic and is independent of numerical weather prediction model input. Therefore, it provides an important supplement to simulated air temperatures to be used for assimilation or global surface temperature reconstructions. A comparison of T2m derived from satellite and ERA-Interim/ERA5 estimates shows that the satellite-derived T2m validates similar to or better than ERA-Interim/ERA5 against in situ measurements in the Arctic. [ABSTRACT FROM AUTHOR]

The flexural strength of ice surfaces bonded by freezing, termed freeze bond, was studied by performing four-point bending tests of bonded freshwater S2 columnar-grained ice samples in the laboratory. The samples were prepared by milling the surfaces of two ice pieces, wetting two of the surfaces with water of varying salinity, bringing these surfaces together, and then letting them freeze under a compressive stress of about 4 kPa. The salinity of the water used for wetting the surfaces to generate the bond varied from 0 to 35 ppt (parts per thousand). Freezing occurred in air under temperatures varying from - 25 to - 3 ∘ C over periods that varied from 0.5 to ∼ 100 h. Results show that an increase in bond salinity or temperature leads to a decrease in bond strength. The trend for the bond strength as a function of salinity is similar to that presented in Timco and O'Brien (1994) for saline ice. No freezing occurs at - 3 ∘ C once the salinity of the water used to generate the bond exceeds ∼ 25 ppt. The strength of the saline ice bonds levels off (i.e., saturates) within 6–12 h of freezing; bonds formed from freshwater reach strengths that are comparable or higher than that of the parent material in less than 0.5 h. [ABSTRACT FROM AUTHOR]

In the 2019/2020 austral summer, the surface melt duration and extent on the northern George VI Ice Shelf (GVIIS) was exceptional compared to the 31 previous summers of distinctly lower melt. This finding is based on analysis of near-continuous 41-year satellite microwave radiometer and scatterometer data, which are sensitive to meltwater on the ice shelf surface and in the near-surface snow. Using optical satellite imagery from Landsat 8 (2013 to 2020) and Sentinel-2 (2017 to 2020), record volumes of surface meltwater ponding were also observed on the northern GVIIS in 2019/2020, with 23 % of the surface area covered by 0.62 km 3 of ponded meltwater on 19 January. These exceptional melt and surface ponding conditions in 2019/2020 were driven by sustained air temperatures ≥0 ∘ C for anomalously long periods (55 to 90 h) from late November onwards, which limited meltwater refreezing. The sustained warm periods were likely driven by warm, low-speed (≤7.5 m s -1) northwesterly and northeasterly winds and not by foehn wind conditions, which were only present for 9 h total in the 2019/2020 melt season. Increased surface ponding on ice shelves may threaten their stability through increased potential for hydrofracture initiation; a risk that may increase due to firn air content depletion in response to near-surface melting. [ABSTRACT FROM AUTHOR]

Near-surface air temperature (Ta) is highly important for modelling glacier ablation, though its spatio-temporal variability over melting glaciers still remains largely unknown. We present a new dataset of distributed Ta for three glaciers of different size in the south-east Tibetan Plateau during two monsoon-dominated summer seasons. We compare on-glacier Ta to ambient Ta extrapolated from several local off-glacier stations. We parameterise the along-flowline sensitivity of Ta on these glaciers to changes in off-glacier temperatures (referred to as "temperature sensitivity") and present the results in the context of available distributed on-glacier datasets around the world. Temperature sensitivity decreases rapidly up to 2000–3000 m along the down-glacier flowline distance. Beyond this distance, both the Ta on the Tibetan glaciers and global glacier datasets show little additional cooling relative to the off-glacier temperature. In general, Ta on small glaciers (with flowline distances <1000 m) is highly sensitive to temperature changes outside the glacier boundary layer. The climatology of a given region can influence the general magnitude of this temperature sensitivity, though no strong relationships are found between along-flowline temperature sensitivity and mean summer temperatures or precipitation. The terminus of some glaciers is affected by other warm-air processes that increase temperature sensitivity (such as divergent boundary layer flow, warm up-valley winds or debris/valley heating effects) which are evident only beyond ∼70 % of the total glacier flowline distance. Our results therefore suggest a strong role of local effects in modulating temperature sensitivity close to the glacier terminus, although further work is still required to explain the variability of these effects for different glaciers. [ABSTRACT FROM AUTHOR]

A series of transient seismic events were discovered in passive seismic recordings from 2-D geophone arrays deployed at a frost polygon site in Adventdalen, Svalbard. These events contain a high proportion of surface wave energy and produce high-quality dispersion images using an apparent offset re-sorting and inter-trace delay minimisation technique to locate the seismic source, followed by cross-correlation beamforming dispersion imaging. The dispersion images are highly analogous to surface wave studies of pavements and display a complex multimodal dispersion pattern. Supported by theoretical modelling based on a highly simplified arrangement of horizontal layers, we infer that a ∼3.5 –4.5 m thick, stiff, high-velocity layer overlies a ∼30 m thick layer that is significantly softer and slower at our study site. Based on previous studies we link the upper layer with syngenetic ground ice formed in aeolian sediments, while the underlying layer is linked to epigenetic permafrost in marine-deltaic sediments containing unfrozen saline pore water. Comparing events from spring and autumn indicates that temporal variation can be resolved via passive seismic monitoring. The transient seismic events that we record occur during periods of rapidly changing air temperature. This correlation, along with the spatial clustering along the elevated river terrace in a known frost polygon, ice-wedge area and the high proportion of surface wave energy, constitutes the primary evidence for us to interpret these events as frost quakes, a class of cryoseism. In this study we have proved the concept of passive seismic monitoring of permafrost in Adventdalen, Svalbard. [ABSTRACT FROM AUTHOR]

The 30-year simulations of seasonal snow cover in 22 physically based models driven with bias-corrected meteorological reanalyses are examined at four sites with long records of snow observations. Annual snow cover durations differ widely between models, but interannual variations are strongly correlated because of the common driving data. No significant trends are observed in starting dates for seasonal snow cover, but there are significant trends towards snow cover ending earlier at two of the sites in observations and most of the models. A simplified model with just two parameters controlling solar radiation and sensible heat contributions to snowmelt spans the ranges of snow cover durations and trends. This model predicts that sites where snow persists beyond annual peaks in solar radiation and air temperature will experience rapid decreases in snow cover duration with warming as snow begins to melt earlier and at times of year with more energy available for melting. [ABSTRACT FROM AUTHOR]

We investigate how sea ice interacts with the atmosphere over adjacent landmasses in the Laptev Sea region as a step towards a better understanding of the connection between sea ice and permafrost. We identify physical mechanisms as well as local and large-scale drivers of sea-ice cover with a focus on one region with highly variable sea-ice cover and high sea-ice productivity: the Laptev Sea region. We analyze the output of a coupled ocean–sea-ice–atmosphere–hydrological-discharge model with two statistical methods. With the recently developed causal-effect networks we identify temporal links between different variables, while we use composites of high- and low-sea-ice-cover years to reveal spatial patterns and mean changes in variables. We find that in the model local sea-ice cover is a driven rather than a driving variable. Springtime melt of sea ice in the Laptev Sea is mainly controlled by atmospheric large-scale circulation, mediated through meridional wind speed and ice export. During refreeze in fall thermodynamic variables and feedback mechanisms are important – sea-ice cover is interconnected with air temperature, thermal radiation and specific humidity. Though low sea-ice cover leads to an enhanced southward transport of heat and moisture throughout summer, links from sea-ice cover to the atmosphere over land are weak, and both sea ice in the Laptev Sea and the atmospheric conditions over the adjacent landmasses are mainly controlled by common external drivers. [ABSTRACT FROM AUTHOR]

Accurate subseasonal-to-seasonal (S2S) atmospheric forecasts and hydrological forecasts have considerable socioeconomic value. This study conducts a multimodel comparison of the Tibetan Plateau snow cover (TPSC) prediction skill using three models (ECMWF, NCEP and CMA) selected from the S2S project database to understand their performance in capturing TPSC variability during wintertime. S2S models can skillfully forecast TPSC within a lead time of 2 weeks but show limited skill beyond 3 weeks. Compared with the observational snow cover analysis, all three models tend to overestimate the area of TPSC. Another remarkable issue regarding the TPSC forecast is the increasing TPSC with forecast lead time, which further increases the systematic positive biases of TPSC in the S2S models at longer forecast lead times. All three S2S models consistently exaggerate the precipitation over the Tibetan Plateau. The exaggeration of precipitation is prominent and always exists throughout the model integration. Systematic bias of TPSC therefore occurs and accumulates with the model integration time. Such systematic biases of TPSC influence the forecasted surface air temperature in the S2S models. The surface air temperature over the Tibetan Plateau becomes colder with increasing forecast lead time in the S2S models. Numerical experiments further confirm the causality. [ABSTRACT FROM AUTHOR]

Along with record-breaking summer air temperatures at an Antarctic Peninsula meteorological station in February 2020, the Larsen C ice shelf experienced an exceptionally long and extensive 2019/2020 melt season. We use a 40-year time series of passive and scatterometer satellite microwave data, which are sensitive to the presence of liquid water in the snow pack, to reveal that the extent and duration of melt observed on the ice shelf in the austral summer of 2019/2020 was the greatest on record. We find that unusual perturbations to Southern Hemisphere modes of atmospheric flow, including a persistently positive Indian Ocean Dipole in the spring and a very rare Southern Hemisphere sudden stratospheric warming in September 2019, preceded the exceptionally warm Antarctic Peninsula summer. It is likely that teleconnections between the tropics and southern high latitudes were able to bring sufficient heat via the atmosphere and ocean to the Antarctic Peninsula to drive the extreme Larsen C Ice Shelf melt. The record-breaking melt of 2019/2020 brought to an end the trend of decreasing melt that had begun in 1999/2000, will reinitiate earlier thinning of the ice shelf by depletion of the firn air content, and probably affected a much greater region than Larsen C Ice Shelf. [ABSTRACT FROM AUTHOR]

Permafrost is a ubiquitous phenomenon in the Arctic. Its future evolution is likely to control changes in northern high-latitude hydrology and biogeochemistry. Here we evaluate the permafrost dynamics in the global models participating in the Coupled Model Intercomparison Project (present generation – CMIP6; previous generation – CMIP5) along with the sensitivity of permafrost to climate change. Whilst the northern high-latitude air temperatures are relatively well simulated by the climate models, they do introduce a bias into any subsequent model estimate of permafrost. Therefore evaluation metrics are defined in relation to the air temperature. This paper shows that the climate, snow and permafrost physics of the CMIP6 multi-model ensemble is very similar to that of the CMIP5 multi-model ensemble. The main differences are that a small number of models have demonstrably better snow insulation in CMIP6 than in CMIP5 and a small number have a deeper soil profile. These changes lead to a small overall improvement in the representation of the permafrost extent. There is little improvement in the simulation of maximum summer thaw depth between CMIP5 and CMIP6. We suggest that more models should include a better-resolved and deeper soil profile as a first step towards addressing this. We use the annual mean thawed volume of the top 2 m of the soil defined from the model soil profiles for the permafrost region to quantify changes in permafrost dynamics. The CMIP6 models project that the annual mean frozen volume in the top 2 m of the soil could decrease by 10 % –40 %∘C-1 of global mean surface air temperature increase. [ABSTRACT FROM AUTHOR]