Cryoconite holes are small depressions of the glacier surface filled with melting water and with a wind-blown debris on the bottom. These environments are considered hot spots of biodiversity and biological activities on glaciers and host communities dominated by bacteria. Most of the studies on cryoconite holes assume that their communities are stable. However, evidence of seasonal variation in cryoconite hole ecological communities exists. We investigated the variation of the bacterial communities of cryoconite holes of Forni Glacier (Central Italian Alps) during the melting seasons (July–September) 2013 and 2016, for which samples at three and five time-points, respectively were available. Bacterial communities were characterized by high-throughput Illumina sequencing of the hypervariable V5−V6 regions of 16S rRNA gene, while meteorological data were obtained by an automatic weather station. We found consistent trends in bacterial communities, which shifted from cyanobacteria-dominated communities in July to communities dominated by heterotrophic orders in late August and September. Temperature seems also to affect seasonal dynamics of communities. We also compared bacterial communities at the beginning of the melting season across 4 years (2012, 2013, 2015 and 2016) and found significant year-to-year variability. Cryoconite hole communities on temperate glaciers are therefore not temporally stable.

Significant salinity anomalies have been observed in the Arctic Ocean surface layer during the last decade. Our study is based on an extensive gridded dataset of winter salinity in the upper 50 m layer of the Arctic Ocean for the periods 1950–1993 and 2007–2012, obtained from ~20 000 profiles. We investigate the interannual variability of the salinity fields, identify predominant patterns of anomalous behavior and leading modes of variability, and develop a statistical model for the prediction of surface-layer salinity. The statistical model is based on linear regression equations linking the principal components of surface-layer salinity obtained through empirical orthogonal function decomposition with environmental factors, such as atmospheric circulation, river runoff, ice processes and water exchange with neighboring oceans. Using this model, we obtain prognostic fields of the surface-layer salinity for the winter period 2013–2014. The prognostic fields generated by the model show tendencies of surface-layer salinification, which were also observed in previous years. Although the used data are proprietary and have gaps, they provide the most spatiotemporally detailed observational resource for studying multidecadal variations in basin-wide Arctic salinity. Thus, there is community value in the identification, dissemination and modeling of the principal modes of variability in this salinity record.

Using repeat GPS measurements during 2005–16, we calculated and updated two-dimensional high-resolution decadal ice surface velocity estimates along the traverse route from Zhongshan Station to and around Dome Argus, East Antarctica. Along the 71 sites of the transect, the magnitudes of ice velocity increased from near 0 in Dome Argus to 1, 10 and ~100 m a−1 at the sites DT416, DT333 and LT980, respectively. The comparison between GPS and interferometric synthetic aperture radar (InSAR) derived results agree well when the magnitude of the ice surface velocities is faster than 5 m a−1, and disagree for slower flow velocities. A scale value 1.15 and 0.12 can be applied to InSAR derived results over this region with ice surface velocity larger and <5 m a−1, respectively. We attributed the cause of the discrepancy to the insensitivity of InSAR to the magnitude of low ice surface velocities, thus confirming the importance of GPS fieldwork-based ground truth high-resolution ice velocity estimates to constrain ice-sheet dynamics.

The catchments of Pine Island Glacier and Thwaites Glacier in the Amundsen Sea Embayment are two of the largest, most rapidly changing, and potentially unstable sectors of the West Antarctic Ice Sheet. They are also neighboring outlets, separated by the topographically unconfined eastern shear margin of Thwaites Glacier and the southwest tributary of Pine Island Glacier. This tributary begins just downstream of the eastern shear margin and flows into the Pine Island ice shelf. As a result, it is a potential locus of interaction between the two glaciers and could result in cross-catchment feedback during the retreat of either. Here, we analyze relative basal reflectivity profiles from three radar sounding survey lines collected using the UTIG HiCARS radar system in 2004 and CReSIS MCoRDS radar system in 2012 and 2014 to investigate the extent and character of ocean access beneath the southwest tributary. These profiles provide evidence of ocean access ~12 km inland of the 1992–2011 InSAR-derived grounding line by 2014, suggesting either retreat since 2011 or the intrusion of ocean water kilometers inland of the grounding line.

Snow can be considered an independent ecosystem that hosts active microbial communities. Snow microbial communities have been extensively investigated in the Arctic and in the Antarctica, but rarely in mid-latitude mountain areas. In this study, we investigated the bacterial communities of snow collected in four glacierized areas (Alps, Eastern Anatolia, Karakoram and Himalaya) by high-throughput DNA sequencing. We also investigated the origin of the air masses that produced the sampled snowfalls by reconstructing back-trajectories. A standardized approach was applied to all the analyses in order to ease comparison among different communities and geographical areas. The bacterial communities hosted from 25 to 211 Operational Taxonomic Units (OTUs), and their structure differed significantly between geographical areas. This suggests that snow bacterial communities may largely derive from ‘local’ air bacteria, maybe by deposition of airborne particulate of local origin that occurs during snowfall. However, some evidences suggest that a contribution of bacteria collected during air mass uplift to snow communities cannot be excluded, particularly when the air mass that originated the snow event is particularly rich in dust.

Sea-ice thickness in the Sea of Okhotsk is estimated for 2004–2008 from ICESat derived freeboard under the assumption of hydrostatic balance. Total ice thickness including snow depth (htot) averaged over 2004–2008 is 95 cm. The interannual variability of htot is large; from 77.5 cm (2008) to 110.4 cm (2005). The mode of htot varies from 50–60 cm (2007 and 2008) to 70–80 cm (2005). Ice thickness derived from ICESat data is validated from a comparison with that observed by Electromagnetic Induction Instrument (EM) aboard the icebreaker Soya near Hokkaido, Japan. Annual maps of htot reveal that the spatial distribution of htot is similar every year. Ice volume of 6.3 × 1011 m3 is estimated from the ICESat derived htot and AMSR-E derived ice concentration. A comparison with ice area demonstrates that the ice volume cannot always be represented by the area solely, despite the fact that the area has been used as a proxy of the volume in the Sea of Okhotsk. The ice volume roughly corresponds to that of annual ice production in the major coastal polynyas estimated based on heat budget calculations. This also supports the validity of the estimation of sea-ice thickness and volume using ICESat data.

In this paper an algorithm for ice/water classification of C- and L-band dual polarization synthetic aperture radar data is presented. A comparison of the two different frequencies is made in order to investigate the potential to improve classification results with multi-frequency data. The algorithm is based on backscatter intensities in co- and cross-polarization and autocorrelation as a texture feature. The mapping between image features and ice/water classification is made with a neural network. Accurate ice/water maps for both frequencies are produced by the algorithm and the results of two frequencies generally agree very well. Differences are found in the marginal ice zone, where the time difference between acquisitions causes motion of the ice pack. C-band reliably reproduces the outline of the ice edge, while L-band has its strengths for thin ice/calm water areas within the icepack. The classification shows good agreement with ice/water maps derived from met.no ice-charts and radiometer data from AMSR-2. Variations are found in the marginal ice zone where the generalization of the ice charts and lower accuracy of ice concentration from radiometer data introduce deviations. Usage of high-resolution dual frequency data could be beneficial for improving ice cover information for navigation and modelling.

Cryoconite holes are water-filled cylindrical holes formed on ablation ice surfaces and commonly observed on glaciers worldwide. Temporal changes of cryoconite holes characteristically <5 cm in diameter were monitored with a time-lapse interval camera over 15 d during the melting season on Qaanaaq Glacier in northwest Greenland. The holes drastically changed their dimensions and synchronously collapsed twice during the study period. When the holes collapsed, the coverage of cryoconite on the ice surface increased from 1.0 to 3.5% in the field of view of the camera, and then decreased again to 0.4% after the holes reformed. Comparison with meteorological data showed that the collapses occurred in cloudy and rainy or windy weather conditions, corresponding to low shortwave solar radiation (68–126 W m−2, 40–55% of the incoming flux). In contrast, holes developed in sunny conditions correspond to high solar radiation (186–278 W m−2, 63–88%). Results suggest that the dimensions of holes drastically changed depending on the weather conditions and that frequent cloudy, warm and windy conditions would cause a decay of holes and weathering crust, inducing an increase in the cryoconite coverage on the ice, consequently darkening the glacier surface.

This paper reports a comparative analysis performed on a fraction-image time series of the Antarctic Peninsula from the period 1999–2009 generated by multiresolution remote-sensing images (SSM/I and SSMI/S with 25 km and QuikSCAT with 2.225 km spatial resolutions) for snow-melt detection. Our method is based on the (a) preprocessing of multitemporal remote-sensing data, (b) subpixel mixture analysis of SSMI and QuikSCAT image time series, and (c) evaluation of subpixel analysis, including an assessment of fraction images of wet snow using an independent ASAR dataset and sensitivity analysis on the melt metrics measured by these images. The temporal dynamics of the melt indices derived from the wet-snow fraction images presented a more realistic pattern than the traditional melt metrics measured by Boolean snow-melt detection approaches. Because the snow melt actually occurs at the pixel fractions, the multiscale analysis that was performed suggests an overestimation of the melt metrics calculated using Boolean approaches (which assume that the entire area of the detected pixel shows snow melt). The melt metrics measurements show an overestimation according to the decrease in spatial resolution related to the multiplicative effect of a larger pixel area.

West Antarctic climate and surface mass balance (SMB) records are sparse. To fill this gap, regional atmospheric climate modelling is useful, providing that such models are employed at sufficiently high horizontal resolution and coupled with a snow model. Here we present the results of a high-resolution (5.5 km) regional atmospheric climate model (RACMO2) simulation of coastal West Antarctica for the period 1979–2015. We evaluate the results with available in situ weather observations, remote-sensing estimates of surface melt, and SMB estimates derived from radar and firn cores. Moreover, results are compared with those from a lower-resolution version, to assess the added value of the resolution. The high-resolution model resolves small-scale climate variability invoked by topography, such as the relatively warm conditions over ice-shelf grounding zones, and local wind speed accelerations. Surface melt and SMB are well reproduced by RACMO2. This dataset will prove useful for picking ice core locations, converting elevation changes to mass changes, for driving ocean, ice-sheet and coupled models, and for attributing changes in the West Antarctic Ice Sheet and shelves to changes in atmospheric forcing.

Dissolved organic matter (DOM) in mountain glaciers is an important source of carbon for downstream aquatic systems, and its impact is expected to increase due to the increased melting rate of glaciers. We present a comprehensive study of Laohugou glacier no. 12 (LHG) at the northern edge of the Tibetan Plateau to characterize the DOM composition and sources by analyzing surface fresh snow, granular ice samples, and snow pit samples which covered a whole year cycle of 2014/15. Excitation–emission matrix fluorescence spectroscopy analysis of the DOM with parallel factor analysis (EEM-PARAFAC) identified four components, including a microbially humic-like component (C1), two protein-like components (C2 and C3) and a terrestrial humic-like component (C4). The use of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) showed that DOM from all these samples was dominated by CHO and CHON molecular formulas, mainly corresponding to lipids and aliphatic/proteins compounds, reflecting the presence of significant amounts of microbially derived and/or deposited biogenic DOM. The molecular compositions of DOM showed more CHON compounds in granular ice than in fresh snow, likely suggesting newly formed DOM from microbes during snowmelting.

The presence of leads with open water or thin ice is an important feature of the Arctic sea ice cover. Leads regulate the heat, gas and moisture fluxes between the ocean and atmosphere and are areas of high ice growth rates during periods of freezing conditions. Here, an algorithm providing an automatic lead detection based on synthetic aperture radar images is described that can be applied to a wide range of Sentinel-1 scenes. By using both the HH and the HV channels instead of single co-polarised observations the algorithm is able to classify more leads correctly. The lead classification algorithm is based on polarimetric features and textural features derived from the grey-level co-occurrence matrix. The Random Forest classifier is used to investigate the importance of the individual features for lead detection. The precision–recall curve representing the quality of the classification is used to define threshold for a binary lead/sea ice classification. The algorithm is able to produce a lead classification with more that 90% precision with 60% of all leads classified. The precision can be increased by the cost of the amount of leads detected. Results are evaluated based on comparisons with Sentinel-2 optical satellite data.

The ability to detect the surface expression of moving water beneath the Antarctic ice sheet by satellite has revealed a dynamic basal environment, with implications for regional ice dynamics, grounding-line stability, and fluxes of freshwater and nutrients to the Southern Ocean. Knowledge of subglacial activity on timescales important for near-term prediction of ice-sheet fluctuations (decadal to century) is limited by the short observational record of NASA's Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry mission used to generate the last continent-wide survey (2003–08). Here, we use synthetic aperture radar-interferometric-mode data from ESA's CryoSat-2 radar altimetry mission (2010–present), which samples 45 of the ICESat-derived subglacial lakes, to extend their time series to the end of 2016. The extended time series show that there have been surface-height changes at 20 of the 45 lakes since 2008, indicating that some of these features are persistent and potentially cyclic, while other features show negligible changes, suggesting these may be transient or nonhydrological features. Continued monitoring of active lakes for both height and velocity changes, as well as developing methods for identifying additional lakes, is critical to quantifying the full distribution of active subglacial lakes in Antarctica.

Pressure ridges impact the mass, energy and momentum budgets of the sea-ice cover and present an obstacle to transportation through ice-infested waters. Quantifying ridge characteristics is important for understanding total sea-ice mass and for improving the representation of sea-ice dynamics in high-resolution models. Multi-sensor measurements collected during annual Operation IceBridge (OIB) airborne surveys of the Arctic provide new opportunities to assess the sea ice at the end of winter. We present a new methodology to derive ridge sail height from high-resolution OIB Digital Mapping System (DMS) visible imagery. We assess the efficacy of the methodology by mapping the full sail height distribution along 12 pressure ridges in the western and central Arctic. Comparisons against coincident Airborne Topographic Mapper (ATM) elevation anomalies are used to demonstrate the methodology and evaluate DMS-derived sail heights. Sail heights and elevation anomalies were correlated at 0.81 or above. On average mean and maximum sail height agreed with ATM elevation to within 0.11 and 0.49 m, respectively. Of the ridges mapped, mean sail height ranged from 0.99 to 2.16 m, while maximum sail height ranged from 2.1 to 4.8 m. DMS also delivered higher sampling along ridge crests than coincident ATM data.

Snowmelt was measured on a daily basis for 17 days at the open site and 18 days at three Japanese cedar sites with canopy closure of 17.8% (cedar stand A), 5.2% (B) and 2.4% (C) in April. Measured daily snowmelt at each site was reproduced by heat-balance calculation with an accuracy of <±1 mm w.e. From 1st April to the date of snow disappearance net radiation accounted for 88.4, 43.0, 32.7 and 34.2% of total snowmelt energy at the open site, the cedar stands A, B and C, respectively. The ratio of sensible and latent heat to total snowmelt was 33.1–37.9 and 25.9–29.4%, respectively, at three cedar stands. The ratios of sensible and latent heat increased over time in accordance with the rise in temperature at all cedar sites. They became large on a daily basis when air temperature and/or wind speed were high. Wind speed is dependent on morphology around each site that also dictated snowmelt.

Changing Arctic sea-ice extent and melt season duration, and increasing economic interest in the Arctic have prompted the need for enhanced marine ecosystem studies and improvements to dynamical and forecast models. Sea-ice melt pond fraction fp has been shown to be correlated with the September minimum ice extent due to its impact on ice albedo and heat uptake. Ice forecasts should benefit from knowledge of fp as melt ponds form several months in advance of ice retreat. This study goes further back by examining the potential to predict fp during winter using backscatter data from the commonly available Sentinel-1 synthetic aperture radar. An object-based image analysis links the winter and spring thermodynamic states of first-year and multiyear sea-ice types. Strong correlations between winter backscatter and spring fp, detected from high-resolution visible to near infrared imagery, are observed, and models for the retrieval of fp from Sentinel-1 data are provided (r2 ≥ 0.72). The models utilize HH polarization channel backscatter that is routinely acquired over the Arctic from the two-satellite Sentinel-1 constellation mission, as well as other past, current and future SAR missions operating in the same C-band frequency. Predicted fp is generally representative of major ice types first-year ice and multiyear ice during the stage in seasonal melt pond evolution where fp is closely related to spatial variations in ice topography.

Supraglacial lakes are known to trigger Antarctic ice-shelf instability and break-up. However, to date, no study has focused on lakes on Greenland's floating termini. Here, we apply lake boundary/area and depth algorithms to Landsat 8 imagery to analyse the inter- and intraseasonal evolution of supraglacial lakes across Petermann Glacier's (81°N) floating tongue from 2014 to 2016, while also comparing these lakes to those on the grounded ice. Lakes start to fill in June and quickly peak in total number, volume and area in late June/early July in response to increases in air temperatures. However, through July and August, total lake number, volume and area all decline, despite sustained high temperatures. These observations may be explained by the transportation of meltwater into the ocean by a river, and by lake drainage events on the floating tongue. Further, as mean lake depth remains relatively constant during this time, we suggest that a large proportion of the lakes that drain, do so completely, likely by rapid hydrofracture. The mean areas of lakes on the tongue are only ~20% of those on the grounded ice and exhibit lower variability in maximum and mean depth, differences likely attributable to the contrasting formation processes of lakes in each environment.

Although the disaster reduction effects of forest braking have long been known empirically, they have not been known in detail down to recent. In this study, we ascertained forest braking effect by numerical simulations using the avalanche dynamics program, TITAN2D, to model large-scale avalanches. One of these avalanches occurred in the Makunosawa valley, Myoko, and damaged a cedar forest; the others occurred on Mt. Iwate and damaged a subalpine forest. All avalanches damaged many trees and terminated within the forests. In our simulations, the resistance of the forests to avalanches is simulated using a larger bed friction angle. Fitting the observations from the Makunosawa avalanche by trial and error, a bed friction angle of 13–14° in the non-forested area and of 25° in the forested area is obtained. We conducted simulations of the Mt. Iwate avalanches using the same method as for the Makunosawa valley avalanche, and obtained good agreement between observations and simulations. Simulations reveal that without the forest, the avalanche would have traveled at least 200 m farther than the forest's actual end in the Makunosawa valley, and at least 200 m and possibly up to 600 m farther on Mt. Iwate. This study therefore clearly shows that forests provide a braking effect for avalanches.

Knowledge of Arctic sea-ice conditions is of great interest for Arctic residents, as well as for commercial usage, and to study the effects of climate change. Information gained from analysis of satellite data contributes to this understanding. In the course of using in situ data in combination with remotely sensed data, the question of how representative local scale measurements are of a wider region may arise. We compare in situ total sea-ice thickness measurements from the Norwegian young sea ICE expedition in the area north of Svalbard with airborne-derived total sea-ice thickness from electromagnetic soundings. A segmented and classified synthetic aperture radar (SAR) quad-pol ALOS-2 Palsar-2 satellite scene was grouped into three simplified ice classes. The area fractions of the three classes are: 11.2% ‘thin’, 74.4% ‘level’, and 14.4% ‘deformed’. The area fractions of the simplified classes from ground- and helicopter-based measurements are comparable with those achieved from the SAR data. Thus, this study shows that there is potential for a stepwise upscaling from in situ, to airborne, to satellite data, which allow us to assess whether in situ data collected are representative of a wider region as observed by satellites.

Recent greening of vegetation across the Arctic is associated with warming temperatures, hydrologic change and shorter snow-covered periods. Here we investigated trends for a subset of arctic vegetation on the island of Greenland. Vegetation in Greenland is unique due to its close proximity to the Greenland Ice Sheet and its proportionally large connection to the Greenlandic population through the hunting of grazing animals. The aim of this study was to determine whether or not longer snow-free periods (SFPs) were causing Greenlandic vegetation to dry out and become less productive. If vegetation was drying out, a subsequent aim of the study was to determine how widespread the drying was across Greenland. We utilized a 15-year time-series obtained by the MODerate Resolution Imaging Spectroradiometer (MODIS) to analyze the Greenland vegetation by deriving descriptors corresponding with the SFP, the number of cumulative growing degree-days and the time-integrated Normalized Difference Vegetation Index. While the productivity of most vegetated areas increased in response to longer growing periods, there were localized regions that exhibited signs consistent with the drying hypothesis. In these areas, vegetation productivity decreased in response to longer SFPs and more accumulated growing degree-days.