Glaciers depicted on old maps reveal their historical extents, before the advent of aerial and satellite remote sensing. Digital glacier inventories produced from these maps can be employed in assessments of centennial-scale glacier change. This study reconstructs the ~1899 (covering the period 1882–1916) glacier extent in Nordland, northern Norway, from historical gradteigskart maps, with an emphasis on examining the accuracy of the mapped glaciers. Glacier outlines were digitised from georectified scans of the analogue maps in a raster graphics editor and were subsequently inventoried in a GIS. The accuracy of the historical glacier extent was established from written descriptions and landscape photographs created during the original field surveys, and further validated against independent glacier outlines of (1) the maximum Little Ice Age extent derived from geomorphological evidence, and (2) the 1945 extent derived from vertical aerial photographs. An overall uncertainty of ±17% is associated with our inventory. Nordland's glaciers covered an area of 1712 ± 291 km2 in 1899. By 2000, total ice cover had decreased by 47% (807 ± 137 km2) at a rate of 6% 10 a−1 (80 ± 14 km2 10 a−1). The approach presented here may serve as a blueprint for future studies intending to derive glacier inventories from historical maps.

The high-Alpine ice-core drilling site Colle Gnifetti (CG), Monte Rosa, Swiss/Italian Alps, provides climate records over the last millennium and beyond. However, the full exploitation of the oldest part of the existing ice cores requires complementary knowledge of the intricate glacio-meteorological settings, including glacier dynamics. Here, we present new ice-flow modeling studies of CG, focused on characterizing the flow at two neighboring drill sites in the eastern part of the glacier. The3-D full Stokes ice-flow model is thermo-mechanically coupled and includes firn rheology, firn densification and enthalpy transport, and is implemented using the finite element software Elmer/Ice. Measurements of surface velocities, accumulation, borehole inclination, density and englacial temperatures are used to validate the model output. We calculate backward trajectories and map the catchment areas. This constrains, for the first time at this site, the so-called upstream effects for the stable water isotope time series of the two ice cores drilled in 2005 and 2013. The model also provides a 3-D age field of the glacier and independent ice-core chronologies for five ice-core sites. Model results are a valuable addition to the existing glaciological and ice-core datasets. This especially concerns the quantitative estimate of upstream conditions affecting the interpretation of the deep ice-core layers.

Small mountain glaciers are an important part of the cryosphere and tend to respond rapidly to climate warming. Historically, mapping very small glaciers (generally considered to be <0.5 km2) using satellite imagery has often been subjective due to the difficulty in differentiating them from perennial snowpatches. For this reason, most scientists implement minimum size-thresholds (typically 0.01–0.05 km2). Here, we compare the ability of different remote-sensing approaches to identify and map very small glaciers on imagery of varying spatial resolutions (30–0.25 m) and investigate how operator subjectivity influences the results. Based on this analysis, we support the use of a minimum size-threshold of 0.01 km2 for imagery with coarse to medium spatial resolution (30–10 m). However, when mapping on high-resolution imagery (<1 m) with minimal seasonal snow cover, glaciers <0.05 km2 and even <0.01 km2 are readily identifiable and using a minimum threshold may be inappropriate. For these cases, we develop a set of criteria to enable the identification of very small glaciers and classify them as certain, probable or possible. This should facilitate a more consistent approach to identifying and mapping very small glaciers on high-resolution imagery, helping to produce more comprehensive and accurate glacier inventories.

Climate variability can complicate efforts to interpret any long-term glacier mass-balance trends due to anthropogenic warming. Here we examine the impact of climate variability on the seasonal mass-balance records of 14 glaciers throughout Norway, Sweden and Svalbard using dynamical adjustment, a statistical method that removes orthogonal patterns of variability shared between each mass-balance record and sea-level pressure or sea-surface temperature predictor fields. For each glacier, the two leading predictor patterns explain 27–81% of the winter mass-balance variability and 24–69% of the summer mass-balance variability. The spatial and temporal structure of these patterns indicates that accumulation variability for all of the glaciers is strongly related to the North Atlantic Oscillation (NAO), with the Atlantic Multidecadal Oscillation (AMO) also modulating accumulation variability for the northernmost glaciers. Given this result, predicting glacier change in the region may depend on NAO and AMO predictability. In the raw mass-balance records, the glaciers throughout southern Norway have significantly negative summer trends, whereas the glaciers located closer to the Arctic have negative winter trends. Removing the effects of climate variability suggests it can bias trends in mass-balance records that span a few decades, but its effects on most of the longer-term mass-balance trends are minimal.

Accurately estimating winter surface mass balance on glaciers is central to assessing glacier health and predicting glacier run-off. However, measuring and modelling snow distribution is inherently difficult in mountainous terrain. Here, we explore rigorous statistical methods of estimating winter balance and its uncertainty from multiscale measurements of snow depth and density. In May 2016, we collected over 9000 manual measurements of snow depth across three glaciers in the St. Elias Mountains, Yukon, Canada. Linear regression, combined with cross-validation and Bayesian model averaging, as well as ordinary kriging are used to interpolate point-scale values to glacier-wide estimates of winter balance. Elevation and a wind-redistribution parameter exhibit the highest correlations with winter balance, but the relationship varies considerably between glaciers. A Monte Carlo analysis reveals that the interpolation itself introduces more uncertainty than the assignment of snow density or the representation of grid-scale variability. For our study glaciers, the winter balance uncertainty from all assessed sources ranges from 0.03 to 0.15 m w.e. (5–39%). Despite the challenges associated with estimating winter balance, our results are consistent with a regional-scale winter-balance gradient.

The phase-sensitive radio-echo sounder (pRES) is a powerful new instrument that can measure the depth of internal layers and the glacier bed to millimetre accuracy. We use a stationary 16-antenna pRES array on Store Glacier in West Greenland to measure the three-dimensional orientation of dipping internal reflectors, extending the capabilities of pRES beyond conventional depth sounding. This novel technique portrays the effectiveness of pRES in deriving the orientation of dipping internal layers that may complement profiles obtained through other geophysical surveying methods. Deriving ice vertical strain rates from changes in layer depth as measured by a sequence of pRES observations assumes that the internal reflections come from vertically beneath the antenna. By revealing the orientation of internal reflectors and the potential deviation from nadir of their associated reflections, the use of an antenna array can correct this assumption. While the array configuration was able to resolve the geometry of englacial layers, the same configuration could not be used to accurately image the glacier bed. Here, we use simulations of the performance of different array geometries to identify configurations that can be tailored to study different types of basal geometry for future deployments.

We simulate the ice dynamics of the San Rafael Glacier (SRG) in the Northern Patagonia Icefield (46.7°S, 73.5°W), using glacier geometry obtained by airborne gravity measurements. The full-Stokes ice flow model (Elmer/Ice) is initialized using an inverse method to infer the basal friction coefficient from a satellite-derived surface velocity mosaic. The high surface velocities (7.6 km a−1) near the glacier front are explained by low basal shear stresses (<25 kPa). The modelling results suggest that 98% of the surface velocities are due to basal sliding in the fast-flowing glacier tongue (>1 km a−1). We force the model using different surface mass-balance scenarios taken or adapted from previous studies and geodetic elevation changes between 2000 and 2012. Our results suggest that previous estimates of average surface mass balance over the entire glacier (Ḃ) were likely too high, mainly due to an overestimation in the accumulation area. We propose that most of SRG imbalance is due to the large ice discharge (−0.83 ± 0.08 Gt a−1) and a slightly positive Ḃ (0.08 ± 0.06 Gt a−1). The committed mass-loss estimate over the next century is −0.34 ± 0.03 Gt a−1. This study demonstrates that surface mass-balance estimates and glacier wastage projections can be improved using a physically based ice flow model.

Simple models of glacier volume evolution are important in understanding features of glacier response to climate change, due to the scarcity of data adequate for running more complex models on a global scale. Two quantities of interest in a glacier's response to climate changes are its response time and its volume sensitivity to changes in the equilibrium line altitude (ELA). We derive a simplified, computationally inexpensive model of glacier volume evolution based on a block model with volume–area–length scaling. After analyzing its steady-state properties, we apply the model to each mountain glacier worldwide and estimate regionally differentiated response times and sensitivities to ELA changes. We use a statistical method from the family of global sensitivity analysis methods to determine the glacier quantities, geometric and climatic, that most influence the model output. The response time is dominated by the climatic setting reflected in the mass-balance gradient in the ablation zone, followed by the surface slope, while volume sensitivity is mainly affected by glacier size, followed by the surface slope.

The controls on rapid surface lake drainage on the Greenland ice sheet (GrIS) remain uncertain, making it challenging to incorporate lake drainage into models of GrIS hydrology, and so to determine the ice-dynamic impact of meltwater reaching the ice-sheet bed. Here, we first use a lake area and volume tracking algorithm to identify rapidly draining lakes within West Greenland during summer 2014. Second, we derive hydrological, morphological, glaciological and surface-mass-balance data for various factors that may influence rapid lake drainage. Third, these factors are used within Exploratory Data Analysis to examine existing hypotheses for rapid lake drainage. This involves testing for statistical differences between the rapidly and non-rapidly draining lake types, as well as examining associations between lake size and the potential controlling factors. This study shows that the two lake types are statistically indistinguishable for almost all factors investigated, except lake area. Thus, we are unable to recommend an empirically supported, deterministic alternative to the fracture area threshold parameter for modelling rapid lake drainage within existing surface-hydrology models of the GrIS. However, if improved remotely sensed datasets (e.g. ice-velocity maps, climate model outputs) were included in future research, it may be possible to detect the causes of rapid drainage.