Combinations of various numerical models and datasets with diverse observation characteristics have been used to assess the mass evolution of ice sheets. As a consequence, a wide range of estimates have been produced using markedly different methodologies, data, approximation methods and model assumptions. Current attempts to reconcile these estimates using simple combination methods are unsatisfactory, as common sources of errors across different methodologies may not be accurately quantified (e.g. systematic biases in models). Here we provide a general approach which deals with this issue by considering all data sources simultaneously, and, crucially, by reducing the dependence on numerical models. The methodology is based on exploiting the different space–time characteristics of the relevant ice-sheet processes, and using statistical smoothing methods to establish the causes of the observed change. In omitting direct dependence on numerical models, the methodology provides a novel means for assessing glacio-isostatic adjustment and climate models alike, using remote-sensing datasets. This is particularly advantageous in Antarctica, where in situ measurements are difficult to obtain. We illustrate the methodology by using it to infer Antarctica’s mass trend from 2003 to 2009 and produce surface mass-balance anomaly estimates to validate the RACMO2.1 regional climate model.

The meltwater from glaciers in Alaska contributes strongly to global sea-level rise, but accurate determination is challenging as only two comparatively small glaciers have long-term measurements of annual mass balance (Gulkana and Wolverine). Simple upscaling of their values to the entire region is error-prone as their representativeness is unknown and might be biased. Alternatively, differencing digital elevation models (DEMs) from two epochs provides overall volume changes for a longer period of time that can be converted to mass changes using appropriate density assumptions. Here we combine outlines from two glacier inventories to determine glacier-specific elevation changes over a 50 year period for 3180 glaciers in western Alaska using DEM differencing. This allows us to determine the representativeness of the land-terminating Gulkana and Wolverine Glaciers for the entire region and to exclude calving glaciers (marine and lacustrine) from the sample. Mean changes for all land-terminating, lake-terminating and tidewater glaciers are –0.23 ± 0.44, –0.63 ± 0.40 and –0.64 ± 0.66 m a–1, respectively, and –0.7 and –0.6 m a–1 for the two mass-balance or benchmark glaciers. Thus fortuitously their changes better represent calving glaciers and the overall mean (–0.63 ± 1.14 m a–1) than the change of land-terminating glaciers, i.e. they are not representative for their own type. Different methods of considering potential DEM artefacts provide variable mean changes but the same general result.

Despite their importance as freshwater reservoirs for downstream river systems, few glaciers in central Chile have been comprehensively surveyed. This study presents ground-penetrating radar (GPR) and field-based observations for characterizing the englacial and basal conditions of Glaciar Olivares Alfa (33°110 S, 70°130 W), central Chilean Andes. Using a 50 MHz radar mounted onto a helicopter platform, data were collected covering large portions of the glacier accumulation and ablation zones. The radar data revealed boundaries of a temperate-ice layer at the base of the eastern body of Glaciar Olivares Alfa which appears to be covered by colder ice that extends throughout large parts of the glacier. The thickness of the temperate ice layer is highly variable across the glacier, being on average 40% of the total ice thickness. Radar data analyses reveal regions of cold ice at the bottom/base of the glacier and also patterns of highly saturated sediments beneath the glacier. Using GPR data, this study represents the most exhaustive analysis of glacier ice structure performed in the central Chilean Andes. The results will enable improved estimations of the glacier’s mass balance and ice dynamics, helping us to understand its further development and its impact on water availability.

This study provides an estimate of fresh water derived from ice melt for the ablation areas of glaciers in the Central Karakoram National Park (CKNP), Pakistan. In the CKNP there are ~700 glaciers, covering ~4600 km2, with widespread debris cover (518 km2). To assess meltwater volume we applied a distributed model able to describe both debris-covered and debris-free ice ablation. The model was calibrated using data collected in the field in the CKNP area and validated by comparison with ablation data collected in the field, independent of the data used in building the model. During 23 July–9 August 2011, the mean model-estimated ablation in the CKNP was 0.024 m w.e. d–1 in debris-covered areas and 0.037 m w.e. d–1 in debris-free areas. We found a mean error of +0.01 m w.e. (corresponding to 2%) and a root-mean-square error equal to 0.09 m w.e. (17%). According to our model, the ablation areas of all the glaciers in the CKNP produced a water volume of 1.963 km3 during the study period. Finally, we performed several sensitivity tests for assessing the impact of the input data variations.