Abstract.To better understand the spatio-temporal variability of the glaciological environment in Dronning Maud Land (DML), East Antarctica, a 2800-km-long Japanese-Swedish traverse was carried out. The route includes ice divides between two ice-coring sites at Dome Fuji and EPICA DML. We determined the surface mass balance (SMB) averaged over various time scales in the late Holocene based on studies of snow pits and firn cores, in addition to radar data. We find that the large-scale distribution of the SMB depends on the surface elevation and continentality, and that the SMB differs between the windward and leeward sides of ice divides for strong-wind events. We suggest that the SMB is highly influenced by interactions between the large-scale surface topography of ice divides and the wind field of strong-wind events that are often associated with high-precipitation events. Local variations in the SMB are governed by the local surface topography, which is influenced by the bedrock topography. In the eastern part of DML, the accumulation rate in the second half of the 20th century is found to be higher by ∼15 % Correspondence to: S. Fujita (sfujita@nipr.ac.jp) than averages over longer periods of 722 a or 7.9 ka before AD 2008. A similar increasing trend has been reported for many inland plateau sites in Antarctica with the exception of several sites on the leeward side of the ice divides.

Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.Electronic supplementary materialThe online version of this article (doi:10.1007/s13280-016-0770-0) contains supplementary material, which is available to authorized users.

Maintaining long time series of observations of the Cryosphere is a key issue in climate research. Long observational time series involve problems due to change in methodology or observers. In order to extend time series and introduce new methods, careful comparisons must be made to ensure homogeneity in the observational data. We have compared an established method for snow grain-size observations used by the Abisko Scientific Research Station (ASRS) in northern Sweden, based on visual interpretation, with a newly developed method for Digital Snow Particle Properties (DSPP) analysis. Transition from subjective visual method into digital reproducible analysis creates less subjective and more comparable results. The ASRS method generates size classifications excluding quantitative analysis size ranges. By determining the sizes of the classified snow using the DSPP method, actual size ranges for classified snow can be established. By performing a digital analysis of the reference samples and the snow samples classified, we can compare the ASRS classification system to existing official classification systems. The results indicate underestimation of the visual particle size in comparison to the reference samples. Our results show how to quantify the historical data set, which enables us to perform quantitative analysis on the historical data set.

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ABSTRACT. We studied the variability of elemental carbon (EC) over 3 years in the winter snowpack of Storglaciären, Sweden. The goal of this study was to relate the seasonal variation in EC to specific snow accumulation events in order to improve understanding of how different atmospheric circulation patterns control the deposition of EC. Specifically, we related meteorological parameters (e.g. wind direction, precipitation) to snow physical properties, EC content, stable-isotope d d 18O ratios and anion concentrations in the snowpack. The distribution of EC in the snowpack varied between years. Low EC contents corresponded to a predominance of weather systems originating in the northwest, i.e. North Atlantic. Analysis of single layers within the snowpacks showed that snow layers enriched in heavy isotopes coincided predominantly with low EC contents but high chloride and sulfate concentration. Based on this isotopic and geochemical evidence, snow deposited during these events had a strong oceanic, i.e. North Atlantic, imprint. In contrast, snow layers with high EC content coincided with snow layers depleted in heavy isotopes but high anion concentrations, indicating a more continental source of air masses and origin of EC from industrial emissions.