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Holocene rockwall retreat rates quantify integral values of rock slope erosion and talus cone evolution. Here we investigate Holocene rockwall retreat of exposed arctic sandstone cliffs in Longyeardalen, central Svalbard and apply laboratory‐calibrated electrical resistivity tomography (ERT) to determine talus sediment thickness. Temperature–resistivity functions of two sandstone samples are measured in the laboratory and compared with borehole temperatures from the talus slope. The resistivity of the higher and lower‐porosity sandstone at relevant borehole permafrost temperatures defines a threshold range that accounts for the lithological variability of the dominant bedrock and debris material. This helps to estimate the depth of the transition from higher resistivities of ice‐rich debris to lower resistivities of frozen bedrock in the six ERT transects. The depth of the debris–bedrock transition in ERT profiles is confirmed by a pronounced apparent resistivity gradient in the raw data plotted versus depth of investigation. High‐resolution LiDAR‐scanning and ERT subsurface information were collated in a GIS to interpolate the bedrock surface and to calculate the sediment volume of the talus cones. The resulting volumes were referenced to source areas to calculate rockwall retreat rates. The rock mass strength was estimated for the source areas. The integral rockwall retreat rates range from 0.33 to 1.96 mm yr–1, and are among the highest rockwall retreat rates measured in arctic environments, presumably modulated by harsh environmental forcing on a porous sandstone rock cliff with a comparatively low rock mass strength. Here, we show the potential of laboratory‐calibrated ERT to provide accurate estimates of rockwall retreat rates even in ice‐rich permafrost talus slopes. Copyright © 2012 John Wiley & Sons, Ltd.

Knowledge of the spatio-temporal occurrence of avalanche activity is critical for avalanche forecasting. We present a near-real time automatic avalanche monitoring system that outputs detected avalanche polygons within roughly 10 min after Sentinel-1 SAR data are download. Our avalanche detection algorithm has an average probability of detection (POD) of 67.2% with a false alarm rate (FAR) averaging 45.9, with a maximum POD of over 85% and a minimum FAR of 24.9% compared to manual detection of avalanches. The high variability in performance stems from the dynamic nature of snow in the Sentinel-1 data. After tuning parameters of the detection algorithm, we processed five years of Sentinel-1 images acquired over a 150 × 100 km large area in Northern Norway, with the best setup. Compared to a dataset of field-observed avalanches, 77.3% were manually detectable. Using these manual detections as benchmark, the avalanche detection algorithm achieved an accuracy of 79% with high POD in cases of medium to large wet snow avalanches. For the first time, we present a dataset of spatio-temporal avalanche activity over several winters from a large region. Currently, the Norwegian Avalanche Warning Service is using our processing system for pre-operational use in three regions in Norway.

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Abstract. Cornice fall avalanches endanger life and infrastructure in Nybyen, a part of Svalbard's main settlement Longyearbyen, located at 78 • N in the High Arctic. Thus, cornice dynamics -accretion, cracking and eventual failure -and their controlling meteorological factors were studied along the ridgeline of the Gruvefjellet plateau mountain above Nybyen in the period 2008-2010. Using two automatic time-lapse cameras and hourly meteorological data in combination with intensive field observations on the Gruvefjellet plateau, cornice process dynamics were investigated in larger detail than previously possible. Cornice accretion starts directly following the first snowfall in late September and October, and proceeds throughout the entire snow season under a wide range of air temperature conditions that the maritime winter climate of Svalbard provides. Cornice accretion is particularly controlled by distinct storm events, with a prevailing wind direction perpendicular to the ridge line and average wind speeds from 12 m s −1 . Particularly high wind speeds in excess of 30 m s −1 towards the plateau ridgeline lead to cornice scouring and reduce the cornice mass both vertically and horizontally. Induced by pronounced air temperature fluctuations which might reach above freezing and lead to midwinter rainfall events, tension cracks develop between the cornice mass and the plateau. Our measurements indicate a linear crack opening due to snow creep and tilt of the cornice around a pivot point. Four to five weeks elapsed between the first observations of a cornice crack until cornice failure. Throughout the two snow seasons studied, 180 cornice failures were recorded, of which 70 failures were categorized as distinctive cornice fall avalanches. A clear temporal pattern with the majority of cornice failures in June was found. Thus only daily air temperature could determine avalanche from nonavalanche days. Seven large cornice fall avalanches reached the avalanche fans on which the Nybyen settlement is located. The size of the avalanches was primarily determined by the size of the cornice that detached. The improved process understanding of the cornice dynamics provides a first step towards a better predictability of this natural hazard, but also highlights that any type of warning based on meteorological factors is not an adequate measure to ensure safety of the housing at risk.

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On 11 April 2016 we observed high slushflow and wet snow avalanche activity at the environmental monitoring station Kobbefjord in W-Greenland. Snow avalanches released as a result of snow wetting induced by rain-on-snow in combination with a strong rise in air temperature. We exploit high-resolution satellite imagery covering pre-and post-event conditions for avalanche quantification and show that nearly 800 avalanches were triggered during this cycle. The nature of this extraordinary event is put into a longer temporal context by analysing several years of meteorological data and time-lapse imagery. We find that no event of similar size has occurred during the past 10 years of intense environmental monitoring in the study area. Meteorological reanalysis data reveal consistent relevant weather patterns for potential rain-on-snow events in the study area being warm fronts from Southwest with orographic lifting processes that triggered heavy precipitation.