ALBERT

Description: The mountainous and ice-free terrains of the maritime Antarctic generate complex mosaics of snow patches, ranging from tens to hundreds of metres. These can only be accurately mapped using high-resolution remote sensing. In this paper we evaluate the application of radar scenes from TerraSAR-X in High Resolution SpotLight mode for mapping snow patches at a test area on Fildes Peninsula (King George Island, South Shetlands). Snow-patch mapping and characterization of snow stratigraphy were conducted at the time of image acquisition on 12 and 13 January 2012. Snow was wet in all studied snow patches, with coarse-grain and rounded crystals showing advanced melting and with frequent ice layers in the snow pack. Two TerraSAR-X scenes in HH and VV polarization modes were analysed, with the former showing the best results when discriminating between wet snow, lake water and bare soil. However, significant overlap in the backscattering signal was found. Average wet-snow backscattering was −18.0 dB in HH mode, with water showing −21.1 dB and bare soil showing −11.9 dB. Single-band pixel-based and object-oriented image classification methods were used to assess the classification potential of TerraSAR-X SpotLight imagery. The best results were obtained with an object-oriented approach using a watershed segmentation with a support vector machine (SVM) classifier, with an overall accuracy of 92 % and Kappa of 0.88. The main limitation was the west to north-west facing snow patches, which showed significant error, an issue related to artefacts from the geometry of satellite imagery acquisition. The results show that TerraSAR-X in SpotLight mode provides high-quality imagery for mapping wet snow and snowmelt in the maritime Antarctic. The classification procedure that we propose is a simple method and a first step to an implementation in operational mode if a good digital elevation model is available.

Description: Relict and present-day periglacial features have been reported in the literature for the upper reaches of the High Atlas mountains, which is the highest range in North Africa (Djebel Toubkal – 4167 m a.s.l.). A lobate feature in the Irhzer Ikhibi south at 3800 m a.s.l. has been previously interpreted as an active rock glacier, but no measurements of ground or air temperatures are known to exist for the area. In order to assess the possible presence of permafrost, we analyse data from June 2015 to June 2016 from two air temperature measurement sites at 2370 and 3210 m a.s.l. and from four ground surface temperature (GST) sites at 3220, 3815, 3980 and 4160 m a.s.l. to characterize conditions along an altitudinal gradient along the Oued Ihghyghaye valley to the summit of the Djebel Toubkal. GSTs were collected at 1 h intervals, and the presence of snow cover at the monitoring sites was validated using Landsat 8 and Sentinel-2 imagery. Two field visits allowed for logger installation and collection and for assessing the geomorphological features in the area. The results show that snow plays a major role on the thermal regime of the shallow ground, inducing important spatial variability. The lowest site at 3220 m had a thermal regime characterized by frequent freeze–thaw cycles during the cold season but with few days of snow. When snow settled, the ground surface remained isothermal at 0 °C , indicating the absence of permafrost. The highest sites at 3980 and 4160 m a.s.l. showed very frequent freeze–thaw cycles and a small influence of the snow cover on GST, reflecting the lack of snow accumulation due to the wind-exposed settings on a ridge and on the summit plateau. The site located at 3815 m in the Irhzer Ikhibi south valley had a cold, stable thermal regime with GST varying from −4.5 to −6 °C from December to March, under a continuous snow cover. The site's location in a concave setting favours wind-driven snow accumulation and lower incoming solar radiation due to the shading effect of a ridge, inducing the conservation of a thick snow pack. The stable and low GSTs are interpreted as a strong indicator of the probable presence of permafrost at this site, which is an interpretation supported by the presence of lobate and arcuate features in the talus deposits. We present first results and further observations using geophysics, and borehole measurements are foreseen. This is the first time that probable permafrost has been reported from temperature observations in the mountains of North Africa.

Description: Permafrost is present within almost all of the Antarctic's ice-free areas, but little is known about spatial variations in permafrost temperatures except for a few areas with established ground temperature measurements. We modelled a temperature at the top of the permafrost (TTOP) for all the ice-free areas of the Antarctic mainland and Antarctic islands at 1 km2 resolution during 2000–2017. The model was driven by remotely sensed land surface temperatures and downscaled ERA-Interim climate reanalysis data, and subgrid permafrost variability was simulated by variable snow cover. The results were validated against in situ-measured ground temperatures from 40 permafrost boreholes, and the resulting root-mean-square error was 1.9 ∘C. The lowest near-surface permafrost temperature of −36 ∘C was modelled at Mount Markham in the Queen Elizabeth Range in the Transantarctic Mountains. This is the lowest permafrost temperature on Earth, according to global-scale modelling results. The temperatures were most commonly modelled between −23 and −18 ∘C for mountainous areas rising above the Antarctic Ice Sheet and between −14 and −8 ∘C for coastal areas. The model performance was good where snow conditions were modelled realistically, but errors of up to 4 ∘C occurred at sites with strong wind-driven redistribution of snow.

Description: Climate-induced warming of permafrost soils is a global phenomenon, with regional and site-specific variations which are not fully understood. In this context, a 2-D automated electrical resistivity tomography (A-ERT) system was installed for the first time in Antarctica at Deception Island, associated to the existing Crater Lake site of the Circumpolar Active Layer Monitoring – South Program (CALM-S) – site. This setup aims to (i) monitor subsurface freezing and thawing processes on a daily and seasonal basis and map the spatial and temporal variability in thaw depth and to (ii) study the impact of short-lived extreme meteorological events on active layer dynamics. In addition, the feasibility of installing and running autonomous ERT monitoring stations in remote and extreme environments such as Antarctica was evaluated for the first time. Measurements were repeated at 4 h intervals during a full year, enabling the detection of seasonal trends and short-lived resistivity changes reflecting individual meteorological events. The latter is important for distinguishing between (1) long-term climatic trends and (2) the impact of anomalous seasons on the ground thermal regime. Our full-year dataset shows large and fast temporal resistivity changes during the seasonal active layer freezing and thawing and indicates that our system setup can resolve spatiotemporal thaw depth variability along the experimental transect at very high temporal resolution. The largest resistivity changes took place during the freezing season in April, when low temperatures induce an abrupt phase change in the active layer in the absence of snow cover. The seasonal thawing of the active layer is associated with a slower resistivity decrease during October due to the presence of snow cover and the corresponding zero-curtain effect. Detailed investigation of the daily resistivity variations reveals several periods with rapid and sharp resistivity changes of the near-surface layers due to the brief surficial refreezing of the active layer in summer or brief thawing of the active layer during winter as a consequence of short-lived meteorological extreme events. These results emphasize the significance of the continuous A-ERT monitoring setup which enables detecting fast changes in the active layer during short-lived extreme meteorological events. Based on this first complete year-round A-ERT monitoring dataset on Deception Island, we believe that this system shows high potential for autonomous applications in remote and harsh polar environments such as Antarctica. The monitoring system can be used with larger electrode spacing to investigate greater depths, providing adequate monitoring at sites and depths where boreholes are very costly and the ecosystem is very sensitive to invasive techniques. Further applications may be the estimation of ice and water contents through petrophysical models or the calibration and validation of heat transfer models between the active layer and permafrost.

Description: Climate induced warming of permafrost soils is a global phenomenon, with regional and site-specific variations, which are not fully understood. In this context, a 2D automated electrical resistivity tomography (A-ERT) system was installed for the first time in Antarctica at Deception Island, associated to the existing Crater Lake site of the Circumpolar Active Layer Monitoring Network (CALM-S) I) to evaluate the feasibility of installing and running autonomous ERT monitoring stations in remote and extreme environments such as Antarctica, II) to monitor subsurface freezing and thawing processes on a daily and seasonal basis and to map the spatial and temporal variability of thaw depth, and III) to study the impact of short-lived extreme meteorological events on active layer dynamics. Measurements were repeated at 4-hour intervals during a full year, enabling the detection of seasonal trends, as well as short-lived resistivity changes reflecting individual meteorological events. The latter is important to distinguish between (1) long-term climatic trends and (2) the impact of anomalous seasons on the ground thermal regime. Our full-year dataset shows large and fast temporal resistivity changes during the seasonal active layer freezing and thawing and indicates that our system set-up can successfully map spatiotemporal thaw depth variability along the experimental transect at very high temporal resolution. Largest resistivity change took place during the freezing season in April when low temperatures induce an abrupt phase change in the active layer in the absence of a snow cover. The seasonal thawing of the active layer is associated with a slower resistivity decrease during October due to the presence of a snow cover and the corresponding zero-curtain effect. Detailed investigation of the daily resistivity variations reveals several periods with rapid and sharp resistivity changes of the near-surface layers due to the brief surficial refreezing of the active layer in summer or brief thawing of the active layer during winter as a consequence of short-lived meteorological extreme events. These results emphasize the significance of the continuous A-ERT monitoring set-up which enables to detect fast changes in the active layer during short-lived extreme meteorological events. Based on this first complete year-round A-ERT monitoring data set in Deception Island, we believe that this system shows high potential for autonomous applications in remote and harsh polar environments such as Antarctica.

Description: Permafrost is present under almost all of the Antarctic’s ice-free areas but little is known about spatial variations of permafrost temperatures outside a few areas with established ground temperature measurements. We modelled a temperature at the top of the permafrost (TTOP) for all the ice-free areas of Antarctic mainland and Antarctic Islands at 1 km2 resolution during 2000–2017. The model was driven by remotely-sensed land surface temperatures and down-scaled ERA-Interim climate reanalysis data and subgrid permafrost variability was simulated by variable snow cover. The results were validated against in-situ measured ground temperatures from 40 permafrost boreholes and the resulting root mean square error was 1.9 °C. The lowest near-surface permafrost temperature of −33 °C was modelled at Mount Markham in Queen Elizabeth Range in the Transantarctic Mountains. This is the lowest permafrost temperature on Earth according to the modelling results on global scale. The temperatures were most commonly modelled between −23 and −18 °C for mountainous areas rising above the Antarctic Ice Sheet and between −14 and −8 °C for coastal areas. The model performance was good where snow conditions were modelled realistically but errors of up to 4 °C can occur at sites with strong wind-driven redistribution of snow.