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Airborne electromagnetic induction sensors have demonstrated their extensive capacities to measure sea-ice thickness distributions. However, biases can emerge when comparing these 1-D measurements to a broader 2-D regional scale due to the spatial anisotropy inherent to sea-ice cover. Automated processing of available sea-ice maps could significantly ease the decision on how to set up an optimised flight pattern, which would result in representative ice thickness numbers for the region. In this study, first we investigate the extent to which the sea-ice anisotropy can influence the representativeness of an airborne survey compared to the regional situation. Second, we propose a method to process sea-ice maps prior to flights to help preparing the most representative flight plan possible for the local area. The method is based on automated segmentation of radar satellite images and extensive simulation of flight transects over the image. The spatial analysis of these transects enables for the identification of the most representative survey trajectories for the area. The method was applied for seven different synthetic aperture radar satellite images over Arctic sea ice north of Svalbard. The results indicate that the proposed method improved the representativeness of the airborne survey by identifying the most suitable transect over the ice pack. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) satellite images are used to monitor Arctic sea ice, with systematic data records dating back to 1991. We propose a semi-supervised classification method that separates open water from sea ice and can utilise ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1 SAR images. The classification combines automatic segmentation with a manual segment selection stage. The segmentation algorithm requires only the backscatter intensities and incidence angle values as input, therefore can be used to establish a consistent decadal sea ice record. In this study we investigate the sea ice conditions in two Svalbard fjords, Kongsfjorden and Rijpfjorden. Both fjords have a seasonal ice cover, though Rijpfjorden has a longer sea ice season. The satellite image dataset has weekly to daily records from 2002 until now, and less frequent records between 1991 and 2002. Time overlap between different sensors is investigated to ensure consistency in the reported sea ice cover. The classification results have been compared to high-resolution SAR data as well as in-situ measurements and sea ice maps from Ny-Ålesund. For both fjords the length of the sea ice season has shortened since 2002 and for Kongsfjorden the maximum sea ice coverage is significantly lower after 2006. [ABSTRACT FROM AUTHOR]

Research on young thin sea ice is essential to understand the changes in the Arctic. But it is also the most challenging to investigate, both in situ and from satellites. If satellite remote-sensing techniques are developing rapidly, fieldwork remains crucial for the mandatory validation of such data. In April 2016, an Arctic fieldwork campaign was conducted at Kongsfjorden, Svalbard. This campaign provided an opportunity to combine various techniques to record the fjord ice properties ranging from local field sampling to broader ground-based and satellite radar remote sensing of the fjord. Tracking the boat used to access the field sites with hand-held GPS devices offered a good opportunity to map fjord ice and assess the limits of radar identification of small icebergs and thin ice. During 1 week, 17 icebergs and the thin ice edges in two different locations were mapped. The GPS tracks present a good agreement with the Radarsat-2 data analysis for one of the two ice edges. The second ice edge track only partly corresponds to the radar scene. Ice movement, recorded by a ground-based radar, is likely to explain this result. Grounded icebergs could be identified in both Radarsat-2 and ground-based radar. [ABSTRACT FROM AUTHOR]

Knowledge of Arctic sea-ice conditions is of great interest for Arctic residents, as well as for commercial usage, and to study the effects of climate change. Information gained from analysis of satellite data contributes to this understanding. In the course of using in situ data in combination with remotely sensed data, the question of how representative local scale measurements are of a wider region may arise. We compare in situ total sea-ice thickness measurements from the Norwegian young sea ICE expedition in the area north of Svalbard with airborne-derived total sea-ice thickness from electromagnetic soundings. A segmented and classified synthetic aperture radar (SAR) quad-pol ALOS-2 Palsar-2 satellite scene was grouped into three simplified ice classes. The area fractions of the three classes are: 11.2% ‘thin’, 74.4% ‘level’, and 14.4% ‘deformed’. The area fractions of the simplified classes from ground- and helicopter-based measurements are comparable with those achieved from the SAR data. Thus, this study shows that there is potential for a stepwise upscaling from in situ, to airborne, to satellite data, which allow us to assess whether in situ data collected are representative of a wider region as observed by satellites. [ABSTRACT FROM AUTHOR]

We present sea-ice surface roughness estimates, i.e. the standard deviation of relative surface elevation, in the Arctic regions of Fram Strait and the Nansen Basin north of Svalbard acquired by an airborne laser scanner and a single-beam laser altimeter in 2010. We compare the scanner to the altimeter and compare the differences between the two survey regions. We estimate and correct sensor roll from the scanner data using the hyperbolic response of the scanner over a flat surface. Measurement surveys had to be longer than 5 km north of Svalbard and longer than 15 km in Fram Strait before the statistical distribution in surface roughness from the scanner and altimeter became similar. The shape of the surface roughness probability distributions agrees with those of airborne electromagnetic induction measurements of ice thickness. The ice in Fram Strait had a greater mean surface roughness, 0.16 m vs 0.09 m, and a wider distribution in roughness values than the ice in the Nansen Basin. An increase in surface roughness with increasing ice thickness was observed over fast ice found in Fram Strait near the coast of Greenland but not for the drift ice. [ABSTRACT FROM AUTHOR]

Variability of sea-ice and snow conditions on the scale of a few hundred meters is examined using in situ measurements collected in first-year pack ice in the European Arctic north of Svalbard. Snow thickness and surface elevation measurements were performed in the standard manner using a snow stick and a rotating laser. Altogether, 4109m of measurement lines were surveyed. The snow loading was large, and in many locations the ice freeboard was negative (38.8% of snowline measurements), although the modal ice and snow thickness was 1.8m. The mean of all the snow thickness measurements was 36 cm, with a standard deviation of 26 cm. The mean freeboard was only 3 cm, with a standard deviation of 23 cm. There were noticeable differences in snow thickness among the measurement sites. Over the undeformed ice areas, the mean snow thickness and freeboard were 23 and 2.4 cm, respectively. Over the ridged ice areas, the mean freeboard was only -0.3 cm due to snow accumulation on the sails of ridges (average thickness 54 cm). These findings imply that retrieval algorithms for converting freeboard to ice thickness should take account of spatial variability of snow cover. [ABSTRACT FROM AUTHOR]

The large-scale thickness distribution of sea ice was measured during several campaigns in the European Arctic north of Svalbard from 2007 using an airborne electromagnetic induction device. In August 2010 and April-May 2011, this was complemented by extensive on-ice work including measurements of snow thickness and freeboard. Ice thicknesses show a clear difference between the seasons, with thicker ice during spring than in summer. In spring 2011, negative freeboard and flooding were observed as a result of the extensive snow cover. We find that the characteristics of the first-year sea ice allow combining observations from different years. The ice thickness in the marginal ice zone increases with increasing latitude and increasing distance to the ice edge; however, in the inner ice pack from ~100 km from the ice edge the thickness remains almost constant. Modal ice thickness in spring reaches 2.4m whereas in summer it is 1.0-1.4m. Our study provides new insight into ice thickness distributions of a typical ice cover consisting of mainly first- and second-year ice, which may become the dominant ice type in the Arctic in the future. [ABSTRACT FROM AUTHOR]

Rijpfjorden (80° N, 22° E) is a high-Arctic fjord on Nordaustlandet in the Svalbard archipelago. To monitor the thermodynamic change of sea ice in spring, an ice mass-balance buoy (IMB) was deployed for 2.5 months (10 April-26 June 2011), with accompanying in situ measurements, sea-ice sampling on three occasions and ice-core analysis. Uncertainties and sources of error in in situ measurements and IMB data are discussed. The in situ measurements, ice-core analysis and IMB data together depict the development of snow and ice in spring. Snow and ice thickness exhibited large spatial and temporal variability. After relatively stable conditions with only little change in ice thickness and accumulation of snow, a layer of superimposed ice ~0.06m thick formed at the snow–ice interface due to refreezing of snow meltwater in late spring. Ice thickness (except for growth of superimposed ice) did not change significantly based on in situ observations. In contrast, the under-ice sonar data from the IMB show reflections from a layer deeper than the underside of the ice during the melting phase. This can be explained as a reflection of the sonar pulses from an interface between a freshwater layer under the ice and more saline water below, or as a false-bottom formation. [ABSTRACT FROM AUTHOR]