Abstract:The Terrain Observation by Progressive Scans (TOPS) acquisition mode of the Sentinel-1 mission provides a wide coverage per acquisition with resolutions of 5 m in range and 20 m in azimuth, which makes this acquisition mode attractive for glacier velocity monitoring. Here, we retrieve surface velocities from the southern Ellesmere Island ice caps (Canadian Arctic) using both offset tracking and Differential Interferometric Synthetic Aperture Radar (D-InSAR) techniques and combining ascending and descending passes. We optimise the offset tracking technique by omitting the azimuth offsets. By doing so, we are able to improve the final resolution of the velocity product, as Sentinel-1 shows a lower resolution in the azimuth direction. Simultaneously, we avoid the undesired ionospheric effect manifested in the data as azimuth streaks. The D-InSAR technique shows its merits when applied to slow-moving areas, while offset tracking is more suitable for fast-moving areas. This research shows that the methods used here are complementary and the use of both to determine glacier velocities is better than only using one or the other. We observe glacier surface velocities of up to 1200 m year −1 for the fastest tidewater glaciers. The land-terminating glaciers show typical velocities between 12 and 33 m year −1 , though with peaks up to 150 m year −1 in narrowing zones of the confining valleys.

We present a first version of the Svalbard ice‐free topography (SVIFT1.0) using a mass conserving approach for mapping glacier ice thickness. SVIFT1.0 is informed by more than 1 million point measurements, totalling more than 8,700 km of thickness profiles. SVIFT1.0 is publicly available and represents the geometric state around the year 2010. Our estimate for the total ice volume is 6,199 km3, equivalent to 1.5‐cm sea level rise. The thickness map suggests that 13% of the glacierized area is grounded below sea level. A complementary map of error estimates comprises uncertainties in the thickness surveys as well as in other input variables. Aggregated error estimates are used to define a likely ice‐volume range of 5,200–7,300 km3. The ice front thickness of marine‐terminating glaciers is a key quantity for ice loss attribution because it controls the potential ice discharge by iceberg calving into the ocean. We find a mean ice front thickness of 135 m for the archipelago (likely range 123–158 m).

We determined ice velocities for the Academy of Sciences Ice Cap, Severnaya Zemlya, Russian Arctic, during November 2016–November 2017, by feature-tracking 54 pairs of Sentinel-1 synthetic-aperture radar images. Seasonal velocity variations with amplitudes up to 10% of the yearly-averaged velocity were observed. Shorter-term (<15 d) intra-annual velocity variations had average and maximum deviations from the annual mean of up to 16 and 32%, respectively. This indicates the errors that could be incurred if ice discharge values determined from a single pair of images were extrapolated to the whole year. Average ice discharge for 2016–2017 was 1.93 ± 0.12 Gt a−1. The difference from an estimate of ~ 1.4 Gt a−1 for 2003–2009 was attributed to the initiation of ice stream flow in Basin BC. The total geodetic mass balance over 2012–2016 was − 1.72 ± 0.67 Gt a−1 (− 0.31 ± 0.12 m w.e. a−1). The climatic mass balance was not significantly different from zero, at 0.21 ± 0.68 Gt a−1 (0.04 ± 0.12 m w.e. a−1), and has remained near zero at decadal-scale for the last four decades. Therefore, the total mass balance has been controlled largely by variations in ice discharge, whose long-term changes do not appear to have responded to environmental changes but to the intrinsic characteristics of the ice cap governing tidewater glacier dynamics.

We analyse the various error sources in the estimation of ice discharge through flux gates, distinguishing the cases with ice-thickness data available for glacier cross-sections or only along the centreline. For the latter, we analyse the performance of three U-shaped cross-sectional approaches. We apply this methodology to glaciers of the Canadian High Arctic. The velocity field is the main error source for small and medium-size glaciers (discharge <100 Mt a−1) with low velocities (<100 m a−1), while for large glaciers (discharge >100 Mt a−1) with high velocities (>100 m a−1) the error in cross-sectional area dominates. Thinning/thickening between ice-thickness and velocity measurements should be considered, as it implies systematic errors up to 8% in our study. The U-shaped parabolic approach, which allows for an adjusted estimation when the ice-thickness measurement point is displaced from the glacier centreline, performs best, with small bias and admissible standard error. We observe an increase of ice discharge from the main glaciers (Trinity and Wykeham) of the Prince of Wales Icefield from 2015 to 2016, by 5 and 20%, respectively, followed by a decrease in 2017, by 10 and 15%, respectively. Belcher Glacier, of the Devon Ice Cap, maintains similar discharges during 2015–17.

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) missions are providing brightness temperature measurements at 1.4 GHz (L-band) for about 10 and 4 years respectively. One of the new areas of geophysical exploitation of L-band radiometry is on thin (i.e., less than 1 m) Sea Ice Thickness (SIT), for which theoretical and empirical retrieval methods have been proposed. However, a comprehensive validation of SIT products has been hindered by the lack of suitable ground truth. The in-situ SIT datasets most commonly used for validation are affected by one important limitation: They are available mainly during late winter and spring months, when sea ice is fully developed and the thickness probability density function is wider than for autumn ice and less representative at the satellite spatial resolution. Using Upward Looking Sonar (ULS) data from the Woods Hole Oceanographic Institution (WHOI), acquired all year round, permits overcoming the mentioned limitation, thus improving the characterization of the L-band brightness temperature response to changes in thin SIT. State-of-the-art satellite SIT products and the Cumulative Freezing Degree Days (CFDD) model are verified against the ULS ground truth. The results show that the L-band SIT can be meaningfully retrieved up to 0.6 m, although the signal starts to saturate at 0.3 m. In contrast, despite the simplicity of the CFDD model, its predicted SIT values correlate very well with the ULS in-situ data during the sea ice growth season. The comparison between the CFDD SIT and the current L-band SIT products shows that both the sea ice concentration and the season are fundamental factors influencing the quality of the thickness retrieval from L-band satellites.