Intercomparison and Validation of SAR-Based Ice Velocity Measurement Techniques within the Greenland Ice Sheet CCI Project

Ice velocity is one of the products associated with the Ice Sheets Essential Climate Variable. This paper describes the intercomparison and validation of ice-velocity measurements carried out by several international research groups within the European Space Agency Greenland Ice Sheet Climate Change Initiative project, based on space-borne Synthetic Aperture Radar (SAR) data. The goal of this activity was to survey the best SAR-based measurement and error characterization approaches currently in practice. To this end, four experiments were carried out, related to different processing techniques and scenarios, namely differential SAR interferometry, multi aperture SAR interferometry and offset-tracking of incoherent as well as of partially-coherent data. For each task, participants were provided with common datasets covering areas located on the Greenland ice-sheet margin and asked to provide mean velocity maps, quality characterization and a description of processing algorithms and parameters. The results were then intercompared and validated against GPS data, revealing in several cases significant differences in terms of coverage and accuracy. The algorithmic steps and parameters influencing the coverage, accuracy and spatial resolution of the measurements are discussed in detail for each technique, as well as the consistency between quality parameters and validation results. This allows several recommendations to be formulated, in particular concerning procedures which can reduce the impact of analyst decisions, and which are often found to be the cause of sub-optimal algorithm performance

Surface velocity of the Northeast Greenland Ice Stream (NEGIS): assessment of interior velocities derived from satellite data by GPS

The Northeast Greenland Ice Stream (NEGIS) extends around 600 km upstream from the coast to its onset near the ice divide in interior Greenland. Several maps of surface velocity and topography of interior Greenland exist, but their accuracy is not well constrained by in situ observations. Here we present the results from a GPS mapping of surface velocity in an area located approximately 150 km from the ice divide near the East Greenland Ice-core Project (EastGRIP) deep-drilling site. A GPS strain net consisting of 63 poles was established and observed over the years 2015–2019. The strain net covers an area of 35 km by 40 km, including both shear margins. The ice flows with a uniform surface speed of approximately 55 m a^−1 within a central flow band with longitudinal and transverse strain rates on the order of 10−4 a^−1 and increasing by an order of magnitude in the shear margins. We compare the GPS results to the Arctic Digital Elevation Model and a list of satellite-derived surface velocity products in order to evaluate these products. For each velocity product, we determine the bias in and precision of the velocity compared to the GPS observations, as well as the smoothing of the velocity products needed to obtain optimal precision. The best products have a bias and a precision of ∼0.5 m a^−1. We combine the GPS results with satellite-derived products and show that organized patterns in flow and topography emerge in NEGIS when the surface velocity exceeds approximately 55 m a−1 and are related to bedrock topography

Autonomous Repeat Image Feature Tracking (autoRIFT) and Its Application for Tracking Ice Displacement

In this paper, we build on past efforts with regard to the implementation of an efficient feature tracking algorithm for the mass processing of satellite images. This generic open-source feature tracking routine can be applied to any type of imagery to measure sub-pixel displacements between images. The routine consists of a feature tracking module (autoRIFT) that enhances computational efficiency and a geocoding module (Geogrid) that mitigates problems found in existing geocoding algorithms. When applied to satellite imagery, autoRIFT can run on a grid in the native image coordinates (such as radar or map) and, when used in conjunction with the Geogrid module, on a user-defined grid in geographic Cartesian coordinates such as Universal Transverse Mercator or Polar Stereographic. To validate the efficiency and accuracy of this approach, we demonstrate its use for tracking ice motion by using ESA’s Sentinel-1A/B radar data (seven pairs) and NASA’s Landsat-8 optical data (seven pairs) collected over Greenland’s Jakobshavn Isbræ glacier in 2017. Feature-tracked velocity errors are characterized over stable surfaces, where the best Sentinel-1A/B pair with a 6 day separation has errors in X/Y of 12 m/year or 39 m/year, compared to 22 m/year or 31 m/year for Landsat-8 with a 16-day separation. Different error sources for radar and optical image pairs are investigated, where the seasonal variation and the error dependence on the temporal baseline are analyzed. Estimated velocities were compared with reference velocities derived from DLR’s TanDEM-X SAR/InSAR data over the fast-moving glacier outlet, where Sentinel-1 results agree within 4% compared to 3–7% for Landsat-8. A comprehensive apples-to-apples comparison is made with regard to runtime and accuracy between multiple implementations of the proposed routine and the widely-used “dense ampcor" program from NASA/JPL’s ISCE software. autoRIFT is shown to provide two orders of magnitude of runtime improvement with a 20% improvement in accuracy

Subglacial Drainage Evolution Modulates Seasonal Ice Flow Variability of Three Tidewater Glaciers in Southwest Greenland

B.J.D was funded in the form of a PhD studentship provided by the Scottish Association for Geosciences, Environment and Society (SAGES) and the University of St Andrews, UK. J.M.L is supported by a UKRI Future Leaders Fellowship (Grant No. MR/S017232/1). D.F would like to acknowledge the support of this work through the EPSRC and ESRC Centre for Doctoral Training on Quantification and Management of Risk and Uncertainty in Complex Systems Environments Grant No. (EP/L015927/1).Surface‐derived meltwater can access the bed of the Greenland Ice Sheet, causing seasonal velocity variations. The magnitude, timing and net impact on annual average ice flow of these seasonal perturbations depends on the hydraulic efficiency of the subglacial drainage system. We examine the relationships between drainage system efficiency and ice velocity, at three contrasting tidewater glaciers in southwest Greenland during 2014‐2019, using high‐resolution remotely sensed ice velocities, modelled surface melting, subglacial discharge at the terminus and results from buoyant plume modelling. All glaciers underwent a seasonal speed‐up, which usually coincided with surface melt‐onset, and subsequent slow‐down, which usually followed inferred subglacial channelisation. The amplitude and timing of these speed variations differed between glaciers, with the speed‐up being larger and more prolonged at our fastest study glacier. At all glaciers, however, the seasonal variations in ice flow are consistent with inferred changes in hydraulic efficiency of the subglacial drainage system, and qualitatively indicative of a flow regime in which annually‐averaged ice velocity is relatively insensitive to inter‐annual variations in meltwater supply – so‐called ‘ice flow self‐regulation’. These findings suggest that subglacial channel formation may exert a strong control on seasonal ice flow variations, even at fast‐flowing tidewater glaciers.Publisher PDFPeer reviewe