Monitoring of Key Climate Variables on Glaciers and Ice Sheets using Sentinel-1 SAR

The limited availability of Synthetic Aperture Radar (SAR) data over glaciers and ice sheets in the past, which formed a major obstacle for obtaining consistent climate data records, has been overcome by the Copernicus Sentinel-1 (S-1) mission, launched in 2014. S-1 SAR data in Greenland, Antarctica and other polar regions have since been regularly acquired every 6 to 12 days, allowing for the operational monitoring and time series analysis of key climate variables at a high spatial and temporal resolution. Exploiting the extensive archive of S-1 acquisitions, we have developed algorithms for retrieving dense time series of glacier and ice sheet velocities, ice discharge and surface melt processes, facilitated by the ESA Climate Change Initiative (ESA CCI), ESA Polar Science Cluster (ESA POLAR+) and EU Copernicus Climate Change Service (C3S) programs.

In order to improve existing ice velocity products, we have implemented an InSAR processing line for generation of high-resolution velocity fields from crossing orbits and included a tide correction module to the offset-tracking processing line which accounts for the vertical motion of floating ice shelves and ice tongues due to ocean tides and pressure differences. We present synergistic InSAR and offset tracking ice velocity products, derived from repeat pass S-1 Interferometric Wide (IW mode) swath data, for the Greenland Ice Sheet and report on the performance of the products using in-situ GPS data. Additionally, we show velocity variations of major outlet glaciers in Greenland and Antarctica and other polar ice bodies. The generated ice velocity maps, complemented with ice thickness and other Earth observation datasets, form the basis for deriving ice flow and discharge fluctuations and trends at sub-monthly to multi-annual time scales.

To evaluate snowmelt dynamics in Greenland and Antarctica, we have also developed an algorithm for generating maps of snowmelt extent based on multitemporal S-1 SAR and Advanced Scatterometer (ASCAT) data. The dense backscatter time series yields a unique temporal signature that is used to identify the different stages of the melt/freeze cycle and to estimate the melting intensity of the surface snowpack. The high-resolution melt maps form the main input for deriving value-added products on annual melt onset, ending and duration. Intercomparisons with in-situ weather station data and melt products derived from regional climate models (RCMs) and passive microwave radiometers confirm the ability of the algorithm to detect short-lived and longer melt events.

Our results demonstrate the excellent capability of the S-1 mission in combination with other sensors for comprehensive monitoring of key climate variables on glaciers and ice sheets, providing essential input for various applications such as ice dynamic and climate modelling.