Generating large-scale sea ice motion from Sentinel-1 and the RADARSAT Constellation Mission using the Environment and Climate Change Canada automated sea ice tracking system

• Published in: The Cryosphere
• Main Authors: Howell, Stephen E. L., Brady, Mike, Komarov, Alexander S.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2022
• Subjects: article; Verlagsveröffentlichung; Arctic; Bering Sea; Canada; Canadian Arctic Archipelago; Hudson; Hudson Bay; North Pole; Arctic Archipelago; Beaufort Sea; Climate change; Davis Strait; National Snow and Ice Data Center; Sea ice; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-16-1125-2022; https://noa.gwlb.de/receive/cop_mods_00060495; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00060124/tc-16-1125-2022.pdf; https://tc.copernicus.org/articles/16/1125/2022/tc-16-1125-2022.pdf

As Arctic sea ice extent continues to decline, remote sensing observations are becoming even more vital for the monitoring and understanding of sea ice. Recently, the sea ice community has entered a new era of synthetic aperture radar (SAR) satellites operating at C-band with the launch of Sentinel-1A in 2014 and Sentinel-1B (S1) in 2016 and the RADARSAT Constellation Mission (RCM) in 2019. These missions represent five spaceborne SAR sensors that together routinely cover the pan-Arctic sea ice domain. Here, we describe, apply, and validate the Environment and Climate Change Canada automated sea ice tracking system (ECCC-ASITS) that routinely generates large-scale sea ice motion (SIM) over the pan-Arctic domain using SAR images from S1 and RCM. We applied the ECCC-ASITS to the incoming image streams of S1 and RCM from March 2020 to October 2021 using a total of 135 471 SAR images and generated new SIM datasets (7 d 25 km and 3 d 6.25 km) by combining the image stream outputs of S1 and RCM (S1 + RCM). Results indicate that S1 + RCM SIM provides more coverage in the Hudson Bay, Davis Strait, Beaufort Sea, Bering Sea, and directly over the North Pole compared to SIM from S1 alone. Based on the resolvable S1 + RCM SIM grid cells, the 7 d 25 km spatiotemporal scale is able to provide the most complete picture of SIM across the pan-Arctic from SAR imagery alone, but considerable spatiotemporal coverage is also available from 3 d 6.25 SIM products. S1 + RCM SIM is resolved within the narrow channels and inlets of the Canadian Arctic Archipelago, filling a major gap from coarser-resolution sensors. Validating the ECCC-ASITS using S1 and RCM imagery against buoys indicates a root-mean-square error (RMSE) of 2.78 km for dry ice conditions and 3.43 km for melt season conditions. Higher speeds are more apparent with S1 + RCM SIM as comparison with the National Snow and Ice Data Center (NSIDC) SIM product and the Ocean and Sea Ice Satellite Application Facility (OSI SAF) SIM product indicated an RMSE of u=4.6 km d−1 and v=4.7 km d−1 for the NSIDC and u=3.9 km d−1 and v=3.9 km d−1 for OSI SAF. Overall, our results demonstrate the robustness of the ECCC-ASITS for routinely generating large-scale SIM entirely from SAR imagery across the pan-Arctic domain.