First results of sea ice detection using GNSS-R data from the Chinese Tianmu-1 satellite constellation

Sea ice detection is crucial for climate monitoring and polar safety. This study evaluates the Chinese Tianmu-1 (TM-1) satellite constellation’s performance for sea ice detection using the Global Navigation Satellite System Reflectometry (GNSS-R) technique, which offers all-weather capabilities at lower costs compared to active microwave approaches like Synthetic Aperture Radar (SAR). Previous satellite-based detection methods were limited by coverage and temporal resolution. The TM-1 constellation, operational since 2023, addresses these limitations. We developed a convolutional neural network algorithm for sea ice detection and conducted a 10-month experiment (from 1 June 2023 to 29 March 2024) in the Arctic and Antarctic regions. Results show that the coverage rate increased as TM-1 satellites grew from 6 to 23 units, ultimately reaching 60% coverage in both polar regions. When verified against the Sea Ice Edge (SIE) products from the Ocean and Sea Ice Satellite Application Facility (OSI SAF), detection accuracy averaged 96.70% in the Arctic and 97.05% in the Antarctic. The detection results successfully captured seasonal sea ice changes, though the open ice proportion significantly affected accuracy. This study demonstrates that the TM-1 constellation provides an effective solution for continuous high-coverage polar sea ice monitoring, enhancing climate research capabilities and polar navigation safety.