Spatiotemporal fusion of radar backscatter for enhanced monitoring of surface melt dynamics over Antarctic ice shelves

Surface meltwater over the Antarctic Ice Sheet acts as a primary modulator of the polar energy budget, potentially triggering ice shelf collapse and exerting far-reaching impacts on the global climate system. Radar scatterometers enable daily melt detection but at coarse resolution, whereas Synthetic Aperture Radar (SAR) achieves fine spatial detail with limited temporal coverage. Spatiotemporal fusion methods present a viable solution to balance this trade-off, but these approaches are applied only to optical remote sensing and have not yet been successfully adapted to radar backscatter data. In this study, we propose the Spatiotemporal Radar Backscatter Data Fusion (SRBDF) method, a multi-source C-band active microwave data fusion technique that can integrate Sentinel-1 and Advanced Scatterometer (ASCAT) observations. SRBDF generates a high-resolution daily backscatter dataset for monitoring surface melt dynamics at the Larsen C and George VI Ice Shelves throughout 2018–2021 melt seasons. The fused dataset preserves spatial details from Sentinel-1, while maintaining the daily frequency of ASCAT. Across the Larsen C and George VI Ice Shelves, SRBDF melt/freeze detection shows overall consistency approaching or above 0.90 with Sentinel-1 and ASCAT. High-resolution daily observations reveal an extreme melt season during 2019–2020, when melt occurrence was more than 50 % above the previous season. Pronounced melt was observed on Larsen C and George VI ice shelves driven by foehn winds and sustained warm air advection from low-speed northerly winds, respectively. These results demonstrate the effectiveness of SRBDF in capturing Antarctic ice shelf surface melt variability and its potential for broader applications in polar surface process research.