Claude Duguay (University of Waterloo, Canada); Jennifer Fatt (University of Waterloo, Canada); Hayley Kavanagh (University of Waterloo, Canada)

The properties of ice-covered lakes, namely ice thickness and extent provide a proxy for monitoring climate and are an indicator of climate change. Changing snow patterns and quantity expected in Arctic regions may affect ice cover duration and thickness, indicating the need for better quantification of snow water equivalent (SWE) on lakes across the Northern Hemisphere. The Surface Water Ocean Topography (SWOT) mission offers the potential to retrieve ice thickness and snow parameters through the use of temporally coincident Ku-band altimetry and Ka-band Interferometric SAR (KaRIn), respectively. This project highlights two specific objectives, to 1) assess and improve the accuracy of freshwater ice thickness retrievals using Ku-band altimetry, and 2) quantify the influence of the snow cover overlaying lake ice on Ka-band pixel cloud product interferometric observations to aid in developing snow water equivalent (SWE) retrieval algorithms. While lake ice thickness has been shown to be possible using altimetry in the past, the added information of the overlying snow cover has commonly been assumed or a fitted parameter within thermodynamic modeling of lakes. This presentation highlights altimetry and KaRIn acquisitions on Kluane Lake, Yukon in winter seasons with contrasting snow regimes where some winters presented a considerable snowpack on the ice (2022-23, 2023-24), and others where the ice was nearly bare (2024-25). Variation in lake ice parameter retrieval capacity is also explored for SWOT’s Fast Sampling phase (1-day repeat) in 2023, and Science Data Collection phase (21 day repeat) in 2024.