Claude Duguay (H2O Geomatics and University of Waterloo, Canada); Pierre Thibaut (CLS, France); Justin Murfitt (University of Waterloo, Canada); Samira Amraoui (CLS, France); Thomas Moreau (CLS, France); Craig Donlon (ESA-ESTEC, The Netherlands); Clement Albergel (ESA-ECSAT, UK); Jerome Bouffard (ESA-ESRIN, Italy)

Lake ice thickness (LIT) is recognized as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). LIT is a sensitive indicator of weather and climate conditions through its dependency on changes in air temperature and on-ice snow depth. The monitoring of seasonal variations and trends in ice thickness is not only important from a climate change perspective, but it is also relevant for the operation of winter ice roads that northern communities rely on. Yet, field measurements tend to be sparse in both space and time, and many northern countries have seen an erosion of in situ observational networks over the last three decades. Therefore, there is a pressing need to develop retrieval algorithms from satellite remote sensing to provide consistent, broad-scale and regular monitoring of LIT at northern high latitudes in the face of climate change.

This talk presents a novel, physically-based retracking approach for the estimation of LIT by using conventional low-resolution mode (LRM) and synthetic aperture radar (SAR) Ku-band radar altimetry data on both unfocused and fully-focused modes. Details will be provided about the formalism of the LRM and the SAR retracking methods and on the assessment of the retrieved ice thickness by using thermodynamical simulations. The results presented will focus on the LIT estimation obtained using Jason-1-2-3, and Sentinel-6 data over the Great Slave Lake (GSL) and the Baker lake (Canada). The first long LIT timeseries (more than 20 years) obtained with radar altimetry data over the GSL will be presented. These data are generated within the ESA CCI Lakes project and will be released in the fall 2023. The talk will highlight how these methods significantly improve the accuracy of the LIT estimations, paving the way towards regular and robust LIT monitoring with current and future LRM and SAR altimetry missions.

The LRM_LIT algorithm has been developed in the framework of the European Space Agency’s Climate Change Initiative (CCI+) Lakes project and is currently implemented to produce LIT time series from LRM data. These data will be publicly available to the scientific community through a dedicated data platform, following the project schedule. The SAR_LIT and the FFSAR_LIT algorithms are developed within the ESA S6JTEX project that aims at enhancing the scientific return of the tandem phase between the Jason-3 and Sentinel-6 reference missions, allowing for continuity of observations across 30 years between conventional altimetry and SAR altimetry data. Finally, the SAR LIT retrackers will be tailored for the future CRISTAL mission within the ESA CLE2VER project.