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Snow is the only component of the water cycle that does not have a dedicated earth observation mission. Snow impacts many sectors like the health and well-being of communities, the economy, and sustains ecosystems. Snow also contributes to many costly hazards like floods, droughts, and avalanches. The current lack of information on how much water is stored as snow (snow water equivalent, SWE), and how it varies in space and time, limits the hydrological, climate, and weather services provided by Environment and Climate Change Canada (ECCC). To address this knowledge gap, ECCC, the Canadian Space Agency (CSA) and Natural Resources Canada (NRCan) are working in partnership to advance the scientific and technical readiness for a Ku-band synthetic aperture radar (SAR) mission presently named the ‘Terrestrial Snow Mass Mission’ – TSMM. An observing concept capable of providing dual-polarization (VV/VH), moderate resolution (500 m), wide swath (~250 km), and high duty cycle (~25% SAR-on time) Ku-band radar measurements at two frequencies (13.5; 17.25 GHz) is under development. This Canadian radar mission will provide weekly coverage of the northern hemisphere with Ku-band SAR data, and coupled with modeled data in the Canadian Land Data Assimilation System (CaLDAS), will provide daily snow water equivalent data, to assist hydrological applications and decision-making. It has been proven that Ku-Band backscatter measurements are sensitive to SWE through the volume scattering of the signal by the snow microstructure. Radar measurements are also well known to be able to discriminate between wet and dry snow conditions.In this presentation, we will review recent progress at ECCC (supported by the mission science team and the international snow community). Key areas of ongoing development include:(1) The Ku-band radar SWE retrieval algorithm proof of concept, based on the use of physical snow modeling to provide initial estimates of snow microstructure which can effectively parameterize forward model simulations for prediction of snow volume scattering. (2) Improvements to radiative transfer modelling codes to improve computation efficiency.(3) Improvements to physical snow modeling in the Canadian land surface model Soil Vegetation Snow version 2 (SVS2).(4) Development of the capability for direct assimilation of Ku-band backscatter into environmental prediction systems at ECCC. (5) Segmentation of wet from dry snow based on the time evolution of radar backscatter.Testbed experiments in which snow physical modeling, SWE retrievals, and data assimilation are analyzed collectively are currently under development. These experiments will be facilitated by the TSMM simulator and will incorporate outputs from SVS2 and are supported by airborne and ground-based Ku-band radar measurements from national and international academic partners.