Ice thickness and water level estimation for ice-covered lakes with satellite altimetry waveforms and backscattering coefficients

Abstract. Lake ice, serving as a sensitive indicator of climate change, is an important regulator regional hydroclimate and lake ecosystems. For ice-covered lakes, traditional satellite altimetry-based water level estimation often subject to winter anomalies that are closely related the thickening ice. Despite recent efforts made exploit altimetry data resolve two interrelated variables, i.e., ice thickness (LIT) several issues remain unsolved, including inability estimate LIT with altimetric backscattering coefficients in ungauged lakes due dependence on situ data. It still unclear what role surface snow plays retrieval levels Here we developed novel method by combining waveforms without using To overcome complicated initial conditions better represent thick conditions, logarithmic regression model was transform into LIT. We investigated differential impact estimating for when different threshold retracking methods used. The method, validated against cross-validated modeled LIT, shows accuracy ∼ 0.2 m effective at detecting thin cannot be retrieved waveforms. also improved strategy merging derived from methods. This study facilitates interpretation signals provides opportunities wider application cryosphere.