Deterministic structures in functionals of Baikal ice deformations

This study investigates deterministic structures in statistical functionals derived from high-resolution measurements of Lake Baikal ice cover deformations preceding ice shocks - events caused by thermal expansion during spring warming. Understanding these precursors is essential for reliable forecasting in cryoseismology. Using statistical-functional analysis, the measured signals are decomposed into background noise and precursor-related components. Deterministic linear structures of the function, including channels and sliding boundaries, as well as short-term precursors lasting up to one hour, are identified. Spatially distributed measurements show high topological similarity of the statistical functionals preceding ice shocks. These findings demonstrate the effectiveness of nonlinear functional analysis in detecting early-warning signals and provide a framework for future studies on natural hazard prediction.