Seismic constraints on glacier density

Terrestrial ice bodies are important regulators of climate and sea level variations. They influence the water cycle, provide fresh water and energy for human society, and contribute to the living basis of numerous ecosystems. Understanding the structure and dynamics of land ice requires knowledge of its mass density, which is essential for ice core climatology and estimates of mass balance components, such as mass loss, ice discharge and surface melt. We combine densely sampled fiber-optic sensing data from strong serendipitous anthropogenic sources with Hamiltonian Monte Carlo sampling to extract direct seismic constraints on firn density (i.e. the transitional layer between fresh snow and glacial ice). Our approach avoids biases introduced by subjective regularization choices, does not require empirical scaling relations from seismic wave speeds to density, and provides reliable uncertainty estimates. We demonstrate that high-quality surface-wave overtone data can directly constrain density to around 100 m depth. Commonly used scaling relations from seismic wave speeds to density, however, fail to reproduce resolvable details of glacial density structure, and they tend to deviate from direct constraints on the order of ±10 %. Consequently, ice mass inferred from seismic wave speed may be incorrect by a similar amount.