Seasonal Variability of Snow Cover and Impact on Albedo and Thermal Properties in the Antarctic Marginal Ice Zone

TL;DR

This study examines how seasonal changes in snow cover affect the albedo and energy fluxes of Antarctic sea ice, revealing that detailed snow modeling improves climate predictions.

Contribution

It introduces a fractional snow cover approach that better captures surface heterogeneity, improving the accuracy of sea ice energy balance models.

Findings

Modest snow fractions significantly increase surface reflectivity.

Simplified binary snow assumptions cause biases in flux estimates.

Explicit fractional snow modeling reveals nonlinear surface responses.

Abstract

Snow cover plays a critical yet often underrepresented role in shaping the thermodynamic behavior of Antarctic sea ice. In this study, we investigate the seasonal variability of snow distribution and its impact on surface albedo and energy fluxes across the marginal ice zone (MIZ), using a unique dataset from five shipborne expeditions conducted between 2019 and 2024. High-resolution visible and infrared imagery, combined with field observations and meteorological data, reveal that even modest snow fractions substantially increase surface reflectivity and suppress conductive heat transfer. Our results demonstrate that simplified binary assumptions-such as assigning dry snow in winter and bare ice in summer-systematically misrepresent surface conditions, introducing significant biases in modelled radiative and turbulent fluxes. By explicitly resolving fractional snow cover, we show that surface albedo and energy exchange respond nonlinearly to snow-ice composition, with implications for sea ice growth, melt, and climate feedbacks. These findings advocate for a revision of current model parameterizations, emphasizing the need for multi-component surface schemes that reflect the observed heterogeneity of the Antarctic MIZ.