Estimating thermal conductivity of snow, firn, and porous ice is key for modeling the thermal regime of alpine and polar glaciers. Whereas thermal conductivity of snow was widely investigated, studies on firn and porous ice are very scarce. This study presents the effective thermal conductivity tensor computed from 64 3‐D images of microstructures of snow, antarctic firn, and porous ice at −3, −20, and −60°C. We show that, in contrast with snow, conductivity of firn and porous ice correlates linearly with density, is approximately isotropic, and is largely impacted by temperature. We report that performances of commonly used estimates of thermal conductivity vary largely with density. In particular, formulas designed for snow lead to significant underestimations when applied to denser ice structures. We present a new formulation to accurately estimate the thermal conductivity throughout the whole density range, from fresh snow to bubbly ice, and for any temperature conditions encountered in glaciers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.