Thermal Conductivity of Snow, Firn, and Porous Ice From 3‐D Image‐Based Computations
Thermal Conductivity of Snow, Firn, and Porous Ice From 3‐D Image‐Based Computations
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基于 3D 图像计算的雪、冰和多孔冰的热导率
DOI：
10.1029/2019gl085228
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发表时间：
2019
影响因子：
5.2
通讯作者：
C. Geindreau
中科院分区：
文献类型：
--
作者：
N. Calonne;Lucas Milliancourt;A. Burr;A. Philip;C. L. Martin;F. Flin;C. Geindreau
估算雪、雪和多孔冰的导热率是模拟高山和极地冰川热状况的关键。虽然雪的导热性得到了广泛的研究，但对雪和多孔冰的研究却很少。这项研究提出了根据 -3、-20 和 -60°C 下的雪、南极冰和多孔冰的 64 个 3D 微观结构图像计算出的有效导热率张量。我们表明，与雪相反，冰和多孔冰的电导率与密度线性相关，近似各向同性，并且很大程度上受温度影响。我们报告说，常用的导热系数估计的性能随密度的变化很大。特别是，当应用于更密集的冰结构时，为雪设计的公式会导致严重低估。我们提出了一种新的公式，可以准确估计整个密度范围（从新雪到气泡冰）以及冰川中遇到的任何温度条件的导热率。
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.