A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity
Finding relevant microstructural parameters beyond density is a longstanding problem which hinders the formulation of accurate parameterizations of physical properties of snow. Towards a remedy, we address the effective thermal conductivity tensor of snow via anisotropic, second-order bounds. The bo...
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ftdoajarticles:oai:doaj.org/article:47be930c8410438cab4f4d39235cb6c5 2023-05-15T18:32:30+02:00 A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity H. Löwe F. Riche M. Schneebeli 2013-09-01T00:00:00Z https://doi.org/10.5194/tc-7-1473-2013 https://doaj.org/article/47be930c8410438cab4f4d39235cb6c5 EN eng Copernicus Publications http://www.the-cryosphere.net/7/1473/2013/tc-7-1473-2013.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-7-1473-2013 1994-0416 1994-0424 https://doaj.org/article/47be930c8410438cab4f4d39235cb6c5 The Cryosphere, Vol 7, Iss 5, Pp 1473-1480 (2013) Environmental sciences GE1-350 Geology QE1-996.5 article 2013 ftdoajarticles https://doi.org/10.5194/tc-7-1473-2013 2022-12-31T00:27:35Z Finding relevant microstructural parameters beyond density is a longstanding problem which hinders the formulation of accurate parameterizations of physical properties of snow. Towards a remedy, we address the effective thermal conductivity tensor of snow via anisotropic, second-order bounds. The bound provides an explicit expression for the thermal conductivity and predicts the relevance of a microstructural anisotropy parameter Q , which is given by an integral over the two-point correlation function and unambiguously defined for arbitrary snow structures. For validation we compiled a comprehensive data set of 167 snow samples. The set comprises individual samples of various snow types and entire time series of metamorphism experiments under isothermal and temperature gradient conditions. All samples were digitally reconstructed by micro-computed tomography to perform microstructure-based simulations of heat transport. The incorporation of anisotropy via Q considerably reduces the root mean square error over the usual density-based parameterization. The systematic quantification of anisotropy via the two-point correlation function suggests a generalizable route to incorporate microstructure into snowpack models. We indicate the inter-relation of the conductivity to other properties and outline a potential impact of Q on dielectric constant, permeability and adsorption rate of diffusing species in the pore space. Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles The Cryosphere 7 5 1473 1480 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
spellingShingle |
Environmental sciences GE1-350 Geology QE1-996.5 H. Löwe F. Riche M. Schneebeli A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
Finding relevant microstructural parameters beyond density is a longstanding problem which hinders the formulation of accurate parameterizations of physical properties of snow. Towards a remedy, we address the effective thermal conductivity tensor of snow via anisotropic, second-order bounds. The bound provides an explicit expression for the thermal conductivity and predicts the relevance of a microstructural anisotropy parameter Q , which is given by an integral over the two-point correlation function and unambiguously defined for arbitrary snow structures. For validation we compiled a comprehensive data set of 167 snow samples. The set comprises individual samples of various snow types and entire time series of metamorphism experiments under isothermal and temperature gradient conditions. All samples were digitally reconstructed by micro-computed tomography to perform microstructure-based simulations of heat transport. The incorporation of anisotropy via Q considerably reduces the root mean square error over the usual density-based parameterization. The systematic quantification of anisotropy via the two-point correlation function suggests a generalizable route to incorporate microstructure into snowpack models. We indicate the inter-relation of the conductivity to other properties and outline a potential impact of Q on dielectric constant, permeability and adsorption rate of diffusing species in the pore space. |
format |
Article in Journal/Newspaper |
author |
H. Löwe F. Riche M. Schneebeli |
author_facet |
H. Löwe F. Riche M. Schneebeli |
author_sort |
H. Löwe |
title |
A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity |
title_short |
A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity |
title_full |
A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity |
title_fullStr |
A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity |
title_full_unstemmed |
A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity |
title_sort |
general treatment of snow microstructure exemplified by an improved relation for thermal conductivity |
publisher |
Copernicus Publications |
publishDate |
2013 |
url |
https://doi.org/10.5194/tc-7-1473-2013 https://doaj.org/article/47be930c8410438cab4f4d39235cb6c5 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 7, Iss 5, Pp 1473-1480 (2013) |
op_relation |
http://www.the-cryosphere.net/7/1473/2013/tc-7-1473-2013.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-7-1473-2013 1994-0416 1994-0424 https://doaj.org/article/47be930c8410438cab4f4d39235cb6c5 |
op_doi |
https://doi.org/10.5194/tc-7-1473-2013 |
container_title |
The Cryosphere |
container_volume |
7 |
container_issue |
5 |
container_start_page |
1473 |
op_container_end_page |
1480 |
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1766216609362345984 |