Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-4889-2018
https://doi.org/10.5194/gmd-11-4889-2018
Model description paper
 | 
06 Dec 2018
Model description paper |  | 06 Dec 2018

CVPM 1.1: a flexible heat-transfer modeling system for permafrost

Gary D. Clow

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Cited articles

Arctic Climate Impact Assessment: ACIA Overview Report, Cambridge University Press, Cambridge, 1020 pp., 2005. a
Anderson, D. A., Tannehill, J. C., and Pletcher, R. H.: Computational Fluid Mechanics and Heat Transfer, Hemisphere Publishing Corp., New York, 599 pp., 1984. a, b
Anderson, D. M., Tice, A. R., and McKim, H. L.: The unfrozen water and the apparent specific heat capacity of frozen soils, in: Proceedings of the Second International Conference on Permafrost, Yakutsk, USSR, 13–28 July 1973, 289–295, 1973. a, b
Angell, C. A., Oguni, M., and Sichina, W. J.: Heat capacity of water at extremes of supercooling and superheating, J. Phys. Chem., 86, 998–1002, 1982. a
Anthony, K., Daanen, R., Anthony, P., Deimling, T. S., Ping, C.-L., Chanton, J., and Grosse, G.: Methane emissions proportional to permafrost carbon thawed in Arctic lakes since the 1950s, Nat. Geosci., 9, 679–682, https://doi.org/10.1038/NGEO2795, 2016. a
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Short summary
CVPM is a modular heat-transfer modeling system designed for scientific and engineering studies in permafrost terrain, and as an educational tool. CVPM implements the heat-transfer equations in both Cartesian and cylindrical coordinates. To accommodate a diversity of geologic settings, a variety of materials can be specified within the model domain. CVPM can be used over a broad range of depth, temperature, porosity, water saturation, and solute conditions on either Earth or Mars.