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https://doi.org/10.5194/egusphere-2024-2989
https://doi.org/10.5194/egusphere-2024-2989
18 Oct 2024
 | 18 Oct 2024
Status: this preprint is open for discussion.

Simple analytical–statistical models (ASMs) for mean annual permafrost table temperature and active-layer thickness estimates

Tomáš Uxa, Filip Hrbáček, and Michaela Kňažková

Abstract. A variety of numerical, analytical and statistical models have been developed for estimating the mean annual permafrost table temperature (MAPT) and active-layer thickness (ALT). These tools typically require at least a few ground physical properties, such as thermal conductivity, heat capacity, water content or bulk density, as input parameters in addition to temperature variables, which are, however, unavailable or unrepresentative at most sites. Ground physical properties are therefore commonly estimated, which may yield model outputs of unknown validity. Hence, we devised two simple analytical–statistical models (ASMs) for estimating MAPT and ALT, which are driven solely by pairwise combinations of thawing and freezing indices in the active layer; no ground physical properties are required. ASMs reproduced MAPT and ALT well in most numerical validations, which corroborated their theoretical assumptions under idealized scenarios. Under field conditions of Antarctica and Alaska, the mean ASMs deviations in MAPT and ALT were less than 0.03 °C and 5 %, respectively, which is similar or better than other analytical or statistical models. This suggests that ASMs can be useful tools for estimating MAPT and ALT under a wide range of climates and ground physical conditions.

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Tomáš Uxa, Filip Hrbáček, and Michaela Kňažková

Status: open (until 29 Nov 2024)

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Tomáš Uxa, Filip Hrbáček, and Michaela Kňažková
Tomáš Uxa, Filip Hrbáček, and Michaela Kňažková

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Short summary
We devised two simple models for estimating the mean annual permafrost table temperature and active-layer thickness, which are driven solely by temperatures measured in the active layer; no ground physical properties are required. The models showed deviations of less than 0.03 °C and 5 %, and can therefore be useful tools for permafrost modelling under a wide range of environmental conditions.