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Permafrost, as an important part of the Cryosphere, has been strongly affected by climate warming, and a wide spread of permafrost responses to the warming is currently observed. In particular, at some locations rather slow rates of permafrost degradations are noticed. We related this behavior to the presence of unfrozen water in frozen fine‐grained earth material. In this paper, we examine not‐very‐commonly‐discussed heat flux from the ground surface into the permafrost and consequently discuss implications of the presence of unfrozen liquid water on long‐term thawing of permafrost. We conducted a series of numerical experiments and demonstrated that the presence of fine‐grained material with substantial unfrozen liquid water content at below 0°C temperature can significantly slow down the thawing rate and hence can increase resilience of permafrost to the warming events. This effect is highly nonlinear, and a difference between the rates of thawing in fine‐ and coarse‐grained materials is more drastic for lower values of heat flux incoming into permafrost. For high heat flux, the difference between these rates almost disappears. As near‐surface permafrost temperature increases towards 0°C and the changes in the ground temperature become less evident, the future observation networks should try to incorporate measurements of unfrozen liquid water content in the near‐surface permafrost and heat flux into permafrost in addition to the existing temperature observations.
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Ground Heat Flux Reconstruction Using Bayesian Uncertainty Quantification Machinery and Surrogate Modeling
Abstract Ground heat flux (G0) is a key component of the land‐surface energy balance of high‐latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming,G0is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstructG0across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using availableG0data (measured or modeled) for snow‐free period as a reference. When observedG0is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state‐of‐the‐art uncertainty quantification methods, the developedG0reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.
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- PAR ID:
- 10561235
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Earth and Space Science
- Volume:
- 11
- Issue:
- 3
- ISSN:
- 2333-5084
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1029/2023EA003435
