Improved permafrost modelling in mountain environments by including air convection in a hydrological model
Bibliographic record
Abstract
Abstract. Permafrost occurrence in mountainous regions is influenced by complex topography and surficial geology, leading to high spatial heterogeneity. Coarse sediments create a unique thermal regime that allows permafrost to persist even under positive mean annual air temperatures due to natural convection lowering ground temperatures. Although this process has been recognized as a key factor in explaining the persistence of permafrost formation within coarse sediments, studies assessing the impact of natural convection on ground temperatures and permafrost are limited, partly due to the absence of hydrological models that take this process into account. This article expands on a well-established hydrological model to incorporate the effects of natural air convection on heat transfer. The modified model includes airflow through Darcy's equation and the Oberbeck–Boussinesq approximation to account for density-driven buoyancy effects, as well as a heat advection–conduction equation for the air phase without assuming local thermal equilibrium between the air and the other phases. The model was tested on a talus slope in the Canadian Rockies, where conventional models failed to represent field-based evidence of permafrost. The results revealed that coarse-sized sediments can lower ground temperatures by several degrees when natural convection is considered. Additionally, the study demonstrated that local thermal equilibrium approaches underestimate the impact of natural convection especially on short timescales. This enhanced model improves our understanding of permafrost dynamics in alpine landforms and enables a more accurate analysis of permafrost extent and its influence on groundwater discharges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".