Representing moisture fluxes and phase changes in glacier debris cover using a reservoir approach
Bibliographic record
Abstract
Abstract. Due to the complexity of treating moisture in supraglacial debris, surface energy balance models to date have neglected moisture infiltration and phase changes in the debris layer. The latent heat flux (QL) is also often excluded due to the uncertainty in determining the surface vapour pressure. To quantify the importance of moisture on the surface energy and climatic mass balance (CMB) of debris-covered glaciers, we developed a simple reservoir parameterization for the debris ice and water content, as well as an estimation of the latent heat flux. The parameterization was incorporated into a CMB model adapted for debris-covered glaciers. We present the results of two point simulations, using both our new "moist" and the conventional "dry" approaches, on the Miage Glacier, Italy, during summer 2008 and fall 2011. The former year coincides with available in situ glaciological and meteorological measurements, including the first eddy-covariance measurements of the turbulent fluxes over supraglacial debris, while the latter contains two refreeze events that permit evaluation of the influence of phase changes. The simulations demonstrate a clear influence of moisture on the glacier energy and mass-balance dynamics. When water and ice are considered, heat transmission to the underlying glacier ice is lower, as the effective thermal diffusivity of the saturated debris layers is reduced by increases in both the density and the specific heat capacity of the layers. In combination with surface heat extraction by QL, subdebris ice melt is reduced by 3.1% in 2008 and by 7.0% in 2011 when moisture effects are included. However, the influence of the parameterization on the total accumulated mass balance varies seasonally. In summer 2008, mass loss due to surface vapour fluxes more than compensates for the reduction in ice melt, such that the total ablation increases by 4.0%. Conversely, in fall 2011, the modulation of basal debris temperature by debris ice results in a decrease in total ablation of 2.1%. Although the parameterization is a simplified representation of the moist physics of glacier debris, it is a novel attempt at including moisture in a numerical model of debris-covered glaciers and one that opens up additional avenues for future research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".