High-resolution interactive modelling of the mountain glacier–atmosphere interface: an application over the Karakoram
Bibliographic record
Abstract
Abstract. The traditional approach to simulations of alpine glacier mass balance (MB) has been one-way, or offline, thus precluding feedbacks from changing glacier surface conditions on the atmospheric forcing. In addition, alpine glaciers have been only simply, if at all, represented in atmospheric models to date. Here, we extend a recently presented, novel technique for simulating glacier–atmosphere interactions without the need for statistical downscaling, through the use of a coupled high-resolution mesoscale atmospheric and physically-based climatic mass balance (CMB) modelling system that includes glacier CMB feedbacks to the atmosphere. We compare the model results over the Karakoram region of the northwestern Himalaya with remote sensing data for the ablation season of 2004 as well as with in situ glaciological and meteorological measurements from the Baltoro glacier. We find that interactive coupling has a localized but appreciable impact on the near-surface meteorological forcing data and that incorporation of CMB processes improves the simulation of variables such as land surface temperature and snow albedo. Furthermore, including feedbacks from the glacier model has a non-negligible effect on simulated CMB, reducing modelled ablation, on average, by 0.1 m w.e. (−6.0%) to a total of −1.5 m w.e. between 25 June–31 August 2004. The interactively coupled model shows promise as a new, multi-scale tool for explicitly resolving atmospheric-CMB processes of mountain glaciers at the basin scale.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".