MATLAB code for firn thermodynamic and hydrological modelling
Bibliographic record
Abstract
This repository contains MATLAB source code for a model of glacier surface energy balance, coupled with a subsurface (snow and firn) thermodynamic and hydrological evolution. The default configuration of the subsurface model is for a 35-m firn column, with 0.1-m thick layers from 0-0.6 m, 0.2-m thick layers from 0.6-2 m, 0.4-m thick layers from 2-10 m, and 1-m thick layers below that. The model requires forcing from mean daily automatic weather station, climate model, or climate reanalysis data, with the default inputs being: minimum, mean, and maximum daily air temperature, mean daily relative or specific humidity, wind speed, air pressure, and longwave radiation, and mean and maximum daily incoming incoming shortwave. The model internally calculates snow albedo and snow surface temperature (hence, outgoing longwave radiation), as well as conductive heat flux to the snow surface, based on temperature gradients in the top three layers of the subsurface snow/firn model. See the referenced papers for further details on the model physics and parameterizations. The readme file with the code repository includes additional details and references.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".