Prediction of spatially distributed regional‐scale fields of air temperature and vapor pressure over mountain glaciers
Bibliographic record
Abstract
Physically based models of glacier melt require fields of near‐surface air temperature ( T g ) and vapor pressure ( e g ) for estimating turbulent heat exchanges. However, katabatic boundary layer (KBL) processes limit the effectiveness of standard interpolation or extrapolation routines for estimating T g and e g from regional weather station networks. Climate data collected from nine automatic weather stations operated over three ablation seasons at three glaciers in the southern Coast Mountains of British Columbia are analyzed in this study. On‐glacier observations were compared to ambient values ( T a and e a ) estimated from a regional network of off‐glacier weather stations. Piecewise regressions of T g versus T a at each AWS site reveal (1) a critical threshold temperature ( T *) that denotes the onset of katabatic boundary layer (KBL) development and (2) a temperature damping that is consistent at each site, but variable between sites. Variations in near‐surface vapor pressure are related to processes of condensation or evaporation/sublimation at the glacier surface, which are controlled by the vapor pressure gradient between the surface and the ambient air. Statistical relations with flow path lengths calculated from glacier digital elevation models are used to predict the strength of KBL effects on T g and e g , and examples of the approach for generating distributed fields of T g and e g are given.
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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 | 0.001 |
| 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".