The influence of low‐level thermal inversions on estimated melt‐season characteristics in the central Canadian Arctic
Bibliographic record
Abstract
Abstract Daily vertical temperature gradients were examined in order to infer melt‐event characteristics at an elevation relevant to basin‐scale snow and plateau ice‐melt studies in the Canadian Arctic. Surface and upper‐air temperature data from Resolute, Cornwallis Island, was used to estimate vertical lapse rates up to 300 m asl, and to identify the presence of inversions at that altitude. Lapse rates vary throughout the melt season and are substantially less than typically published generalized values. Thermal inversions are more frequent during the melt season than in the periods immediately before and after, suggesting a strong control on intraseasonal temperature patterns. In July, the period of maximum temperature in the Arctic, inversion frequency is highest and closely related to calculated melting degree‐days. Results show that increased summer mean temperature resulted in a substantial lengthening of estimated melt events, as opposed to increased event intensity. Increased inversion frequency leading to shallower vertical lapse rates since the late 1980s is speculated to be the result of synoptic‐scale climate patterns, and is potentially an important meteorological mechanism for enhanced glacial melt since the late 1980s. Copyright © 2008 Royal Meteorological Society
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".