Influences of the Sierra Nevada on Intermountain Cold-Front Evolution
Bibliographic record
Abstract
Abstract Recent studies indicate that strong cold fronts develop frequently downstream of the Sierra Nevada over the Intermountain West. To help ascertain why, this paper examines the influence of the Sierra Nevada on the rapidly developing Intermountain cold front of 25 March 2006. Comparison of a Weather Research and Forecasting (WRF) model control simulation with a simulation in which the height of the Sierra Nevada is restricted to 1500 m (roughly the elevation of the valleys and basins of the Intermountain West) shows that the interaction of southwesterly prefrontal flow with the formidable southern High Sierra produces a leeward orographic warm anomaly that enhances the cross-front temperature contrast. Several processes generate this orographic warm anomaly, including flow modification by the Sierra Nevada (i.e., windward blocking of low-level Pacific air, leeward subsidence, and increased southerly flow from the Mojave Desert and lower Colorado River basin into the Intermountain West), diabatic heating and water vapor loss associated with orographic precipitation, and increased sensible heating and reduced subcloud diabatic cooling in the downstream cloud and precipitation shadow. In contrast, the postfrontal air mass experiences comparatively little orographic modification as it moves across the relatively low northern Sierra Nevada. These results show that the Sierra Nevada can enhance frontal development, which may contribute to the high frequency of strong cold-frontal passages over the Intermountain West.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".