Why a large‐scale monsoon does not exist in North America: Orographic effects
Bibliographic record
Abstract
Abstract To understand why a large‐scale monsoon does not exist in North America, we performed a series of sensitivity simulations to investigate orographic effects of the Rocky Mountains (RMs) using the Community Atmosphere Model version 5.1. Results show that the height of the RMs plays a fundamental role in shaping the monsoon over North America that is confined to a small area from northwestern Mexico to the southwestern United States. When the RMs' height is increased by five times their actual height, a larger part of the non‐monsoon region over North America becomes a monsoon region. The mechanical effects of the RMs uplift dominate in winter, while thermal effects dominate in summer. During winter the mechanical effects induce an equivalent barotropic atmospheric response in the troposphere. With the uplift of the RMs, the ridge and trough located on the western and eastern sides of Canada are strengthened. Most areas of North America are influenced by the northerlies during winter such that enhanced descending motion over the eastern RMs favours a dry winter climate. However, thermal effects dominate during summer through enhanced baroclinic atmospheric responses. The Mexico high and lower‐level cyclonic circulation are strengthened with the RMs uplift, triggering large‐scale ascending motion. Eastern North America is mainly controlled by the enhanced southerly wind along the western flank of the North Atlantic subtropical high. Thus, the enhanced water‐vapour transport and upward motion on the eastern side of the RMs increase summer precipitation. As a result, an obvious seasonal variation with the feature of ‘dry winter and wet summer’ finally develops, indicating that the height of the RMs plays a crucial role in shaping the monsoon over the central United States. Additional experiments show that the base area of the RMs has little effect on the large‐scale monsoon formation over North America.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".