Upper-Tropospheric Jet Axis Detection and Application to the Boreal Winter 2013/14
Bibliographic record
Abstract
Abstract This study presents a detection scheme for upper-tropospheric jets. The scheme identifies locations on the dynamical tropopause where the wind shear perpendicular to the wind direction vanishes, and subsequently uses a masking criterion to filter out zero-shear locations that do not belong to jets. The scheme reliably detects jet axes in ERA-Interim data with instantaneous, weekly, or monthly averaged wind fields. The dynamical implications of the detected jet axes and their relation to objectively detected wave breaking and blocking are demonstrated for the synoptic evolution during the boreal winter 2013/14. This winter featured a remarkable episode with a stationary ridge–trough couplet over the American continent leading to anomalously cold conditions from central Canada to the eastern United States. The mean synoptic situation during this episode resembles the climatological winter mean, but featured a more spatially focused jet axis distribution in the northeastern Pacific. The tight distribution suggests that a sequence of similar weather events lead to the mean synoptic conditions. Although the distribution of jet axes and wave breaking events together with the persistence of the anomalous ridge over the northeastern Pacific indicate a blocked situation, the block is not detected with common conventional methods due to the lack of a persistent gradient reversal of potential temperature on the dynamical tropopause. In addition, the importance of subseasonal variations in this winter is demonstrated by pointing out a period in which the jet configuration deviated considerably from the seasonal mean.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".