Upper‐level winds over eastern North America: A regional jet stream climatology
Bibliographic record
Abstract
Although it is well known that jet streams play a vital role in everyday weather and long‐term climate variability, very few regional climatological studies on jet streams exist to date. Using the high‐resolution North American Regional Reanalysis (NARR), this study aims to create a preliminary jet stream, and more specifically a jet core, database for a relatively narrow region in eastern North America covering the period 1979 through 2016 inclusive. We use regional maxima in the smoothed horizontal wind field to locate both the latitudinal and vertical (pressure) location of jet cores along specific meridians. Results show that the median pressure level of all jet cores in the region of interest is 250 hPa and that two is the most likely number of distinct jet cores to occur along a given meridian at any given time. The jet cores are categorized into three bins based on their latitude in an attempt to capture the characteristics of the different tropopause‐level jet types. However, as the vertical and horizontal extents of the jet streams were not analysed, we cannot conclude for certain that each of the geographical bins corresponds to specific jet types. Statistically significant negative trends in the seasonal and overall mean pressure of the jet cores, implying an increased height, supports the findings of previous studies. Our analysis of NARR winds shows that jet core wind speeds increased in the region studied. This may be related to the increased height of jet cores through the thermal wind equation as well as increased baroclinicity across sections of the region studied. Jet core latitude and meridional circulation index (MCI) trends were generally negligible and not statistically significant. An absence of significant increases in |MCI| diverges from expectations and some theories of what to expect with Arctic amplification in a warming world.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".