The Role of a Tropopause Polar Vortex in the Generation of the January 2019 Extreme Arctic Outbreak
Bibliographic record
Abstract
Abstract An extreme Arctic cold air outbreak took place across the Midwest, Great Lakes, and Northeast during 29 January to 1 February 2019. The event broke numerous long-standing records with wide-reaching and detrimental societal impacts. This study found that this rare and dangerous cold air outbreak (CAO) was a direct consequence of a tropopause polar vortex (TPV) originating at high latitudes and subsequently tracking southward into the United States. The tropopause depression at the center of this TPV extended nearly to the surface. Simulations using the atmospheric component of the Model for Prediction Across Scales (MPAS) were conducted, revealing excellent predictability at 6–7-day lead times with the strength, timing, and location of the CAO linked to the earlier characteristics of the TPV over the Arctic. Within the middle latitudes, the TPV subsequently developed a tilt with height. Warming and the destruction of potential vorticity also took place as the TPV passed over the Great Lakes initiating a lake-effect snow storm. The climatological investigation of CAOs suggests that TPVs frequently play a role in CAOs over North America with a TPV located within 1000 km of a CAO 85% of the time. These TPVs tended to originate in the northern Canadian Arctic and are ejected equatorward into the Great Lakes/Upper Midwest and then to the Northeast over Labrador. This study also provides insight into how the impact of Arctic circulations on middle latitudes may vary within the framework of a rapidly changing Arctic.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".