Linking upstream cold, continental air to the intensity of marine cold air outbreaks along the western boundary currents of the North Pacific and North Atlantic: A Lagrangian analysis
Bibliographic record
Abstract
Marine cold air outbreaks (CAOs) occurring at the entrance of the Northern Hemisphere storm tracks induce severe air-sea interaction and may alter storm track activity downstream. However, a mechanistic understanding of the processes governing the intensity of marine CAOs is lacking. A reanalysis-based climatology of marine CAOs occurring in the winters of 1979-2023 along the Gulf Stream and the Kuroshio Current highlights that such phenomena involve the advection of dry, cold air from the upstream continents, where surface radiative cooling occurs during the winter months over Canada and Siberia. We refer to these extremely cold regions as boreal cold air reservoirs (BCARs). Leveraging the Lagrangian perspective to diagnose the origins of air involved in CAOs, we identify distinct airstreams contributing to CAOs, among which the one originating from BCARs and the dry intrusion (DI). The two airstreams modulate the intensity of sensible and latent heat fluxes within the CAOs, respectively. The strongest CAOs feature a large contribution of BCAR trajectories and are preceded by the development of a strong surface anticyclone over the upstream continent 6-8days prior to the CAOs. Our findings suggest that the interaction of a thermal high with an upper-level ridge is a crucial precursor to the strongest CAOs. Thus, our study offers insights into the adiabatic and non-adiabatic processes governing the intensity of CAOs, which determine the climatological hot spots of global air-sea interaction near the western boundary currents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".