Baffin Bay surface flux perspectives on autumn Greenland blocking
Bibliographic record
Abstract
The northwest Atlantic Arctic has been recently characterized by rapid environmental change. Examples in the last two-to-three decades include: accelerated retreat of eastern Canadian Arctic glaciers, melt over high-elevation and latitude areas of the Greenland Ice Sheet (GrIS), and shifts in Baffin Bay ice phenology. Many of these glaciological changes and associated extreme events are linked to atmospheric circulation anomalies over the North Atlantic and surrounding areas, including the frequent, intense, and/or persistent presence of Greenland blocking anticyclones. These mid-tropospheric (i.e., 500 hPa) high-pressure cells are often accompanied by invigorated temperature and moisture advection and cloud radiative processes that are known to provoke widespread melt of the region’s cryosphere, even during periods when melt tends to be uncommon. Blocking characteristics are often associated with melt processes, but how these processes and related air-sea exchanges feedback on this type of upper-level atmospheric pattern largely remain uncertain. Evaluating these processes and their uncertainties is especially relevant in the cold season, when upward surface fluxes persist along the ice edge and through thin sea ice cover. Such system-level interactions deserve attention for their multi-scalar effects on the local climate and cryosphere and impacts on the polar jet stream that influences North American and European weather regimes. This study focuses on the autumn season (September-December) to evaluate interactions involving Baffin Bay’s ice cover and its turbulent and radiative fluxes, and regional atmospheric circulation and winds. Focus is directed on this season as net surface fluxes climatologically tend to intensify from one month to the next and have increased roughly in tandem with the strength and motion characteristics of the overlying circulation described by the Greenland Blocking Index (GBI), and Greenland Streamfunction Index (GSI), respectively. Using flux data from ERA5 reanalysis and the Atmospheric Infrared Sounder (AIRS), we utilize bi-and-multivariate techniques to examine how individual and collective surface flux terms relate to the autumn GBI/GSI variability and trends since 1979. We then take a process-scale view, and investigate such interactions between the Baffin Bay boundary conditions, associated surface fluxes, and the GBI/GSI patterns in months where extremes occur in the ice cover and GBI/GSI independently as well as in tandem for applicable cases. We further aim to model the interaction between autumn Baffin ice-ocean surface fluxes and upper-level patterns using CAM6 Prescribed SST AMIP Ensembles and wind-nudging CESM experiments to isolate the role of Baffin environmental change on the large-scale atmospheric circulation and vice versa.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.060 | 0.004 |
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".