MétaCan
Menu
← Back to cohort
Record W4220865809 · doi:10.5194/egusphere-egu22-6260

Baffin Bay surface flux perspectives on autumn Greenland blocking

2022· preprint· en· W4220865809 on OpenAlexaboutno aff
Thomas J. Ballinger, Dániel Topál, Qinghua Ding, Zhe Li, Linette Boisvert, Edward Hanna, Timo Vihma

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsGreenland ice sheetClimatologyCryosphereArctic ice packBaySea iceGlacierArcticOceanographyIce sheetAtmospheric circulationEnvironmental scienceArctic geoengineeringGeologyAtmospheric sciencesPhysical geographyGeographySea ice thickness

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.561
Threshold uncertainty score0.873

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0600.004

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.

Opus teacher head0.031
GPT teacher head0.241
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicCryospheric studies and observations→French-language works237,207→