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Record W2905349995 · doi:10.1029/2018gl080956

Extreme Variability in Irminger Sea Winter Heat Loss Revealed by Ocean Observatories Initiative Mooring and the ERA5 Reanalysis

2018· article· en· W2905349995 on OpenAlexafffund
Simon A. Josey, M. Femke de Jong, Marilena Oltmanns, G. W. K. Moore, Robert A. Weller

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsDairy Farmers of OntarioUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNatural Environment Research CouncilSight Research UK
KeywordsMooringClimatologyEnvironmental scienceForcing (mathematics)OceanographyLatitudeNorth Atlantic oscillationMiddle latitudesSea surface temperatureAtmospheric sciencesGeology

Abstract

fetched live from OpenAlex

Abstract Ground‐breaking measurements from the ocean observatories initiative Irminger Sea surface mooring (60°N, 39°30′W) are presented that provide the first in situ characterization of multiwinter surface heat exchange at a high latitude North Atlantic site. They reveal strong variability (December 2014 net heat loss nearly 50% greater than December 2015) due primarily to variations in frequency of intense short timescale (1–3 days) forcing. Combining the observations with the new high resolution European Centre for Medium Range Weather Forecasts Reanalysis 5 (ERA5) atmospheric reanalysis, the main source of multiwinter variability is shown to be changes in the frequency of Greenland tip jets (present on 15 days in December 2014 and 3 days in December 2015) that can result in hourly mean heat loss exceeding 800 W/m 2 . Furthermore, a new picture for atmospheric mode influence on Irminger Sea heat loss is developed whereby strongly positive North Atlantic Oscillation conditions favor increased losses only when not outweighed by the East Atlantic Pattern.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.064
GPT teacher head0.306
Teacher spread0.243 · 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 teacher head, not a consensus.

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

Citations60
Published2018
Admission routes2
Has abstractyes

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