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Record W2918899115 · doi:10.1029/2018jc014459

Sensitivity of Labrador Sea Water Formation to Changes in Model Resolution, Atmospheric Forcing, and Freshwater Input

2019· article· en· W2918899115 on OpenAlexafffundabout
Yarisbel Garcia‐Quintana, Peggy Courtois, Xianmin Hu, Clark Pennelly, Dagmar Kieke, Paul G. Myers

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans CanadaUniversity of Alberta
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsForcing (mathematics)ConvectionPrecipitationClimatologyGeologyDeep convectionAtmospheric sciencesHorizontal resolutionStormEnvironmental scienceOceanographyMeteorologyGeography

Abstract

fetched live from OpenAlex

Abstract Labrador Sea Water (LSW) is one of the main contributors to the lower limb of the Atlantic Meridional Overturning Circulation. In this study, we explore the sensitivity of LSW formation to model resolution, Greenland melt, absence of high‐frequency atmospheric phenomena, and changes in precipitation. We use five numerical model simulations at both (1/4)° and (1/12)° resolutions. A kinematic subduction approach is used to obtain the LSW formation rate over the period 2004 to 2016. The control simulation, with (1/4)° resolution, showed a mean annual production rate of 1.9 Sv (1 Sv = 10 6 m 3 /s) in the density range of 27.68–27.80 kg/m 3 for the period 2004–2016. Deep convection events that occurred during 2008, 2012, and 2014–2016 were captured. We found that with (1/4)° resolution the LSW formation rate is 19% larger compared with its counterpart at (1/12)° resolution. The presence of Greenland melt and an increase in the precipitation impact the denser LSW layer replenishment but do not decrease the overall LSW formation rate nor the maximum convection depth. A dramatic response was found when filtering the atmospheric forcing, which induced a decrease of 44% in heat loss over the Labrador Sea, strong enough to halt the deep convection and decrease the LSW formation rate by 89%. Even if our experiment was extreme, a decrease in the storms crossing the Labrador Sea with a consequent reduction in the winter heat loss might be a bigger threat to deep convection and LSW formation in the future than the expected increases in the freshwater input.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.259
Teacher spread0.240 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations37
Published2019
Admission routes3
Has abstractyes

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