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Record W4248124143 · doi:10.5194/bgd-11-8023-2014

Wind driven changes in the ocean carbon sink

2014· preprint· en· W4248124143 on OpenAlexafffund
Neil C. Swart, John C. Fyfe, Oleg A. Saenko, Michael Eby

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Victoria
FundersWestern Canada Research GridCompute Canada
KeywordsEnvironmental scienceMesoscale meteorologySink (geography)ClimatologyEddyAtmospheric sciencesForcing (mathematics)Ocean currentCarbon sinkWind stressWind shearWind speedMeteorologyGeologyOceanographyClimate changeTurbulenceGeography

Abstract

fetched live from OpenAlex

Abstract. We estimate the historical ocean carbon sink over 1871 to 2010 using an ocean biogeochemical model driven with observed wind forcing. We focus on the influence of wind and mesoscale eddy changes on the net surface CO2 flux, which are most significant after 1950. The observed wind changes act to reduce the annual ocean carbon sink by 0.009 to 0.023 Pg yr−1 decade−1 over 1950 to 2010, and are consistent with previous studies covering only the latter part of the 20th century. The response of the ocean circulation and the carbon cycle to wind changes is sensitive to the parameterization of mesoscale eddies in our coarse resolution simulations. With a variable eddy transfer coefficient, eddy activity in the Southern Ocean increases in response to intensifying historical winds, partially compensating for direct wind-driven circulation changes. Thus with a variable eddy transfer coefficient the response to wind changes is about 2.5 times smaller than when using a constant coefficient. Finally, we show by comparing six reanalyses over 1980 to 2010 that estimated historical wind trends differ significantly. Through simulations forced with these reanalysis winds we show that the influence of historical wind changes on ocean carbon uptake is highly uncertain and depends on the choice of surface wind forcing product.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.241
Teacher spread0.215 · 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 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

Citations2
Published2014
Admission routes2
Has abstractyes

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