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Record W2002097506 · doi:10.1029/2000jc000365

A quasi‐one‐dimensional coupled climate‐carbon cycle model: 2. The carbon cycle component

2001· article· en· W2002097506 on OpenAlexafffund
L. D. Danny Harvey

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAlkalinityCarbon cycleBiological pumpDissolved organic carbonCarbon fibersDiffusionTRACERAtmospheric sciencesIsopycnalEnvironmental scienceGeologyChemistryMaterials scienceClimatologyThermodynamicsOceanographyPhysics

Abstract

fetched live from OpenAlex

A quasi‐one‐dimensional, coupled climate‐carbon cycle model is presented which consists of two polar domains and one nonpolar domain. The model simulates the distribution of dissolved inorganic carbon (DIC), alkalinity, phosphate, dissolved oxygen, and temperature and contains a biological pump with production of organic tissue, calcite, and arogonite. Bottom water is conditioned in one polar domain through interaction with the atmosphere and convective mixing and is injected into the lower portion of the nonpolar domain. Intermediate water flows into the other polar domain and upwells. Successful simultaneous simulation of the observed distribution of all the tracers (including isotope ratios) requires (1) an upwelling velocity in the nonpolar domain that peaks around 2 m yr−1 at a depth of 1 km, with a gradual decrease above and below this depth; (2) effective vertical diffusion coefficients for temperature and other tracers that are different in the upper 0.5 km; and (3) a carbonate carbon to organic carbon production ratio of only 0.09. These requirements are consistent with physical considerations and/or observational evidence. In particular, observational data combined with a consideration of mixing along isopycnal surfaces and model results both indicate that the effective vertical diffusion coefficient in the upper ocean should be smallest for temperature and largest for oxygen, with the values for alkalinity and phosphate modestly smaller than for DIC. The model parameters obtained by tuning the model to preindustrial tracer distributions also provide the best (and generally excellent) fit to observed transient isotope changes. Interactions between alkalinity and DIC modulate the effect on steady state atmospheric pCO2 of changes in the model parameters. However, the model uptake of anthropogenic CO2 and the computed atmospheric CO2 variation to year 2200 are remarkably insensitive to the choice of model mixing parameters, given that these are assumed to be constant during a given simulation. Finally, the sensitivity of the model atmospheric pCO2 to changes in the temperature of warm ocean surface matches that obtained by three‐dimensional ocean carbon cycle models.

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)0.000
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 score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.029
GPT teacher head0.276
Teacher spread0.247 · 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

Citations16
Published2001
Admission routes2
Has abstractyes

Explore more

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