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Record W4390114657 · doi:10.1007/s00382-023-06989-z

A new conceptual model of global ocean heat uptake

2023· article· en· W4390114657 on OpenAlexaff
Jonathan M. Gregory, Jonah Bloch‐Johnson, Matthew P. Couldrey, Eleftheria Exarchou, Stephen M. Griffies, Till Kuhlbrodt, Emily R. Newsom, Oleg A. Saenko, Tatsuo Suzuki, Quran Wu, L. Shogo Urakawa, Laure Zanna

Bibliographic record

VenueClimate Dynamics · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Victoria
FundersJapan Society for the Promotion of ScienceU.S. Department of EnergyNatural Environment Research CouncilSight Research UKEuropean Research CouncilJapan Advanced Institute of Science and Technology
KeywordsLatitudeZonal and meridionalClimatologyOcean heat contentOcean general circulation modelEnvironmental scienceAtmospheric sciencesForcing (mathematics)General Circulation ModelGeologyOcean currentClimate changeOceanography

Abstract

fetched live from OpenAlex

Abstract We formulate a new conceptual model, named “ MT 2”, to describe global ocean heat uptake, as simulated by atmosphere–ocean general circulation models (AOGCMs) forced by increasing atmospheric CO $$_{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow/> <mml:mn>2</mml:mn> </mml:msub> </mml:math> , as a function of global-mean surface temperature change T and the strength of the Atlantic meridional overturning circulation (AMOC, M ). MT 2 has two routes whereby heat reaches the deep ocean. On the basis of circumstantial evidence, we hypothetically identify these routes as low- and high-latitude. In low latitudes, which dominate the global-mean energy balance, heat uptake is temperature-driven and described by the two-layer model, with global-mean T as the temperature change of the upper layer. In high latitudes, a proportion p (about 14%) of the forcing is taken up along isopycnals, mostly in the Southern Ocean, nearly like a passive tracer, and unrelated to T . Because the proportion p depends linearly on the AMOC strength in the unperturbed climate, we hypothesise that high-latitude heat uptake and the AMOC are both affected by some characteristic of the unperturbed global ocean state, possibly related to stratification. MT 2 can explain several relationships among AOGCM projections, some found in this work, others previously reported: $$\bullet $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>∙</mml:mo> </mml:math> Ocean heat uptake efficiency correlates strongly with the AMOC. $$\bullet $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>∙</mml:mo> </mml:math> Global ocean heat uptake is not correlated with the AMOC. $$\bullet $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>∙</mml:mo> </mml:math> Transient climate response (TCR) is anticorrelated with the AMOC. $$\bullet $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>∙</mml:mo> </mml:math> T projected for the late twenty-first century under high-forcing scenarios correlates more strongly with the effective climate sensitivity than with the TCR.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.026
GPT teacher head0.257
Teacher spread0.231 · 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

Citations17
Published2023
Admission routes1
Has abstractyes

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