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Record W2526781111

Understanding and predicting changes in North Atlantic Sea Surface Temperature

2013· article· en· W2526781111 on OpenAlexaboutno aff
Stephen Yeager

Bibliographic record

VenueCU Scholar (University of Colorado Boulder) · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersClimate Program OfficeU.S. Department of EnergyOffice of ScienceNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsSea surface temperatureClimatologyEnvironmental scienceOceanographyGeology
DOInot available

Abstract

fetched live from OpenAlex

The mechanisms associated with sea surface temperature variability in the North Atlantic are explored using observation-based reconstructions of the historical surface states of the atmosphere and ocean as well as simulations run with the Community Earth System Model, version 1 (CESM1). The relationship between air-sea heat flux and SST between 1948 and 2009 yields evidence of a positive heat flux feedback at work in the subpolar gyre region on quasi-decadal timescales. Warming of the high latitude Atlantic precedes an atmospheric response which resembles a negative NAO state. The historical flux data set is used to estimate temporal variations in North Atlantic deep water formation which suggest that NAO variations drove strong decadal changes in thermohaline circulation strength in the last half century. Model simulations corroborate the observation-based inferences that substantial changes in the strength of the Atlantic Meridional Overturning Circulation (AMOC) ensued as a result of NAO-driven water mass perturbations, and that changes in the large-scale ocean circulation played a significant role in modulating North Atlantic SST. Surface forcing perturbation experiments show that the simulated low-frequency AMOC variability is mainly driven by turbulent buoyancy forcing over the Labrador Sea region, and that the decadal ocean variability, in uncoupled experiments, derives from low-frequency variability in the overlying atmospheric state. Surface momentum forcing accounts for most of the interannual variability in AMOC at all latitudes, and also most of the decadal AMOC variability south of the Equator. We show that the latter relates to the trend in wind stress forcing of the Southern Ocean, but that Southern Ocean forcing explains very little of the North Atlantic signal. The sea surface height in the Labrador Sea is identified as a strongly buoyancy-forced observable which supports its use as a monitor of AMOC strength. The dynamics which characterize the model mean overturning and gyre circulations, and which explain the model response to surface momentum and buoyancy forcing perturbations, are investigated in terms of mean and time-varying vorticity balances. The significant effect of bottom vortex stretching, noted in previous studies, is shown here to play a key role in a variety of time-dependent phenomena, such as the covariation of overturning and gyre circulations, the variation of the barotropic streamfunction in the intergyre-gyre region, and changes in AMOC associated with momentum forcing perturbations. We show that latitudinal changes in the AMOC vorticity balance explains the attenuation of buoyancy-forced signals south of Cape Hatteras, and that the dominant frictional balance near the Equator greatly inhibits the propagation of AMOC variability signals from one hemisphere to the other. The long persistence of buoyancy-forced, high-latitude circulation anomalies results in significant predictability of SST in the subpolar gyre. This is demonstrated with an analysis of initialized, fully coupled retrospective predictions of the mid-1990s warming in that region. The atmospheric response is shown to be relatively unimportant on timescales of up to 10 years, but skill for longer lead times is inhibited by an incorrect heat flux feedback in the North Atlantic in the coupled CESM1.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.569

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 communication0.0000.001
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 head0.015
GPT teacher head0.176
Teacher spread0.161 · 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 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

Citations7
Published2013
Admission routes1
Has abstractyes

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