MétaCan
Menu
← Back to cohort

“Climate shift of the Atlantic Meridional Overturning Circulation (AMOC) in Reanalyses (ORAS5): possible causes, and sources of uncertainty”

2020· article· en· W3101328208 on OpenAlexaboutno aff
Vincenzo de Toma, Chunxue Yang, Vincenzo Artale

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAmpereOutflowOceanographyChemistryGeologyCurrent (fluid)

Abstract

fetched live from OpenAlex

We present preliminary results and insights from the analysis of the ensemble of Oceanic Reanalysis System 5 (ORAS5), produced by the European Center for Medium Weather Forecast (ECMWF), which reconstruct ocean’s past history from 1979 to 2018, with monthly means temporal and spatial resolution of 0.25° and 75 vertical levels. We focused on the AMOC, which can be considered as one of the main drivers of the Earth’s Climate System, and we observed that the strength at 26.5°N presents a shift in the mean of about 5 Sverdrup in the period 1995-2000 which can be considered as a climate tipping point. We aim to investigate the causes of this reduction and propose three mechanisms responsible for the observed AMOC volume transport reduction: the Gulf Stream Separation path, changes of the Mediterranean Outflow Water (MOW) and the North Atlantic Deep Water (NADW) formation processes in the Labrador Sea respectively. The Gulf Stream Separation path is investigated by visualizing the barotropic stream function averaged over two periods, before and after the 1995-2000. In particular it is possible to detect a shift in the direction of the barotropic currents, which is enhanced further by seasonal climatology analysis. In the first period (greater volume transport), patterns are more intense, and the Gulf Stream reach higher latitudes, allowing for a more vigorous deep water formation in the Labrador Sea than in the second period. Moreover, we observe the AMOC volume transport reduction at 26.5°N accompanied with a reduction in the heat fluxes over the Labrador Sea. We think this reduction of heat fluxes has a cascade effect on horizontal averages for temperature, salinity, and potential density profiles, which are manifestations of less deep water production in the Labrador Sea, that can ultimately drive the AMOC weakening. Finally, the Mediterranean Sea has experienced, in the last decades, a general warming trend, in particular of deep water temperatures since the mid-1980s. It is well known that this warming induce a large variability in the hydrological characteristics of the MOW becoming more likely one key factor driving the AMOC variability observed in ORAS5. In fact, there’s a larger ensemble spread in both the temperature and salinity climatological profiles at 40°N, i. e. in correspondence of the Gibraltar Strait and Gulf of Cadiz. This analysis highlights the high sensitivity of the MOW to perturbations producing the different ensemble members of ORAS5. Our hypothesis is that the nonlinear interaction between these three mechanisms could have a complex feedback on the AMOC variability. In conclusion, our preliminary results brought out the relevance of the deep water formation process in the Labrador Sea, the MOW and the Gulf Stream path as the main sources of the AMOC variability and stability. Besides, our analysis points out the need for further studies, e. g. increasing resolution at the Straits (like Gibraltar Strait), investigating correlations with the variability of the subpolar gyre and developing conceptual studies, using Intermediate Complexity Models interpreted under the lens of Dynamical System Theory and Statistical Mechanics.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.016
GPT teacher head0.222
Teacher spread0.206 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicAtmospheric and Environmental Gas Dynamics→French-language works237,207→