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Record W6986249876

Overturning Strength of the Sub-Polar Gyre in the North Atlantic Ocean, within the GLORYS12 reanalysis model

2023· dissertation· en· W6986249876 on OpenAlexaboutno aff

Bibliographic record

VenueResearch Repository (Delft University of Technology) · 2023
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsOcean gyreThermohaline circulationShutdown of thermohaline circulationOcean currentClimate changeBoundary currentLead (geology)Climate model
DOInot available

Abstract

fetched live from OpenAlex

The Earth’s climate is changing, due to global warming, impacting the ocean circulation around the world. As the ocean circulation distributes large amounts of energy around the world, this can alter climate drastically if changed. The Atlantic Meridional Overturning Circulation (AMOC) is a fundamental ocean component to comprehend climate change and further investigation enhances our capacity to predict it. The AMOC plays a pivotal role in regulating the ocean heat transport within the North Atlantic Ocean, influencing the climates of North America and Europe. This study centers its attention on the Sub-Polar Gyre (SPG), a critical region where the AMOC activity peaks. Within this region, this study aims to get a better understanding of the overturning dynamics of the SPG, on a seasonal and annual time scale. To achieve this, the reanalysis model GLORYS12 is used, which offers a detailed simulation of ocean dynamics spanning the period from 1993 to 2020. With its high-resolution, eddy-resolving capabilities, GLORYS12 is particularly well-suited for capturing the nuanced small-scale overturning processes associated with the AMOC. From these model data, the overturning is calculated from alongstream changes in boundary current transport divided in density classes. The analysis is performed for the entire SPG by dividing it into its major basins: the Iceland Basin, Irminger Sea, and Labrador Sea. Subsequently, the boundary currents of the SPG are further subdivided into seventeen individual segments, providing insights into how overturning dynamics vary along the SPG. The results reveal that the mean overturning strength in the SPG for 1993-2020 is 23.8 Sverdrups (106 m3/s (Sv)). The distribution in overturning strength between the basins is 41%, 29%, and 30% for the Iceland Basin, Irminger Sea, and Labrador Sea respectively. Furthermore,<br/>the results shows overturning occurs at increasingly higher densities, the further west you go. Each basin displays a pronounced seasonal pattern, with maximum overturning occurring in March and the minimum in September. On an inter-annual time scale, the overturning strength in both the Iceland Basin and Irminger Sea exhibits a decreasing trend of -0.04 and -0.02 Sv/year respectively, whereas the Labrador Sea has an increasing trend of 0.02 Sv/year over 1993-2020. A further division in shorter segments yields large spatial differences in overturning, both in overall strength and the distribution over density classes. However, these outcomes are less robust as flows are highly variable and numerical errors associated with the overturning calculations become more prominent. This also raises questions about the reliability of the assessment<br/>of overturning along segments from observations to determine the local overturning dynamics. In conclusion, this study leverages GLORYS12 for a detailed basin and segmented analyses to offer a comprehensive understanding of the AMOC within the SPG. The findings provide valuable insights into the AMOC’s long-term behavior, seasonal variations, annual trends, and high spatial variability. Using this increased understanding, future research can improve on why the AMOC behaves in the observed way, by analyzing the overturning dynamics sensitivity to oceanic and atmospheric conditions

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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