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Record W6991903404

Interannual variability and long-term trends of surface hydrography around the Prince Edward Island Archipelago, Southern Ocean

2022· dissertation· en· W6991903404 on OpenAlexaboutno aff

Bibliographic record

VenueOpen University of Cape Town (University of Cape Town) · 2022
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsPolar frontAntarctic oscillationGeostrophic windArctic oscillationEkman transportOcean currentCurrent (fluid)Sea surface temperatureForcing (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

The Prince Edward Islands (PEIs) Archipelago are situated in a prime location for the study of ecosystem response to intrinsic climate variability in the Southern Ocean and the impact of climate change. They are positioned in the Polar Frontal Zone, which is constrained by the subAntarctic Front and the Antarctic Polar Front, all of which are part of the strong, uninterrupted Antarctic Circumpolar Current (ACC). Due to its remoteness and challenging accessibility, there is a severe lack of data in the Southern Ocean and at the PEIs. The existing data are only available as single points observations or snapshots from past research cruises. This study thus makes use of 23 years (1993 – 2016) of satellite and reanalysis data to determine the annual/interannual and long-term variability of Sea Surface Temperature (SST), wind forcing and surface circulation at the PEIs and determine whether natural modes of climate variability like the El Niño Southern Oscillation (ENSO), Southern Annular Mode (SAM) or SemiAnnual Oscillation (SAO) were affecting these parameters. SST, wind speed, wind stress curl and the Ekman current did not express any long-term trend. A significant increasing but very small trend was only perceived in the geostrophic current and total surface current which was concluded to not be associated with the intensification of the ACC caused by a more positive SAM phase. The anomalies in SST showed striking interannual variability at a periodicity of 0.8, 2.8 and 7.5 years showing a similar pattern to that of ENSO with a periodicity of 1.5, 2.9 and 6 years. There has however been no relationship established between SST and any of the climate modes, but the Antarctic Circumpolar Wave (ACW), which is one of ENSO's teleconnection, could be responsible for the interannual changes seen in the SST anomalies. The anomalies in wind speed did not show any apparent periodicity and no relationship with ENSO. More so, while the impact of SAM and SAO has been seen on the westerly wind belt which governs the latitude of the PEIs, no correlation was established between the wind speed at the islands and SAM or SAO. The anomalies in wind stress curl presented no visible interannual variability but some sign of short-term variability. There was also no link 2 established between wind stress curl at the PEIs and any of the climate modes. Finally, a periodicity of 1.3 and 4 years was seen in the geostrophic current anomalies which also coincided with the pattern of ENSO but only showed minor correlation with ENSO. The ACW was deduced to perhaps also be responsible for the surface currents anomalies since the ACW is primarily propagated within the ACC. The trends perceived in the parameters considered for this study and the impact of climate modes on them appeared to be different to patterns which has been historically observed across the Southern Ocean. This further confirms the fact that the neighbouring oceanography and surface wind speed variability surrounding the PEIs differ from other regions of the Southern Ocean, most probably due to the frequent mesoscale instability such as eddies and frontal movement influencing the region. The impact of climate change on the PEIs ecosystem thus cannot be expected to be the same as the rest of the Southern Ocean.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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