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Record W4385344731 · doi:10.3390/jmse11081499

Investigation of Multi-Timescale Sea Level Variability near Jamaica in the Caribbean Using Satellite Altimetry Records

2023· article· en· W4385344731 on OpenAlexfundno aff
Deron O. Maitland, Michael A. Taylor, Tannecia S. Stephenson

Bibliographic record

VenueJournal of Marine Science and Engineering · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
FundersUniversity of BristolMcGill University
KeywordsStorm surgeClimatologyTide gaugeSea levelAltimeterEmpirical orthogonal functionsEnvironmental scienceCoastal floodStormOceanographyClimate changeGeographyGeologySea level riseMeteorology

Abstract

fetched live from OpenAlex

There is a dearth of studies characterizing historical sea level variability at the local scale for the islands in the Caribbean. This is due to the lack of reliable long term tide gauge data. There is, however, a significant need for such studies given that small islands are under increasing threat from rising sea levels, storm surges, and coastal flooding due to global warming. The growing length of satellite altimetry records provides a useful alternative to undertake sea level analyses. Altimetry data, spanning 1993–2019, are used herein to explore multi-timescale sea level variability near the south coast of Jamaica, in the northwest Caribbean. Caribbean basin dynamics and largescale forcing mechanisms, which could account for the variability, are also investigated. The results show that the average annual amplitude off the south coast of Jamaica is approximately 10 cm with a seasonal peak during the summer (July–August). The highest annual sea levels occur within the Caribbean storm season, adding to the annual risk. The annual trend over the 27 years is 3.3 ± 0.4 mm/yr when adjusted for Glacial Isostatic Adjustment (GIA), instrumental drift, and accounting for uncertainties. This is comparable to mean global sea level rise, but almost twice the prior estimates for the Caribbean which used altimetry data up to 2010. This suggests an accelerated rate of rise in the Caribbean over the last decade. Empirical Orthogonal Function (EOF) and correlation analyses show the long-term trend to be a basin-wide characteristic and linked to warming Caribbean sea surface temperatures (SSTs) over the period. When the altimetry data are detrended and deseasoned, the leading EOF mode has maximum loadings over the northwest Caribbean, including Jamaica, and exhibits interannual variability which correlates significantly with a tropical Pacific-tropical Atlantic SST gradient index, local wind strength, and the Caribbean Low Level Jet (CLLJ). Correlations with the El Niño Southern Oscillation (ENSO) in summer, seen in this and other studies, likely arise through the contribution of the ENSO to the SST gradient index and the ENSO’s modulation of the CLLJ peak strength in July. The results demonstrate the usefulness of altimetry data for characterizing sea level risk on various timescales for small islands. They also suggest the potential for developing predictive models geared towards reducing those risks.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.374
Threshold uncertainty score0.744

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.054
GPT teacher head0.236
Teacher spread0.182 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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