Investigation of Multi-Timescale Sea Level Variability near Jamaica in the Caribbean Using Satellite Altimetry Records
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".