Satellite-derived ocean climatology around Santo Antão Island: 20 years of surface and near-surface observations
Bibliographic record
Abstract
Understanding the implications of climate change is especially critical for the Cape Verde Islands, which are acutely vulnerable to climate variability and its associated impacts. This study characterised the temporal variability of surface and near-surface biophysical properties around Santo Antão using 20 years of MODIS-Aqua Level-2 imagery at 1 km resolution for Ocean Colour and Thermal Infrared parameters. The results of this study show that the waters around this island exhibited stable Sea Surface Temperature conditions with a pronounced seasonal cycle and no long-term warming over two decades, contrasting with global trends. Bio-optical parameters (Chlorophyll a , Diffuse Attenuation Coefficient and Particulate Organic Carbon) reflected the oligotrophic nature of the waters, with slight positive trends hinting at increasing concentrations of primary productivity. Consistently high levels of Photosynthetically Available Radiation affirmed light is not a limiting factor, with nutrient dynamics likely playing a dominant role. Particulate Inorganic Carbon displayed distinct variability, with no significant trends, underscoring the need for further research into its unique drivers. Based on ocean surface temperature cycles, the newly proposed seasonal classification successfully captured the dynamics of key parameters and demonstrated the value of satellite-derived data for long-term ecosystem monitoring. These findings enhanced the understanding of Santo Antão’s oceanographic dynamics and highlight the importance of regionally specific studies to complement global assessments. The results also provide a valuable baseline to support future research and inform conservation strategies and sustainable marine resource management in the Cape Verde region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 source (direct Gemma or distilled Codex), 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".