Variability and Long‐Term Trends in the Shelf Circulation Off Eastern Tasmania
Bibliographic record
Abstract
Abstract This study investigates trends and interannual variability of the marine climate across the continental shelf off eastern Tasmania for 1993–2016. This region is a hotspot for global warming and biodiversity. Eastern Tasmania lies at the boundary between two ocean currents (the East Australian Current Extension, or EAC Extension, and the Zeehan Current, ZC) leading to the local marine climate exhibiting trends and variability from both boundary currents. A numerical ocean model is used to provide high‐resolution (∼2 km) estimates of the temperature, salinity, and circulation for the region. Results indicate significant positive trends in temperature, salinity, and southward flow over the shelf, consistent with an increasing EAC Extension. These trends are particularly strong in autumn, indicating a lengthening of the warm season. The interannual variability in the EAC Extension and ZC was quantified by a simple index, based on a modal analysis of surface circulation, indicating the relative dominance of each current. Strong EAC years were related to significantly more summertime marine heat wave days. Large‐scale remote drivers of variability were considered, and we found weak but significant links with El Niño–Southern Oscillation and Tasman Sea Blocking. El Niño–Southern Oscillation was found to modulate the EAC Extension in summer with a El Niño leading to enhanced southward flow and warming over the shelf. Tasman Sea Blocking was found to drive enhanced southward surface flow, particularly in winter. Nonetheless, large‐scale forcing modes explain less than 25% of the total variability in the EAC‐ZC system indicating that most of the variability is internally generated.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".