Numerical Study of Topographic Effects on Wind-Driven Coastal Upwelling on the Scotian Shelf
Bibliographic record
Abstract
Wind-driven coastal upwelling can cause a sudden drop in sea surface temperatures (SSTs) of up to more than 8 °C on the inner Scotian Shelf (ScS) in the summer months. Three major coastal upwelling events on the ScS in the summer of 2012 are analyzed using in-situ SST observations and satellite remote sensing SST data. A spatial correlation analysis of satellite SST data shows an asymmetric distribution in the along-shore direction with smaller correlation coefficients in the downstream area than in the upstream area over the inner ScS during upwelling events. A regression analysis indicates that the wind impulse plays a major role in generating the SST cooling during the initial response stage of upwelling events. A nested-grid ocean circulation model (DalCoast-CSS) is used to examine the effect of irregular coastline and rugged bathymetry on the spatial and temporal variability of wind-driven upwelling over the inner ScS. The model has four submodels downscaling from the eastern Canadian Shelf to the central ScS. The model external forcing includes tides, winds, river discharges, and net heat flux at the sea surface. A comparison of model results with the satellite SST data reveals a satisfactory performance of the model in reproducing the development of coastal upwelling on the ScS. Model results demonstrate that the irregular coastline and rugged bathymetry play important roles in influencing the temporal and spatial evolution of the upwelling plume over the inner ScS. The irregular coastline (e.g., cape) is responsible for the relatively warm SSTs in two downstream inlets (i.e., St. Margarets Bay and Mahone Bay) and adjacent coastal waters. The rugged bathymetry (e.g., submerged bank) influences the spatial extent of filaments through the advection process.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".