Seasonal and Interannual Variability in the Circulation of Puget Sound, Washington: A Box Model Study
Bibliographic record
Abstract
A prognostic, time‐dependent box model of circulation in Puget Sound, Washington is used to study seasonal and interannual variations in residence times and interbasin transports. The model is capable of reproducing salinity variability in the Sound at seasonal timescales, and is shown to have hindcast skill at interannual timescales. Modelled transports vary as much between years as between seasons. The largest seasonal feature is a sharp transport drop in late autumn into the deep Main Basin of the Sound, which is shown to be caused by increased river flow into Whidbey Basin. The high degree of transport variability leads to large interannual differences in residence times; for instance, for Whidbey Basin the residence time varies from 33 to 44 days in the period between 1992 and 2001 and for southern Hood Canal it varies from 64 to 121 days. This indicates that residence time estimates based on a year or less of data may not yield representative values. A forcing sensitivity study shows that in all basins except the South Sound, salinity variability in the Strait of Juan de Fuca accounts for more of the seasonal variability than river variability does. However, year‐to‐year variability in river discharge affects interannual variability in transports as much as the Strait of Juan de Fuca salinity does. The model demonstrates poorest skill in the basins most affected by the Strait of Juan de Fuca salinity, indicating that the sparse data available for the Strait may not provide adequate boundary conditions for the model.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".