Seasonality of Vertical Wind Shear in the Northwestern North Atlantic
Bibliographic record
Abstract
ABSTRACT Compared to onshore, offshore wind offers a more consistent resource, potential close proximity to load centers, and greater distance from people's view sheds. Much of our understanding of the wind resources in the western north Atlantic derives from remote sensing and scattered measurements. In contrast, offshore wind turbines typically have hub heights exceeding 150 m above sea level. This study uses anemometer data from near hub height obtained from offshore oil and gas exploration and production vessels, combined with well‐established and vetted historical reanalysis data of 10‐m wind heights to develop an observational wind shear model. Although the wind shear magnitudes themselves are in line with other studies of offshore wind, a counterintuitive seasonality is observed. There is more wind shear between 10 m and hub heights during the summer than during the winter. Although this finding seems inconsistent with the physics of atmospheric instability caused by temperature differences between the sea surface and the lower atmosphere, findings at several independent measurement sites in two remote ocean regions of Atlantic Canada are in agreement. This finding may help planning agencies and wind developers to select sites, perform preliminary viability and economic modeling, and thereby facilitate the transition and integration to offshore wind energy.
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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 | 0.000 | 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".