MétaCan
Menu
Back to cohort
Record W4413231655 · doi:10.1002/we.70054

Seasonality of Vertical Wind Shear in the Northwestern North Atlantic

2025· article· en· W4413231655 on OpenAlexafffundabout
Nathaniel S. Pearre, Lukas G. Swan

Bibliographic record

VenueWind Energy · 2025
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsDalhousie University
FundersNova Scotia Department of Energy and MinesNova Scotia Department of EnergyU.S. Department of Energy
KeywordsWind shearOffshore wind powerSubmarine pipelineWind powerWind stressWind gradientEnvironmental scienceWind resource assessmentMeteorologyWind speedSeasonalityWind directionMaximum sustained windSea breezeWind profile power lawGeologyOceanographyClimatologyGeographyEngineering

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.220
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueWind EnergySame topicWind Energy Research and DevelopmentFrench-language works237,207