Diurnal variations of land surface wind speed probability distributions under clear‐sky and low‐cloud conditions
Bibliographic record
Abstract
Long‐term 10 min wind tower data and ceilometer backscatter data at Cabauw in the Netherlands provide quantitative information on the influence of low clouds on the diurnal evolution of the near‐surface wind speed (NSWS) probability distribution (probability density function), the wind power density (WPD), and their vertical structure in the bottom 200 m of the atmosphere. Under clear‐sky conditions, pronounced diurnal cycles are identified in the leading three moments of NSWS as well as WPD and the boundary layer thermal structure in all seasons. When low clouds are present, weaker diurnal cycles with a different vertical structure are observed. Under clear skies, skewness at night is positive within the stable air near the surface but negative above 100 m. In the presence of low clouds, wind speeds are positively skewed and the probability of strong winds is higher associated with a larger geostrophic wind speed.
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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 | 0.000 | 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".