The Probability Distribution of Land Surface Wind Speeds
Bibliographic record
Abstract
Theprobabilitydensityfunction(pdf)oflandsurfacewindspeedsischaracterizedusingaglobalnetworkof observations. Daytime surface wind speeds are shown to be broadly consistent with the Weibull distribution, while nighttime surface wind speeds are generally more positively skewed than the corresponding Weibull distribution (particularly in summer). In the midlatitudes, these strongly positive skewnesses are shown to be generally associated with conditions of strong surface stability and weak lower-tropospheric wind shear. Long-term tower observations from Cabauw, the Netherlands, and Los Alamos, New Mexico, demonstrate that lower-tropospheric wind speeds become more positively skewed than the corresponding Weibull distribution only in the shallow (;50 m) nocturnal boundary layer. This skewness is associated with two populations of nighttime winds: (i) strongly stably stratified with strong wind shear and (ii) weakly stably or unstably stratified with weak wind shear. Using an idealized two-layer model of the boundary layer momentumbudget,itisshownthattheobservedvariabilityofthedaytimeandnighttimesurfacewindspeedscan be accounted for through a stochastic representation of intermittent turbulent mixing at the nocturnal boundary layer inversion.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".