Surface wind speed probability distribution in the Southeast Pacific of Marine Stratus and Stratocumulus regions
Bibliographic record
Abstract
Abstract Probability distributions of surface wind speeds (SWS) near coastal regions are needed for applications such as estimating offshore wind power and ocean surface fluxes and for offshore wind risk assessments. Ocean surface wind speed probability distribution (PDF) is characterized using three-year QuikSCAT and AIRS satellite observations in the southeast Pacific of marine stratus and stratocumulus (MSC) regions. Seasonal variation is removed from wind statistics. It was found that the observed SWS standard deviation has a linear positive relationship with its mean SWS; while the SWS skewness decreases with mean SWS in regimes of strong winds and increases with mean SWS in regimes of weak winds. A simple 1D conceptual model is developed near the Peruvian region, which successfully reproduces the observed relationship between higher moments of SWS and its mean value. The model based physical picture among ocean surface winds, SST, and marine boundary clouds are supported by three-year QuikSCAT surface wind observations and fifteen-year ERA40 re-analysis data. Model sensitive tests suggest that large-scale divergence, and strengths of momentum and cloud fluctuations have significant effects on the ocean SWS-PDF in marine stratus and stratocumulus regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".