High Horizontal and Vertical Resolution Limited-Area Model: Near-Surface and Wind Energy Forecast Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract As harvesting of wind energy grows, so does the need for improved forecasts from the surface to the top of wind turbines. To improve mesoscale forecasts of wind, temperature, and dewpoint temperature in this layer, two different approaches are examined. In the first experiment, the vertical resolution of a limited-area model with 2.5-km grid spacing (LAM-2.5 km) is significantly increased near the surface to better represent profiles in that layer. In the second experiment, prognostic variables for land and ocean surfaces are initialized using results from an external land surface model system [the Global Environmental Multiscale Surface system (GEM-Surf)] and from a regional ocean model. Results show that increasing the vertical resolution near the surface leads to improved temperature and dewpoint temperature forecasts at the surface and in the wind turbine layer. For winds, improvements are more modest, because they are limited to the gradient measured across the span of the vertical wind turbine blades. On the other hand, the replacement of operational surface analyses with high-resolution analyses obtained from GEM-Surf is found to improve summer dewpoint temperature forecasts. It is shown that changes in soil moisture analyses explain the bulk of the improved dewpoint forecasts.
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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 | 0.000 | 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 it