Wind resource assessment of Cuba in future climate scenarios
Bibliographic record
Abstract
The future climatic behavior of the wind resource in Cuba has not been studied in the past. This study presents a preliminary analysis of the behavior of wind speed using the regional climate model PRECIS (Providing Regional Climates for Impacts Studies) in high-resolution scenarios of climate change SRES A1B (Special Report on Emissions Scenarios), driven with boundary conditions from the General Circulation Model ECHAM5 (European Centre/HAMburg climate model) and 6 of the 16 members of the set of perturbed physics HadCM3 (Hadley Center Coupled Model, version 3) global climate model. Changes in the distribution of wind speed for three periods of 30 years in the future—2011–2040, 2041–2070, and 2071–2099—are analyzed. The PRECIS model was also run with reanalysis data during the period of 1 January 1989 to 31 December 2002. It was found that changes in wind speed will be larger in the eastern and northern coast, becoming statistically significant for the second half of this century with an increase in wind magnitude between 0.1 and 0.4 m s −1 . These areas of increased wind power match with the current projection of the Cuban wind program where the construction of 13 new wind farms are contemplated. Finally, this increase is added to the wind speed outputs of the numerical wind atlas of Cuba to estimate the values of wind speed over the three future periods.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".