A multi-decadal analysis of U.S. and Canadian wind and solar energy droughts
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
The spatial and temporal characteristics of wind and solar energy droughts across the contiguous U.S. and most of Canada for the period 1959–2022 are investigated using bias-corrected values of daily wind and solar power generation derived from the ERA5 meteorological reanalysis. The analysis domain has been divided into regions that correspond to four major interconnects and nine sub-regions. Droughts are examined for wind alone, solar alone, or a mix of wind and solar in which each provides 50% of the long-term mean energy produced, for durations of 1–90 days. Wind and solar energy droughts and floods are characterized on a regional basis through intensity–duration–frequency curves. Wind and solar generation are shown to be weakly anti-correlated over most of the analysis domain, with the exception of the southwest U.S. The intensities of wind and solar droughts are found to be strongly dependent on region. In addition, the wind resource in the central U.S. and the solar resource in the southwestern U.S. are sufficiently good that over-weighting capacity in those areas would help mitigate droughts that span the contiguous United States for most duration lengths. The correlation of droughts for the 50%–50% mix of wind and solar generation with temperature shows that the most intense droughts occur when temperatures exhibit relatively moderate values, not when energy demand will be largest. Finally, for all regions except the southeast U.S., winter droughts will have a larger impact on balancing the electric grid than summer droughts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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