Cloud-to-Ground Lightning in Canada: 20 Years of CLDN Data
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
This study presents the spatial and temporal features of more than 45 million cloud-to-ground (CG) lightning flashes recorded by the Canadian Lightning Detection Network for the years 1999–2018. Although sensor upgrades have improved the detection efficiency and location accuracy of CG lightning, the large-scale spatial patterns remain about the same as found in a previous study covering the years 1999–2008. Analyses, using equal-area squares with 10 km sides, describe the regional and seasonal characteristics of negative and positive flashes, the percentage and flash density of positive lightning, and the first-stroke peak currents of both polarities. Lightning activity over the provinces and territories is greatest in the summer, varying from 95.9% to 76.8% of the annual activity in the Northwest Territories and Ontario, respectively. Winter lightning is rare, usually occurring in extreme southern Ontario and the Atlantic Provinces, as well as over offshore regions west of Vancouver Island and the coastal waters off Nova Scotia. Preliminary analysis suggests that, compared with the 1999–2008 period, the majority of western and northern Canada has experienced more lightning days during the 2009–2018 period, whereas much of eastern Canada has experienced fewer lightning days. A statistical analysis performed on 154 stations across Canada found that the decadal increases (decreases) at 5 (31) stations were significant at the 90% confidence level or higher, and 4 (16) of these were significant at the 95% confidence level.
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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 | 0.001 | 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