Seasonal Variability of Lightning Activity in Yakutia in 2009–2019
Bibliographic record
Abstract
The instrumental continuous monitoring of lightning activity in Yakutia has been carried by the lightning direction finder since the 2000s. Devices for detection of sferic (very low frequency radio pulses emitted by lightning discharges) in Yakutia were supplemented in 2009 with relatively short-range (effective detection radius up to 480 km) single-point Stormtracker and LD-250 direction finders from Boltek Corporation (Welland, ON, Canada). The Stormtracker gives a slightly overestimated ratio of CG strokes due to the amplitude threshold of a single-point direction finder, but the device has not changed over the years, which allows for the consideration of the annual dynamics of parameters. In 2009, a sensor in Yakutsk was included in the World Wide Lightning Location Network (WWLLN). The seasonal and diurnal variations of the total lightning stroke number in the central part and the entire area of Yakutia were obtained (up to 1200 km in radius and limited by latitude–longitude boundaries of 105–150° E, 55–75° N). The longest thunderstorm seasons are often observed in the southern part of Yakutia. There was a slight increase in the duration of the thunderstorm season until 2015 in the central part of Yakutia. The interannual variations in the total number of lightning strokes showed periodic fluctuations (with a period of about three years) over the whole area of Yakutia. The periods of high lightning activity shifted within a season from year to year, as revealed by the monthly stroke number variation. Thus, the maximum lightning rate occurred at the beginning of summer, in the middle or at the beginning of August, and had a period of about three years. Every summer, there were 2–3 periods of high lightning activity, resulting from the moving average with a two-week window (according to the longest duration of cyclones). If the periods of high lightning activity shifted toward the beginning of summer, a decrease in the number of days between seasonal peaks was observed. If the maximum shifted to the beginning of August, the number of days between peaks increased. The ratio of cloud-to-ground (CG) lightning strokes and the ratio of negative CG strokes was slightly decreasing by 2015 in the central part of Yakutia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".