Megaflashes: Just How Long Can a Lightning Discharge Get?
Bibliographic record
Abstract
Abstract The existence of mesoscale lightning discharges on the order of 100 km in length has been known since the radar-based findings of Ligda in the mid-1950s. However, it took the discovery of sprites in 1989 to direct significant attention to horizontally extensive “megaflashes” within mesoscale convective systems (MCSs). More recently, 3D Lightning Mapping Arrays (LMAs) have documented sprite-initiating lightning discharges traversing several hundred kilometers. One such event in a 2007 Oklahoma MCS having an LMA-derived length of 321 km, has been certified by the WMO as the longest officially documented lightning flash. The new Geostationary Lightning Mapper (GLM) sensor on GOES-16/17 now provides an additional tool suited to investigating mesoscale lightning. On 22 October 2017, a quasi-linear convective system moved through the central United States. At 0513 UTC, the GLM indicated a lightning discharge originated in northern Texas, propagated north-northeast across Oklahoma, fortuitously traversed the Oklahoma LMA (OKLMA), and finally terminated in southeastern Kansas. This event is explored using the OKLMA, the National Lightning Detection Network (NLDN), and the GLM. The NLDN reported 17 positive cloud-to-ground flashes (+CGs), 23 negative CGs (−CGs), and 37 intracloud flashes (ICs) associated with this massive discharge, including two +CGs capable of inducing sprites, with others triggering upward lightning from tall towers. Combining all available data confirms the megaflash, which illuminated 67,845 km2, was at least 500 km long, greatly exceeding the current official record flash length. Yet even these values are being superseded as GLM data are further explored, revealing that such vast discharges may not be all that uncommon.
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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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".