Occurrence of tornado outbreaks in the context of solar wind coupling to magnetosphere-ionosphere-atmosphere
Bibliographic record
Abstract
The National Oceanic and Atmospheric Administration National Weather Service database of tornadoes provided by the Storm Prediction Center is used to investigate the occurrence of tornado outbreaks in the United States from 1963 to 2021 in the context of solar wind that impacts the Earth’s magnetosphere. A link between the solar wind and large tornado outbreaks is found. Superposed epoch analysis of tornado occurrence reveals a peak in the cumulative number of tornadoes near the interplanetary magnetic field sector boundary (heliospheric current sheet) crossings. The latter often closely precede or coincide with co-rotating interaction regions at the leading edge of high-speed streams from coronal holes. Most of the large tornado outbreaks (20 or more tornadoes per 24 hours) are associated with high-density plasma adjacent to heliospheric current sheets and co-rotating interaction regions. Other large tornado outbreaks followed impacts of interplanetary coronal mass ejections or occurred in a declining phase of major high-speed streams. We consider the role of the solar wind coupling to the magnetosphere-ionosphere-atmosphere system in severe weather development, mediated by globally propagating aurorally excited atmospheric gravity waves. While these gravity waves reach the troposphere with attenuated amplitudes, when over-reflecting in regions of low-level wind shear and opposing winds, they can contribute to conditional symmetric instability release in frontal zones of extratropical cyclones leading to intensification of supercells that spawn tornado outbreaks. The ERA5 meteorological re-analysis is used to evaluate slantwise convective available potential energy (SCAPE) to assess conditional symmetric instability and slantwise convection in cases of large tornado outbreaks.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 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".