Investigation of the Transient Nature of Thunderstorm Winds from Europe, the United States, and Australia Using a New Method for Detection of Changepoints in Wind Speed Records
Bibliographic record
Abstract
Abstract This paper investigates the transient characteristics in 41 velocity records of 19 thunderstorm events from around the world—9 from Europe, 9 from the United States, and 1 from Australia. The transient features of thunderstorm winds were examined by introducing an objective method for the detection of changepoints in the time series. The methodology divides velocity records into segments characterized by different statistical properties. The segmentation is based on the following properties of the isolated segments: mean (M) and the standard deviation (SD). This study demonstrated that the maximum velocity during the thunderstorm peak in the events from Europe is typically 2–4 times larger than the mean wind speed before the thunderstorm. The duration of the thunderstorm velocity peak was 2–5 min in approximately 60% of the analyzed records using the M statistic and 5–10 min when analyzed using the SD statistic. Therefore, the velocity fluctuations caused by thunderstorm winds last longer than the abrupt changes in the mean wind field. Similarly, the ramp-up time was longer when the records were analyzed using the SD statistic. The segmentation methodology was tested for different duration of velocity records and using data with different sampling frequencies. The performances of the introduced method were compared against the results of two other segmentation procedures proposed in the literature. One of the practical applications of this method is the physical separation between the thunderstorm and nonthunderstorm components of a wind event. Significance Statement Thunderstorm outflow winds are short-lived phenomena produced by cold downdrafts that originate in thunderstorm clouds. This study analyzes the transient nature of thunderstorm winds from Europe, the United States, and Australia using a segmentation method applied to anemometer velocity records. This segmentation method identifies abrupt changes of mean wind speed and wind fluctuations in the velocity data. This research provides the means of isolating different segments within the thunderstorm wind records in an objective way that is based on rigorous mathematical principles. The proposed method can automatically distinguish thunderstorm from nonthunderstorm winds. The peak velocities in thunderstorm outflows are 2–4 times the mean wind speed before the thunderstorm. The most intense episodes of thunderstorm winds usually last 2–5 min.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".