Estimating tornado occurrence and tornado wind hazard in China
Why this work is in the frame
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Bibliographic record
Abstract
Tornadoes can potentially damage structures and cause fatalities. Although tornado occurrence is often observed in China’s mainland, a systematic development of a comprehensive catalogue that forms the basis for tornado hazard assessment and mapping was not available. In the present study, a tornado catalogue from 1949 to 2023 over China’s mainland was compiled based on extensive literature research. This catalogue was used as the basis to map the spatially varying tornado occurrence rate and to develop a stochastic tornado occurrence model. For the mapping of the spatially varying tornado occurrence, the adaptive Gaussian kernel smoothing and the adaptive diffusion smoothing were employed. The newly developed stochastic occurrence model together with an adopted practical tornado wind field model were used to map the tornado hazards over China’s mainland in terms of the annual maximum tornado wind speed for given exceedance probabilities. The hazard was assessed for a site represented by a point as well as for a circular area, showing that the hazard is not negligible, and the hazard increases drastically as the size of the circular area increases. This implied that tornado hazard can be significant for a portfolio of structures within a relatively large circular area. The mapped hazard indicated that the hazard is not negligible for nuclear structures by considering the annual exceedance probability of 10 -7 , which is stipulated in the design code. The estimated tornado wind hazard was compared with that estimated based on a code-suggested procedure, which was developed and implemented in the 1970s and 1980s. The comparison indicated that the code procedure, in general, leads to a much greater tornado wind speed hazard. Some of the assumptions that resulted in the overestimation were identified. In addition, two new sets of empirical equations for the tornado path length, width and area were developed. The first set can be used for tornadoes with the F-scale rating and the second set for tornadoes with the EF-scale rating.
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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 | 0.000 | 0.000 |
| 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 it