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Record W4323043566 · doi:10.5194/ecss2023-151

The International Fujita Scale and its implementation

2023· preprint· en· W4323043566 on OpenAlexaboutno aff
Pieter Groenemeijer, Alois M. Holzer, Thilo Kühne, Tomáš Púčik

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFujita scaleScale (ratio)TornadoEnvironmental scienceMeteorologyGeographyCartography

Abstract

fetched live from OpenAlex

<p>Here we report on the development of the International Fujita (IF) scale, developed by ESSL and partners, which provides a globally applicable framework for rating tornado and convective wind damage. </p> <p>Around the world, tornado damage is rated using the Enhanced Fujita (EF-)scale, the original Fujita scale, the T-scale, or national adaptations of the Enhanced Fujita scale. ESSL started the development of the IF-scale when noted that the original Fujita scale damage description provided insufficient guidance for rating tornadoes in Europe, mostly because of varying sturdiness of damaged buildings, an issue that Fujita himself addressed in his later work. The development of the IF-scale was catalysed by the introduction of the EF-scale in the USA in 2007, which drastically reduced wind speed estimates for higher wind speeds while simultaneously raising it for the F0/F1 boundary compared to the original F-scale: a change apparently motivated by a need to correct for biases in tornado rating practices.</p> <p>Instead of referring to building types typical for a specific region, the IF-scale instead defines categories of Damage Indicators that are more universal and can be adapted to other regions, using a damage indicator ‘building’ with an attribute ‘sturdiness’. Any building can be a damage indicator after being assigned a level of sturdiness. The IF-scale also retains the original Fujita-scale wind speed estimates, at least until measured data are available that give better estimates. The wind speed that the scale relates to is instantaneous rather than the average wind speed at 10 m above ground, as evidence is accumulating (through high-quality videos and mobile doppler radar measurements) that the wind speeds responsible for tornado damage often have a much shorter duration than the typical averaging periods for wind gust measurements. The IF-scale heavily borrows from experience in regions that have adapted the EF-scale locally, such as the Japanese and Canadian adaptations, and adds additional damage indicators such as for trees, road and rail vehicles, and many other objects.</p> <p>Recently, ESSL evaluated a preliminary version of the IF-scale by applying it to a violent tornado case in Czechia on 24 June 2021. This application revealed weaknesses that have since been addressed. We will present the latest version of the IF-scale that has become the standard scale used in ESSL’s record of severe weather in Europe, the European Severe Weather Database.</p>

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.293
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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