The Northern Tornadoes Project – Shifting the Post-Event Paradigm in Canada
Notice bibliographique
Résumé
The Northern Tornadoes Project (NTP) was founded in 2017 at Canada's Western University, supported by social impact fund ImpactWX, with the aim of better detecting tornado occurrence, improving severe and extreme weather prediction, mitigating against harm to people and property, and investigating the future implications of climate change. The project was initially limited in scope – attempting to find at least a few undocumented tornadoes in the northern forests of Ontario and Quebec. After demonstrating that the NTP could more than double the annual tornado count in those provinces, the NTP set out to detect, assess and document every tornado that occurs across the country. We also forged other partnerships with Western Libraries, University of Manitoba, York University, Pelmorex’s The Weather Network, Instant Weather, and CatIQ. Research collaborations were undertaken with a number of academic institutions inside and outside of Canada. As the project evolved, the NTP required new techniques and technologies to allow us to meet our ambitious scientific goals. Cutting-edge remote sensing capacity, including ultra high-resolution satellite imagery and piloted and remotely piloted aircraft systems, needed to be utilized and the latest processing techniques adopted. New means of assessing wind damage were employed. Even a new set of definitions related to tornadoes and related phenomenon had to be developed. The societal impacts of significant events are also increasingly being investigated and becoming part of the event record. Interestingly, as our assessment tools reach ever-higher resolution, new problems emerge. A lower-resolution image showing what might have been considered a wide tornado path through the forest in the past now often shows evidence of a mix of tornado and downburst damage, and thorough tree-by-tree analysis is needed to untangle the two. Thus, methods for rating and documenting tornado and downburst damage must also evolve as resolution increases. In addition, the NTP is building new ways of using social media reports of severe weather as crowdsourced data, including creating a community of ‘super-contributors’ that provide high-quality evidence. Sophisticated methods for ‘scraping’ social media for key reports are also under development. As a result of these detection, assessment and documentation processes, we are generating novel research-quality data sets that are being employed by a number of different types of users. All NTP data are open source in order to foster further innovation. The presentation will provide a number of detailed examples showing how the NTP has shifted the post-event paradigm in Canada.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,022 | 0,006 |
| Communication savante | 0,010 | 0,003 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».