Initial soil moisture as a predictor of subsequent severe summer weather in the cropped grassland of the Canadian Prairie provinces
Notice bibliographique
Résumé
Abstract Soil moisture, along with the type and stage of the vegetation, influences the thermodynamic structure of the atmosphere by regulating heat and moisture fluxes in the planetary boundary layer (PBL). This study examined whether the modelled aerial‐average root‐zone soil moisture (RzSm) in ‘wet’ and ‘dry’ areas of the cropped grassland of the Canadian Prairie provinces had predictive value in determining if these areas would subsequently have above‐ or below‐normal occurrences and event days of severe summer convective weather (i.e. tornadoes, hail, heavy rains, and/or strong winds). RzSm, simulated by the Prairie Agro‐climate Model, for the 1997–2003 growing seasons was analyzed three times per season. Dry areas with RzSm ⩽50% of available water holding capacity (AWHC) and wet areas with RzSm > 50% of AWHC were delineated post‐snowmelt, on 15th June, and on 15th July. The aerial‐average RzSm levels in the dry and in the wet areas were calculated, and plotted against the relative number of occurrences and number of event days that were recorded during the remainder of the growing season for the various types of severe summer convective weather. In each case, the best‐fit linear regression line and the variance that it explained ( r 2 value) were computed. The hypothesis that the slope of each regression line was significantly different from zero was then tested. A value of r 2 close to or greater than 0.25 was arbitrarily used as a cut‐off point—a relationship with an r 2 close to or greater than this value, and with a regression line slope that was significantly different from zero, was selected as one which could have potential value in the climatological forecasting of severe summer convective weather. For most of the severe weather types, the relative number of occurrences and the relative number of event days, which were recorded subsequent to the three dates on which the aerial‐average RzSm was determined were greater in the wet areas than in the dry areas. Copyright © 2008 Royal Meteorological Society
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».