Assessing and Reconstructing Community-Scale Weather Variability at Okanese First Nation
Notice bibliographique
Résumé
Time series analysis of weather elements (ie, air temperature, humidity, wind speed and direction, pressure, and rainfall) are used as indicators of Earth’s changing climate. However, the variability amongst these elements are often underrepresented at a community scale. The purpose of this study was to reconstruct an air temperature record at Okanese First Nation, Saskatchewan, Canada. To achieve this purpose, three objectives were identified. The first objective was to visualize and assess the spatial variation of weather elements in Okanese First Nation. The second objective was to determine which spatial interpolation technique performed best at estimating air temperature with the community-scale established. The final objective was to quantify a baseline historic air temperature record at Okanese First Nation. An analysis of weather data from four meteorological stations within the community was used to determine how the weather elements varied in time and space. With this analysis it was possible to determine the total number of stations that were warranted within the community. Knowing how the weather elements were behaving in the community allowed for the start of the second objective. Three different spatial interpolation techniques were tested – inverse distance weighting, ordinary kriging, and universal kriging - to determine which estimated air temperature best within the community. Model values were computed for each technique and directly compared to observed values from the stations established within Okanese First Nation. Through testing, it was determined that IDW was the most suitable technique to use to reconstruct the historic air temperature. For the third objective, data was collected from Environment and Climate Change Canada for a 72-year period (1950-2021). Weather records from ECCC were used to spatially interpolate using IDW the air temperature within Okanese First Nation throughout the past. With this result, warming across every season and an annual average warming was noted. The results are significant as they help the community quantify environmental change in their community in support of their own observations. The community will be able to use this data to help further their Climate Change Adaptation Strategy with hopes of mitigating or adapting to the impacts from climate change.
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 | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».