Statistical downscaling and simulation of daily temperature extremes
Notice bibliographique
Résumé
There is now a broad scientific consensus that the global climate is changing in ways that could have a profound impact on human society and the natural environment over the coming decades. In particular, changes in the frequency and magnitude of extreme temperatures are likely to have more substantial impacts on the environment and human activities than changes in the mean temperature. The present study is therefore addressing three main objectives: (a) to propose a systematic data analysis method for characterizing the variability of daily extreme temperatures at different sites; (b) to develop new statistical downscaling models that could accurately describe the linkage between large-scale climate variables and the characteristics of temperature extremes at a local site; and (c) to develop a stochastic method for simulating accurately the extreme temperature processes. Firstly, a systematic data analysis procedure was proposed for analyzing the variability of daily maximum (Tmax) and minimum (Tmin) temperature characteristics. The suggested procedure consists of performing a detailed statistical analysis of twelve relevant temperature indices that are important for various practical application purposes: mean of diurnal temperature range, frost season length, growing season length, freeze and thaw cycle, 90th percentile of Tmax, 10th percentile of Tmin, means and standard deviations of Tmax, Tmin, and the daily mean temperature. The suggested method was applied to the analysis of daily Tmax and Tmin data for 20 stations in Quebec. The available records used are different from station to station, varying from 44 years to 107 years. In general, it was found that, depending on the temperature index considered as well as on the particular season of the year, there are some significant increasing or decreasing trends at some locations in Quebec. Results of this analysis would provide valuable information on the temporal and spatial variations of daily extreme temperature processes in the region. Furthermore, it can be observed that no systematic spatial variability of the increasing or decreasing trends of any of the twelve temperature indices considered could be identified for a given area in Quebec. Secondly, two new statistical downscaling models were proposed using the stepwise and robust regression methods in order to describe the linkage between largescale climate variables and the characteristics of Tmax and Tmin at a local site. The performance of these two models was tested using daily extreme temperature data available at Dorval Airport station in Quebec and the NCEP data for 25 different climate variables for the 1961-1990 period. It was found that the proposed stepwise and robust regression downscaling models can provide accurate estimates of fundamental statistical and physical properties of Tmax and Tmin. In addition, it has been observed that three climate variables, the mean sea level pressure, the 850hPa-geopotential height, and the near surface specific humidity, had the most significant effect on Tmax and Tmin at Dorval Airport. Furthermore, as compared with the popular SDSM model, the stepwise and robust regression models can provide more accurate estimates of the local Tmax and Tmin characteristics. In particular, the robust regression model was found to be the most accurate. Finally, a new stochastic simulation procedure was developed in this study for simulating the Tmax and Tmin temperature time series at a local site using the combination of the first-order autoregressive AR(1) model and the SVD technique. Results of the evaluation of the proposed AR(1)-SVD simulation method using daily extreme temperature data at Dorval Airport for the 1961-1990 period have indicated the feasibility of this method in describing accurately the observed basic statistical properties (mean, standard deviation, and first order autocorrelation) of the daily Tmax and Tmin time series at a local site.
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».