Spatial Modeling of Day-Within-Year Temperature Time Series: An Examination of Daily Maximum Temperatures in Aragon, Spain

Castillo-Mateo, Jorge (Universidad de Zaragoza) ; Lafuente, Miguel (Universidad de Zaragoza) ; Asin, Jesus (Universidad de Zaragoza) ; Cebrian, Ana C. (Universidad de Zaragoza) ; Gelfand, Alan E. ; Abaurrea, Jesus (Universidad de Zaragoza)

Resumen: Acknowledging a considerable literature on modeling daily temperature data, we propose a multi-level spatiotemporal model which introduces several innovations in order to explain the daily maximum temperature in the summer period over 60 years in a region containing Aragon, Spain. The model operates over continuous space but adopts two discrete temporal scales, year and day within year. It captures temporal dependence through autoregression on days within year and also on years. Spatial dependence is captured through spatial process modeling of intercepts, slope coefficients, variances, and autocorrelations. The model is expressed in a form which separates fixed effects from random effects and also separates space, years, and days for each type of effect. Motivated by exploratory data analysis, fixed effects to capture the influence of elevation, seasonality, and a linear trend are employed. Pure errors are introduced for years, for locations within years, and for locations at days within years. The performance of the model is checked using a leave-one-out cross-validation. Applications of the model are presented including prediction of the daily temperature series at unobserved or partially observed sites and inference to investigate climate change comparison. Supplementary materials accompanying this paper appear online.

Idioma: Inglés

DOI: 10.1007/s13253-022-00493-3

Año: 2022

Publicado en: JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS 27 (2022), 487–505
ISSN: 1085-7117

Factor impacto JCR: 1.4 (2022)

Categ. JCR: STATISTICS & PROBABILITY rank: 64 / 125 = 0.512 (2022) - Q3 - T2
Categ. JCR: MATHEMATICAL & COMPUTATIONAL BIOLOGY rank: 44 / 55 = 0.8 (2022) - Q4 - T3
Categ. JCR: BIOLOGY rank: 72 / 92 = 0.783 (2022) - Q4 - T3

Factor impacto CITESCORE: 3.2 - Agricultural and Biological Sciences (Q2) - Mathematics (Q2) - Decision Sciences (Q2) - Environmental Science (Q2)

Factor impacto SCIMAGO: 0.711 - Agricultural and Biological Sciences (miscellaneous) (Q1) - Statistics, Probability and Uncertainty (Q2) - Statistics and Probability (Q2) - Applied Mathematics (Q2) - Environmental Science (miscellaneous) (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA/E46-20R
Financiación: info:eu-repo/grantAgreement/ES/MCED/FPU-1505266
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2020-116873GB-I00

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Estadís. Investig. Opera. (Dpto. Métodos Estadísticos)