Long-term spatial modelling for characteristics of extreme heat events

Schliep, Erin M. ; Gelfand, Alan E. ; Abaurrea, Jesús (Universidad de Zaragoza) ; Asín, Jesús (Universidad de Zaragoza) ; Beamonte, María A. (Universidad de Zaragoza) ; Cebrián, Ana C. (Universidad de Zaragoza)

Resumen: There is increasing evidence that global warming manifests itself in more frequent warm days and that heat waves will become more frequent. Presently, a formal definition of a heat wave is not agreed upon in the literature. To avoid this debate, we consider extreme heat events, which, at a given location, are well-defined as a run of consecutive days above an associated local threshold. Characteristics of extreme heat events (EHEs) are of primary interest, such as incidence and duration, as well as the magnitude of the average exceedance and maximum exceedance above the threshold during the EHE. Using approximately 60-year time series of daily maximum temperature data collected at 18 locations in a given region, we propose a spatio-temporal model to study the characteristics of EHEs over time. The model enables prediction of the behaviour of EHE characteristics at unobserved locations within the region. Specifically, our approach employs a two-state space–time model for EHEs with local thresholds where one state defines above threshold daily maximum temperatures and the other below threshold temperatures. We show that our model is able to recover the EHE characteristics of interest and outperforms a corresponding autoregressive model that ignores thresholds based on out-of-sample prediction.

Idioma: Inglés

DOI: 10.1111/rssa.12710

Año: 2021

Publicado en: Journal of the Royal Statistical Society. Series A. Statistics in society 184, 3 (2021), 1070-1092
ISSN: 0964-1998

Factor impacto JCR: 2.175 (2021)

Categ. JCR: SOCIAL SCIENCES, MATHEMATICAL METHODS rank: 25 / 53 = 0.472 (2021) - Q2 - T2
Categ. JCR: STATISTICS & PROBABILITY rank: 39 / 125 = 0.312 (2021) - Q2 - T1

Factor impacto CITESCORE: 3.6 - Social Sciences (Q1) - Economics, Econometrics and Finance (Q1) - Mathematics (Q1) - Decision Sciences (Q2)

Factor impacto SCIMAGO: 1.191 - Economics and Econometrics (Q1) - Statistics, Probability and Uncertainty (Q1) - Social Sciences (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/MTM2017-83812-P

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Estadís. Investig. Opera. (Dpto. Métodos Estadísticos)
Área (Departamento): Área Métodos Cuant.Econ.Empres (Dpto. Economía Aplicada)