000156582 001__ 156582 000156582 005__ 20251017144612.0 000156582 0247_ $$2doi$$a10.1111/rssa.12710 000156582 0248_ $$2sideral$$a124675 000156582 037__ $$aART-2021-124675 000156582 041__ $$aeng 000156582 100__ $$aSchliep, Erin M. 000156582 245__ $$aLong-term spatial modelling for characteristics of extreme heat events 000156582 260__ $$c2021 000156582 5203_ $$aThere 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. 000156582 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/MTM2017-83812-P 000156582 540__ $$9info:eu-repo/semantics/closedAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000156582 590__ $$a2.175$$b2021 000156582 591__ $$aSOCIAL SCIENCES, MATHEMATICAL METHODS$$b25 / 53 = 0.472$$c2021$$dQ2$$eT2 000156582 591__ $$aSTATISTICS & PROBABILITY$$b39 / 125 = 0.312$$c2021$$dQ2$$eT1 000156582 592__ $$a1.191$$b2021 000156582 593__ $$aEconomics and Econometrics$$c2021$$dQ1 000156582 593__ $$aStatistics, Probability and Uncertainty$$c2021$$dQ1 000156582 593__ $$aSocial Sciences (miscellaneous)$$c2021$$dQ1 000156582 594__ $$a3.6$$b2021 000156582 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000156582 700__ $$aGelfand, Alan E. 000156582 700__ $$0(orcid)0000-0002-7974-7435$$aAbaurrea, Jesús$$uUniversidad de Zaragoza 000156582 700__ $$0(orcid)0000-0002-0174-789X$$aAsín, Jesús$$uUniversidad de Zaragoza 000156582 700__ $$0(orcid)0000-0003-2617-4167$$aBeamonte, María A.$$uUniversidad de Zaragoza 000156582 700__ $$0(orcid)0000-0002-9052-9674$$aCebrián, Ana C.$$uUniversidad de Zaragoza 000156582 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera. 000156582 7102_ $$14014$$2623$$aUniversidad de Zaragoza$$bDpto. Economía Aplicada$$cÁrea Métodos Cuant.Econ.Empres 000156582 773__ $$g184, 3 (2021), 1070-1092$$pJ. R. Stat. Soc., Ser. A Stat. soc.$$tJournal of the Royal Statistical Society. Series A. Statistics in society$$x0964-1998 000156582 8564_ $$s956086$$uhttps://zaguan.unizar.es/record/156582/files/texto_completo.pdf$$yVersión publicada 000156582 8564_ $$s1509112$$uhttps://zaguan.unizar.es/record/156582/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000156582 909CO $$ooai:zaguan.unizar.es:156582$$particulos$$pdriver 000156582 951__ $$a2025-10-17-14:18:03 000156582 980__ $$aARTICLE