000163928 001__ 163928
000163928 005__ 20251121145034.0
000163928 0247_ $$2doi$$a10.1093/jrsssc/qlaf046
000163928 0248_ $$2sideral$$a146059
000163928 037__ $$aART-2025-146059
000163928 041__ $$aeng
000163928 100__ $$0(orcid)0000-0003-3859-0248$$aCastillo-Mateo, Jorge$$uUniversidad de Zaragoza
000163928 245__ $$aJoint space-time modelling for upper daily maximum and minimum temperature record-breaking
000163928 260__ $$c2025
000163928 5060_ $$aAccess copy available to the general public$$fUnrestricted
000163928 5203_ $$aRecord-breaking temperature events are now frequently in the news, proffered as evidence of climate change, and often bring significant economic and human impacts. Our previous work undertook the first substantial spatial modelling investigation of temperature record-breaking across years for any given day within the year, employing a dataset consisting of over 60 years of daily maximum temperatures across peninsular Spain. That dataset also supplies daily minimum temperatures (which, in fact, are now available through 2023). Here, the dataset is converted into a daily pair of binary events, indicators, for that day, of whether a yearly record was broken for the daily maximum temperature and/or for the daily minimum temperature. Joint modelling addresses several inference issues: (i) defining/modelling record-breaking with bivariate time series of yearly indicators, (ii) strength of relationship between record-breaking events, (iii) prediction of joint, conditional and marginal record-breaking, (iv) persistence in record-breaking across days, and (v) spatial interpolation across peninsular Spain. We substantially expand our previous work to enable investigation of these issues. We observe strong correlation between both processes but a growing trend of climate change that is well differentiated between them both spatially and temporally as well as different strengths of persistence and spatial dependence.
000163928 536__ $$9info:eu-repo/grantAgreement/ES/AEI/TED2021-130702B-I00$$9info:eu-repo/grantAgreement/ES/DGA/E46-23R$$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-116873GB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2023-150234NB-I00
000163928 540__ $$9info:eu-repo/semantics/embargoedAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000163928 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000163928 700__ $$0(orcid)0000-0003-2461-8588$$aGracia-Tabuenca, Zeus$$uUniversidad de Zaragoza
000163928 700__ $$0(orcid)0000-0002-0174-789X$$aAsín, Jesús$$uUniversidad de Zaragoza
000163928 700__ $$0(orcid)0000-0002-9052-9674$$aCebrián, Ana C$$uUniversidad de Zaragoza
000163928 700__ $$aGelfand, Alan E
000163928 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera.
000163928 773__ $$g(2025), qlaf046 [28 pp.]$$pAppl. stat.$$tJOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS$$x0035-9254
000163928 8564_ $$s4782757$$uhttps://zaguan.unizar.es/record/163928/files/texto_completo.pdf$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2026-10-15
000163928 8564_ $$s1729334$$uhttps://zaguan.unizar.es/record/163928/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2026-10-15
000163928 909CO $$ooai:zaguan.unizar.es:163928$$particulos$$pdriver
000163928 951__ $$a2025-11-21-14:41:10
000163928 980__ $$aARTICLE