61333 20210507081943.0 doi 10.1007/s00477-014-0953-9 sideral 89059 ART-2015-89059 eng Abaurrea, J. Universidad de Zaragoza (orcid)0000-0002-7974-7435 Modeling and projecting the occurrence of bivariate extreme heat events using a non-homogeneous common Poisson shock process 2015 Access copy available to the general public Unrestricted A joint model is proposed for analyzing and predicting the occurrence of extreme heat events in two temperature series, these being daily maximum and minimum temperatures. Extreme heat events are defined using a threshold approach and the suggested model, a non-homogeneous common Poisson shock process, accounts for the mutual dependence between the extreme events in the two series. This model is used to study the time evolution of the occurrence of extreme events and its relationship with temperature predictors. A wide range of tools for validating the model is provided, including influence analysis. The main application of this model is to obtain medium-term local projections of the occurrence of extreme heat events in a climate change scenario. Future temperature trajectories from general circulation models, conveniently downscaled, are used as predictors of the model. These trajectories show a generalized increase in temperatures, which may lead to extrapolation errors when the model is used to obtain projections. Various solutions for dealing with this problem are suggested. The results of the fitted model for the temperature series in Barcelona in 1951–2005 and future projections of extreme heat events for the period 2031–2060 are discussed, using three global circulation model trajectories under the SRES A1B scenario. info:eu-repo/grantAgreement/ES/MEC/CGL2009-09646 info:eu-repo/grantAgreement/ES/MMA/ESTCENA 2009-0017 info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 2.237 2015 STATISTICS & PROBABILITY 8 / 123 = 0.065 2015 Q1 T1 ENGINEERING, CIVIL 19 / 126 = 0.151 2015 Q1 T1 WATER RESOURCES 15 / 85 = 0.176 2015 Q1 T1 ENGINEERING, ENVIRONMENTAL 21 / 50 = 0.42 2015 Q2 T2 ENVIRONMENTAL SCIENCES 88 / 225 = 0.391 2015 Q2 T2 1.051 2015 Environmental Science (miscellaneous) 2015 Q1 Environmental Engineering 2015 Q1 Water Science and Technology 2015 Q1 Safety, Risk, Reliability and Quality 2015 Q1 Environmental Chemistry 2015 Q2 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Asín, J. Universidad de Zaragoza (orcid)0000-0002-0174-789X Cebrián, A.C. Universidad de Zaragoza (orcid)0000-0002-9052-9674 2007 265 Universidad de Zaragoza Dpto. Métodos Estadísticos Área Estadís. Investig. Opera. 29, 1 (2015), 309-322 Stoch. environ. res. risk assess. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 1436-3240 545923 http://zaguan.unizar.es/record/61333/files/texto_completo.pdf Postprint 53968 http://zaguan.unizar.es/record/61333/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:61333 articulos driver 2021-05-07-08:09:05 ARTICLE