Modeling and projecting the occurrence of bivariate extreme heat events using a non-homogeneous common Poisson shock process
Resumen: 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.
Idioma: Inglés
DOI: 10.1007/s00477-014-0953-9
Año: 2015
ISSN: 1436-3240

Factor impacto JCR: 2.237 (2015)
Categ. JCR: STATISTICS & PROBABILITY rank: 8 / 123 = 0.065 (2015) - Q1 - T1
Categ. JCR: ENGINEERING, CIVIL rank: 19 / 126 = 0.151 (2015) - Q1 - T1
Categ. JCR: WATER RESOURCES rank: 15 / 85 = 0.176 (2015) - Q1 - T1
Categ. JCR: ENGINEERING, ENVIRONMENTAL rank: 21 / 50 = 0.42 (2015) - Q2 - T2
Categ. JCR: ENVIRONMENTAL SCIENCES rank: 88 / 225 = 0.391 (2015) - Q2 - T2

Factor impacto SCIMAGO: 1.051 - Environmental Science (miscellaneous) (Q1) - Environmental Engineering (Q1) - Water Science and Technology (Q1) - Safety, Risk, Reliability and Quality (Q1) - Environmental Chemistry (Q2)

Financiación: info:eu-repo/grantAgreement/ES/MEC/CGL2009-09646
Financiación: info:eu-repo/grantAgreement/ES/MMA/ESTCENA 2009-0017
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Estadís. Investig. Opera. (Dpto. Métodos Estadísticos)

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