A Bayesian hierarchical spatio-temporal model for summer extreme temperatures in Spain
[EN] A statistical study was made of the summer extreme temperatures over peninsular Spain in the last forty years. Records from 158 observatories regularly distributed over Iberia with no missing data were available for the common period from 1981 to 2020. For this purpose, a hierarchical spatio-te...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad de León |
| Repositorio: | BULERIA. Repositorio Institucional de la Universidad de León |
| OAI Identifier: | oai:buleria.unileon.es:10612/23762 |
| Acceso en línea: | https://link.springer.com/article/10.1007/s00477-024-02754-8 https://hdl.handle.net/10612/23762 |
| Access Level: | acceso abierto |
| Palabra clave: | Estadística Física Meteorología Bayesian hierarchical model Gaussian copula Extreme temperature GEV distribution |
| Sumario: | [EN] A statistical study was made of the summer extreme temperatures over peninsular Spain in the last forty years. Records from 158 observatories regularly distributed over Iberia with no missing data were available for the common period from 1981 to 2020. For this purpose, a hierarchical spatio-temporal model with a Gaussian copula and a generalized extreme value parametrization of the extreme events was used. The temporal trend in maximum extreme temperatures was studied making use of both a stationary model and a nonstationary one that takes into account the infuence of anthropogenic climate change on extreme temperatures using the global mean temperature as a function of time for the study period. The results led to a better ft of the nonstationary model, with there being a 3.5-fold greater increase in the 20-year return level of the extreme temperatures than in that corresponding to the global mean temperature. |
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