Recent trends of extreme precipitation indices in the Iberian Peninsula using observations and WRF model results |
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| Institution: | 1. Dipartimento di Scienze della Terra e Geoambientali, Università degli Studi di Bari “Aldo Moro”, via E. Orabona 4, I-70125, Bari, Italy;2. Dipartimento di Scienze della Terra, Università di Pisa, via S. Maria 53, I-56100, Pisa, Italy;3. Dipartimento di Scienze, Università di Roma Tre, Largo S. Leonardo Murialdo 1, I-00146, Roma, Italy;4. INFN-Laboratori Nazionali di Frascati, Via E. Fermi 40, I-00044, Frascati, Roma, Italy;1. FEUP – Engineering Faculty, Porto University, Rua Dr. Roberto Frias, 4200-465, Portugal;2. ISEP – School of Engineering, Polytechnic of Porto, Rua Dr. Antonio Bernardino de Almeida, 431, 4200-072 Porto, Portugal;3. CERENA – Centre for Natural Resources and the Environment, Instituto Superior Técnico, Technical University of Lisbon (TULisbon), Av. Rovisco Pais, 1049-001 Lisboa, Portugal;4. PROA – Laboratory for Prevention of Environmental and Occupational Risks, Engineering Faculty, Porto University, Rua Dr. Roberto Frias, 4200-465, Portugal;5. LAETA – Associated Laboratory for Energy, Transports and Aeronautics, Engineering Faculty, Porto University, Rua Dr. Roberto Frias, 4200-465, Portugal;1. Instituto Geológico y Minero de España (IGME), Ríos Rosas 23, 28003 Madrid, Spain;2. Departamento de Ciencias Politécnicas, Escuela Universitaria Politécnica, Universidad Católica San Antonio de Murcia (UCAM), 30107 Murcia, Spain;3. Instituto de Ciencias Químicas Aplicadas, Facultad de Ingeniería, Universidad Autónoma de Chile, 7500138 Santiago, Chile;1. Space Research Institute, Russian Academy of Sciences, 84/32, Profsoyuznaya Str., Moscow 117997, Russian Federation;2. P.P. Shirshov Institute of Oceanology, Russian Academy of Sciences, 36, Nakhimovsky Pr, Moscow 117997, Russian Federation;3. Laboratory of Integrated Research of Water Resources, S.Yu. Witte Moscow University, Second Kozhukhovsky pr. 12, Build. 1, Moscow 115432, Russian Federation;1. Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, United States;2. International Research Institute for Climate and Society, Palisades, NY, United States |
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| Abstract: | Spatial and temporal distributions of the trends of extreme precipitation indices were analysed between 1986 and 2005, over the Iberian Peninsula (IP). The knowledge of the patterns of extreme precipitation is important for impacts assessment, development of adaptation and mitigation strategies. As such, there is a growing need for a more detailed knowledge of precipitation climate change.This analysis was performed for Portuguese and Spanish observational datasets and results performed by the Weather Research and Forecast (WRF) model forced by the ERA-Interim reanalysis. Extreme precipitation indices recommended by the Expert Team for Climate Change Detection Monitoring and Indices were computed, by year and season. Then, annual and seasonal trends of the indices were estimated by Theil-Sen method and their significance was tested by the Mann-Kendal test. Additionally, a second simulation forced by the Max Planck Institute Earth System Model (MPI-ESM), was considered. This second modelling configuration was created in order to assess its performance when simulating extremes of precipitation.The annual trends estimated for the 1986–2005, from the observational datasets and from the ERA-driven simulation reveal: 1) negative statistically significant trends of the CWD index in the Galicia and in the centre of the IP; 2) positive statistically significant trends of the CDD index over the south of the IP and negative statistically significant trends in Galicia, north and centre of Portugal; 3) positive statistically significant trends of the R75p index in some regions of the north of the IP; 4) positive statistically significant trends in the R95pTOT index in the Central Mountains Chain, Leon Mountains and in the north of Portugal.Seasonally, negative statistically significant trends of the CWD index were found in Galicia, in winter and in the south of the IP, in summer. Positive statistically significant trends of the CWD index were identified in the Leon Mountains, in spring, and in Galicia, in autumn. For the CDD index, negative statistically significant trends were seen in Valencia, in the spring, and, in Galicia and Portugal (north and centre), in summer. Positive statistically significant trends of the CDD index were found: in the east of the IP, in the winter; in the Cantabrian Mountain, in the spring; and, in the south of the IP, in summer. Regarding to the R75p index, negative statistically significant trends were found in Galicia, in winter and positive statistically significant trends in the north of Portugal, in spring and in the Central Mountains Chain and north of Portugal, in autumn. For the R95pTOT index, negative statistically significant trends were found over the Sierra Cuenca and Sierra Cazorla, in winter and positive statistically significant trends were found over the Sierra Cebollera, in winter and in Castile-la Mancha region, in spring.The results of the annual and seasonal trends of the extreme precipitation indices performed for observational datasets and the simulation forced by ERA-Interim, are similar. The results obtained for the simulation forced by MPI-ESM are not satisfactory, and can be a source of criticism for the use of simulation forced by MPI-ESM in this type of climate change studies. Even for the relatively short period used, the WRF model, when properly forced is a useful tool due to the similar results of Portuguese and Spanish observational datasets and the simulation forced by ERA-Interim. |
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| Keywords: | Extreme precipitation indices Iberian Peninsula Trends Observations MPI-ESM ERA-Interim |
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