Mean and extreme temperatures in a warming climate: EURO CORDEX and WRF regional climate high-resolution projections for Portugal

Abstract

Large temperature spatio-temporal gradients are a common feature of Mediterranean climates. The Portuguese complex topography and coastlines enhances such features, and in a small region large temperature gradients with high interannual variability is detected. In this study, the EURO-CORDEX high-resolution regional climate simulations (0.11° and 0.44° resolutions) are used to investigate the maximum and minimum temperature projections across the twenty-first century according to RCP4.5 and RCP8.5. An additional WRF simulation with even higher resolution (9 km) for RCP8.5 scenario is also examined. All simulations for the historical period (1971–2000) are evaluated against the available station observations and the EURO-CORDEX model results are ranked in order to build multi-model ensembles. In present climate models are able to reproduce the main topography/coast related temperature gradients. Although there are discernible differences between models, most present a cold bias. The multi-model ensembles improve the overall representation of the temperature. The ensembles project a significant increase of the maximum and minimum temperatures in all seasons and scenarios. Maximum increments of 8 °C in summer and autumn and between 2 and 4 °C in winter and spring are projected in RCP8.5. The temperature distributions for all models show a significant increase in the upper tails of the PDFs. In RCP8.5 more than half of the extended summer (MJJAS) has maximum temperatures exceeding the historical 90th percentile and, on average, 60 tropical nights are projected for the end of the century, whilst there are only 7 tropical nights in the historical period. Conversely, the number of cold days almost disappears. The yearly average number of heat waves increases by seven to ninefold by 2100 and the most frequent length rises from 5 to 22 days throughout the twenty-first century. 5% of the longest events will last for more than one month. The amplitude is overwhelming larger, reaching values which are not observed in the historical period. More than half of the heat waves will be stronger than the extreme heat wave of 2003 by the end of the century. The future heatwaves will also enclose larger areas, approximately 100 events in the 2071–2100 period (more than 3 per year) will cover the whole country. The RCP4.5 scenario has in general smaller magnitudes.

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    http://esg-dn1.nsc.liu.se/esgf-web-fe/live.

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Acknowledgements

The authors wish to acknowledge the projects SOLAR (PTDC/GEOMET/7078/2014), SHARE (RECI/GEOMET/0380/2012) and the EarthSystems Doctoral Programme at the Faculty of Sciences of the University of Lisbon (Grant PD/BD/ 106008/2014) without which this work wouldn’t be possible. This work was also supported by project FCT UID/GEO/50019/ 2013—Instituto Dom Luiz. The authors thank IPMA, I.P. for the data provided for this work (observational temperature station observations). Finally, the authors acknowledge the World Climate Research Programme’s Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5. The authors also thank the climate modelling groups (listed in Table 1 of this paper) for producing and making available their model output. The authors also acknowledge the Earth System Grid Federation infrastructure, an international effort led by the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling and other partners in the Global Organisation for Earth System Science Portals (GO-ESSP).

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Correspondence to Rita M. Cardoso.

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Cardoso, R.M., Soares, P.M.M., Lima, D.C.A. et al. Mean and extreme temperatures in a warming climate: EURO CORDEX and WRF regional climate high-resolution projections for Portugal. Clim Dyn 52, 129–157 (2019). https://doi.org/10.1007/s00382-018-4124-4

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Keywords

  • Climate change
  • Regional climate modelling
  • Extreme temperatures
  • Heat waves
  • High resolution multi-model ensembles