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Open AccessArticle

Recurrence Spectra of European Temperature in Historical Climate Simulations

1
Laboratoire des Sciences du Climat et de l’ Environnement, UMR 8212 CEA-CNRS-UVSQ, IPSL, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
2
Climate Simulation and Prediction Division, Centro Euro-Mediterraneo sui Cambiamenti Climatici, CMCC, Viale Berti Pichat, 6/2, 40127 Bologna, Italy
3
London Mathematical Laboratory, 8 Margravine Gardens, London W6 8RH, UK
4
The Climate Data Factory, 12 Rue de Belzunce, 75010 Paris, France
*
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(4), 166; https://doi.org/10.3390/atmos10040166
Received: 16 January 2019 / Revised: 22 March 2019 / Accepted: 23 March 2019 / Published: 28 March 2019
(This article belongs to the Special Issue Weather and Climate Extremes: Current Developments)
We analyse and quantify the recurrences of European temperature extremes using 32 historical simulations (1900–1999) of the fifth Coupled Model Intercomparison Project (CMIP5) and 8 historical simulations (1971–2005) from the EUROCORDEX experiment. We compare the former simulations to the 20th Century Reanalysis (20CRv2c) dataset to compute recurrence spectra of temperature in Europe. We find that, (1) the spectra obtained by the model ensemble mean are generally consistent with those of 20CR; (2) spectra biases have a strong regional dependence; (3) the resolution does not change the order of magnitude of spectral biases between models and reanalysis, (4) the spread in recurrence biases is larger for cold extremes. Our analysis of biases provides a new way of selecting a subset of the CMIP5 ensemble to obtain an optimal estimate of temperature recurrences for a range of time-scales. View Full-Text
Keywords: dynamical systems; temperature extremes; return levels; CMIP5; historical climatology dynamical systems; temperature extremes; return levels; CMIP5; historical climatology
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Alvarez-Castro, M.C.; Faranda, D.; Noël, T.; Yiou, P. Recurrence Spectra of European Temperature in Historical Climate Simulations. Atmosphere 2019, 10, 166.

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