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| Titel |
Normal, rare or extreme? A recurrence-based technique for the detection of genuine extremes |
| VerfasserIn |
Davide Faranda, Carmen Alvarez-Castro, Pascal Yiou |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250106384
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| Publikation (Nr.) |
 EGU/EGU2015-6055.pdf |
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| Zusammenfassung |
| We analyze several outputs of model simulations and instrumental records of temperatures at
different locations by using new techniques originally developed for the analysis of extreme
values of dynamical systems. We show that they have the same recurrence time statistics as a
chaotic dynamical system perturbed with dynamical noise and by instrument errors. The
technique provides a criterion to discriminate whether the recurrence of a certain temperature
belongs to the normal variability or can be considered as a genuine extreme event with
respect to a specific timescale fixed as parameter. The method gives a self-consistent
estimation of the convergence of the statistics of recurrences toward the theoretical extreme
value laws. We focus on Millennium simulations using data from CMIP5 (Coupled Model
Intercomparison Project phase 5) and a couple of IPSL simulations with differents climate
forcings in order to assess how models simulate the extreme events in the recent past. |
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