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  5. On the spectral characteristics of the Atlantic multidecadal variability in an ensemble of multi-century simulations
 
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On the spectral characteristics of the Atlantic multidecadal variability in an ensemble of multi-century simulations

Author(s)
Mavilia, Irene  
Bellucci, Alessio  
Athanasiadis, Panos  
Gualdi, Silvio  
Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Bologna, Bologna, Italia  
Msadek, Rym  
Ruprich-Robert, Yohan  
Language
English
Obiettivo Specifico
4A. Oceanografia e clima
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Journal
Climate Dynamics  
Issue/vol(year)
/51 (2018)
Publisher
Springer-Verlag GmbH Germany, part of Springer Nature
Pages (printed)
3507–3520
Date Issued
2018
DOI
10.1007/s00382-018-4093-7
URI
https://www.earth-prints.org/handle/2122/12491
Abstract
The Atlantic multidecadal variability (AMV) is a coherent pattern of variability of the North Atlantic sea surface temperature
field affecting several components of the climate system in the Atlantic region and the surrounding areas. The relatively
short observational record severely limits our understanding of the physical mechanisms leading to the AMV. The present
study shows that the spatial and temporal characteristics of the AMV, as assessed from the historical records, should also
be considered as highly uncertain. Using 11 multi-century preindustrial climate simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database, we show that the AMV characteristics are not constant along the simulation
when assessed from different 200-year-long periods to match the observed period length. An objective method is proposed to
test whether the variations of the AMV characteristics are consistent with stochastic internal variability. For 7 out of the 11
models analysed, the results indicate a non-stationary behaviour for the AMV time series. However, the possibility that the
non-stationarity arises from sampling errors can be excluded with high confidence only for one of the 7 models. Therefore,
longer time series are needed to robustly assess the AMV characteristics. In addition to any changes imposed to the AMV
by external forcings, the detected dependence on the time interval identified in most models suggests that the character of
the observed AMV may undergo significant changes in the future.
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