Observed El Niño‐La Niña Asymmetry in a Linear Model

Previous studies indicate an asymmetry in the amplitude and persistence of El Niño (EN) and La Niña (LN) events. We show that this observed EN‐LN asymmetry can be captured with a linear model driven by correlated additive and multiplicative (CAM) noise, without resorting to a deterministic nonlinear...

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Bibliographic Details
Published in:Geophysical research letters 2019-08, Vol.46 (16), p.9909-9919
Main Authors: Martinez‐Villalobos, Cristian, Newman, Matthew, Vimont, Daniel J., Penland, Cécile, David Neelin, J.
Format: Article
Language:English
Subjects:
Additives
Amplitude
Amplitudes
Asymmetry
El Nino
El Nino phenomena
ENSO
La Nina
LIM
Noise
nonlinear
Null hypothesis
predictability
Sea surface
Sea surface temperature
Statistical methods
stochastic
Surface temperature
tropical Pacific
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Summary:Previous studies indicate an asymmetry in the amplitude and persistence of El Niño (EN) and La Niña (LN) events. We show that this observed EN‐LN asymmetry can be captured with a linear model driven by correlated additive and multiplicative (CAM) noise, without resorting to a deterministic nonlinear model. The model is derived from 1‐month lag statistics taken from monthly sea surface temperature (SST) data sets spanning the twentieth century, in an extension of an empirical‐dynamical technique called Linear Inverse Modeling. Our results suggest that noise amplitudes tend to be stronger for EN compared to LN events, which is sufficient to generate asymmetry in amplitude and also produces more persistent LN events on average. These results establish a null hypothesis for EN‐LN asymmetry and suggest that strong EN events may not be more predictable that what can be accounted for by a multivariate linear system driven by CAM noise. Key Points El Niño‐La Niña asymmetry, usually associated with deterministic nonlinearity, may also be generated by a stochastically forced linear model A linear model forced by “correlated additive‐multiplicative noise” is empirically calculated from observed Tropical Pacific SST data Our linear model generates El Niño‐La Niña amplitude and persistence asymmetry consistent with observations (5th–95th confidence interval)
ISSN:0094-8276
1944-8007
DOI:10.1029/2019GL082922