Effect of Heterogeneity in Models of El-Niño Southern Oscillations

Meena, Chandrakala; Kumari, Shweta; Sharma, Anjana; Sinha, Sudeshna

doi:10.48550/arxiv.1705.08171

Cited by 1 publication

(7 citation statements)

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“…14-15 that there are four attracting states when the system is under the influence of noise. Note that in [19] we had seen that lower strengths of self-delay coupling yield more steady states, compared to higher strengths of self-delay coupling. Here too we observe four robust states for α 1 = α 2 = α = 0.5, and only two robust states for α 1 = α 2 = α = 0.75.…”

Section: Robustness Of the Dynamical Attractors Under Noisementioning

confidence: 71%

“…Namely, a sub-region with very low delay (δ < 2), which would naturally go to a steady state when uncoupled, yields oscillations when coupled to another sub-region with high enough delay (δ > 2). shown in red and for region 2, T 2 is shown in green [19].…”

Section: Dynamics Of Coupled Non-identical Sub-regionsmentioning

confidence: 99%

“…This approach was taken further in Ref. [19] where two sub-regions of the Pacific was incorporated in the model. Specifically, these models mimicked the coupling of regions along the equator, where one expects varying self-delay coupling strengths in the sub-regions, as well as varying (possibly strong) delay times [18].…”

Section: Introductionmentioning

confidence: 99%

“…We will first describe this coupled model in detail, and then review the patterns emerging in this class of models, as obtained in Ref. [19].…”

Section: Introductionmentioning

confidence: 99%

“…Consider two coupled sub-regions, given by following dimensionless delay differential equations, as introduced in [18,19]:…”

Section: Introductionmentioning

confidence: 99%

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Coexistence of attractors in a coupled nonlinear delayed system modelling El Niño Southern Oscillations

Meena¹,

Surovyatkina²,

Sinha³

2017

IASCS

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We study the dynamics of the sea surface temperature (SST) anomaly using a model of the temporal patterns of two sub-regions, mimicking behaviour similar to El Niño Southern Oscillations (ENSO). Specifically, we present the existence, stability, and basins of attraction of the solutions arising in the model system in the space of these parameters: self delay, delay and inter-region coupling strengths. The emergence or suppression of oscillations in our models is a dynamical feature of utmost relevance, as it signals the presence or absence of ENSO-like oscillations. In contrast to the well-known low order model of ENSO, where the influence of the neighbouring regions on the region of interest is modelled as external noise, we consider neighbouring regions as a coupled deterministic dynamical systems. Different parameters yield a rich variety of dynamical patterns in our model, ranging from steady states and homogeneous oscillations to irregular oscillations and coexistence of oscillatory attractors, without explicit inclusion of noise. Interestingly, if we take the self-delay coupling strengths of the two sub-regions to be such that the temperature of one region goes to a fixed point regime when uncoupled, while the other system is in the oscillatory regime, then on coupling both systems show oscillations. This implies that oscillations may arise in certain sub-regions through coupling to neighbouring regions. Namely, a sub-region with very low delay, which would naturally go to a steady state when uncoupled, yields oscillations when coupled to another sub-region with high enough delay.We explicitly obtain the basins of attraction for the different steady states and oscillatory states in the model. Our results might be helpful for forecasting of El Niño (or La Niña) progress, as it indicates the combination of initial SST anomalies in the sub-regions that can result in a El Niño/La Niña episodes. In particular, the result suggests using an interval as a criterion to estimate the El-Nino or La-Nino progress instead of the currently used the single value criterion.2

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Section: Robustness Of the Dynamical Attractors Under Noisementioning

confidence: 71%

Section: Dynamics Of Coupled Non-identical Sub-regionsmentioning

confidence: 99%