A Nonlinear Cause for the seasonal Predictability Barrier of SST anomaly
in the 2 tropical Pacific
Abstract
The seasonal Predictability Barrier (PB) of Sea Surface Temperature
Anomaly (SSTA) is characterized by a rapid loss of prediction skills at
a specific season in dynamic models. To investigate whether this PB
phenomenon is caused by the inherent nonlinearity of the air-sea coupled
system that leads to chaos under certain conditions, a statistical
method - Sample Entropy, was introduced to investigate the
spatial-temporal distribution of the chaotic degree of SSTA time series
in the tropic Pacific. The results showed that high chaotic values
existed in Niño 3 and Niño 3.4 regions in April and May, and in Niño 4
region in May and June, which matched the PB timing previously reported
in these regions. Furthermore, the chaotic signal moves westward from
March to June longitudinally in the tropical Pacific, leading to a
similar linear variation of PB timing along the longitude.