A climate index is a time series that quantifies the temporal evolution of a climate process in a particular region. Various climatic patterns, such as the El Niño-Southern Oscillation, Pacific Decadal Oscillation (PDO), Arctic Oscillation, and North Atlantic Oscillation (NAO), have been summarized into climate indices corresponding to the respective regions; a comparison among these indices enables various further inferences. In this study, we investigated the interconnection between the Pacific and Atlantic Oceans using the representative climate indices, i.e. the PDO and NAO indices, respectively. Using empirical mode decomposition (EMD) and statistical analysis, it was shown that these two indices share the same long-term oscillation phase in the low-frequency domain, while in the high-frequency domain, the cross-correlation and the serial correlations of the two indices vary according to the phase of the long-term oscillation. This implies that a certain long-term oscillatory forcing influences both the Atlantic and Pacific regions. Three global gridded climate variables [i.e. sea-level pressure (SLP), precipitable water (PW), and sea-surface temperature (SST)] were studied over three different periods (i.e. the negative phase period of the long-term oscillation centered on 1960 and the positive phase centered on 1990). The mean 11 year anomalies revealed a noticeable particular spatial pattern and opposing tendencies for these periods. Furthermore, the global spatial patterns inducing the cross-correlation between the NAO and PDO indices and the lag-1 auto-correlations of the NAO index are presented. Based on the results presented in the current study, a long-term oscillation with a 70 to 80 year cycle may exist in the Pacific and Atlantic regions simultaneously. Because the slow and cyclic long-term oscillation can be predictable using EMD, if the same climate conditions of the Pacific and Atlantic Oceans continue as the last several decades, the spatial evolution of climate variables might also be inferred according to the phase of the long-term oscillation. Further physical study and analysis of long proxy records should help provide more conclusive results. Copyright © 2012 Royal Meteorological Society
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