Quantitative assessment of the climate components driving the pacific decadal oscillation in climate models

Abstract

The Pacific decadal oscillation (PDO) is defined as the first empirical orthogonal function (EOF) mode of the North Pacific sea surface temperature anomalies. In this study, we reconstructed the PDO using the first-order autoregressive model from various climate indices representing the El Nino-Southern oscillation (ENSO), Aleutian Low (AL), sea surface height (SSH), and thermocline depth over the Kuroshio–Oyashio extension (KOE) region. The climate indices were obtained from observation and twentieth-century simulations of the eight coupled general circulation models (CGCMs) participating in the Climate Model Intercomparison Project Phase III (CMIP3). In this manner, we quantitatively assessed the major climate components generating the PDO using observation and models. Based on observations, the PDO pattern in the central to eastern North Pacific was accurately reconstructed by the AL and ENSO indices, and that in the western North Pacific was best reconstructed by the SSH and thermocline indices. In the CMIP3 CGCMs, the relative contribution of each component to the generation of the PDO varied greatly from model to model, and observations, although the PDO patterns from most of the models were similar to the pattern observed. In the models, the PDO pattern in the eastern and western North Pacific were well reconstructed using the AL and SSH indices, respectively. However, the PDO pattern reconstructed by the ENSO index was quite different from the observed pattern, which was possibly due to the model's common deficiency in simulating the amplitude and location of the ENSO. Furthermore, the differences in the contribution of the KOE thermocline index between the observed pattern and most of the models indicated that the PDO pattern associated with ocean wave dynamics is not properly simulated by most models. Therefore, the virtually well simulated PDO pattern by models is a result of physically inconsistent processes.