Interannual to decadal predictability of tropical and North Pacific sea surface temperatures

A multivariate empirical model is used to show that predictability of the dominant patterns of tropical and North Pacific oceanic variability, El Nino-Southern Oscillation (ENSO), and the Pacific decadal oscillation (PDO), is mostly limited to little more than a year, despite the presence of spectral peaks on decadal time scales. The model used is a linear inverse model (LIM) derived from the observed simultaneous and 1-yr lag correlation statistics of July-June-averaged SST from the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) dataset for the years 1900-2002. The model accurately reproduces the power spectra of the data, including interannual and interdecadal spectral peaks that are significant relative to univariate red noise. Eigenanalysis of the linear dynamical operator yields propagating eigenmodes that correspond to these peaks but have very short decay times and, thus, limited predictability. Longer-term predictability does exist, however, due to two stationary eigenmodes that are more weakly damped. These eigenmodes do not strongly correspond to the canonical ENSO and PDO patterns. Instead, one is similar to the 1900-2002 trend and might represent anthropogenic effects, while the second represents multidecadal fluctuations of a pattern that potentially represents natural decadal variability; however, neither attribution can be made unambiguously with the analysis presented in this paper. Predictability of these two stationary eigenmodes is significantly enhanced by tropical-North Pacific coupling. Neither stationary eigenmode is well captured in the control run of any coupled GCM in the CMIP-3 project of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), perhaps because in all of the GCMs tropical SST decadal variability is too weak and North Pacific SSTs are too independent of the Tropics. A key implication of this analysis is that the PDO may represent not a single physical mode but rather the sum of several phenomena, each of which represents a different red noise with its own autocorrelation time scale and spatial pattern. The sum of these red noises can give rise to apparent PDO regime shifts and seeming characteristics of a long memory process. Such shifts are not predictable beyond the time scale of the most rapidly decorrelating noise, less than two years, although the expected duration of regimes may be determined from the relative amplitudes of different eigenmodes.