National Oceanic and
Atmospheric Administration
United States Department of Commerce


 

FY 2006

Regime shifts and red noise in the North Pacific

Overland, J.E., D.B. Percival, and H.O. Mofjeld

Deep-Sea Res. Pt. I, 53(4), 582–588, doi: 10.1016/j.dsr.2005.12.011 (2006)


Regimes and regime shifts are important concepts for understanding decadal variability in the physical system of the North Pacific because of the potential for an ecosystem to reorganize itself in response to such shifts. There are two prevalent senses in which these concepts are taken in the literature. The first is a formal definition and posits multiple stable states and rapid transitions between these states. The second is more data-oriented and identifies local regimes based on differing average climatic levels over a multi-annual duration, i.e. simply interdecadal fluctuations. This second definition is consistent with realizations from stochastic red noise processes to a degree that depends upon the particular model. Even in 100 year long records for the North Pacific a definition of regimes based solely on distinct multiple stable states is difficult to prove or disprove, while on interdecadal scales there are apparent local step-like features and multi-year intervals where the state remains consistently above or below the long-term mean. The terminologies climatic regime shift, statistical regime shift or climatic event are useful for distinguishing this second definition from the first.

To illustrate the difficulty of advocating one definition over the other based upon a relatively short time series, we compare three simple models for the Pacific Decadal Oscillation (PDO). The 104-year PDO record is insufficient to statistically distinguish a single preference between a square wave oscillator consistent with the formal definition for regime shifts, and two red noise models that are compatible with climatic regime shifts. Because of the inability to distinguish between underlying processes based upon data, it is necessary to entertain multiple models and to consider how each model would impact resource management. In particular the persistence in the fitted models implies that certain probabilistic statements can be made regarding climatic regime shifts, but we caution against extrapolation to future states based on curve fitting techniques.




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