Source of Seasonality and Scale Dependence of Predictability in a Coupled Ocean–Atmosphere Model

Abstract

The seasonality of predictability of ENSO (related to the so-called spring predictability barrier) is investigated using the Cane?Zebiak coupled model. Observed winds are used to force the ocean component of the model to generate analyzed initial conditions. It is shown that decrease of predictability during Northern Hemispheric spring is due to fast error growth (with a doubling time of small errors of about seven months) being associated with many, but not all, spring analyzed initial conditions. With winter analyzed initial conditions, errors always grow more slowly (with a doubling time of about 15 months). The fast growth rate of errors seen in the dominant empirical orthogonal function (EOF) in spring is present in all smaller scales of motion (higher EOFs) in all seasons. The coupled model allows initial errors in smaller scales to quickly cascade to the dominant scale in spring of certain years, while it does not allow this in winter. Further, if the initial conditions are generated from a long coupled run (coupled initial conditions as opposed to analyzed initial conditions), then errors in the dominant mode grow slowly both in spring and winter. These results establish that the origin of the seasonality of predictability lies in the use of observed winds to create initial conditions. The authors propose that the analyzed initial conditions have an ?imbalance? that arises from the fact that the variability of observed winds has a much larger small-scale high-frequency component than model winds. Such imbalances in the spring initial conditions in certain years quickly affect the evolution of the dominant mode, leading to loss of predictability. Even though such imbalances may be present in the winter initial conditions, they take a much longer time to influence the dominant mode, thus accounting for the greater predictability in winter.