| description abstract | The effect of air?sea coupling on tropical climate variability is investigated in a coupled linear inverse model (LIM) derived from the simultaneous and 6-day lag covariances of observed 7-day running mean departures from the annual cycle. The model predicts the covariances at all other lags. The predicted and observed lag covariances, as well as the associated power spectra, are generally found to agree within sampling uncertainty. This validates the LIM?s basic premise that beyond daily time scales, the evolution of tropical atmospheric and oceanic anomalies is effectively linear and stochastically driven. It also justifies a linear diagnosis of air?sea coupling in the system. The results show that air?sea coupling has a very small effect on subseasonal atmospheric variability. It has much larger effects on longer-term variability, in both the atmosphere and the ocean, including greatly increasing the amplitude of ENSO and lengthening its dominant period from 2 to 4 years. Consistent with these results, the eigenvectors of the system?s dynamical evolution operator also separate into two distinct, but nonorthogonal, subspaces: one governing the nearly uncoupled subseasonal dynamics and the other governing the strongly coupled longer-term dynamics. These subspaces arise naturally from the LIM analysis; no bandpass frequency filtering need be applied. One implication of this remarkably clean separation of the uncoupled and coupled dynamics is that GCM errors in anomalous tropical air?sea coupling may cause substantial errors on interannual and longer time scales but probably not on the subseasonal scales associated with the MJO. | |
