The influence of air-sea interaction on subannual and intraseasonal tropical variability is explored through analysis of three long simulations of the Commonwealth Scientific and Industrial Research Organisation atmospheric general circulation model (GCM) with differing ocean specifications: a coupled ocean GCM, a simple 50-m mixed layer model, or climatological sea surface temperatures (SST); together with 50-year simulations with mixed layer depths of 10 m and 20 m. The analysis focuses initially on a signal similar to a Madden-Julian Oscillation (MJO) contained in the first two empirical orthogonal functions (EOF) of monthly anomalies of tropical 807-hPa winds in January in the coupled model. Time-lag regression is used to demonstrate that these patterns propagate eastward, although at only half the speed of the MJO, and induce perturbations to the Australian monsoon. The specified SST model shows no such propagation. Similar results are then obtained using daily data filtered to retain subannual periods. The eastward propagation speed is faster in the shallower mixed layer cases, with the 10-m case producing speeds close to observations. In the interactive models, surface energy fluxes force SST anomalies propagating ahead of the EOF convergence. These fluxes are largely consistent with evaporation perturbed by wind anomalies to the monsoon westerlies, augmented by solar radiation. The SST anomalies then further perturb the winds, as is confirmed by a separate SST perturbation experiment. From the examination of other seasons, it is seen that air-sea interaction generally enhances the amplitude of the MJO-like patterns. It also enhances their eastward propagation along westerly wind bands. Analysis of zonal wave number one winds confirms the strong sensitivity to mixed layer depth in the amplitude and period of the eastward propagating component, particularly during September through February. The results suggest that air-sea interaction may be important to the MJO, provided that the SSTs are sufficiently responsive to the atmospheric patterns.