Past studies have shown the Super-Parameterized Community Atmospheric Model (SPCAM) to be a shining light among contemporary models in the dark abyss of MJO simulation. In atmosphere-only mode, SPCAM simulates a robust MJO, whose strength and propagation increase when SPCAM is coupled to a dynamical ocean model (SPCCSM). However, SPCCSM shows similar cold tropical SST errors to those shown to worsen the representation of the MJO in the MetUM. The representation of air-sea interactions in SPCCSM is quite poor -- the diurnal cycle is absent and the top ocean layer is 10 metres thick, both of which limit the amplitude and propagation of the MJO in other models. This raises the question of how air-sea interactions in SPCCSM manage to produce such an excellent MJO.
We employ a framework in which SPCAM is coupled to a one-dimensional ocean mixed-layer model, which allows the ocean mean state to be controlled through heat and salt corrections. Under the observed ocean mean state (i.e., very small SST biases), we show that air-sea interactions only slightly improve the MJO in SPCAM, but that MJO activity remains below the level seen in SPCCSM. Further, we show that the SPCCSM ocean mean state substantially weakens the MJO relative to the observed ocean mean state, seemingly in contradiction to the strong MJO seen in the SPCCSM simulation itself. By sub-sampling the SPCCSM simulation with respect to the ENSO state, we find that SPCCSM produces a robust MJO only in El Nino years, when the warm SST anomalies in the equatorial Pacific cancel the cold mean-state bias. We confirm these results by imposing the composite SPCCSM ENSO cycle in our mixed-layer ocean configuration, demonstrating that SPCCSM produces a robust MJO in spite of its tropical SST biases due to excessive ENSO variability and a strong response of the simulated MJO to El Nino warming, not due to air-sea interactions in the MJO itself.
These results suggest that experiments targeting air-sea interactions in the MJO must control for the effect of inter-annual variability on simulated tropical sub-seasonal variability.