While the Indian monsoon exhibits substantial variability on interannual timescales, its intraseasonal variability is of greater magnitude and hence of critical importance for the predictability of monsoon rainfall. This intraseasonal variability comprises a 30-50 day northward-propagating oscillation (NPISO) between active and break events of enhanced and reduced rainfall, respectively, over the subcontinent. Several recent studies have implied that coupled general circulation models (CGCMs) are better able to simulate the NPISO than their atmosphere-only counterparts (AGCMs). Lacking atmosphere-to-ocean feedbacks, AGCMs too-readily initiate convection over warm SSTs, which in observations coincide with break events of suppressed convection. These studies have forced their AGCM simulations with SSTs from coupled integrations or observations from infrared instruments onboard satellites, both of which substantially underestimate intraseasonal SST variability in the tropical oceans.

We have forced the Hadley Centre Atmospheric Model (HadAM3) with a high-frequency, observed SST dataset from the Met Office that shows substantially more intraseasonal variance in the Indian Ocean than existing analyses. One ensemble of simulations was forced by daily observed SSTs and a second with monthly means. When compared, the ensemble with daily SSTs displays significantly greater variability in 20-50 day precipitation across the monsoon domain, variability much more in-line with observations. Individual ensemble members contain intraseasonal events with a strength, propagating speed, and organization that closely matches events from an observed dataset. Even when members from the ensemble with monthly mean SSTs display power in intraseasonal rainfall, the intraseasonal events themselves are weak, disorganized, and fail to move northwards from the equator to India. We conclude that high-frequency SST anomalies not only increase the variance in intraseasonal rainfall, but help to organize and maintain the coherent convective events that comprise the NPISO. Further, our results indicate that an atmosphere-only model can respond to accurate and frequent SST forcing to generate intraseasonal variability that compares well with observations.