Fundamental challenge in simulation and prediction of summer monsoon rainfall

The scientific basis for two-tier climate prediction lies in the predictability determined by the ocean and land surface conditions. Here we show that the state-of-the-art atmospheric general circulation models (AGCMs), when forced by observed sea surface temperature (SST), are unable to simulate properly Asian-Pacific summer monsoon rainfall. All models yield positive SST-rainfall correlations in the summer monsoon that are at odds with observations. The observed lag correlations between SST and rainfall suggest that treating monsoon as a slave possibly results in the models' failure. We demonstrate that an AGCM, coupled with an ocean model, simulates realistic SST-rainfall relationships; however, the same AGCM fails when forced by the same SSTs that are generated in its coupled run, suggesting that the coupled ocean-atmosphere processes are crucial in the monsoon regions where atmospheric feedback on SST is critical. The present finding calls for reshaping of current strategies for monsoon seasonal prediction. The notion that climate can be modeled and predicted by prescribing the lower boundary conditions is inadequate for validating models and predicting summer monsoon rainfall.