Promises and Prospects for Predicting the South Asian Monsoon

There is ample evidence that dynamical coupled models of the Earth's climate system are reasonably good sources of seasonal predictions of the Indian monsoon. There is also evidence that the Indian monsoon is more predictable in theory than can be achieved with current prediction models. There are many sources of this predictability, including the influence of long-lived sea surface temperature anomalies in the tropical Pacific and Indian Oceans and of the soil moisture anomalies in Eurasia that act to alter the circulation and thermodynamic forcing of the atmosphere in the vicinity of south Asia, thereby influencing the precipitation over India during the Asian summer monsoon season. Complex land-atmosphere and ocean-atmosphere interactions, as well as complex interactions of the atmospheric circulation in different regions, all contribute to predictability as well, which is one reason that dynamical models produce predictions that are superior to those obtainable from empirical methods. As part of the Indian National Monsoon Mission, COLA, in collaboration with the Indian Institute of Tropical Meteorology in Pune, India, has conducted experiments with the Climate Forecast System, version 2 (CFSv2) of the U.S. National Centers for Environmental Prediction (NCEP), arguably among the best systems for predicting climate fluctuations on seasonal to interannual time scales. Experiments with the CFSv2 will be described in which the land-atmosphere and ocean-atmosphere interactions, the initialization of the global ocean, and the role of convective clouds are all evaluated for their effects on Indian monsoon prediction skill. It is found that inhibiting the onset of convection, more accurately representing the state of the upper ocean, particularly in the tropics, and correcting biases even in very remote areas (such as the Arctic and North Atlantic) can all significantly improve both sub-seasonal and seasonal mean predictions of the Indian monsoon rainfall, including onset date and geographical distribution of rainfall.