Advances in Seasonal Climate Forecasting

Sir Walker's early pioneering efforts in making long range forecasting of monsoon rainfall in India, led to several concepts on teleconnection and statistical relations in the field of climate forecasting especially the El Niño-Southern Oscillation (ENSO). Shukla and Paolino (1983) studied relations of Southern Oscillation on possibility of long range forecasting of Indian summer monsoon rainfall. Ropelewski and Halpert (1987, 1996) established better correlation of Pacific Ocean sea surface temperatures (SSTs) compared to Indian Ocean SSTs with rainfall variability in Indian subcontinent which also indicated the skill of October-November-December (OND) seasonal rainfall prediction in southern India. Both these efforts were focused on understanding the ENSO dynamics on slowly varying equatorial ocean temperatures, and established relationships to their manifestations on changing atmosphere and observed climate variability.

Virmani et al. (1982) estimated seasonal rainfall probabilities using statistical models for many locations in the semi-arid India. Gadgil et al. (1999) identified stronger relationship between El Niño years and rainfall in Anantapur compared to all-India summer monsoon rainfall from their analyses on seasonal rainfall from 1911-1998. Stone et al. (2000) demonstrated statistical methods to generate rainfall probabilities of climate forecasts from general circulation model (GCM)-derived southern oscillation index (SOI) phases that are useful inputs for agricultural simulations to derive management decision options. Predictability of climate at regional scale presents an opportunity to identify feasible alternatives to mitigate the climate risks, improve productivity and food security.

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