  Scientific basis for long-lead seasonal prediction of Indian summer monsoon
rainfall (ISMR) critical for water resource and crop strategy planning is
lacking. Using a new predictor discovery method, here we show that the depth of
20 degree isotherm (D20) is least influenced by atmospheric noise and that the
18-month lead forecasts of ISMR have high potential skill (r = 0.86). The high
potential predictability is due to smaller initial errors associated with the
18-month lead initial conditions and their slow growth associated with the El
Nino and Southern Oscillation (ENSO). The potential skill arises not only from
the correlation between ISMR and large-scale slowly varying D20 but also
contributed significantly by that with the interannual small-scale D20
anomalies indicating a seminal role of the nonlinearity on the potential
predictability. It is, therefore, imperative that a nonlinear predictor
discovery as well as nonlinear prediction model is essential for realizing this
potential predictability.
