Unraveling the Mystery of Indian Summer Monsoon Prediction: Improved Estimate of Predictability Limit

TL;DR

This study demonstrates that the predictability of the Indian Summer Monsoon (ISM) can be significantly improved by accounting for sub-seasonal variability linked to slowly varying forces like El Nino, challenging previous low estimates of predictability.

Contribution

The paper shows that sub-seasonal fluctuations of the ISM, previously considered chaotic, are partly predictable and can be linked to external forcing, leading to a higher actual predictability limit.

Findings

Predictability limit of ISM rainfall is higher than previously estimated.

Sub-seasonal variability tied to external forcing improves forecast skill.

Enhanced climate model physics yields a correlation of r~0.82 in predictions.

Abstract

Large socio-economic impact of the Indian Summer Monsoon (ISM) extremes motivated numerous attempts at its long range prediction over the past century. However, a rather estimated low potential predictability limit (PPL) of seasonal prediction of the ISM, contributed significantly by 'internal' interannual variability was considered insurmountable. Here we show that the 'internal' variability contributed by the ISM sub-seasonal (synoptic + intra-seasonal) fluctuations, so far considered chaotic, is partly predictable as found to be tied to slowly varying forcing (e.g. El Nino and Southern Oscillation). This provides a scientific basis for predictability of the ISM rainfall beyond the conventional estimates of PPL. We establish a much higher actual limit of predictability (r~0.82) through an extensive re-forecast experiment (1920 years of simulation) by improving two major physics in a global coupled climate model, which raises a hope for a very reliable dynamical seasonal ISM forecasting in the near future.