Decomposition of monsoon rainfall time series into mutually uncorrelated intrinsic mode functions (IMF) has distinct advantages in empirical forecasting of rainfall quantity ahead of the season. The attractive feature of this approach is its ability to separate out the nonlinear (non-Gaussian) and the linear (Gaussian) parts of the data as uncorrelated narrow-band processes for further modelling. (Correspondence)

Year to year variation of Indian monsoon rainfall is described qualitatively in some ancient Sanskrit texts. Interestingly, these are cyclic with periods of 3, 5, 7, 18 and 60 years. Time series analysis of actual seasonal rainfall data shows that at very near the above periods the spectrum has significant peaks.

In earlier publications, we had explained how the monsoon seasonal time series data of regional and All-India rainfall (AIRF) can be decomposed into its six basic modes by the method of empirical mode decomposition. This method helps one to recognize the first mode due to ENSO as being highly non-Gaussian, whereas the remaining progressively less important modes tend to be Gaussian.