on the identification of intra-seasonal changes in the indian summer monsoon
Intra-seasonal changes in the Indian summer monsoon are generally characterized by its active and break (A&B) states. Existing methods for identifying the A&B states using rainfall data rely on subjective thresholds, ignore temporal dependence in the data, and disregard inherent uncertainty in their identification. This paper develops a method to identify intra-seasonal changes in the monsoon using a hidden Markov model (HMM) that allows objective classification of the monsoon states. The method facilitates probabilistic interpretation which is especially useful during the transition period between the two monsoon states. The developed method can also be used to - (i) identify monsoon states in real time, (ii) forecast rainfall values, and (iii) generate synthetic data. Comparisons of the results from the proposed model with those from existing methods suggest that the new method is a promising for detecting intra-seasonal changes in the Indian summer monsoon.
indian summer monsoon hidden markov models variational bayes active and break states