Prediction of seasonal summer monsoon rainfall over homogenous regions of India using dynamical prediction system

Abstract

Seasonal prediction of Indian summer monsoon rainfall is a challenging task for the modeling community and predicting seasonal mean rainfall at smaller regional scale is much more difficult than predicting all India averaged seasonal mean rainfall. The regional scale prediction of summer monsoon mean rainfall at longer lead time (e.g., predicting 3–4months in advance) can play a vital role in planning of hydrological and agriculture aspects of the society. Previous attempts for predicting seasonal mean rainfall at regional level (over 5 Homogeneous regions) have resulted with limited success (anomaly correlation coefficient is low, ACC≈0.1–0.4, even at a short lead time of one month). The high resolution Climate Forecast System, version 2 (CFSv2) model, with spectral resolution of T382 (∼38km), can predict the Indian summer monsoon rainfall (ISMR) at lead time of 3–4months, with a reasonably good prediction skill (ACC≈0.55). In the present study, we have investigated whether the seasonal mean rainfall over different homogenous regions is predictable using the same model, at 3–4months lead time? Out of five homogeneous regions of India three regions have shown moderate prediction skill, even at 3months lead time. Compared to lower resolution model, high resolution model has good skill for all the regions except south peninsular India. High resolution model is able to capture the extreme events and also the teleconnections associated with large scale features at four months lead time and hence shows better skill (ACC≈0.45) in predicting the seasonal mean rainfall over homogeneous regions.