Seasonal prediction of Indian summer monsoon extreme rainfall frequency

Abstract

Skillful forewarning of daily extreme rainfall activity (ERA) is imperative for adaptation against disastrous threats of socio-economic loss from Indian monsoon extreme rainfall events (ERE). Yet, unlike tropical cyclone (TC) activity forecasting, no attempt has been made for seasonal prediction of Indian monsoon ERE frequency and ERA. Here, we establish that the seasonal prediction of ERE frequency during Indian monsoon is associated with the global El Niño-Southern Oscillation (G-ENSO) in a manner similar to the Indian Summer Monsoon Rainfall (ISMR). We develop a deep learning model trained on the physical relationship between seasonal frequency of ERE and G-ENSO from an ensemble of Atmosphere-Ocean General Circulation Models (AOGCMs) for skillful seasonal forecast of ERE frequency at one-month lead. Integrating such seasonal forecasts of ERE frequency with ISMR seasonal forecast system is likely to be critical in disaster preparedness and loss minimization against increasing threat of ERE frequency damages in coming decades.