Improved Predictability of the Indian Ocean Dipole Using Seasonally Modulated ENSO Forcing Forecasts

Abstract

©2019. American Geophysical Union. All Rights Reserved.Despite recent progress in seasonal forecast systems, the predictive skill for the Indian Ocean Dipole (IOD) remains typically limited to a lead time of one season or less in both dynamical and empirical models. Here we develop a simple stochastic-dynamical model (SDM) to predict the IOD using seasonally modulated El Niño–Southern Oscillation (ENSO) forcing together with a seasonally modulated Indian Ocean coupled ocean-atmosphere feedback. The SDM, with either observed or forecasted ENSO forcing, exhibits generally higher skill and longer lead times for predicting IOD events than the operational Climate Forecast System version 2 and the Scale Interaction Experiment–Frontier system. The improvements mainly originate from better prediction of ENSO-dependent IOD events and from reducing false alarms. These results affirm our hypothesis that operational IOD predictability beyond persistence is largely controlled by ENSO predictability and the signal-to-noise ratio of the system. Therefore, potential future ENSO improvements in models should translate to more skillful IOD predictions