The strengthened role of new predictors of Indian Ocean Dipole (IOD) during the recent decades of weakened ENSO-IOD relationship

Indian Ocean Dipole (IOD) is the major interannual ocean-atmosphere interaction phenomena in the Indian Ocean (IO) and is influenced by external forcing such as El Nino Southern Oscillation (ENSO). Meanwhile, its co-occurrence and stronger relationship with ENSO have decreased during recent decades. The IOD variability also reduced after 2000, accompanied by a shift of the western pole to central IO extending further southward. The study reports that the boreal fall (SON, September, October, November) season IOD has an intensified relationship with the previous winter Subtropical Indian Ocean dipole (SIOD) and spring season equatorial north tropical Atlantic (NTA) SST anomalies., while the ENSO relationship is reduced from its pre-2000 value. It is found that the persistent warming (cooling) in the western side of positive (negative) SIOD during the previous winter induces easterly (westerly) wind anomalies in the equatorial IO during the following summer and fall, leading to positive (negative) IOD events. These IOD events have the western pole shifted to south-central IO instead of the canonical northwestern warming. The spring season NTA SST anomalies induce stronger summer season circulation and SST gradient in the equatorial Pacific, like ENSO. During the SON season, this pattern is associated with cooling and easterly wind anomalies in the tropical eastern IO and IOD. These two patterns explain the major mode of IOD variability after 2000. While the IOD associated with NTA have co-occurring ENSO during summer and fall, the SIOD-induced IOD events are independent of ENSO in the Pacific. Thus, these two predictors provide long-lead predictability (2–3 seasons ahead) of IOD for both ENSO co-occurring and non-ENSO IOD events. However, the IOD predictability of seasonal prediction models mainly depends on the ENSO-IOD relationship, resulting in reduced IOD skills for many of them after 2000. The models such as COLA-CCSM4, which has improved skill have stronger than observed ENSO-IOD relationship than the pre-2000 period. A linear regression model including SIOD and NTA SST indices of the previous winter and spring season respectively as predictors simulates IOD with a skill of around 0.65 during the recent period, indicating the necessity of seasonal prediction models to capture the variability in the southern IO and NTA and their teleconnections for better prediction of IOD in the recent period of reduced ENSO skill.