Synergistic effects of El Niño–Southern Oscillation and the Indian Ocean Dipole on Middle Eastern subseasonal precipitation variability and predictability

Abstract This study investigates the influence of tropical sea‐surface temperature (SST) on subseasonal precipitation variability and predictability in the Middle East. With this aim, we focus on the synergistic effects of the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) during October. We confirmed that these phenomena exhibit a seasonal correlation, with its highest value in October (). Analysis revealed a significant correlation between tropical SST and total precipitation with a minimum two‐month lag (). Notably, the combined effect of a positive ENSO and IOD produces significantly more precipitation than a negative ENSO and IOD, mainly over the Fertile Crescent. This is attributed to increased water‐vapor flux directed towards the Middle East, which is more pronounced during positive ENSO and IOD. Moreover, the study highlights the broader implications of tropical SST on the frequency of rain‐bearing weather types in the eastern Mediterranean, that is, the Red Sea Trough and the Mediterranean low‐pressure systems often termed ‘Cyprus Lows’. Specifically, positive ENSO events coupled with a positive IOD diminish the occurrence of the Red Sea Trough while concurrently increasing the frequency of Cyprus Lows. The increase in Cyprus Low occurrence relates to the relative location and intensity of the subtropical jet, thus influencing the Mediterranean storm track. Despite this apparent effect, the synergistic interaction of a positive ENSO and IOD poses challenges for subseasonal precipitation prediction, both practically and intrinsically. The October 1997 anomalously positive ENSO and IOD case study provided additional support and understanding to the statistical analysis. This research underscores the relationship between tropical SST and precipitation patterns in the Middle East, shedding light on the challenges and complexities of subseasonal to seasonal weather and climate prediction in this vulnerable region.