Jourdain N. C. auteur aut IRD Lengaigne Matthieu auteur aut IRD Vialard Jérôme auteur aut IRD Izumo Takeshi auteur aut IRD Sen Gupta A. auteur aut IRD text journalArticle eng text/pdf born digital access Recent observational studies have suggested that negative and positive Indian Ocean dipole (IOD) events (nIOD and pIOD, respectively) favor a transition toward, respectively, El Nino and La Nina events one year later. These statistical inferences are however limited by the length and uncertainties in the observational records. This paper compares observational datasets with twenty-one 155-yr historical simulations from phase 5 of CMIP (CMIP5) to assess IOD and El Nino-Southern Oscillation (ENSO) properties along with their synchronous and delayed relationships. In the observations and most CMIP5 models, it is shown that El Ninos tend to be followed by La Ninas but not the opposite, that pIODs co-occur more frequently with El Ninos than nIODs with La Ninas, that nIODs tend to be followed by El Ninos one year later less frequently than pIODs by La Ninas, and that including an IOD index in a linear prediction based on the Pacific warm water volume improves ENSO peak hindcasts at 14 months lead. The IOD-ENSO delayed relationship partly results from a combination of ENSO intrinsic properties (e.g., the tendency for El Ninos to be followed by La Ninas) and from the synchronous IOD-ENSO relationship. The results, however, reveal that this is not sufficient to explain the high prevalence of pIOD-Nina transitions in the observations and 75% of the CMIP5 models, and of nIOD-Nino transitions in 60% of CMIP5 models. This suggests that the tendency of IOD to lead ENSO by one year should be explained by a physical mechanism that, however, remains elusive in the CMIP5 models. The ability of many CMIP5 models to reproduce the delayed influence of the IOD on ENSO is nonetheless a strong incentive to explore extended-range dynamical forecasts of ENSO. specialized Geographic location entity Indian Ocean Circulation Dynamics ENSO Physical Meteorology and Climatology Climate prediction Mathematical and statistical techniques Statistical techniques Models and modeling Climate models Variability Tropical variability OCEAN INDIEN 032 020 29 2 637-658 2016 0894-8755 https://www.documentation.ird.fr/hor/fdi:010066149 10.1175/jcli-d-15-0481.1 0894-8755 [F B010066149] https://www.documentation.ird.fr/hor/fdi:010066149 https://www.documentation.ird.fr/intranet/publi/2016/02/010066149.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2016-02-26 2021-03-16 fdi:010066149 fre