Abstract

We assess the impact of the tropical Madden Julian Oscillation (MJO) on global ocean wind waves using 30 years of wave data from a wave model hindcast that is forced with high resolution surface winds from the NCEP–CFSR reanalysis. We concentrate on the boreal winter season when the MJO has its greatest amplitude and is potentially a source of predictable wave impacts at intra-seasonal lead times. Statistically significant anomalies in significant wave height (Hs), peak wave period (Tp) and zonal wave energy flux (CgE) are found to covary with the intra-seasonal variation of surface zonal wind induced by the MJO as it traverses eastward from the western tropical Indian Ocean to the eastern tropical Pacific. Tp varies generally out of phase with Hs over the life cycle of the MJO, indicating that these MJO-wave anomalies are locally wind-generated rather than remotely generated by ocean swell.Pronounced Hs anomalies develop on the northwest shelf of Australia, where the MJO is known to influence sea level and surface temperatures, and in the western Caribbean Sea and Guatemalan–Panama Seas with enhanced wave anomalies apparent in the vicinity of the Tehuantepec and Papagayo gaps. Significant wave anomalies are also detected in the North Pacific and North Atlantic oceans in connection with the MJO teleconnection to the extratropics via atmospheric wave propagation. The impact in the north Atlantic stems from induction of the high phase of the North Atlantic Oscillation (NAO) about 1 week after MJO convection traverses the Indian Ocean, and the low phase of the NAO about one week after suppressed convection traverses the Indian Ocean. Strong positive Hs anomalies maximize on the Northern European coast in the positive NAO phase and vice versa for the negative NAO phase. The MJO also influences the occurrence of daily low (below the 5th percentile) and high (above the 95th percentile) wave conditions across the tropics and in the North Pacific and North Atlantic, emphasizing that the MJO may be a valuable source of intra-seasonal predictability of surface wave variability.

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