4.7 Article

Interbasin and Multiple-Time-Scale Interactions in Generating the 2019 Extreme Indian Ocean Dipole

Journal

JOURNAL OF CLIMATE
Volume 34, Issue 11, Pages 4553-4566

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-20-0760.1

Keywords

Climate prediction; Climate variability; Indian Ocean dipole; Interbasin interaction; Intraseasonal oscillation

Funding

  1. National Science Foundation (NSF) [OCE 1658132, AGS 1935279]
  2. NASA OSTST [NNX17AI63G]

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In 2019, an unprecedented extreme positive Indian Ocean dipole event occurred, leading to disastrous impacts on countries bordering the Indian Ocean. Various factors, including easterly wind bursts, warm sea surface temperature anomalies in the central-western tropical Pacific Ocean, and Madden-Julian oscillation events played key roles in triggering and sustaining the extreme pIOD.
An unprecedented extreme positive Indian Ocean dipole event (pIOD) occurred in 2019, which has caused widespread disastrous impacts on countries bordering the Indian Ocean, including the East African floods and vast bushfires in Australia. Here we investigate the causes for the 2019 pIOD by analyzing multiple observational datasets and performing numerical model experiments. We find that the 2019 pIOD was triggered in May by easterly wind bursts over the tropical Indian Ocean associated with the dry phase of the boreal summer intraseasonal oscillation, and it was sustained by the local atmosphere-ocean interaction thereafter. During September-November, warm sea surface temperature anomalies (SSTA) in the central-western tropical Pacific Ocean further enhanced the Indian Ocean's easterly winds, bringing the pIOD to an extreme magnitude. The central-western tropical Pacific warm SSTA was strengthened by two consecutive Madden-Julian oscillation (MJO) events that originated from the tropical Indian Ocean. Our results highlight the important roles of cross-basin and cross-time-scale interactions in generating extreme IOD events. The lack of accurate representation of these interactions may be the root for a short lead time in predicting this extreme pIOD with a state-of-the-art climate forecast model.

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