ENSO, the IOD and the intraseasonal prediction of heat extremes across Australia using POAMA-2

Christopher J. White, Debra Hudson, Oscar Alves

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27 Citations (Scopus)

Abstract

The simulation and prediction of extreme heat over Australia on intraseasonal timescales in association with the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) is assessed using the Bureau of Meteorology’s Predictive Ocean Atmosphere Model for Australia (POAMA). The analysis is based on hindcasts over 1981–2010 and focuses on weeks 2 and 3 of the forecasts, i.e. beyond a typical weather forecast. POAMA simulates the observed increased probabilities of extreme heat during El Niño events, focussed over south eastern and southern Australia in SON and over northern Australia in DJF, and the decreased probabilities of extreme heat during La Niña events, although the magnitude of these relationships is smaller than observed. POAMA also captures the signal of increased probabilities of extreme heat during positive phases of the IOD across southern Australia in SON and over Western Australia in JJA, but again underestimates the strength of the relationship. Shortcomings in the simulation of extreme heat in association with ENSO and the IOD over southern Australia may be linked to deficiencies in the teleconnection with Indian Ocean SSTs. Forecast skill for intraseasonal episodes of extreme heat is assessed using the Symmetric Extremal Dependence Index. Skill is highest over northern Australia in MAM and JJA and over south-eastern and eastern Australia in JJA and SON, whereas skill is generally poor over south-west Western Australia. Results show there are windows of forecast opportunity related to the state of ENSO and the IOD, where the skill in predicting extreme temperatures over certain regions is increased.

Original languageEnglish
Pages (from-to)1791-1810
Number of pages20
JournalClimate Dynamics
Volume43
Issue number7-8
Early online date11 Dec 2013
DOIs
Publication statusPublished - 31 Oct 2014

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Keywords

  • El Niño–Southern Oscillation
  • extreme events
  • heat waves
  • Indian Ocean Dipole
  • intraseasonal forecasts
  • predictability

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