Springtime rainfall changes in Australia related to projected changes in large-scale modes of variability

Christine T. Y. Chung; Scott B. Power; Ghyslaine Boschat; Zoe Gillett; Andréa Taschetto; Sugata Narsey; Acacia Pepler

doi:10.1071/ES25030

RESEARCH ARTICLE (Open Access)

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Springtime rainfall changes in Australia related to projected changes in large-scale modes of variability

Christine T. Y. Chung

^A ^* , Scott B. Power ^B ^C ^D , Ghyslaine Boschat ^A , Zoe Gillett ^A , Andréa Taschetto

^E ^F , Sugata Narsey

^A and Acacia Pepler

^A

+ Author Affiliations

- Author Affiliations

^A Bureau of Meteorology, Melbourne, Vic., Australia.

^B Australian Research Council (ARC) Centre of Excellence for Climate Extremes, School of Earth, Atmosphere and Environment, Monash University, Melbourne, Vic., Australia.

^C Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba, Qld, Australia.

^D Climate Services International, Oakleigh, Vic., Australia.

^E Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia.

^F ARC Centre of Excellence for the Weather of the 21st Century, University of New South Wales, Sydney, NSW, Australia.

^* Correspondence to: christine.chung@bom.gov.au, media@bom.gov.au
Media enquiries: media@bom.gov.au

Handling Editor: Tony Hirst

Journal of Southern Hemisphere Earth Systems Science 75, ES25030 https://doi.org/10.1071/ES25030

Submitted: 13 May 2025 Accepted: 11 August 2025 Published: 5 September 2025

© 2025 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of the Bureau of Meteorology. This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY).

Abstract

In this study, we estimate changes in Australian springtime (September–November) rainfall associated with projected changes in large-scale climate modes of variability. Using 33 climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we assess the fraction of models that project large future increases or decreases in the strength of El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Southern Annular Mode (SAM) variability. We identify ‘representative’ subgroups of models that display the most common large changes corresponding to: stronger ENSO variability (19 models), weaker IOD variability (15 models) and stronger SAM variability (22 models). The sign of the projected change in the strength of SAM is independent of the changes in ENSO and IOD strengths, whereas the sign of the projected change in IOD strength is weakly (and positively) correlated with the change in ENSO strength. Australian rainfall changes averaged across each subgroup of models are presented. They indicate an overall strengthening of teleconnections to both phases of ENSO and SAM, but indicate mixed results for positive and negative IOD phases. The changes in teleconnections vary across regions and depend on the sign of change of ENSO, IOD and SAM amplitude. However, results indicate that mean-state drying over south-west Western Australia and southern Victoria is projected to occur regardless of how the large-scale modes of variability change. Rainfall changes associated with projected changes to the frequency of co-occurring and consecutive ENSO and IOD are also discussed.

Keywords: Australia, climate model, CMIP, El Niño–Southern Oscillation, ENSO, Indian Ocean Dipole, IOD, modes of variability, projections, rainfall, SAM, Southern Annular Mode.

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