The Machine Learning Attribution of Quasi-Decadal Precipitation and Temperature Extremes in Southeastern Australia during the 1971–2022 Period

Aug 5, 2026

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Much of eastern and southeastern Australia (SEAUS) experienced historic flooding, heat waves, and drought during the quasi-decadal 2010–2022 period, reflecting global patterns. Double La Niña (2010–2012) coincided with record rainfall, while 2013–2019 brought drought, heat waves, and bushfires, interrupted by notable inland record rainfall in 2016 linked to a strong negative Indian Ocean Dipole. A rare triple La Niña (2020–2022) drove widespread extreme rainfall and flooding. Machine learning attribution was applied to representative eight-site data across 1971–2022 and to 1971–1996 and 1997–2022 sub-periods to identify key precipitation and temperature extreme drivers, including changes in global and local tropospheric circulation.

LanguageEnglish

CategoryResearch & Report

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Pages17

Reading Time43 min

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climate Article The Machine Learning Attribution of Quasi-Decadal Precipitation and Temperature Extremes in Southeastern Australia during the 1971–2022 Period Milton Speer 1, *, Joshua Hartigan 2 and Lance Leslie 1 Citation: Speer, M.; Hartigan, J.; Leslie, L. The Machine Learning Attribution of Quasi-Decadal Precipitation and Temperature Extremes in Southeastern Australia during the 1971–2022 Period. Climate 2024, 12, 75. [https://doi.org/](https://doi.org/)[ ](https://doi.org/)[10.3390/cli12050075](10.3390/cli12050075) Academic Editor: Antonello Pasini Received: 1 April 2024 Revised: 11 May 2024 Accepted: 13 May 2024 Published: 17 May 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) . 1 School of Mathematical and Physical Sciences, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia; [Lance.Leslie@uts.edu.au](Lance.Leslie@uts.edu.au) 2 The Climate Risk Group, Newcastle, NSW 2300, Australia; [Joshua.Hartigan@theclimateriskgroup.com](Joshua.Hartigan@theclimateriskgroup.com) * [Correspondence: Milton.Speer@uts.edu.au](Correspondence: Milton.Speer@uts.edu.au) Abstract: Much of eastern and southeastern Australia (SEAUS) suffered from historic flooding, heat waves, and drought during the quasi-decadal 2010–2022 period, similar to that experienced globally. During the double La Niña of the 2010–2012 period, SEAUS experienced record rainfall totals. Then, severe drought, heat waves, and associated bushfires from 2013 to 2019 affected most of SEAUS, briefly punctuated by record rainfall over parts of inland SEAUS in the late winter/spring of 2016, which was linked to a strong negative Indian Ocean Dipole. Finally, from 2020 to 2022 a rare triple La Niña generated widespread extreme rainfall and flooding in SEAUS, resulting in massive property and environmental damage. To identify the key drivers of the 2010–2022 period’s precipitation and temperature extremes due to accelerated global warming (GW), since the early 1990s, machine learning attribution has been applied to data at eight sites that are representative of SEAUS. Machine learning attribution detection was applied to the 52-year period of 1971–2022 and to the successive 26-year sub-periods of 1971–1996 and 1997–2022 . The attributes for the 1997–2022 period, which includes the quasi-decadal period of 2010–2022, revealed key contributors to the extremes of the 2010–2022 period. Finally, some drivers of extreme precipitation and temperature events are linked to significant changes in both global and local tropospheric circulation. Keywords: rainfall and temperature extremes; decadal climate; significance testing; climate drivers; machine learning; atmospheric circulation; southeast Australia 1. Introduction Global warming (GW) has accelerated in recent decades, with precipitation and temperature extremes becoming more common [1–3] . It is known from previous studies, e.g., [4,5], that water availability in southeastern Australia (SEAUS, Figure 1) has been diminishing in both quantity and quality owing to a combination of prolonged dry periods and a rapidly increasing population. Consequently, to assist in increasing water sustainability and preparing for increased heatwave frequency, there is a need to examine the complex relationships between changes in the patterns of precipitation and higher temperatures resulting from the impacts of ocean and atmospheric climate drivers affecting SEAUS. GW increases the frequency and intensity of extreme precipitation and heatwavesand associated floods and droughts by amplifying the effects of the various SEAUS climate drivers [4,5] . Accordingly, despite the mean annual rainfal

FAQs

What climatic extremes characterized the 2010–2022 quasi-decadal period in southeastern Australia?

The period featured historic flooding, heat waves, and drought across SEAUS, with widespread environmental and property impacts.

How did La Niña phases relate to precipitation outcomes in different sub-periods?

Double La Niña (2010–2012) produced record rainfall totals, while a rare triple La Niña (2020–2022) generated widespread extreme rainfall and flooding.

What method was used to identify the key drivers behind precipitation and temperature extremes?

The study used machine learning attribution on data from eight representative sites, analyzing the full 1971–2022 period and the sub-periods 1971–1996 and 1997–2022.

Aug 5, 2026

Upload by Levi