Machine Learning Indicates Stronger Future Thunderstorm Downbursts Affecting Southeast Australian Airports

Speer, M; Leslie, L; Wang, S

Machine Learning Indicates Stronger Future Thunderstorm Downbursts Affecting Southeast Australian Airports

Speer, M

Leslie, L

Wang, S

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Climate, 2025, 13, (6)
Issue Date:: 2025-06-01

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Field	Value	Language
dc.contributor.author	Speer, M https://orcid.org/0000-0003-0421-7744
dc.contributor.author	Leslie, L https://orcid.org/0000-0001-5616-2330
dc.contributor.author	Wang, S
dc.date.accessioned	2026-02-16T00:39:05Z
dc.date.available	2026-02-16T00:39:05Z
dc.date.issued	2025-06-01
dc.identifier.citation	Climate, 2025, 13, (6)
dc.identifier.issn	2225-1154
dc.identifier.issn	2225-1154
dc.identifier.uri	http://hdl.handle.net/10453/193511
dc.description.abstract	Thunderstorms downbursts can be hazardous during aircraft landing and take-off. A warming climate increases low- to mid-level troposphere water vapor, typically transported from high sea-surface temperature regions. Consequently, the future occurrence and intensity of destructive wind gusts from wet microburst thunderstorms are expected to increase. Wet microbursts are downdrafts from heavily precipitating thunderstorms and are several kilometers in diameter, often producing near-surface extreme wind gusts. Brisbane airport recorded a wet microburst wind gust of 157 km/h in November 2016. Numerous locations in eastern Australia experience warm season (October to March) wet microbursts. Here, eight machine learning techniques comprising forward and backward linear regression, radial basis forward and backward support vector regression, polynomial-based forward and backward support vector regression, and forward and backward random forest selection were employed. They identified primary attributes for increased atmospheric instability by warm moist air influx from regions of high sea-surface temperatures. The climate drivers detected here are indicative of increased future eastern Australian warm season thunderstorm downbursts, occurring as wet microbursts. They suggest a greater frequency and intensity of impacts on aircraft safety and operations affecting major east coast airports, such as Sydney and Brisbane, and smaller aircraft at inland regional airports in southeastern Australia.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Climate
dc.relation.isbasedon	10.3390/cli13060127
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	3701 Atmospheric sciences
dc.subject.classification	3702 Climate change science
dc.subject.classification	4101 Climate change impacts and adaptation
dc.title	Machine Learning Indicates Stronger Future Thunderstorm Downbursts Affecting Southeast Australian Airports
dc.type	Journal Article
utslib.citation.volume	13
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Science
pubs.organisational-group	University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2026-02-16T00:39:03Z
pubs.issue	6
pubs.publication-status	Published
pubs.volume	13
utslib.citation.issue	6

Abstract:

Thunderstorms downbursts can be hazardous during aircraft landing and take-off. A warming climate increases low- to mid-level troposphere water vapor, typically transported from high sea-surface temperature regions. Consequently, the future occurrence and intensity of destructive wind gusts from wet microburst thunderstorms are expected to increase. Wet microbursts are downdrafts from heavily precipitating thunderstorms and are several kilometers in diameter, often producing near-surface extreme wind gusts. Brisbane airport recorded a wet microburst wind gust of 157 km/h in November 2016. Numerous locations in eastern Australia experience warm season (October to March) wet microbursts. Here, eight machine learning techniques comprising forward and backward linear regression, radial basis forward and backward support vector regression, polynomial-based forward and backward support vector regression, and forward and backward random forest selection were employed. They identified primary attributes for increased atmospheric instability by warm moist air influx from regions of high sea-surface temperatures. The climate drivers detected here are indicative of increased future eastern Australian warm season thunderstorm downbursts, occurring as wet microbursts. They suggest a greater frequency and intensity of impacts on aircraft safety and operations affecting major east coast airports, such as Sydney and Brisbane, and smaller aircraft at inland regional airports in southeastern Australia.

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http://hdl.handle.net/10453/193511