Gray, Jessie, Verdon‐Kidd, Danielle C., Jaffrés, Jasmine B.D., Hewson, Michael G., Clarke, John M., Sharma, Krishneel K., and English, Nathan B. (2023) Characterizing Australia's east coast cyclones (1950–2019). International Journal of Climatology, 43 (7). pp. 3324-3352.

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Abstract

East coast cyclones (ECCs) provide an essential reprieve from dry periods across eastern Australia. They also deliver flood‐producing rains with significant economic, social and environmental impacts. Assessing and comparing the influence of different types of cyclones is hindered by an incomplete understanding of ECC typology, given their widely variable spatial and temporal characteristics. This study employs a track‐clustering method (probabilistic curve‐aligned regression model) to identify key cyclonic pathways for ECCs from 1950 to 2019. Six spatially independent clusters were successfully distinguished and further sub‐classified (coastal, continental and tropical) based on their genesis location. The seasonality and long‐term variability, intensity (maximum Laplacian value ± two days) and event‐based rainfall were then evaluated for each cluster to quantify the impact of these storms on Australia. The highest quantity of land‐based rainfall per event is associated with the tropical cluster (Cluster 6), whereas widespread rainfall was also found to occur in the two continental lows (Cluster 4 and 5). Cyclone tracks orientated close to the coast (clusters 1, 2 and 3) were determined to be the least impactful in terms of rainfall and intensity, despite being the most common cyclone type. In terms of interannual variability, sea surface temperature anomalies suggest an increased cyclone frequency for clusters 1 (austral winter) and 4 (austral spring) during a central Pacific El Niño. Further, cyclone incidence during IOD‐negative conditions was more pronounced in winter for clusters 1, 2, 3 – and clusters 4 and 5 in spring. All cyclones also predominantly occurred in SAM‐positive conditions. However, winter ECCs for clusters 1 and 3 had a higher frequency in SAM‐negative. This new typology of ECCs via spatial clustering provides crucial insights into the systems that produce extreme rainfall across eastern Australia and should be used to inform future hazard management of cyclone events. This article is protected by copyright. All rights reserved.

Item ID:	80678
Item Type:	Article (Research - C1)
ISSN:	1097-0088
Keywords:	Australia, east coast cyclones, eastern seaboard, ECL, ENSO, IOD, regression mixture model cluster analysis
Copyright Information:	This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2023 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.
Date Deposited:	10 Oct 2023 23:44
FoR Codes:	37 EARTH SCIENCES > 3701 Atmospheric sciences > 370101 Adverse weather events @ 50% 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490508 Statistical data science @ 50%
SEO Codes:	19 ENVIRONMENTAL POLICY, CLIMATE CHANGE AND NATURAL HAZARDS > 1904 Natural hazards > 190405 Meteorological hazards (e.g. cyclones and storms) @ 80% 18 ENVIRONMENTAL MANAGEMENT > 1801 Air quality, atmosphere and weather > 180103 Atmospheric processes and dynamics @ 20%
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