Characterizing Australia's east coast cyclones (1950–2019)

Abstract

AbstractEast 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 ± 2 days) and event‐based rainfall were then evaluated for each cluster to quantify the impact of these lows 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 clusters (clusters 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. Furthermore, 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.