The drivers of extreme rainfall event timing in Australia

Abstract

Australia experiences some of the world's most variable rainfall. Previous studies have mostly focused on understanding rainfall variability in terms of frequency and intensity. However, understanding the timing of when extreme rainfall occurs is crucial for seasonal prediction, although it largely remains unexplored. Here we investigate the timing of extreme rainfall in Australia and the spatial variability of this timing. This study examines how some of the large-scale drivers, such as the El Niño–Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO), determine the timing and interannual variability of the timing of extreme rainfall in Australia. Our results show that there is a clear spatial north–south delineation in the season when extreme rainfall occurs in Australia, shown by a contour diagonally extending roughly from 21°S in the west of Australia to 33°S in the east. North of this contour, extreme rainfall usually occurs in austral summer, with the smallest interannual variability in the timing of extreme rainfall in this region. In the south, extreme rainfall usually occurs in autumn/winter months; however, the timing is highly variable. In southeast Australia (SEA), extreme rainfall can fall at any time of the year, which makes seasonal prediction extremely challenging for this region. Both observation and reanalysis data show that the area where extreme rainfall occurs in summer extends further south during negative IPO years. We also find that IPO and ENSO phases, and the interaction between them, play significant roles in both determining the timing of extreme rainfall and constraining the interannual variability, especially in SEA. We focus on SEA for further analysis as this region shows the greatest shift in seasonality of extremes in response to large-scale variability. We conclude that studying the relationship between rainfall and large-scale drivers is important for verification and improvement of the seasonal prediction of extreme rainfall. Show more