A weather system perspective on winter–spring rainfall variability in southeastern Australia during El Niño

Hauser, Seraphine; Grams, Christian M.; Reeder, Michael J.; McGregor, Shayne; Fink, Andreas H.; Quinting, Julian

doi:10.1002/qj.3808

Cited by 23 publications

(20 citation statements)

References 61 publications

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“…(2018) and Hauser et al . (2020) which has three terms: The first term describes the influence of the cluster frequency, the second term the influence of the rainfall intensity and the third term is a combination of both metrics. For grid points in the yellow polygon in Figure 1, the first term was twice as large as the second, whereas the third term was negligible for April for cluster EE days.…”

Section: Discussionmentioning

confidence: 99%

“…The employed method does not allow a quantitative assessment of the relative roles of position, intensity, and width of the TRB. As a quick check, we used the formula given in for example, Clark et al (2018) and Hauser et al (2020) which has three terms: The first term describes the influence of the cluster frequency, the second term the influence of the rainfall intensity and the third term is a combination of both metrics. For grid points in the yellow polygon in Figure 1, the first term was twice as large as the second, whereas the third term was negligible for April for cluster EE days.…”

Section: Discussionmentioning

confidence: 99%

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Using seasonal rainfall clusters to explain the interannual variability of the rain belt over the Greater Horn of Africa

Seregina

Fink

Linden

et al. 2020

Intl Journal of Climatology

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The seasonal cycle of rainfall over the Greater Horn of Africa (GHA) is dominated by the latitudinal migration and activity of the tropical rain belt (TRB). The TRB exhibits high interannual variability in the GHA and the reasons for the recent dry period in the Long Rains (March-May) are poorly understood. In addition, few studies have addressed the rainfall fluctuations during the Msimu Rains (Dec.-Mar.) in the southern GHA region. Interannual variations of the seasonal cycle of the TRB between 1981 and 2018 were analysed using two statistical indices. The Rainfall Cluster Index (RCI) describes the seasonal cycle as a succession of six characteristic rainfall patterns, while the Seasonal Location Index (SLI) captures the latitudinal location of the TRB. The SLI and RCI depict the full seasonal cycle of the TRB supporting interpretations of the interannual variations and trends. The Msimu Rains are dominated by two clusters with opposite rainfall

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Using seasonal rainfall clusters to explain the interannual variability of the rain belt over the Greater Horn of Africa

Seregina

Fink

Linden

et al. 2020

Intl Journal of Climatology

Self Cite

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“…On the other hand, Hauser et al . (2020) identified a distinct northwest pathway for moisture transport associated with warm conveyor belt rainfall in southeast Australia. Given this inconsistency, and the fact that both studies focussed primarily on monthly mean rainfall, we suggest that further work is needed to understand the moisture sources for short‐duration Australian rainfall extremes.…”

Section: Environmental Characteristicsmentioning

confidence: 99%

Heavy versus extreme rainfall events in southeast Australia

Warren

Jakob

Hitchcock

et al. 2021

Quart J Royal Meteoro Soc

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Focussing on the major cities of Brisbane, Sydney, and Melbourne in southeast Australia, this study seeks to determine the environmental factors that distinguish between heavy rainfall events (HREs) and extreme rainfall events (EREs). Using daily rain gauge observations, HREs and EREs are defined for each domain based, respectively, on the 95th and 99th percentiles of wet‐day rainfall for the period 1979–2018. K‐means clustering is applied to mean sea‐level pressure, data from ERA5 to obtain a set of representative large‐scale circulation patterns associated with these events. Composite synoptic maps, mean vertical profiles, and a series of column‐integrated diagnostics are then examined for each cluster and used to compare the environmental characteristics of HREs and EREs. For all three cities, HREs are associated with an upper‐level trough to the west, with large‐scale ascent, positive column water vapour (CWV) anomalies, and strong moisture transport over the analysis domain. For Brisbane and Sydney, the clusters are characterised by a coastal trough/low with moist onshore flow from the Tasman and Coral Seas. For Melbourne, circulation patterns are more distinct, with clusters characterised by a front, a cut‐off low, and an inland trough. Compared with HREs, EREs show a more amplified upper‐level trough, with stronger vertical motion and larger CWV anomalies over the analysis domain. In Brisbane and Sydney, EREs also feature stronger and deeper onshore flow, promoting enhanced moisture transport. A diagnostic termed upward vapour transport, which combines the key ingredients of high CWV and large‐scale ascent, is shown to discriminate well between HREs and EREs in all three domains. In contrast, surface temperature, which is frequently linked to rainfall extremes via Clausius–Clapeyron scaling, shows significant overlap between the different event categories, particularly for Brisbane and Sydney.

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“…Australia (Chung and Power 2017;Risbey et al 2009a,b;Murphy and Timbal 2008;Nicholls et 75 al. 1996;McBride and Nicholls 1983;Allan et al 1996;Schepen et al 2012;Min et al 2013;76 King et al 2014;Ashcroft et al 2019). Based on these studies, winter-spring rainfall is usually 77 reduced during El Niño and enhanced during La Niña over the eastern and southeastern parts of 78 Australia.…”

Section: Introductionmentioning

confidence: 99%

A Radar Object-Based Examination of Rain System Climatology and Including Climate Variability

Ayat¹,

Evans²,

Sherwood³

et al. 2021

Preprint

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We know the climate is warming and this is changing some aspects of storms, but we have little knowledge of storm characteristics beyond intensity, which limits our understanding of storms overall. In this study, we apply a cell-tracking algorithm to 20 years of radar data at a mid-latitude coastal-site (Sydney, Australia), to establish a regional storm climatology. The results show that extreme storms in terms of translation-speed, size and rainfall intensity usually occur in the warm season, and are slower and more intense over land between ~10am and ~8pm (AEST), peaking in the afternoon. Storms are more frequent in the cold season and often initiate over the ocean and move northward, leading to precipitation mostly over the ocean. Using clustering algorithms, we have found five storm types with distinct properties, occurring throughout the year but peaking in different seasons. While overall rainfall statistics don't show any link to climate modes, links do appear for some storm types using a multivariate approach. This climatology for a variety of storm characteristics will allow future study of any changes in these characteristics due to climate change.

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A weather system perspective on winter–spring rainfall variability in southeastern Australia during El Niño

Cited by 23 publications

References 61 publications

Using seasonal rainfall clusters to explain the interannual variability of the rain belt over the Greater Horn of Africa

Using seasonal rainfall clusters to explain the interannual variability of the rain belt over the Greater Horn of Africa

Heavy versus extreme rainfall events in southeast Australia

A Radar Object-Based Examination of Rain System Climatology and Including Climate Variability

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