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Extreme Rainfall Variability in Australia: Patterns, Drivers, and Predictability

Andrew D. King ARC Centre of Excellence for Climate System Science, and Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia

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Nicholas P. Klingaman National Centre for Atmospheric Science, and Department of Meteorology, University of Reading, Reading, United Kingdom

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Lisa V. Alexander ARC Centre of Excellence for Climate System Science, and Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia

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Markus G. Donat ARC Centre of Excellence for Climate System Science, and Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia

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Nicolas C. Jourdain Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia

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Penelope Maher ARC Centre of Excellence for Climate System Science, and Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia

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Print Publication:
01 Aug 2014
DOI:
https://doi.org/10.1175/JCLI-D-13-00715.1
Page(s):
6035–6050
Restricted access

Abstract

Leading patterns of observed monthly extreme rainfall variability in Australia are examined using an empirical orthogonal teleconnection (EOT) method. Extreme rainfall variability is more closely related to mean rainfall variability during austral summer than in winter. The leading EOT patterns of extreme rainfall explain less variance in Australia-wide extreme rainfall than is the case for mean rainfall EOTs. The authors illustrate that, as with mean rainfall, the El Niño–Southern Oscillation (ENSO) has the strongest association with warm-season extreme rainfall variability, while in the cool season the primary drivers are atmospheric blocking and the subtropical ridge. The Indian Ocean dipole and southern annular mode also have significant relationships with patterns of variability during austral winter and spring. Leading patterns of summer extreme rainfall variability have predictability several months ahead from Pacific sea surface temperatures (SSTs) and as much as a year in advance from Indian Ocean SSTs. Predictability from the Pacific is greater for wetter-than-average summer months than for months that are drier than average, whereas for the Indian Ocean the relationship has greater linearity. Several cool-season EOTs are associated with midlatitude synoptic-scale patterns along the south and east coasts. These patterns have common atmospheric signatures denoting moist onshore flow and strong cyclonic anomalies often to the north of a blocking anticyclone. Tropical cyclone activity is observed to have significant relationships with some warm-season EOTs. This analysis shows that extreme rainfall variability in Australia can be related to remote drivers and local synoptic-scale patterns throughout the year.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-13-00715.s1.

Corresponding author address: Andrew D. King, Climate Change Research Centre, Level 4, Mathews Building, University of New South Wales, Sydney NSW 2052, Australia. E-mail: andrew.king@student.unsw.edu.au

Abstract

Leading patterns of observed monthly extreme rainfall variability in Australia are examined using an empirical orthogonal teleconnection (EOT) method. Extreme rainfall variability is more closely related to mean rainfall variability during austral summer than in winter. The leading EOT patterns of extreme rainfall explain less variance in Australia-wide extreme rainfall than is the case for mean rainfall EOTs. The authors illustrate that, as with mean rainfall, the El Niño–Southern Oscillation (ENSO) has the strongest association with warm-season extreme rainfall variability, while in the cool season the primary drivers are atmospheric blocking and the subtropical ridge. The Indian Ocean dipole and southern annular mode also have significant relationships with patterns of variability during austral winter and spring. Leading patterns of summer extreme rainfall variability have predictability several months ahead from Pacific sea surface temperatures (SSTs) and as much as a year in advance from Indian Ocean SSTs. Predictability from the Pacific is greater for wetter-than-average summer months than for months that are drier than average, whereas for the Indian Ocean the relationship has greater linearity. Several cool-season EOTs are associated with midlatitude synoptic-scale patterns along the south and east coasts. These patterns have common atmospheric signatures denoting moist onshore flow and strong cyclonic anomalies often to the north of a blocking anticyclone. Tropical cyclone activity is observed to have significant relationships with some warm-season EOTs. This analysis shows that extreme rainfall variability in Australia can be related to remote drivers and local synoptic-scale patterns throughout the year.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-13-00715.s1.

Corresponding author address: Andrew D. King, Climate Change Research Centre, Level 4, Mathews Building, University of New South Wales, Sydney NSW 2052, Australia. E-mail: andrew.king@student.unsw.edu.au

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