University of Tasmania, Australia

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CSIRO-UTAS PhD Program in Quantitative Marine Science

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Dynamical downscaling of near-shore marine climate, extremes, and biogeochemistry around Southeast Australia


Dr Eric C. J. Oliver (UTAS) -Contact

Assoc Prof Neil J. Holbrook (UTAS)

Dr Mark Baird (CSIRO)


The surface waters of southeast Australia are warming at almost four times the global average rate (Holbrook & Bindoff, 1997; Ridgway, 2007), and this warming is associated with the multi-decadal intensification of the South Pacific gyre and southward extension of the nutrient-poor East Australian Current (EAC). This warming is projected to increase under anthropogenic-driven climate change (Matear et al, 2013) and may lead to dramatic changes to extreme ocean temperature events off southeast Australia, not only in terms of their increased frequency, but also their persistence – known as "marine heat waves" (Oliver et al., 2014). Much effort has focussed on understanding the offshore warming and forcing mechanisms (e.g., Cai et al., 2005; Cai, 2006; Sun et al., 2012; Oliver and Holbrook, 2014). However, comprehensive investigations of the coastal effects of this warming have been limited due to the paucity of coastal oceanographic observations and absence of high-resolution model data across the continental shelf.  The large-scale warming of Australia's southeast region is nevertheless expected to have implications for biological productivity and, by extension, human interests in the region such as fisheries and species conservation.  In particular, the impact of this warming on coastal marine heat waves, which are poorly understood in this region, are of great interest.  It is important to understand how this dramatic change in Australia's southeast regional marine waters is related to, and affects, the shallow waters of the continental shelf.

High-resolution predictions of ocean variability on Australia's continental shelf are essential for characterising how the complex near-coastal marine climate (e.g., circulation, temperature, salinity) and ecology will change in the coming decades.  Existing observations are too sparse in time and space to adequately characterise the ocean variability that define the relevant coastal oceanographic processes at the scales of ecological importance. Efforts to provide reanalysed ocean variability using data-assimilative numerical models have had success in predicting the large-scale ocean circulation but the model designs have limited the accuracy of predictions of ocean variability on the continental shelf (e.g., Bluelink ReANalysis, or BRAN). Some regions have employed high-resolution regional models to address this limitation through dynamical downscaling (e.g., using: SAROM in South Australia; SEAPOM in New South Wales; eReefs for the waters of the Great Barrier Reef) but there has not been a regional-scale downscaling effort for the continental shelf around Tasmania.  We intend to develop and implement a high-resolution regional model for southeast Australia (focused at first on Tasmanian waters) to downscale BRAN and future marine climate projections onto the continental shelf.  This will enable questions to be answered regarding changes in marine climate on the continental shelf at scales and locations that are in line and more consistent with the biological changes that have been observed, and are of concern into the future.


Cai W (2006). Geophys. Res. Lett. 33: L03712, doi:10.1029/2005GL024911.

Cai W, Shi G, Cowan T, et al. (2005). Geophys. Res. Lett. 32: L23706, doi:10.1029/2005GL024701.

Holbrook NJ, Bindoff NL (1997). Journal of Climate, 10, 1035-1049.

Matear RJ, Chamberlain MA, Sun C, Feng M (2013), Journal of Geophysical Research, 118, 2961-2976

Oliver ECJ, Wotherspoon SJ, Chamberlain MA, Holbrook NJ (2014), Journal of Climate, 27(5), 1980-1998

Oliver ECJ, Holbrook NJ (2014), Journal of Geophysical Research, 119, 2788-2805

Ridgway KR (2007). Geophys. Res. Lett. 34: L13613, doi:10.1029/2007GL030393.

Sun C, Feng M, et al. (2012). Journal of Climate, 25, 2947-2962.
Skills Needed to Complete Project:

First Class Honours (or equivalent) or Master's degree in physical oceanography, physics or mathematics required. Desirable skills include familiarity with computer programming languages (C, FORTRAN, MATLAB), ocean dynamics, and time series analysis.