Comparison of various climate change projections of eastern Australian rainfall.

Grose, M.R., J.Bhend, D. Argueso, M. Ekström, A. Dowdy, P. Hoffman, J.P. Evans, B. Timbal
Australian Meteorological and Oceanographic Journal, 65(1), 72-89, 2015.


The Australian eastern seaboard is a distinct climate entity from the interior of the continent, with different climatic influences on each side of the Great Dividing Range. Therefore, it is plausible that downscaling of global climate models could reveal meaningful regional detail, or ‘added value’, in the climate change signal of mean rainfall change in eastern Australia un- der future scenarios. However, because downscaling is typically done using a limited set of global climate models and downscaling methods, the results from a downscaling study may not represent the range of uncertainty in plausible projected change for a region suggested by the ensemble of host global climate models. A complete and unbiased representation of the plausible changes in the climate is essential in producing climate projections useful for future planning. As part of this aim it is important to quantify any differences in the change signal between global climate models and downscaling, and understand the cause of these differ- ences in terms of plausible added regional detail in the climate change signal, the impact of sub-sampling global climate models and the effect of the downscaling models themselves. Here we examine rainfall projections in eastern Australia under a high emissions scenario by late in the century from ensembles of global climate models, two dynamical downscaling models and one statistical downscaling model. We find no cases where all three downscaling methods show the same clear regional spatial detail in the change signal that is distinct from the host models. However, some downscaled projections suggest that the eastern seaboard could see little change in spring rainfall, in contrast to the substantial rainfall decrease inland. The change signal in the downscaled outputs is broadly similar at the large scale in the various model outputs, with a few notable exceptions. For example, the model median from dynamical downscaling projects a rainfall increase over the entirety of eastern Australia in autumn that is greater than the global models. Also, there are some instances where a downscaling method produces changes outside the range of host models over eastern Australia as a whole, thus ex- panding the projected range of uncertainty. Results are particularly uncertain for summer, where no two downscaling studies clearly agree. There are also some confounding factors from the model configuration used in downscaling, where the particular zones used for statis- tical models and the model components used in dynamical models have an influence on results and produce additional uncertainty.

Key Figure

Fig. 4. Projected change in mean rainfall per degree of global warming (%/°C) for various modelling studies by calendar season averaged over NRM cluster regions Central Slopes (left) and East Coast South (right). CMIP5-based results are for RCP8.5 1986-2005 to 2080-2099 and CMIP3-based results are for SRES A2, 1990-2009 to 2060-2079. Bars in each plot show projections from left to right: 39 CMIP5 models (red), BOM-SDM results (purple), CCAM results (blue), CMIP3 results (olive), and NARCliM results (green). Thick bars show the 90 th and 10th percentile of the model range and dark lines mark the 50th percentile.

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