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.
This page is maintaind by Jason Evans |
Last updated 29 November 2013