Past and future rainfall change in sub-regions of Victoria, Australia

Surendra P. Rauniyar () and Scott B. Power
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Surendra P. Rauniyar: Australian Bureau of Meteorology
Scott B. Power: University of Southern Queensland

Climatic Change, 2023, vol. 176, issue 7, No 13, 23 pages

Abstract: Abstract We examine rainfall variability and change in three sub-regions of the state of Victoria in Australia: the Murray Basin Victoria (MBVic), southeast Victoria (SEVic), and southwest Victoria (SWVic). These sub-regions represent three different hydrological super-catchments over Victoria and received average cool season rainfall for the 1997–2018 period, about 15%, 11%, and 8% less, respectively, than the 1900–1959 average. All three observed declines are shown to be very unusual in terms of historical variability. On analysing CMIP5 models under different forcing conditions (preindustrial, historical-all, historical-GHGs-only, historical-natural-only, RCP2.6, RCP4.5, and RCP8.5), we estimate that external forcing caused 30% of the observed drying in SWVic, 18% in MBVic, and 17% in SEVic. The external forcing contributions to the observed trend for the 1900–2018 period are estimated to be 56%, 17%, and 24% for SWVic, MBVic, and SEVic, respectively. Taken at face value, these figures suggest that only the 1900–2018 trend in SWVic was dominated by external forcing. Nearly all models underestimate the magnitude of the observed drying. This arises because models underestimate the magnitude of decadal variability, and because models might also underestimate externally forced drying, and/or the contribution of internal variability in the real world to the observed event was unusually large. By 2037, approximately 90% of the models simulate drying in SWVic, even under a low emissions scenario. Under a high emission scenario, the anthropogenically forced drying towards the late twenty-first century is so large in all three sub-regions that internal variability appears too small to offset it.

Keywords: Drought; Climate change; Rainfall projection; Climate models; Internal variability (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10584-023-03562-9

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