Comparing precipitation and temperature trends between inland and coastal locations
- Publication Type:
- Journal Article
- ANZIAM Journal : Electronic Supplement, 2018, 60 pp. C109 - C126
- Issue Date:
Motivated by the Millennium Drought and the current drought over much of southern and eastern Australia, this detailed statistical study compares trends in annual wet season precipitation and temperature between a coastal site (Newcastle) and an inland site (Scone). Bootstrap permutation tests reveal Scone precipitation has decreased significantly over the past 40 years (p-value=0.070) whereas Newcastle has recorded little to no change (p-value=0.800). Mean maximum and minimum temperatures for Newcastle have increased over the past 40 years (p-values of 0.002 and 0.015, respectively) while the mean maximum temperature for Scone has increased (p-value = 0.058) and the mean minimum temperature has remained stable. This suggests mean temperatures during the wet season for both locations are increasing. Considering these trends along with those for precipitation, water resources in the Hunter region will be increasingly strained as a result of increased evaporation with either similar or less precipitation falling in the region. Wavelet analysis reveals that both sites have similar power spectra for precipitation and mean maximum temperature with a statistically significant signal in the two to seven year period, typically indicative of the El-Nino Southern Oscillation climate driver. The El-Nino Southern Oscillation also drives the Newcastle mean minimum temperature, whereas the Scone power spectra has no indication of a definitive driver for mean minimum temperature. References R. A., R. L. Kitching, F. Chiew, L. Hughes, P. C. D. Newton, S. S. Schuster, A. Tait, and P. Whetton. Climate change 2014: Impacts, adaptation, and vulnerability. Part B: Regional aspects. Contribution of Working Group II to the Fifth Assessment of the Intergovernmental Panel on Climate Change. Technical report, Intergovernmental Panel on Climate Change, 2014. URL https://www.ipcc.ch/report/ar5/wg2/. Bureau of Meteorology. Climate Glossary-Drought. URL http://www.bom.gov.au/climate/glossary/drought.shtml. K. M. Lau and H. Weng. Climate signal detection using wavelet transform: How to make a time series sing. B. Am. Meteorol. Soc., 76:23912402, 1995. doi:10.1175/1520-0477(1995)0762391:CSDUWT>2.0.CO;2. M. B. Richman and L. M. Leslie. Uniqueness and causes of the California drought. Procedia Comput. Sci., 61:428435, 2015. doi:10.1016/j.procs.2015.09.181. M. B. Richman and L. M. Leslie. The 20152017 Cape Town drought: Attribution and prediction using machine learning. Procedia Comput. Sci., 140:248257, 2018. doi:10.1016/j.procs.2018.10.323.