Title: Development of prediction model for forecasting rainfall in Western Australia using lagged climate indices
Authors: Farhana Islam; Monzur A. Imteaz
Addresses: Department of Civil and Construction Engineering, Faculty of Science, Engineering and Technology, Swinburne University of Technology, Melbourne, VIC 3122, Australia ' Department of Civil and Construction Engineering, Faculty of Science, Engineering and Technology, Swinburne University of Technology, Melbourne, VIC 3122, Australia
Abstract: The aim of the study was to develop a model to forecast autumn rainfall several months in advance for south-west division (SWD) of Western Australia (WA), by identifying and incorporating the relationship among major climate indices such as dipole mode index (DMI), southern oscillation index (SOI), ENSO Modoki index (EMI) and autumn rainfall. Eight rainfall stations from two regions of SWD were considered. Statistical analysis showed that DMI, SOI, Nino3.4, Nino3 and Nino4 have significant correlations with autumn rainfall for all these stations. On the other hand, EMI showed significant correlations for the stations in the north-coast region only. Meanwhile, DMI effect has been found stronger for all the stations compared to other climate indices. Several multiple regression analyses were conducted using lagged ENSO-DMI, lagged SOI-DMI and lagged EMI-DMI indices, and significant increase in the correlations between autumn rainfall and climate indices was observed. However, only statistically significant models were suggested.
Keywords: climate indices; dipole mode index; DMI; El Nino southern oscillation; ENSO; southern oscillation index; SOI; ENSO Modoki index; EMI; Australia.
International Journal of Water, 2019 Vol.13 No.3, pp.248 - 268
Received: 12 Jun 2018
Accepted: 29 Dec 2018
Published online: 02 Aug 2019 *