Analysing lagged ENSO and IOD as potential predictors for long-term rainfall forecasting using multiple regression modelling

Several climate indices around Australia were found to have strong correlations with south-east Australian seasonal rainfalls. Any such correlation with lagged climate indices and seasonal rainfall afterwards can be used for forecasting long-term seasonal rainfall. In this study, long-term forecasting of Victorian spring rainfall has been investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) indices using multiple regression analysis. Three stations of Buchan (east VIC), Malmsbury (Central VIC) and Kaniva (West VIC) were chosen as case study. Rainfall was classified according to El Nino, La Nina and Neutral years of ENSO, and also positive and negative years of IOD. It was discovered that categorizing rainfalls based on the years of ENSO and IOD do not have significant effect on its relationship with these climate modes. It was also found that the Pearson correlation coefficient between ENSO and Buchan in east Victoria is very weak; for Malmsbury and Kaniva ENSO indicators are showing higher correlations compared to Buchan. DMI effect is stronger in these two regions as well. Using the non-classified rainfalls, correlation coefficient between spring rainfall at year n and Decn-1-Augn monthly values of ENSO and IOD indicators (Nino3.4, SOI and DMI) were calculated ('n' being the year for which spring rainfall is being predicted); It was discovered that only the three months of June, July and August of Nino3.4, SOI and DMI have significant correlation with spring rainfall. Several multiple regression models were investigated using lagged ENSO and IOD as potential predictors of spring rainfall; the models that satisfied the limits of statistical significance and multicollinearity were used to forecast spring rainfall three consecutive years in advance. Multiple regression analysis showed poor results in regards to forecasting ability in east Victoria, however it was able to forecast spring rainfall three consecutive years in advance for central and west Victoria with a correlation of 0.48 and 0.67 respectively.