Long-term variability of the leading seasonal modes of rainfall in south-eastern Australia
- Publisher: Elsevier
Weather and Climate Extremes,
Meteorology. Climatology | QC851-999 | Seasonal rainfall | PCA analysis | Running correlation | Australian climate drivers | Climate variability | Sptio-temporal analysis
Knowledge of temporal and spatial variability of climate and rainfall can improve agriculture production and can help to manage risks caused by climate variability. Available high-quality monthly rainfall data from the Australian Bureau of Meteorology for 1907–2011 was used to investigate the leading seasonal mode of the long-term rainfall variability over south-eastern and eastern Australia. Spatio-temporal variations of seasonal rainfall and their connection to oceanic-atmospheric predictors were analysed. The links between the first two Principal Components of rainfall of each season with lagged Southern Oscillation Index (SOI), Indian Ocean Dipole (IOD) and Southern Annular Mode (SAM) were season-dependent. The relationship between these climatic indices changed within both inter-seasonal and decadal time scales. Spring and winter rainfalls were continuously positively correlated with lagged (SOI). However, summer rainfall variations indicated negative correlations with lagged SOI which increase from 1970. The correlations between lagged SOI and autumn variations were weak and change to a stronger relationship from 1990. Correlations between lagged (IOD) which varied across all seasons have recently been increasing. Variations in rainfall across all seasons were highly correlated with Southern Annular Mode (SAM) with different signs. Overall, the relationship between predictors and seasonal rainfall has changed after 1970. The results of running correlations between leading modes of seasonal rainfall and lagged SOI, SAM, and IOD indices indicates non-stationary in these links. The relationships of climatic indices and leading modes of seasonal rainfall changed since 1970, with stronger evidence in case of IOD. Recent changes in the relationships between climatic indices and rainfall need to be considered in climate prediction systems. The results of this study suggests that improvement in statistical regional rainfall forecast system with fixed climatic indices for each season and region is achievable by using suitable seasonal and regional climatic indices.