Improving Australian Rainfall Prediction Using Sea Surface Salinity

Abstract This study uses sea surface salinity (SSS) as an additional precursor for improving the prediction of summer [December–February (DJF)] rainfall over northeastern Australia. From a singular value decomposition between SSS prior seasons and DJF rainfall, we note that Indo-Pacific warm pool region [SSSP (150°E–165°W 10°S–10°N) SSSI (50°–95°E 10°S–10°N)] covaries with Australian particularly in northeast region. Composite analysis is based on high or low events SSSP regions performed to understand physical links atmospheric moisture originating from anomalously low, respectively, precipitation The composites show signature co-occurring La Niña negative Indian Ocean dipole wet conditions Australia conversely El Niño positive dry there. During regions, convergence incoming flux results soil anomaly. Conversely, during divergence We random-forest regression local moisture, Niño–Southern Oscillation (ENSO), are most important precursors whereas Brisbane ENSO, SSSP, important. using shows improvement by including season. evidence suggests sustained observations can improve monitoring regional hydrological cycle.