Abstract

Large scale modes of climate variability influence rainfall and soil moisture in southeastern Australia, and extended dry conditions have been associated with a lack of climate mode phases conducive to wetter conditions. However, the role of large-scale climate variability in breaking ongoing soil moisture droughts has not been well quantified, and the utility of large-scale signals in drought recovery assessments have not been explored. Here, we study the influence of El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on the probability of soil moisture drought breaking in eastern and southeastern Australia, using logistic regression modelling. A long-term historical dataset from the Australian Water Resources Assessment Landscape (AWRA-L) model is used for the assessment. The probability estimates from the logistic regression modelling validate well against observed probability of a drought ending. We then use model estimates to understand the probability contributions from different climate modes. We show that there is a seasonal pattern in soil moisture drought breaking probabilities with higher probabilities in austral summer in eastern Australia and summer/autumn in southeastern Australia. ENSO has the largest influence on probabilities in winter with extreme opposite phases of the mode resulting in regional average probability differences of 15–26%. The IOD exhibits the largest influences during spring and winter and opposite phases result in differences of about 18%. The method can be used to estimate soil moisture drought breaking probabilities in near real-time during drought events, and may assist decision making by managers engaged in drought risk and water resources planning.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call