Project summary

Australia’s climate is extremely variable and it is difficult to predict. This variability affects agricultural regions most acutely on a seasonal scale and seasonal climate in different regions of Australia is driven by a complex interaction of large-scale ocean-atmosphere systems. We will assess the relative importance of the major climate drivers on regional climate across Australia. To better understand the processes that drive variability in seasonal rainfall, we will also explore the relationship between synoptic weather events and large-scale climate drivers. The process understanding gained will be crucial in assessing and developing skilful seasonal climate forecasts using dynamical models and hybrid dynamical/statistical methods. This understanding will also be essential in assessing the limits of predictability of seasonal climate, and it will inform future investment in seasonal climate research. In particular, key gaps and areas of work where progress is most likely to be valuable will be identified.

Project objectives

• Identify regional and seasonal climate regimes for the major agricultural regions of Australia, and their relationship to large-scale climate drivers such as El Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD)  the Southern Annular Mode (,SAM) and the atmospheric long waves of the Southern Hemisphere.
• Explore how a synoptic analysis of weather events that make up seasonal rainfall can better inform our understanding of broad-scale climate drivers and regional climate variability, using SW Australia as a test region. Compare this new technique with existing knowledge of weather systems derived as part of the research reported by the Indian Ocean Climate Initiative (IOCI).
• Evaluate the existing predictability of the major climate drivers, and hence the confidence of regional seasonal forecasts.
• Produce a research roadmap identifying key knowledge gaps and areas of work where progress is most likely to be of value, particularly in relation to agriculture. Suggest key science and alliances likely to be crucial to long-term progress in improving seasonal forecasting skill.