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Two-year-long simulations of the atmosphere and ocean by the Commonwealth Scientific and Industrial Research Organisation's (CSIRO) Climate Analysis Forecast Ensemble (CAFE) modelling system are analysed, with a focus on Indo-Pacific sea surface temperature (SST) climate drivers and their teleconnection to Australian rainfall. The simulations are 11-member ensemble forecasts (strictly, hindcasts) initiated each month from 2002 to 2015, supplemented by a 100-year-long control simulation. Using correlations r between seasonal and annual means, it is shown that the links between the interannual variations of All-Australia precipitation (AApr) and the standard driver indices, together with the Pacific-Indian Dipole (PID), are mostly similar to those derived from observational data. The vertically integrated meridional flux of moisture towards northern Australia is linked to both the SSTs and AApr. Correlations between ensemble averages and observations are used as a measure of forecast skill, calculated for each start month and for lead time after start. Positive correlations hold over the first year for much of the low-latitude Pacific and for the drivers. The forecasts become more skillful than persistence, with r for PID averaging 0.3 higher over lead times of 7–13 months. The forecast of seasonal AApr has moderate to good correlations (r 0.4–0.8) for seasons centred on September–February. This is largely consistent with skill in both the flux and in the SST drivers. Correlations are also good for 1-year and 2-year means. This apparent skill is currently being explored using a new larger suite of CAFE forecasts.

Australian rainfall anomalies and Indo-Pacific driver indices: links and skill in 2-year-long forecasts