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Indices derived from daily rainfall time series are used to measure "burst" features of the northern Australia monsoon, corresponding to one or more days of heavy rainfall. These indices include number of burst days, numbers and durations of burst events, and average intensity. The results using observational data show how these features can vary from one year to the next, and how they can vary from the station scale (Darwin) to the regional scale (northern Australia). The results from Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model simulations under both historical and future greenhouse gas conditions have also been analysed and indicate how well models can capture these features and how they might change by the end of the 21st century under a high emissions scenario. While most models provide a reasonable simulation of present‐day burst features, there is little consensus for a significant change to seasonal rainfall totals when looking at the full CMIP5 ensemble. A subset of models with detectable skills with respect to the Madden‐Julian Oscillation shows evidence for an increase in the seasonal total rainfall amount and most other monsoon metrics, except a slight decrease in the number of burst events. This is consistent with a basic thermodynamic response to warming and consistent with findings elsewhere. However, the Australian monsoon is strongly influenced by the large‐scale circulation and there remains some doubt about whether we can confidently diagnose all the changes to monsoon bursts that could occur given the limited ability of many of the current generation of models to simulate tropical cyclones, the Madden‐Julian Oscillation and other relevant features. [ABSTRACT FROM AUTHOR]

The article focuses on ranking the AR4 climate models over the Murray-Darling Basin using simulated maximum temperature, minimum temperature and precipitation. It states that assessment is taken on the capacity of models submitted for Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), to simulate maximum and minimum temperatures and precipitation the Murray-Darling Basin in Australia. The team use daily data from AR4 to calculate the mean of three quantities, but also derive probability density functions (PDFs) for each variable. It notes that to demonstrate skill in simulating the daily derived PDFs is more challenging than simulating the mean.