A trend of increasing rainfall over much of north and northwest Australia over recent decades has contrasted with decreases over much of the rest of the continent. The increases have occurred during the summer months when the rainy season is dominated by the Australian monsoon but is also affected by other events such as tropical cyclones, Madden-Julian oscillations, and sporadic thunderstorms. The problem of diagnosing these trends is considered in terms of changes in the timing of the rainy season. While numerous definitions for rainy/monsoon season onset exist, most are designed to be useful in a predictive sense and can be limited in their application to diagnostic studies, particularly when they involve predetermined threshold amounts. Here the authors define indices, based on daily rainfall observations, that provide relatively simple, robust descriptions of each rainy season at any location. These are calculated using gridded daily rainfall data throughout the northern Australian tropics and also for selected stations. The results indicate that the trends in summer rainfall totals over the period from 1950 to 2005 appear to be mainly the result of similar trends in average intensity. Furthermore, the links between the SeptemberOctober average Southern Oscillation index indicate that ENSO events affect season duration rather than average intensity. Because duration and average intensity are derived as independent features of each season, it is argued that the trends in rainfall totals are largely unrelated to trends in ENSO and most likely reflect the influence of other factors. Finally, diagnosing these features of the rainy season provides a basis for assessing the confidence one can attach to different climate model projections of changes to rainfall.

The aim of this study is to examine the statistics of convective storms and their concomitant changes with thermodynamic variability. The thermodynamic variability is analyzed by performing a cluster analysis on variables derived from radiosonde releases at Brisbane Airport in Australia. Three objectively defined regimes are found: a dry, stable regime with mainly westerly surface winds, a moist northerly regime, and a moist trade wind regime. S-band radar data are analyzed and storms are identified using objective tracking software [Thunderstorm Identification, Tracking, Analysis, and Nowcasting (TITAN)]. Storm statistics are then investigated, stratified by the regime subperiods. Convective storms are found to form and maintain along elevated topography. Probability distributions of convective storm size and rain rate are found to follow lognormal distributions with differing mean and variance among the regimes. There was some evidence of trimodal storm-top heights, located at the trade inversion (1.5-2 km), freezing level (3.6-4 km), and near 6 km, but it was dependent on the presence of the trade inversion. On average, storm volume and height are smallest in the trade regime and rain rate is largest in the westerly regime. However, westerly regime storms occur less frequently and have shorter lifetimes, which were attributed to the enhanced stability and decreased humidity profiles. Furthermore, time series of diurnal rain rate exhibited early morning and midafternoon maxima for the northerly and trade regimes but were absent for the westerly regime. The observations indicate that westerly regime storms are primarily driven by large-scale forcing, whereas northerly and trade wind regime storms are more responsive to surface characteristics.

The subtropical ridge (STR) is the mean pressure ridge in the mid-latitudes, and is one of the key features affecting climate variability and change in southeast Australia. Changes to the STR and associated changes to rainfall in a warming climate are of strong interest, and the new Coupled Model Inter-comparison Project phase 5 (CMIP5) model archive provides new opportunities to examine this. Here we show that the STR is projected to strengthen and move pole-ward under global warming, contributing to reduced rainfall in the cool season in southeast Australia. This result is largely consistent among 35 models examined, and CMIP5 shows a greater increase in intensity relative to position than CMIP3 did. We show that the simulation of the STR in the CMIP5 is similar to that of the previous CMIP3 in many respects, including the underestimation of both the historical trends in the STR intensity and the correlation between inter-annual STR intensity and southeast Australian rainfall. These issues mean we still have reduced confidence in regional rainfall projections for southeast Australia and suggest that CMIP5 rainfall projections for this region in April to October may be underestimates.

A projected drying of the extra-tropics under enhanced levels of atmospheric greenhouse gases has large implications for natural systems and water security across southern Australia. The drying is driven by well studied changes to the atmospheric circulation and is consistent across climate models, providing a strong basis from which adaptation planners can make decisions. However, the magnitude and seasonal expression of the drying is expected to vary across the region. Here we describe the spatial signature of the projected change from the new CMIP5 climate models and downscaling of those models, and review various lines of evidence about the seasonal expression.Winter rainfall is projected to decline across much of southern Australia with the exception of Tasmania, which is projected to experience little change or a rainfall increase in association with projected increases in the strength of the westerlies. Projected winter decrease is greatest in southwest Western Australia. A 'seasonal paradox' between observations and CMIP5 model projections in the shoulder seasons is evident, with strong and consistent drying projected for spring and less drying projected for autumn, the reverse of the observed trends over the last 50 years. The models have some biases in the simulation of certain synoptic types (e.g. cutoff lows), the rainfall brought by those synoptic types, and the mechanism of rainfall production. Rainfall projections based on statistical downscaling are examined in relation to some of these biases, projecting stronger future declines in some regions of southeast Australia in autumn than indicated by the host models, as well as little change to the magnitude of the projected declines in spring. Apart from Tasmania in winter, the decline of rainfall in southern Australia during the cool season remains a confident projection but the seasonal expression of change remains an ongoing research topic.

Model evaluation is an important tool to help rate confidence in climate model simulations. This can add to the overall confidence assessment for future projections of the Australian climate. Additionally it can highlight significant model deficiencies that may affect the selection of a subset of models for use in impact assessment.Here we present results from an extensive model evaluation undertaken as part of the Natural Resource Management (NRM) Project in order to inform the newest set of climate change projections for Australia.The assessment covers mean climate skill over Australia as well as variability measures and teleconnections from up to 47 CMIP5 models and 23 CMIP3 models (for comparison where appropriate). Additionally, the skill in representing important climate features such as MJO, SAM, blocking and cut-off lows are also reviewed. Selected extremes are evaluated as well as simulations of two different types of downscaling simulations used within the NRM project. Finally, an attempt is made to synthesise this information in order to highlight a small group of CMIP5 models which show consistent deficiencies in representing the Australian climate and its features.