Outputs from new state-of-the-art climate models under the Coupled Model Inter-comparison Project phase 6 (CMIP6) promise improvement and enhancement of climate change projections information for Australia. Here we focus on three key aspects of CMIP6: what is new in these models, how the available CMIP6 models evaluate compared to CMIP5, and their projections of the future Australian climate compared to CMIP5 focussing on the highest emissions scenario. The CMIP6 ensemble has several new features of relevance to policymakers and others, for example, the integrated matrix of socioeconomic and concentration pathways. The CMIP6 models show incremental improvements in the simulation of the climate in the Australian region, including a reduced equatorial Pacific cold tongue bias, slightly improved rainfall teleconnections with large-scale climate drivers, improved representation of atmosphere and ocean extreme heat events, as well as dynamic sea level. However, important regional biases remain, evident in the excessive rainfall over the Maritime Continent and rainfall pattern biases in the nearby tropical convergence zones. Projections of Australian temperature and rainfall from the available CMIP6 ensemble broadly agree with those from CMIP5, except for a group of CMIP6 models with higher climate sensitivity and greater warming and increase in some extremes after 2050. CMIP6 rainfall projections are similar to CMIP5, but the ensemble examined has a narrower range of rainfall change in austral summer in Northern Australia and austral winter in Southern Australia. Overall, future national projections are likely to be similar to previous versions but perhaps with some areas of improved confidence and clarity.

El Niño-Southern Oscillation (ENSO) has significant variations and nonlinearities in its pattern and strength. ENSO events vary in their position along the equator, with some located in the central Pacific (CP) and others in the east Pacific (EP). To study how these variations are reflected in global ENSO teleconnections, both observations and idealized atmospheric general circulation model (AGCM) simulations are analyzed. Clear nonlinearities exist in observed teleconnections of sea level pressure (SLP) and precipitation. However, it is difficult to distinguish if these are caused by the different signs, strengths, or spatial patterns of events (strong El Niño events mostly being EP events and strong La Niña events mostly being CP events) or by combinations of these. Therefore, sensitivity experiments are performed with an AGCM forced with idealized EP and CP ENSO sea surface temperature (SST) patterns with varying signs and strengths. The response is generally stronger for warm events than for cold events and the teleconnection patterns vary with changing SST anomaly patterns. EP events show stronger nonlinearities than CP events. The nonlinear responses to ENSO events can be explained as a combination of nonlinear responses to a linear ENSO (fixed pattern but varying signs and strengths) and a linear response to a nonlinear ENSO (varying patterns). Any observed event is a combination of these aspects. While in most tropical regions these add up, leading to stronger nonlinear responses than expected from the single components, in some regions they cancel each other, resulting in little overall nonlinearity. This leads to strong regional differences in ENSO teleconnections.

We present the results of a series of adiabatic hydrodynamical simulations of several quintessence models (both with a free and an interacting scalar field) in comparison to a standard ΛCDM cosmology. For each we use 2 × 1024 3 particles in a 250h −1 Mpc periodic box assuming WMAP7 cosmology. In this work we focus on the properties of haloes in the cosmic web at z = 0. The web is classified into voids, sheets, filaments and knots depending on the eigenvalues of the velocity shear tensor, which are an excellent proxy for the underlying overdensity distribution. We find that the properties of objects classified according to their surrounding environment shows a substantial dependence on the underlying cosmology; for example, while V max shows average deviations of ≈ 5 per cent across the different models when considering the full halo sample, comparing objects classified according to their environment, the size of the deviation can be as large as 20 per cent.We also find that halo spin parameters are positively correlated to the coupling, whereas halo concentrations show the opposite behaviour. Furthermore, when studying the concentration-mass relation in different environments, we find that in all cosmologies underdense regions have a larger normalization and a shallower slope. While this behaviour is found to characterize all the models, differences in the best-fit relations are enhanced in (coupled) dark energy models, thus providing a clearer prediction for this class of models.