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Recent increases in computational resources have led to the application of kilometre- and sub-kilometre-scale simulations in research, numerical weather prediction, and climate modelling alike. Despite anticipated improvements with resolution, there is still considerable work needed to evaluate how well such models improve the representation of intense convection. In this study we conduct ensemble simulations with kilometre- and sub-kilometre-scale horizontal grids to investigate intense convective events in the tropical island thunderstorm system Hector, which frequently occurs over the Tiwi Islands in North Australia. To avoid losing information through spatio-temporal averaging we apply a tracking algorithm to simulated and observed storms. When compared with observations, the model storms exhibit a lack of propagation across the study domain. In general, simulated storms are too intense but too small and too short-lived. This is especially true for the sub-kilometre simulations, where storms are more intense, smaller, and more numerous than in the kilometre-scale counterparts. We argue that size and duration errors compensate for storm number and intensity errors, which could lead to misleading interpretations when only comparing time and space averages of rainfall fields. Investigating some properties of the simulated storms suggests that storms with high rainfall intensities have stronger updrafts in the sub-kilometre model and are accompanied by an increase in cold pool intensity. The results and their resolution sensitivities highlight that the remaining parametrisations and their many tuning parameters in high-resolution set-ups influence the representation of convective storms in such models.

A model for the spread of a wildfire is developed within the U.K. Met Office Unified Model (UM) and used to simulate the Kilmore East fire complex (in southeastern Australia) on Black Saturday (7 February 2009). The UM is configured with four nests with horizontal grid spacings of 4 km, 1.5 km, 444 m, and 144 m. In the first simulation, the UM simply provides predictions of the near‐surface conditions for the wildfire model with no feedbacks to the atmosphere from the fire. In the second, the atmosphere and fire are coupled, allowing the fire to affect the local‐scale weather. The agreement between the coupled simulation and the observed fire behavior is reasonably good. For example, the area burnt is approximately 80% of the actual area burnt. However, such agreement is achieved only by coupling the fire to the atmosphere and, importantly, by igniting 18 additional fires at the times and places the long‐range transport of burning material (spotting) was observed. Without coupling the burnt area is about half of that observed. The calculations reported here suggest that the behavior and spread of fires like the Kilmore East fire are predictable but only when long‐range spotting is included and the atmosphere and fires are coupled. Additional numerical experiments with coarser grids suggest that, although the details of the fire spread are lost, a grid spacing of 1.5 km may be sufficient to simulate the main features of the fire spread.

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.

The role of local atmospheric forcing on the ocean mixed layer depth (MLD) over the global oceans is studied using ocean reanalysis data products and a single-column ocean model coupled to an atmospheric general circulation model. The focus of this study is on how the annual mean and the seasonal cycle of the MLD relate to various forcing characteristics in different parts of the world’s oceans, and how anomalous variations in the monthly mean MLD relate to anomalous atmospheric forcings. By analysing both ocean reanalysis data and the single-column ocean model, regions with different dominant forcings and different mean and variability characteristics of the MLD can be identified. Many of the global oceans’ MLD characteristics appear to be directly linked to the different atmospheric forcing characteristics at different locations. Here, heating and wind-stress are identified as the main drivers; in some, mostly coastal, regions the atmospheric salinity forcing also contributes. The annual mean MLD is more closely related to the annual mean wind-stress and the MLD seasonality is more closely related to the seasonality in heating. The single-column ocean model, however, also points out that the MLD characteristics over most global ocean regions, and in particular in the tropics and subtropics, cannot be maintained by local atmospheric forcings only, but are also a result of ocean dynamics that are not simulated in a single-column ocean model. Thus, lateral ocean dynamics are essential in correctly simulating observed MLD.

El Nino-Southern Oscillation (ENSO) is the leading mode of interannual global climate variability, which in its essence is often described by the equatorial dynamics of the recharge oscillator with a fixed pattern. Here we explore the idea that ENSO can be simulated in a model with a fixed pattern of sea surface temperature variability following the recharge oscillator mechanism, which interacts with the thermodynamic red noise of a slab ocean. This model is capable of simulating the leading modes of sea surface temperature variability in the tropical Pacific in good agreement with the observations and most coupled general circulation models. ENSO dynamics, amplitude, seasonality, the structure of the leading patterns, its meridional extension, its variations in an eastern and central Pacific pattern and associated positive feedbacks are all influenced and simulated well by including the interaction of recharge oscillator and the thermodynamic coupling to the slab ocean model. We further point out that much of the ENSO diversity in the spatial structure is a reflection of this interaction. However, it also has to be noted that some equatorial dynamics are missing in this model and in coupled general circulation models that are important for the ENSO diversity.

In global warming scenarios, global land surface temperatures ( $$T_{land}$$ ) warm with greater amplitude than sea surface temperatures (SSTs), leading to a land/sea warming contrast even in equilibrium. Similarly, the interannual variability of $$T_{land}$$ is larger than the covariant interannual SST variability, leading to a land/sea contrast in natural variability. This work investigates the land/sea contrast in natural variability based on global observations, coupled general circulation model simulations and idealised atmospheric general circulation model simulations with different SST forcings. The land/sea temperature contrast in interannual variability is found to exist in observations and models to a varying extent in global, tropical and extra-tropical bands. There is agreement between models and observations in the tropics but not the extra-tropics. Causality in the land-sea relationship is explored with modelling experiments forced with prescribed SSTs, where an amplification of the imposed SST variability is seen over land. The amplification of $$T_{land}$$ to tropical SST anomalies is due to the enhanced upper level atmospheric warming that corresponds with tropical moist convection over oceans leading to upper level temperature variations that are larger in amplitude than the source SST anomalies. This mechanism is similar to that proposed for explaining the equilibrium global warming land/sea warming contrast. The link of the $$T_{land}$$ to the dominant mode of tropical and global interannual climate variability, the El Nino Southern Oscillation (ENSO), is found to be an indirect and delayed connection. ENSO SST variability affects the oceans outside the tropical Pacific, which in turn leads to a further, amplified and delayed response of $$T_{land}$$ .

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 \LCDM\ cosmology. For each we use $2\times1024^3$ particles in a $250$\hMpc\ 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 \emph{voids}, \emph{sheets}, \emph{filaments} and \emph{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 $V_{\rm max}$ shows average deviations of $\approx5$ 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, thus providing a clearer prediction for this class of models., 16 pages, 10 figures. Accepted for publication in MNRAS

We outline a new version of the XMDS code-generator for computational simulations, with many new features and applications to quantum-atom optics.