The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. Among other applications, GC3 is the basis of the United Kingdom's submission to the Coupled Model Intercomparison Project 6 (CMIP6). This paper documents the model components that make up the configuration (although the scientific descriptions of these components are in companion papers) and details the coupling between them. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present‐day forcing. The suitability of the configuration for predictability on shorter time scales (weather and seasonal forecasting) is also briefly discussed. The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2‐AO) which was the submission to CMIP5. In many respects, the performance of GC3 is comparable with GC2, however, there is a notable improvement in the Southern Ocean warm sea surface temperature bias which has been reduced by 75%, and there are improvements in cloud amount and some aspects of tropical variability. Relative to HadGEM2‐AO, many aspects of the present‐day climate are improved in GC3 including tropospheric and stratospheric temperature structure, most aspects of tropical and extratropical variability and top‐of‐atmosphere and surface fluxes. A number of outstanding errors are identified including a residual asymmetric sea surface temperature bias (cool northern hemisphere, warm Southern Ocean), an overly strong global hydrological cycle and insufficient European blocking.

The Australian Community Climate and Earth System Simulator coupled model (ACCESS-CM) has been developed at the Centre for Australian Weather and Climate Research (CAWCR), a partnership between CSIRO 1 and the Bureau of Meteorology. It is built by coupling the UK Met Office atmospheric unified model (UM), and other sub-models as required, to the ACCESS ocean model, which consists of the NOAA/GFDL 2 ocean model MOM4p1 and the LANL 3 sea-ice model CICE4.1, under the CERFACS 4 OASIS3.2-5 coupling framework. The primary goal of the ACCESS-CM development is to provide the Australian climate community with a new generation fully coupled climate model for climate research, and to participate in phase five of the Coupled Model Inter-comparison Project (CMIP5). This paper describes the ACCESS-CM framework and components, and presents the control climates from two versions of the ACCESS-CM, ACCESS1.0 and AC-CESS1.3, together with some fields from the 20 th century historical experiments, as part of model evaluation. While sharing the same ocean sea-ice model (except different setups for a few parameters), ACCESS1.0 and ACCESS1.3 differ from each other in their atmospheric and land surface components: the former is configured with the UK Met Office HadGEM2 (r1.1) atmospheric physics and the Met Office Surface Exchange Scheme land surface model version 2, and the latter with atmospheric physics similar to the UK Met Office Global Atmosphere 1.0 including modifications performed at CAWCR and the CSIRO Community Atmosphere Biosphere Land Exchange land surface model version 1.8. The global average annual mean surface air temperature across the 500-year preindustrial control integrations show a warming drift of 0.35 °C in ACCESS1.0 and 0.04 °C in AC-CESS1.3. The overall skills of ACCESS-CM in simulating a set of key climatic fields both globally and over Australia significantly surpass those from the preceding CSIRO Mk3.5 model delivered to the previous coupled model inter-comparison. However, ACCESS-CM, like other CMIP5 models, has deficiencies in various aspects, and these are also discussed.

Carbon dioxide concentrations due to fossil fuel burning and CO2 exchange with the terrestrial biosphere have been modeled with 12 different three‐dimensional atmospheric transport models. The models include both on‐line and off‐line types and use a variety of advection algorithms and subgrid scale parameterizations. A range of model resolutions is also represented. The modeled distributions show a large range of responses. For the experiment using the fossil fuel source, the annual mean meridional gradient at the surface varies by a factor of 2. This suggests a factor of 2 variation in the efficiency of surface interhemispheric exchange as much due to differences in model vertical transport as to horizontal differences. In the upper troposphere, zonal mean gradients within the northern hemisphere vary in sign. In the terrestrial biotic source experiment, the spatial distribution of the amplitude and the phase of the seasonal cycle of surface CO2 concentration vary little between models. However, the magnitude of the amplitudes varies similarly to the fossil case. Differences between modeled and observed seasonal cycles in the northern extratropics suggest that the terrestrial biotic source is overestimated in late spring and underestimated in winter. The annual mean response to the seasonal source also shows large differences in magnitude. The uncertainty in hemispheric carbon budgets implied by the differences in interhemispheric exchange times is comparable to those quoted by the Intergovernmental Panel on Climate Change for fossil fuel and ocean uptake and smaller than those for terrestrial fluxes. We outline approaches which may reduce this component in CO2 budget uncertainties.

The effective viscosity 77 of a suspension of charged spherical colloidal particles in a general electrolyte of viscosity qo is calculated to first order in the volume fraction q5 to be 77 = 770{1+5q5[1 + P ( S , .a)l).The primary electroviscous coefficient p ( [ , K U ) as a function of the zeta potential [ is derived in terms of the asymptotic behaviour of the hydrodynamic flow field far from a typical colloidal particle. The computation of p ( l , K U ) (for a general mixed electrolyte with f unrestricted in magnitude) is reduced to the solution of a set of linear coupled ordinary differential equations and an accurate and robust numerical scheme for solving them is demonstrated. An analytic approximate expression for p ( [ ) correct to 0 ( l 2 ) is derived and shown to agree with an early result of Booth. Exact numerical results are compared with the approximate expression of Booth.A maximum is predicted in the primary electroviscous coefficient p ( [ ) for all KU values. The measurement of the magnitude of this maximum may be used to test the validity of the underlying equations.

There remains uncertainty in the projected climate change over the 21st century, in part because of the range of responses to rising greenhouse gas concentrations in current global climate models (GCMs). The representation of potential changes in the form of a probability density function (PDF) is increasingly sought for applications. This article presents a method of estimating PDFs for projections based on the “pattern scaling” technique, which separates the uncertainty in the global mean warming from that in the standardized regional change. A mathematical framework for the problem is developed, which includes a joint probability distribution for the product of these two factors. Several simple approaches are considered for representing the factors by PDFs using GCM results, allowing model weighting. The four‐parameter beta distribution is found to provide a smooth PDF that can match the mean and range of GCM results, allowing skewness when appropriate. A beta representation of the range in global warming consistent with the Intergovernmental Panel on Climate Change Fourth Assessment Report is presented. The method is applied to changes in Australian temperature and precipitation, under the A1B scenario of concentrations, using results from 23 GCMs in the CMIP3 database. Statistical results, including percentiles and threshold exceedences, are compared for the case of southern Australian temperature change in summer. For the precipitation example, central Australian winter rainfall, the usual linear scaling assumption produces a net change PDF that extends to unphysically large decreases. This is avoided by assuming an exponential relationship between percentage decreases in rainfall and warming.