This talk describes and evaluates the coupled atmosphere-ocean version of the Conformal Cubic Atmospheric Model (CCAM) for use in regional climate simulations. CCAM employs a variable resolution global cubic grid to simulate the regional climate without lateral boundary conditions.  A Boussinesq ocean model has been developed within the semi-Lagrangian version of CCAM that employs a common reversibly-staggered grid to improve the model’s dispersive properties.  This approach allows for coupling between the atmosphere and ocean at every time-step, but at the expense of being able to optimise the atmosphere and ocean grids independently of each other (e.g., along coastlines).  The CCAM ocean model includes a k-e turbulent mixing option, which is being integrated into a single parameterisation with the atmospheric turbulent mixing.  River routing is included for freshwater inflows based on HydroSHEDS, with a Flow Accumulation Matrix approach employed to quickly remap routing data to the variable resolution CCAM grid.  Since CCAM can be used for dynamically downscaling ensembles of Global Climate Models (GCMs), it employs a convolution-based scale-selective filter for spectral nudging of the large-scale atmosphere.  The scale-selective filter was extended to facilitate nudging of the large-scale ocean circulation as well as accounting for irregular coastlines. The coupled CCAM can also operate by only assimilating Sea Surface Temperature data from the host GCM or reanalysis when necessary.  The coupled atmosphere-ocean CCAM performance was evaluated for the Australasian CORDEX domain, including surface currents and cyclone number density.  The best model performance was found using z* vertical coordinate, as used by MPAS ocean model. The CCAM coupled atmosphere-ocean model has so far proven to be practical and efficient when downscaling GCMs due to the low run-time and flexibility with assimilating data from the host GCMs.  It is also an important step towards the development of a regional Earth system model.