29 April 2013

Exploring a Global Multiresolution Modeling Approach Using Aquaplanet Simulations


Although regional climate modeling efforts have been underway for over two decades, it is unclear which regional climate modeling method provides the most robust results. As part of a DOE-funded project to test the veracity of global high resolution and global variable resolution simulations for regional modeling applications, the researchers examined a series of idealized, full physics aquaplanet test cases performed with the DOE-NCAR Community Atmosphere Model (CAM) coupled to the new MPAS atmospheric dynamical core (CAM-MPAS). Both quasi-uniform and variable resolution (VR) experiments were performed in an aquaplanet setting, which is land and season free, but still contains many realistic climate features. Comparisons between quasi-uniform simulations using CAM-MPAS and other dynamical cores in CAM show that CAM-MPAS provides a reasonable aquaplanet simulation in terms of its kinetic energy spectra, precipitation characteristics, and general circulation. Importantly, the high resolution region in a CAM-MPAS VR simulation has a climate similar to a global quasi-uniform high resolution simulation. Hence, high resolution results are achieved over a given area at a fraction of the computational price of a global high resolution simulation. However, the interaction between the CAM moist physics and the mesh refinement region in the VR simulation also produces a zonally asymmetric response, with a region of high precipitation and an associated diabatic heating anomaly on the western periphery of the high resolution region.


Additional experiments confirm that the varying response of the CAM physical parameterizations with grid resolution is responsible for this zonal asymmetry. Since this "error" incurred from using a VR mesh can be measured by the amplitude of the zonally asymmetric response, improvements in model physical parameterizations can be tracked in future simulations. The VR approach examined here holds promise for regional modeling applications as it can unite both the regional and global modeling communities within a single global framework.

Siyu Chen