Exploring a Global Multiresolution Modeling Approach Using Aquaplanet Simulations*

Abstract

Results from aquaplanet experiments performed using the Model for Prediction across Scales (MPAS) hydrostatic dynamical core implemented within the Department of Energy (DOE)-NCAR Community Atmosphere Model (CAM) are presented. MPAS is an unstructured-grid approach to climate system modeling that supports both quasi-uniform and variable-resolution meshing of the sphere based on conforming grids. Using quasi-uniform simulations at resolutions of 30, 60, 120, and 240 km, the authors evaluate the performance of CAM-MPAS via its kinetic energy spectra, general circulation, and precipitation characteristics. By analyzing an additional variable-resolution simulation with grid spacing that varies from 30 km in a spherical, continental-sized equatorial region to 240 km elsewhere, the CAM-MPAS's potential for use as a regional climate simulation tool is explored.Similar to other quasi-uniform aquaplanet simulations, tropical precipitation increases with resolution, indicating the resolution sensitivity of the physical parameterizations. Comparison with the finite volume (FV) dynamical core suggests a weaker tropical circulation in the CAM-MPAS simulations, which is evident in reduced tropical precipitation and a weaker Hadley circulation. In the variable-resolution simulation, the kinetic energy spectrum within the high-resolution region closely resembles the quasi-uniform 30-km simulation, indicating a robust simulation of the fluid dynamics. As suggested by the quasi-uniform simulations, the CAM4 physics behave differently in the high and low resolution regions. A positive precipitation anomaly occurs on the western edge of the high-resolution region, exciting a Gill-type response; this zonal asymmetry represents the errors incurred in a variable resolution setting. When paired with a multiresolution mesh, the aquaplanet test case offers an exceptional opportunity to examine the response of physical parameterizations to grid resolution. * Lawrence Livermore National Laboratory Report LLNL-JRNL-538911.

Observed Scaling in Clouds and Precipitation and Scale Incognizance in Regional to Global Atmospheric Models

“…The scale-incognizant behavior of the RKZ package likely explains results from a number of recent studies showing strong decreases in total cloud coverage and intensification of stratiform precipitation in CAM4 as resolution increases (Williamson, 2008;Levy et al, In Review;Rauscher et al, 2012). We do not yet have an explanation for why the RKZ package seems to drive such strong resolution-dependent behavior, but a future study that explains this behavior would be invaluable.…”

“…In the two manuscripts describing variable-mesh capabilities in CAM, only CAM4 physics has been used (Levy et al, In Review;Rauscher et al, 2012). Currently, the MPAS dycore only works with CAM4 physics, although a new, non-hydrostatic version with CAM5 physics is currently in development (Skamarock et al, 2012b), and the SE dycore has not been extensively tested with the CAM5 physics.…”

“…This is not the case in variable-resolution simulations using CAM4 physics (Levy et al, In Review;Rauscher et al, 2012). Further, a primary goal of model tuning in this paradigm should be to ensure that the integrals of such scale-invariant quantities match with observations.…”

“…The simulations include output from the tropical-channel WRF and CAM climate models. For the WRF model, only the Eulerian mass coordinate dycore is used, while the CAM simulations are based upon four different dycores including the Eulerian spectral transform dycore (Neale et al, 2010), the spectral element dycore (HOMME) (Dennis et al, 2012a), the finite volume (FV) dycore (Lin, 2004), and the Model for Prediction Across Scales atmospheric (MPAS-A) dycore (Rauscher et al, 2012). The WRF model has been modified to use the parameterizations of the CAM4 physics package, so that the dynamical core is the main difference between the CAM4 and WRF simulations presented here.…”

Eos, Transactions, American Geophysical Union Volume 94, Number 34, 20 August 2013

“…Global models with local refinement using unstructured grids have become available for modeling regional climate [e.g., Rauscher et al, 2012; T. D. Ringler et al, A multiresolution approach to global ocean modeling, submitted to Ocean Modelling, 2013]. While the range of approaches offers opportunities to improve climate simulations, significant efforts are needed to test their veracity for regional-scale climate simulations.…”