We present a numerical analysis of six strategies to couple the dynamical core with physical parameterizations in atmospheric models. The algorithms are outlined on a generic problem and then applied to two idealized test beds: the two-dimensional viscid Burgers' equations and a hydrostatic model which employs the potential temperature as vertical coordinate. The latter is used for vertical...
The lower-resolution physics grid option in CESM is evaluated in both an AMIP-style simulation and fully-coupled with active ocean/sea-ice components, and compared against the standard configuration in which the physics and dynamics grids coincide. As topography boundary conditions are on a coarser grid than in the standard configuration, a portion of this talk will focus on model fidelity in...
Most general circulation models (GCMs) represent boundary layer turbulence by eddy-diffusivity (ED) schemes, and convection by mass-flux (MF) schemes. Because boundary layer and convective processes closely interact with each other, the ED and MF schemes should be coupled appropriately. This study explores two coupling strategies of the ED and MF schemes using GFDL AM4, namely, (1) the...
Understanding of wind stress, or drag coefficient (Cd), in finite depth is important for improving numerical weather and storm surge prediction models. In most applications, Cd is assumed to be the same in open ocean (deep water) and coastal waters (finite to shallow depth). However, if the wind stress is dependent on sea state, Cd is likely different in shallow water compared to that in deep...
Stochastic parameterizations are used in numerical weather prediction and climate modeling to help capture the uncertainty in the simulations and improve their statistical properties. Convergence issues can arise when time integration methods originally developed for deterministic differential equations are applied naively to stochastic problems. (Hodyss et al 2013, 2014) demonstrated that a...
Complex interactions among atmospheric processes like radiation, convection, boundary layer turbulence, cloud microphysics, aerosols, and large-scale dynamics can be an important aspect affecting the evolution of the atmospheric state. These interactions can also be a substantial source of numerical error in atmospheric general circulation models used in numerical weather prediction and...
