.. role:: cpp(code) :language: c++ .. _ERFvsWRF: ERF vs WRF =============== The following comparison is based on the WRF Version 4 Technical Report, titled "A Description of the Advancd Research WRF Model Version 4" Similarities -------------------- **Equations**: both ERF and WRF solve the fully-compressible, Eulerian nonhydrostatic equations, and conserve dry air mass and scalar mass. ERF does not have a hydrostatic option. **Prognostic Variables**: velocity components (u,v,w); perturbation moist potential temperature. Optionally, turbulent kinetic energy and any number of scalars such as water vapor mixing ratio, rain/snow mixing ratio, cloud water / ice mixing ratio. **Horizontal grid**: both ERF and WRF use Arakawa C-grid staggering. **Time Integration**: Time-split integration using 3rd-order Runge-Kutta scheme with smaller time step for acoustic and gravity wave modes. Variable time step capability. Vertically implicit acoustic step off-centering. **Spatial Discretization**: 2nd- to 6th-order advection options in horizontal and vertical. In addition, several different WENO schemes are available for scalar variables other than density and potential temperature. **Turbulent Mixing**: ERF and WRF have the same sub-grid scale turbulence closures with the Smagorinsky or 1.5-order TKE (Deardorff) model, in isotropic or anisotropic forms, for large-eddy simulation (LES); planetary boundary layer (PBL) schemes (MYNN, YSU) are available. ERF also has support for RANS turbulence modeling. **Diffusion**: In WRF and ERF, constant diffusion coefficients may be specified (:math:`K_h` and :math:`K_v` for horizontal and vertical diffusion). Constant dynamic viscosity may also be specified in ERF. Variable diffusivity is provided in 3-D through LES modeling and in 1-D through PBL modeling. For mesoscale applications, 3-D diffusion is provided by combining a PBL scheme with the Smagorinsky model. Prandtl and Schmidt numbers are used to derive diffusivities of heat or other scalars from the diffusivity of momentum. **Initial conditions**: both ERF and WRF have the ability to initialize problems from 3-D "real" data (output of real.exe), "ideal" data (output of ideal.exe), and from 1-D input soundings. **Lateral boundary conditions**: Periodic, open, symmetric and specified (in wrfbdy* files). **Bottom boundary conditions**: Frictional (Monin-Obukhov Similarity Theory) or free-slip **Earth's Rotation**: Coriolis terms in ERF controlled by run-time input flag (2-D or 3-D, constant or spatially varying for real-data cases) **Mapping to Sphere**: ERF supports the use of map scale factors for isotropic projections (read in from wrfinput files). **Nesting**: One-way or two-way. Multiple levels and integer ratios. **Wind Energy Modeling**: Wind farm parameterizations and a generalize actuator disk are available. Key Differences -------------------- ERF provides **performance portability** on different computing architectures **including GPUs from all major vendors** (NVIDIA, AMD, and Intel). **Vertical Coordinates**: Unlike WRF, ERF uses a height-based vertical coordinate, with vertical grid stretching permitted. **Governing Equations**: ERF supports both fully compressible and anelastic equation sets. **Time Integration**: ERF supports using a 3rd-order Runge-Kutta scheme with explicit acoustic substepping or no substepping (in addition to the implicit acoustic substepping in WRF). **Representation of Surface Features**: Terrain and urban geometries may be simulated with immersed forcing or embedded (immersed) boundary techniques, in addition to the terrain-fitted coordinates approach. **Interface with AMR-Wind**: ERF may be tightly coupled with AMR-Wind, an incompressible ABL solver with integrated turbine aeroservoelastic dynamics modeling and two-phase flow capabilities. **Particles**: ERF can be compiled with support for particles, for flow visualization or Lagrangian physics modeling. **User-Defined Functions**: ERF provides templates to customize initialization and/or impose spatiotemporally varying source terms. ERF does *not* have the capability for global simulation