Recent Advances in Three-Dimensional PBL Parameterization to Improve Wind Forecasting over Complex Terrain

Numerical weather predictions (NWP) models are being run at sub-kilometer horizontal grid spacing. The increase in horizontal grid spacing allows for a better representation of topography in complex terrain regions. However, NWP models use planetary boundary layer (PBL) parameterizations that only account for one-dimensional (1D) mixing resulting from vertical gradients in turbulent fluxes. This is a convenient assumption for grid spacing of several kilometers. However, assuming horizontally homogeneous turbulence motions no longer holds at sub-kilometer grid spacing limiting the benefit of fine grid spacing over complex terrain regions. Hence, to improve the wind forecasting over complex terrain we propose to account for both vertical and horizontal gradients in turbulent fluxes in our three-dimensional (3D) PBL parameterization.

The 3D PBL parameterization is based on the turbulence model developed by Mellor and Yamada (1982). Our implementation in the Weather Research and Forecasting (WRF) model uses a pure algebraic model (level 2) to diagnose the turbulent fluxes. The 3D PBL parameterization is being tested over the Columbia River Gorge wherein the wind forecast improvement project 2 (WFIP2) field campaign took place. This presentation will emphasize the benefit of the 3D PBL parameterization in an idealized case. The case has a horizontal heterogeneity in the surface heat flux and initial meridional winds. Under this set up, the solution is homogeneous in the along-wind direction. The evaluation focuses on the performance of the 3D PBL scheme and a standard 1D PBL parameterization, using 200 m of horizontal grid spacing, to reproduce LES results and the theoretical solution. It will be shown that accounting for horizontal gradients in our 3D PBL parameterization is necessary to ensure the homogeneous solution in the along-wind direction.