A nonlocal three‐dimensional turbulence parameterization (NLT3D) for numerical weather prediction models

Abstract

AbstractWith increasing resolution of numerical weather prediction (NWP) models, classical subgrid‐scale processes become increasingly resolved on the model grid. In particular, turbulence in the planetary boundary layer (PBL) is vertically already partially resolved in contemporary models. For classical local PBL schemes, resulting up‐gradient heat transports cannot be treated correctly. Thus, nonlocal turbulence schemes have been developed in the past. As the horizontal grid sizes of NWP models become smaller than a few kilometers, the large turbulence eddies in the PBL will also start to become partially resolved in the horizontal direction. A very flexible way to formulate nonlocal turbulent exchange is the transilient matrix method, which is used here to develop a new turbulence parameterization. The resulting NLT scheme applies transilient mixing matrices to subgrid‐scale transports in all three dimensions. We compare results of WRF real‐case simulations including our scheme, a classical local turbulence scheme (MYNN), and an existing nonlocal one‐dimensional scheme (ACM2) with observations from field campaigns over homogeneous terrain (CASES‐99) and complex terrain (CAPTEX). Over homogeneous terrain, all three schemes similarly well capture the observed surface fluxes and radiosonde profiles, whereas over complex terrain more differences become obvious. During a tracer release experiment (CAPTEX) over the Appalachian mountain region, the mixing and vertical extent of the PBL turn out to be decisive to reproduce the observed advection speed of the tracer‐marked air mass. Deeper mixing not only accelerates surface winds but also enables tracer to travel faster at higher altitudes and then mix back to the ground. As results from a version of NLT with only standard horizontal Smagorinsky diffusion (NLT) demonstrate, simulating three‐dimensional turbulence can be beneficial already at horizontal grid sizes of a few kilometers.