Downscaling the North American Regional Reanalysis Wind Dataset

At present, numerical weather prediction (NWP) models are commonly used for wind resource estimations. These prognostic models utilize long-term (on the order of several decades), coarse-resolution (on the order of a few tens of kilometers) climate datasets as input and dynamically downscale the atmospheric fields to resolutions of a few kilometers. However, this type of dynamic downscaling approach is computationally very expensive for sub-kilometer scales. Furthermore, for physical reasons, at sub-kilometer scales, one needs to invoke complex three-dimensional subgrid-scale closures; traditional planetary boundary layer schemes do not suffice. In this presentation, we explore an alternative downscaling approach involving a diagnostic model (based on linearized steady-state Navier-Stokes equations), known as the Wind Atlas Analysis and Application Program (WAsP). The North American Regional Reanalysis (NARR) wind dataset is used as input. We evaluate the downscaled wind fields against tall-tower observations and prognostic model-generated data.