The accuracy of wind forecasts in numerical weather prediction (NWP) models is improved when the drag forces imparted on atmospheric flow by subgrid-scale orography are included. Without such parameterizations, only the terrain resolved by the model grid, along with the small-scale obstacles parameterized by the roughness lengths can have an effect on the flow. This neglects the impacts of subgrid-scale terrain variations, which typically leads to wind speeds that are too strong. Using statistical information about the subgrid-scale orography, such as the mean and variance of the topographic height within a grid cell, the drag forces due to flow blocking, gravity wave drag, and turbulent form drag are estimated and distributed vertically throughout the grid cell column. We recently implemented the small-scale gravity wave drag paramterization of Steeneveld et al. (2008) and Tsiringakis et al. (2017) for stable planetary boundary layers, and the turbulent form drag parameterization of Beljaars et al. (2004) in the High-Resolution Rapid Refresh (HRRR) NWP model developed at the National Oceanic and Atmospheric Administration (NOAA). As a result, a high surface wind speed bias in the model has been reduced and small improvement to the maintenance of stable layers has also been found. We present the results of experiments with the subgrid-scale orographic drag parameterization for the regional HRRR model, as well as for a global model in development at NOAA, showing the direct and indirect impacts.
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