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Assessing and Improving the Local Added Value of WRF for Wind Downscaling

Journal: Journal of Applied Meteorology and Climatology
Year: 2015   Volume: 54
Initial page: 1556   Last page: 1568
Status: Published
In this status since: 21 Jul 2015
Link to PDF: http://journals.ametsoc.org/doi/abs/10.1175/JAMC-D-14-0150.1
DOI: 10.1175/JAMC-D-14-0150.1

Limited Area Models (LAMs) are widely used tools to downscale the wind speed forecasts issued by Global Circulation Models (GCMs). However, only a few studies have systematically analysed the value added by the LAMs to the coarser resolution model wind. The goal of the present work is to investigate how added value depends on the resolution of the global driving model. With this aim, the Weather Research and Forecasting (WRF) model was used to downscale three different global datasets (GFS, ERA-Interim and NCEP-NCAR) to a 9 km resolution grid for a 1-year period. Model results were compared with a large set of surface observations, including land station and offshore buoy data. Substantial biases were found at this resolution over mountainous terrain and a slight modification to the new subgrid orographic drag parameterization was introduced to alleviate the problem. We found that, at this resolution, WRF is able to produce significant added value with respect to NCEP-NCAR and ERA-Interim reanalyses, but only a small amount with respect to GFS forecasts. Results suggest that, above some resolutions, the value added by WRF to its driving GCM wind diminishes as model skill tends to saturate.