ARGYLE, P. and WATSON, S.J., 2016. Mesoscale Models as Alternatives to Meteorological Masts. Presented at the 2nd International Conference on Offshore Renewable Energy (CORE 2016), Glasgow, UK, 12-14th Sept.
This paper compares wind speed and direction output from the WRF mesoscale model with measurements taken on two offshore meteorological masts in the Irish Sea. The WRF model is run using both the reanalysis dataset ERA-Interim supplied by the European Centre for Medium-range Weather Forecasts (ECMWF) and the combined datasets MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications) and GLDAS (Global Land Data Assimilation System) both supplied by the Goddard Earth Sciences Data and Information Services Centre. It is found that using WRF with the ERA-Interim data returns reliable offshore wind resource statistics, both on an individual 10-minute timeframe and averaged across the 40 day validation period. The MERRA-2/GLDAS data however led WRF to significantly underestimate wind speeds and positively bias the wind direction from sectors with longer fetch. There was also evidence of the directional bias being smaller when using the ERA-Interim data for directions with smaller fetch. A good background knowledge is recommended when using WRF.