An Assessment of the impacts of selected Meteorological and Land Use Land Cover Datasets on the accuracy of wind speeds downscaled with the Weather Research and Forecasting Model for coastal areas in Ghana

Abstract

Downscaling of wind speeds with the Weather Research and Forecasting model (WRF) model requires inputs from datasets such as Meteorological and Land Use and Land Cover (LULC) datasets. The accuracy of these datasets is among the factors that significantly impact the accuracy of the wind speeds that are generated by the model. In this study, we assess the accuracy of wind speeds data that are downscaled for an area in coastal Ghana using six meteorological, and two global Land use and Land Cover (LULC) datasets as inputs to the WRF model. In contrast to the LULC datasets tested, model wind speeds for the area were more significantly impacted by the different meteorological datasets. Meteorological datasets that were produced with higher resolution forecasts combined with more advanced data assimilation techniques produced better estimates of wind speed, and vice versa. The JMA JRA55 Reanalysis, NCEP GFS Analysis data, and ECWMF ERA5 gave the relatively best combinations of wind speed error metrics and are therefore recommended for consideration for downscaling of wind speeds for wind resources assessment in the coastal regions of Ghana. However, the ECWMF ERA5 is preferred as its mean error margins are fairly constant and so should be easier to correct.

Keywords

• wrf
• wind resources assessment
• analysis and reanalysis datasets
• land use and land cover datasets
• wind energy