Evaluation of wind resource and mapping during 2009–2018 based on ERA5 reanalysis data: a case study over Algeria

Abstract

Abstract Wind data for large areas and long time periods are for great interest in the field of wind resource assessment, mainly in regions with lack of measurement data. In the present study, the latest high-resolution ERA5 global reanalysis products of the European center for medium weather forecast is investigated for the first time over Algeria. The main goal is to assess its accuracy to reproduce wind field space-time features, as well as establishing wind maps at multi-temporal scales over the whole Algerian territory. 3-hourly wind field components at 10 m above ground level (AGL) derived from ERA5 reanalysis were extracted and analyzed for a study period of ten years (2009–2018). The extracted ERA5 wind fields were compared at daily basis against selected ground measurements data made over three selected potential locations of significant wind resource potential, namely Adrar, In-Salah and Hassi-R’mel. Comparison was conducted in terms of statistical metrics: mean bias error, root mean square error, standard deviation error and correlation coefficient (R). In addition, wind rose diagrams and Weibull probability density functions were also evaluated. The study reveals a good agreement between ERA5 reanalysis and measurement data in reproducing the wind regime for all timescales, despite a slight underestimation of the observed wind speed. Also, analysis of wind field maps at 10 m AGL shows a significant improvement of wind speed assessment along the coastal regions in comparison with earlier study using ERA-interim data. Furthermore, the area with high and permanent wind resource throughout the year was identified in central Sahara geographically bounded by coordinates (26 ∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document} N, 1 ∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document} E, 29 ∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document} N, 5 ∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document} E) and characterized by an average wind speed reaching 5.5m/s\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$5.5\,\mathrm{m}/\mathrm{s}$$\end{document} at 10 m AGL. Extrapolated wind at 50 m and 80 m follows the same pattern, with a mean annual wind speed reaching 7m/s\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$7\,\mathrm{m}/\mathrm{s}$$\end{document} and 8m/s\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$8\,\mathrm{m}/\mathrm{s}$$\end{document} , respectively, over central Sahara.