Evaluation of weather research and forecasting model for the assessment of wind resource over Gharo, Pakistan

Authors

  • Muhammad Amjad,

    Corresponding author
    1. Climatology Section, Global Change Impact Studies Centre (GCISC), National Centre for Physics (NCP), Islamabad, Pakistan
    • Correspondence to: M. Amjad, Climatology Section, Global Change Impact Studies Centre (GCISC), National Centre for Physics (NCP) Complex Near Quaid-i-Azam University, P.O. QAU—45320, Islamabad, Pakistan. E-mail: m.amjad@gcisc.org.pk; callamjad@gmail.com

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  • Qudsia Zafar,

    1. Climatology Section, Global Change Impact Studies Centre (GCISC), National Centre for Physics (NCP), Islamabad, Pakistan
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  • Firdos Khan,

    1. Climatology Section, Global Change Impact Studies Centre (GCISC), National Centre for Physics (NCP), Islamabad, Pakistan
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  • Muhammad Munir Sheikh

    1. Climatology Section, Global Change Impact Studies Centre (GCISC), National Centre for Physics (NCP), Islamabad, Pakistan
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ABSTRACT

Weather research and forecasting (WRF) model is the state-of-the-art mesoscale model that could be used as a guideline to effectively assess the wind resource of Gharo wind station lying in the coastal belt of Pakistan. The anemometer heights of 10 and 30 m for the year 2005 have been used to study the wind profile of the region for summer (June, July, August, September) and winter (December, January, February, March). The study uses an innovative approach for model comparisons, i.e. an eta-half level is added in the model on 60 m height and is interpolated to 30 m height by using well known power law. This is done by studying the diurnal variation of wind shear for the whole year of 2005 in order to reduce maximum possible interpolation error. For both seasons, the error measures of mean bias error (MBE), mean absolute error (MAE) and root mean square error (RMSE) of 30 m interpolated data were found lower than 10 m height data with increased correlation (r). A bias correction methodology (best easy systematic estimator) was further applied over the model output showing a significant improvement toward MBE, MAE and RMSE reduction, i.e. up to 99%, 73% and 68% on 10 m height and 99%, 51% and 46% on 30 m height. Errors were reduced more for summer than winter. The selected bias correction methodology was thus found to be highly applicable for both model heights. The wind energy assessment of Gharo wind station from the corrected model simulation showed summer having more potential for wind energy than winter with an estimated energy of up to 1000 MWh.

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