Abstract
The accurate estimation of wind speed is crucial for wind energy production, given the exponential relationship between wind and power. However, this is a challenging task due to the stochastic nature of meteorology. In this study, the Weather Research and Forecasting Model (WRF) with a 9 km spatial resolution was used to simulate hourly wind speed values for Türkiye, using Global Data Assimilation System (GDAS) 0.25° boundary data. Several statistical metrics, including Root Mean Squared Error (RMSE), Mean Bias Error (MB), Index of Agreement (IoA), and Pearson correlation, were used to evaluate the performance of the WRF model. The WRF model, which used CONUS parametrization and was supplied with GDAS boundary data every 6 h, operated for 17,520 h in a 1-month consecutive run. The ANN model, which has Hecht-Nielsen (2n + 1) topology, was used to perform hindcasting of the WRF model. The input layer of the ANN model used temperature, pressure, and wind speed values obtained from WRF. The analysis was done spatio-temporally for 2 years and presented with seasonal and annual performance values. After applying the ANN model to the WRF model, which had initial values of MB of 1.42, RMSE of 2.26, R of 0.51, and IOA value of 0.02, the new MB, RMSE, R, and IOA values were found to be 0.04, 0.96, 0.56, and 0.60, respectively. Therefore, it can be concluded that the ANN model improved the WRF model's wind speed prediction performance in Türkiye by 11% on average, relatively.
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Data availability
The WRF model boundary data that support the findings of this study are openly available in https://rda.ucar.edu/datasets/ds083.3/ at https://doi.org/10.5065/D65Q4T4Z. Also, Restrictions can be applied to the availability of Wind measurement data, which were used under license for this study. Data are available with the permission of Turkish State Meteorological Service (TSMS).
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Funding
The authors are thankful to The Scientific and Technological Research Council of Turkey (TUBITAK) for their support and funding in the preparation of this study as the output of the project 1919B012100610. In addition, the authors are thankful to ITU Atmospheric Modelling Team for the WRF model infrastructure.
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All authors contributed to the study conception and design. Design of WRF and ANN model, data analysis and visualizations were performed by Yiğitalp KARA and Ilgar AKALIN. The first draft of the manuscript was written by Nursima Gamze DENİZ. Material preparation, data collection completed by Zeynep Feriha ÜNAL and Umur DİNÇ. Paper re-view performed by Hüseyin TOROS. Last, all authors read and approved the final manuscript.
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Kara, Y., Akalin, I.A., Deniz, N.G. et al. Utilizing ANN for improving the WRF wind forecasts in Türkiye. Earth Sci Inform 16, 2167–2186 (2023). https://doi.org/10.1007/s12145-023-01003-w
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DOI: https://doi.org/10.1007/s12145-023-01003-w