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Improvement of Coding for Solar Radiation Forecasting in Dili Timor Leste—A WRF Case Study

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Document pages: 14 pages

Abstract: This paper investigates the accuracy of weather research and forecastingby improving coding for solar radiation forecasting for location in Dili TimorLeste. Weather Research and Forecasting (WRF) model version 3.9.1 is used inthis study for improvement purposes. The shortwave coding of WRF is used toimprove in order to decrease error simulation. The importance of improving WRFcoding at a specific region will reduce the bias and root mean square root whencomparing to the observed data. This study uses high resolution based on theWRF modeling to stabilize the performance of forecasting. The decrease in errorperformance will be expected to enhance the value of renewable energy. Theresults show the root mean square error of the WRF default is 233 W m2higher compared to 205 W m2 from the WRF improvementmodel. In addition, the Mean Bias Error (MBE) of the WRF default is obtainedvalue 0.06 higher than 0.03 from the WRF improvement in rainy days. Meanwhile,on sunny days, the performance Root Mean Square Error (RMSE) of WRF default is327 W m2 higher than 223 W m2from the WRF improvement. The MBE of WRF improvement obtained 0.13 lowercompared to 0.21 of WRF default coding. Finally, this study concludes thatimproving the shortwave code under the WRF model can decrease the errorperformance of the WRF simulation for local weather forecasting.

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