The performance of the weather research & forecasting model (WRF) using ensemble method to predict weather parameters
The performance of the WRF model is evaluated using different physical options for the Riau Province. There are 12 members, and the ensemble mean method is used to evaluate the temperature, humidity, wind direction, and wind speed. The primary purpose of this study is to determine the appropriate pa...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/04/e3sconf_icdm2024_04002.pdf |
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| Summary: | The performance of the WRF model is evaluated using different physical options for the Riau Province. There are 12 members, and the ensemble mean method is used to evaluate the temperature, humidity, wind direction, and wind speed. The primary purpose of this study is to determine the appropriate parameterization for the study area. In this study, two nested domains have been used for performance analysis, with the resolution of the coarser domain set at 9 km and the inner domain set at 3 km. The model was run for five days in 2019 during a forest fire episode in Riau Province. The analysis was carried out by looking at the values of the correlation coefficient, root mean square error (RMSE), and bias. From the weather forecast, WRF, with the sixth parameterization member, produces a better value than the others. RRTM and Dudhia parameterization gave better results for temperature parameters. Meanwhile, the parameterization of Yonsei University (YSU) produces better results for the parameters of wind direction and wind speed. |
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| ISSN: | 2267-1242 |