Rainfall prediction over Ambon Meteorological Station using Multi-Physics Ensemble WRF-ARW
| Autor: | A Khaerima, R Charolydya, F Alfahmi |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | IOP Conference Series: Earth and Environmental Science. 893:012026 |
| ISSN: | 1755-1315 1755-1307 |
| DOI: | 10.1088/1755-1315/893/1/012026 |
| Popis: | One of the methods to create good forecast using WRF-ARW modelling is tuning the parameterization. However, this method cannot provide rainfall event probability. Current research result revealed that it was able to simulate and forecast some weather parameters. However, based on the verification results, there were some weather parameters which still had low accuracy. Due to such low accuracy on some weather parameters, the authors were interested in performing post-processing methods in forecasting the weather during extreme weather at Pattimura Ambon Meteorological Station. In this study, we employed multi-physics ensemble prediction system (MEPS) by combining 20 WRF-ARW parameterization schemas, which were processed to obtain the ensemble mean, ensemble spread, and basic probability to get the uncertainty from each weather parameters. Verification process was done by using spreads, skill method and ROC curves. It was discovered that MEPS products have a better skill compared to the forecast control, the correlation value of MEPS products is larger and has the lowest error value. In addition, the result of ROC curves shows that the MEPS has an ability to predict weather condition during cloudy and extreme rain. |
| Databáze: | OpenAIRE |
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