Impact of WRF Model Parameterization Settings on the Quality of Short-Term Weather Forecasts over Poland
This research examines the impact of various parameterization settings within the Weather Research and Forecasting (WRF) model on the accuracy of short-term weather forecasts for Poland. The study focuses on the sensitivity of key meteorological variables—namely, air temperature, wind speed, relativ...
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MDPI AG
2024-11-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/15/12/1425 |
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| author | Sebastian Kendzierski |
| author_facet | Sebastian Kendzierski |
| author_sort | Sebastian Kendzierski |
| collection | DOAJ |
| description | This research examines the impact of various parameterization settings within the Weather Research and Forecasting (WRF) model on the accuracy of short-term weather forecasts for Poland. The study focuses on the sensitivity of key meteorological variables—namely, air temperature, wind speed, relative humidity, and atmospheric pressure—to different combinations of physical parameterization schemes. Utilizing data from the Global Forecast System (GFS) spanning 2019 to 2022, a series of model simulations were conducted with support from the Poznań Supercomputing and Networking Center (PCSS). To assess the model’s performance across different weather stations, statistical metrics such as the mean absolute error (MAE) and root mean square error (RMSE) were employed. The findings indicate that the configuration labeled “p2” produced the most accurate forecasts for temperature, wind speed, and atmospheric pressure, achieving MAE values of 1.5 °C, 1.6 m/s, and 2 hPa, respectively. However, forecast inaccuracies were notably higher in mountainous regions, particularly regarding wind speed. These results underscore the importance of selecting appropriate parameterization settings tailored to regional characteristics, as different configurations can significantly impact the forecast accuracy, especially in complex terrains. This study contributes to the understanding of short-term weather forecasting models for Central Europe, offering potential pathways for improving localized forecast accuracy. |
| format | Article |
| id | doaj-art-7edb437a1b6741e094e9a1ae2a9b188d |
| institution | Kabale University |
| issn | 2073-4433 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-7edb437a1b6741e094e9a1ae2a9b188d2024-12-27T14:09:43ZengMDPI AGAtmosphere2073-44332024-11-011512142510.3390/atmos15121425Impact of WRF Model Parameterization Settings on the Quality of Short-Term Weather Forecasts over PolandSebastian Kendzierski0Department of Meteorology and Climatology, Adam Mickiewicz University, 61-608 Poznań, PolandThis research examines the impact of various parameterization settings within the Weather Research and Forecasting (WRF) model on the accuracy of short-term weather forecasts for Poland. The study focuses on the sensitivity of key meteorological variables—namely, air temperature, wind speed, relative humidity, and atmospheric pressure—to different combinations of physical parameterization schemes. Utilizing data from the Global Forecast System (GFS) spanning 2019 to 2022, a series of model simulations were conducted with support from the Poznań Supercomputing and Networking Center (PCSS). To assess the model’s performance across different weather stations, statistical metrics such as the mean absolute error (MAE) and root mean square error (RMSE) were employed. The findings indicate that the configuration labeled “p2” produced the most accurate forecasts for temperature, wind speed, and atmospheric pressure, achieving MAE values of 1.5 °C, 1.6 m/s, and 2 hPa, respectively. However, forecast inaccuracies were notably higher in mountainous regions, particularly regarding wind speed. These results underscore the importance of selecting appropriate parameterization settings tailored to regional characteristics, as different configurations can significantly impact the forecast accuracy, especially in complex terrains. This study contributes to the understanding of short-term weather forecasting models for Central Europe, offering potential pathways for improving localized forecast accuracy.https://www.mdpi.com/2073-4433/15/12/1425model parameterizationnumerical weather predictionWRF model |
| spellingShingle | Sebastian Kendzierski Impact of WRF Model Parameterization Settings on the Quality of Short-Term Weather Forecasts over Poland Atmosphere model parameterization numerical weather prediction WRF model |
| title | Impact of WRF Model Parameterization Settings on the Quality of Short-Term Weather Forecasts over Poland |
| title_full | Impact of WRF Model Parameterization Settings on the Quality of Short-Term Weather Forecasts over Poland |
| title_fullStr | Impact of WRF Model Parameterization Settings on the Quality of Short-Term Weather Forecasts over Poland |
| title_full_unstemmed | Impact of WRF Model Parameterization Settings on the Quality of Short-Term Weather Forecasts over Poland |
| title_short | Impact of WRF Model Parameterization Settings on the Quality of Short-Term Weather Forecasts over Poland |
| title_sort | impact of wrf model parameterization settings on the quality of short term weather forecasts over poland |
| topic | model parameterization numerical weather prediction WRF model |
| url | https://www.mdpi.com/2073-4433/15/12/1425 |
| work_keys_str_mv | AT sebastiankendzierski impactofwrfmodelparameterizationsettingsonthequalityofshorttermweatherforecastsoverpoland |