Sensitivity of Different Physical Schemes in WRF Model of a Rainfall Event in Baghdad Station
The Weather Research and Forecasting model (WRF) offers a number of physical options that let users modify it to different scales, regions, and applications. The aim of this study is to test the sensitivity of different physics schemes in the WRF model for rainfall events over Iraq. In this study,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | Arabic |
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Al-Mustansiriyah University
2023-12-01
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| Series: | Mustansiriyah Journal of Science |
| Subjects: | |
| Online Access: | https://mjs.uomustansiriyah.edu.iq/index.php/MJS/article/view/1414 |
| Summary: | The Weather Research and Forecasting model (WRF) offers a number of physical options that let users modify it to different scales, regions, and applications. The aim of this study is to test the sensitivity of different physics schemes in the WRF model for rainfall events over Iraq. In this study, six different physics configurations of the climate version of WRF were evaluated for simulation of a rainfall event in Iraq. Possible combinations among two Planetary Boundary Layers (PBL), three Cumulus (CUM) and two Microphysics (MIC) schemes were tested. The study area is the region surrounded by the longitudes 35o E-55o E and latitudes 290o N–38o N, which typically includes the Iraq region. The WRF model is installed on a Linux platform with a 10 km grid size in the zonal and meridional directions. For the six different simulations and the process of choosing the best performing configuration for the Iraq region, the model outputs tested for a single grid point (Baghdad station) of the atmospheric parameters (temperature, pressure and total precipitation) with modeled data and ECMWF. Model outputs using statistical methods: Bias Error (BE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results show All the simulations predict rainfall with values close to the actual but it was discovered that the cloud microphysics setup had the greatest impact on temperature biases, whereas the cumulus parameterization setup has the greatest impact on precipitation.
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| ISSN: | 1814-635X 2521-3520 |