The WRF Simulation Influence of Assimilating GNSS Water Vapor and Parameterization Schemes on Typhoon Rumbia
The Weather Research and Forecasting (WRF) model was used to simulate Typhoon Rumbia in this paper. The sensitivity experiments were conducted with 16 different parameterization combination schemes, including four microphysics (WSM6, WSM5, Lin, and Thompson), two boundary layers (YSU and MYJ), and t...
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MDPI AG
2024-02-01
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| Online Access: | https://www.mdpi.com/2073-4433/15/3/255 |
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| author | Li Li Yixiang Ma Kai Li Jianping Pan Mingsong Zhang |
| author_facet | Li Li Yixiang Ma Kai Li Jianping Pan Mingsong Zhang |
| author_sort | Li Li |
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| description | The Weather Research and Forecasting (WRF) model was used to simulate Typhoon Rumbia in this paper. The sensitivity experiments were conducted with 16 different parameterization combination schemes, including four microphysics (WSM6, WSM5, Lin, and Thompson), two boundary layers (YSU and MYJ), and two cumulus convection (Kain–Fritsch and Grell–Freitas) schemes. The impacts of 16 parameterization combination schemes and the data assimilation (DA) of Global Navigation Satellite System (GNSS) water vapor were evaluated by the simulation accuracy of typhoon track and intensity. The results show that the typhoon track and intensity are significantly influenced by parameterization schemes of cumulus and boundary layers rather than microphysics. The averaged track error of Lin_KF_Y is 104.73 km in the entire 72-h simulation period. The track errors of all the other combination schemes are higher than Lin_KF_Y. During the entire 72-h, the averaged intensity error of Thompson_GF_M is 1.36 hPa. It is the lowest among all the combination schemes. As for data assimilation, the simulation accuracy of typhoon tracks can be significantly improved by adding the GNSS water vapor. Thompson_GF_M-DA combination scheme has the lowest average track error of 45.05 km in the initial 24 h. The Lin_KF_Y-DA combination scheme exhibits an average track error of 32.17 km on the second day, 28.03 km on the third day, and 35.33 km during 72-h. The study shows that the combination of parameterization schemes and the GNSS water vapor data assimilation significantly improve the initial conditions and the accuracy of typhoon predictions. The study results contribute to the selection of appropriate combinations of physical parameterization schemes for the WRF-ARW model in the mid-latitude region of the western Pacific coast. |
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| spelling | doaj.art-3ea3a636f1204fc1ad285d573a507ca32024-03-27T13:20:30ZengMDPI AGAtmosphere2073-44332024-02-0115325510.3390/atmos15030255The WRF Simulation Influence of Assimilating GNSS Water Vapor and Parameterization Schemes on Typhoon RumbiaLi Li0Yixiang Ma1Kai Li2Jianping Pan3Mingsong Zhang4Research Center of Beidou Navigation and Environmental Remote Sensing, Suzhou University of Science and Technology, Suzhou 215009, ChinaResearch Center of Beidou Navigation and Environmental Remote Sensing, Suzhou University of Science and Technology, Suzhou 215009, ChinaResearch Center of Beidou Navigation and Environmental Remote Sensing, Suzhou University of Science and Technology, Suzhou 215009, ChinaResearch Center of Beidou Navigation and Environmental Remote Sensing, Suzhou University of Science and Technology, Suzhou 215009, ChinaResearch Center of Beidou Navigation and Environmental Remote Sensing, Suzhou University of Science and Technology, Suzhou 215009, ChinaThe Weather Research and Forecasting (WRF) model was used to simulate Typhoon Rumbia in this paper. The sensitivity experiments were conducted with 16 different parameterization combination schemes, including four microphysics (WSM6, WSM5, Lin, and Thompson), two boundary layers (YSU and MYJ), and two cumulus convection (Kain–Fritsch and Grell–Freitas) schemes. The impacts of 16 parameterization combination schemes and the data assimilation (DA) of Global Navigation Satellite System (GNSS) water vapor were evaluated by the simulation accuracy of typhoon track and intensity. The results show that the typhoon track and intensity are significantly influenced by parameterization schemes of cumulus and boundary layers rather than microphysics. The averaged track error of Lin_KF_Y is 104.73 km in the entire 72-h simulation period. The track errors of all the other combination schemes are higher than Lin_KF_Y. During the entire 72-h, the averaged intensity error of Thompson_GF_M is 1.36 hPa. It is the lowest among all the combination schemes. As for data assimilation, the simulation accuracy of typhoon tracks can be significantly improved by adding the GNSS water vapor. Thompson_GF_M-DA combination scheme has the lowest average track error of 45.05 km in the initial 24 h. The Lin_KF_Y-DA combination scheme exhibits an average track error of 32.17 km on the second day, 28.03 km on the third day, and 35.33 km during 72-h. The study shows that the combination of parameterization schemes and the GNSS water vapor data assimilation significantly improve the initial conditions and the accuracy of typhoon predictions. The study results contribute to the selection of appropriate combinations of physical parameterization schemes for the WRF-ARW model in the mid-latitude region of the western Pacific coast.https://www.mdpi.com/2073-4433/15/3/255GNSSWRFtyphoonmicrophysicscumulus convectionboundary layer |
| spellingShingle | Li Li Yixiang Ma Kai Li Jianping Pan Mingsong Zhang The WRF Simulation Influence of Assimilating GNSS Water Vapor and Parameterization Schemes on Typhoon Rumbia Atmosphere GNSS WRF typhoon microphysics cumulus convection boundary layer |
| title | The WRF Simulation Influence of Assimilating GNSS Water Vapor and Parameterization Schemes on Typhoon Rumbia |
| title_full | The WRF Simulation Influence of Assimilating GNSS Water Vapor and Parameterization Schemes on Typhoon Rumbia |
| title_fullStr | The WRF Simulation Influence of Assimilating GNSS Water Vapor and Parameterization Schemes on Typhoon Rumbia |
| title_full_unstemmed | The WRF Simulation Influence of Assimilating GNSS Water Vapor and Parameterization Schemes on Typhoon Rumbia |
| title_short | The WRF Simulation Influence of Assimilating GNSS Water Vapor and Parameterization Schemes on Typhoon Rumbia |
| title_sort | wrf simulation influence of assimilating gnss water vapor and parameterization schemes on typhoon rumbia |
| topic | GNSS WRF typhoon microphysics cumulus convection boundary layer |
| url | https://www.mdpi.com/2073-4433/15/3/255 |
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