| Assimilation of Polarimetric Radar Data Using an Ensemble Kalman Filter for the Analysis and Forecast of Tropical Storm Ewiniar |
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| 作者姓名： | 黎慧琦 刘显通 肖辉 万齐林 |
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| 摘 要： | This study explores the potential for directly assimilating polarimetric radar data (including reflectivity Z and differential reflectivity ZDR) using an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting
(WRF) model to improve analysis and forecast of Tropical Storm Ewiniar (2018). Ewiniar weakened but brought about heavy rainfall over Guangdong, China after its final landfall. Two experiments are performed, one assimilating only Z
and the other assimilating both Z and ZDR. Assimilation of ZDR together with Z effectively modifies hydrometeor fields, and improves the intensity, shape and position of rainbands. Forecast of 24-hour extraordinary rainfall ≥250 mm is
significantly improved. Improvement can also be seen in the wind fields because of cross-variable covariance. The current study shows the possibility of applying polarimetric radar data to improve forecasting of tropical cyclones, which
deserves more researches in the future.
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| 关 键 词： | data assimilation polarimetric radar EnKF tropical cyclone heavy rainfall |
| 收稿时间： | 2021-01-15 |
Assimilation of Polarimetric Radar Data Using an Ensemble Kalman Filter for the Analysis and Forecast of Tropical Storm Ewiniar |
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| LI Hui-qi,LIU Xian-tong,XIAO Hui and WAN Qi-lin.Assimilation of Polarimetric Radar Data Using an Ensemble Kalman Filter for the Analysis and Forecast of Tropical Storm Ewiniar[J].Journal of Tropical Meteorology,2021,27(2):94-108. |
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| Authors: | LI Hui-qi LIU Xian-tong XIAO Hui and WAN Qi-lin |
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| Institution: | 1. Guangzhou Institute of Tropical and Marine Meteorology, China Meteorological Administration,Guangzhou 510640 China; 2. State Key Laboratory of Severe Weather, Chinese Academy ofMeteorological Sciences, Beijing 100081 China |
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| Abstract: | This study explores the potential for directly assimilating polarimetric radar data (including reflectivity Z and differential reflectivity ZDR) using an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting model to improve analysis and forecast of Tropical Storm Ewiniar (2018). Ewiniar weakened but brought about heavy rainfall over Guangdong, China after its final landfall. In the present study, two experiments are performed, one assimilating only Z and the other assimilating both Z and ZDR. Assimilation of ZDR together with Z effectively modifies hydrometeor fields, and improves the forecast of the intensity, shape and position of rainbands. Forecast of 24-hour extraordinary rainfall ≥250 mm is significantly improved. Improvement can also be seen in the wind fields because of cross-variable covariance. The current study shows the possibility of applying polarimetric radar data to improve forecasting of tropical cyclones, which deserves more research in the future. |
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| Keywords: | data assimilation polarimetric radar EnKF tropical cyclone heavy rainfall |
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