基于WRF-EnKF系统的雷达反射率直接同化对台风“天鸽”（1713）预报的影响

利用基于中尺度数值模式WRF(Weather Research and Forecast)的集合卡尔曼滤波(EnKF，Ensemble Kalman Filter)同化系统直接同化广东地区雷达反射率资料，对2017年台风“天鸽”(1713，Hato)近海发展以及降水预报效果进行数值模拟分析研究。结果显示，直接同化雷达反射率资料后，台风的回波强度和范围有了明显改善，可更好地调整水汽场、水凝物和温度场。当台风风场和水汽场调整后，进入台风主体部分的水汽量显著增加，使得台风强度增强，台风中心最低海平面气压降低，与实况更接近。同化雷达反射率资料后，6 h和24 h降水强度和落区预报效果有显著改善，尤其是能提高大暴雨和特大暴雨量级的TS评分，此外地面2 m温度和2 m相对湿度的预报效果也有改进。 

THE IMPACT OF RADAR REFLECTIVITY ON NUMERICAL FORECAST OF TYPHOON HATO (1713) BASED ON WRF-ENKF SYSTEM

The Weather Research and Forecasting model (WRF) coupled with ensemble Kalman filter (EnKF) is used to directly assimilate radar reflectivity data of Guangdong province during the period of Tropical Cyclone Hato (1713). With assimilated radar reflectivity data, the simulated radar echo intensity and location are significantly improved, and the distributions of water vapor, hydrometeor and temperature are better modified. With adjusted wind and water vapor fields, the flux of water vapor flowing into the typhoon main body increases markedly. Ultimately, its intensity enhances and the minimum sea level pressure of typhoon center decreases, being closer to the observation. With directly assimilated radar data, the predictions of 6 h and 24 h accumulated precipitation amount and location are noticeably improved, especially the threat scores of rainstorm and severe rainstorm. Moreover, the predictions of 2 m temperature and relative humidity are also improved.