A Method for Assimilating the Raman Lidar Detecting Temperature in WRF on Simulating the Short-Time Heavy Rainfall
LI Bo1, 2, PU Ya-zhou1, WANG Nan3, WANG Yu-feng1, DI Hui-ge1, SONG Yue-hui1, HUA Deng-xin1*
1. School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China
2. Institute of Tropical and Marine Meteorology/Guangdong Provinical Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510080, China
3. The Meteorological Observatory of Shaanxi Province, Xi’an 710014, China
摘要： 为挖掘激光雷达高垂直分辨探测优势，将其引入降雨观测与研究中，重点构建一套测温数据模式同化方法，目的在于评估激光雷达数据对降雨模拟的影响。借助激光雷达测温数据综合多级质量控制技术对雨前探测信号进行反演优化，获取更可靠的温度廓线，这种垂直间隔4 m左右的雷达数据对于降雨是一种新型数据。设计三步实验研究新数据WRF模式（weather research and forecasting model）同化方法。第一步开展控制实验，通过模式检验与参数调试获取最佳模拟方案，为同化实验提供依据。第二步开展常规探测数据同化实验，通过WRF模式同化模块将90组地面、高空测站数据融入模式初始场，TS评分提高了0.07，并成功消除了陕西西南部虚假暴雨中心，但存在空报率偏高等问题。第三步开展激光雷达数据同化实验，重点解决制约模式初始场中尺度信息测站稀少的关键难题，引入MQ法将单点数据扩展为49组格点数据并完成三维变分同化模拟，克服了常规数据同化所致空报率偏高的问题，且模拟雨强更接近实况，同时降水TS评分提高了0.12，漏报率降低了0.09。定性与定量分析均表明借助Multiquadric将激光雷达探测数据融入WRF模式可造成模拟效果提升。本文结果表明激光雷达可用于探测短时强降雨，且探测位置宜设在对流云外围。
关键词：激光雷达测温；短时强降雨；Multiquadric算法
Abstract：In order to take full advantage of Raman lidar, a high-resolution detecting experiment was carried out at the periphery of the convective cloud, and a temperature with a vertical resolution of 4 m was inversed by using the synthetically multilevel quality analysis and control technique. Three groups of experiments were conducted, and a novel method for assimilating the lidar detecting temperature was especially proposed based on the coupling between the Multiquadric method and WRFDA (the Weather Research and Forecasting model Data Assimilation system). Firstly, a controlled experiment (CTRL) was carried out, and the suitable model parameters were obtained after debugging model. Secondly, based on the WRFDA module, the conventional observational data, including ground station and radiosonde station were integrated into the initial field. The results showed that TS increased by 0.07, and the dummy precipitation in southwest Shaanxi was successfully avoided. Thirdly, the Multiquadric method was used to assimilate Lidar data. TS increased by 0.12, and the Miss hit forecast rate was reduced by 0.09. When the lidar data was integrated into the WRF model, the positive simulation effects could be obtained according to quantitative and qualitative analysis. It was also discovered that the variation of simulation precipitation was because of the change of elements, including wind, water vapor, and temperature. Lidar could be well used to detect short-time heavy rainfall, according to this study.
Key words：The lidar detecting temperature; Short-time heavy rainfall; Multiquadric method
李 博，普亚洲，王 楠，王玉峰，狄慧鸽，宋跃辉，华灯鑫. 基于短时强降雨探测的拉曼激光雷达测温数据WRF同化方法[J]. 光谱学与光谱分析, 2021, 41(07): 2110-2115.
LI Bo, PU Ya-zhou, WANG Nan, WANG Yu-feng, DI Hui-ge, SONG Yue-hui, HUA Deng-xin. A Method for Assimilating the Raman Lidar Detecting Temperature in WRF on Simulating the Short-Time Heavy Rainfall. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(07): 2110-2115.
