多普勒天气雷达资料同化对暴雨模拟的影响

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徐广阔, 孙建华, 雷霆, 赵思雄. 多普勒天气雷达资料同化对暴雨模拟的影响[J]. 应用气象学报, 2009, 20(1): 36-46. 复制到剪切板

Xu Guangkuo, Sun Jianhua, Lei Ting, Zhao Sixiong. Impacts of Chinese Doppler Radar on the Severe Heavy Rainfall Forecast During Meiyu Season[J]. Journal of Applied Meteorological Science, 2009, 20(1): 36-46 复制到剪切板

多普勒天气雷达资料同化对暴雨模拟的影响

徐广阔^1,2, 孙建华¹, 雷霆¹, 赵思雄¹

1. 中国科学院大气物理研究所, 北京 100029;
2. 中国科学院研究生院, 北京 100049

2008-01-24 收到, 2008-08-15 收到修改稿.

资助项目: 国家自然科学基金项目 (40620120437, 40405008) 和国家重点基础研究发展规划项目 (2004CB418301) 共同资助

摘要: 利用我国CINRAD/SA多普勒天气雷达资料与ARPS模式 (Advanced Regional Prediction System) 的资料分析系统ADAS (ARPS Data Analysis System), 对初始场进行调整, 并应用于WRF (Weather Research and Forecasting Model) 模式, 对2003年梅雨期淮河流域两次典型致洪暴雨过程进行模拟试验。对模拟结果的对比分析和检验结果表明:引入雷达资料后, 在雷达观测区的整层风场和水汽场都随之调整, 雷达径向风和反射率因子资料对初始场调整有不同影响, 径向风资料侧重于对风场的调整, 而反射率因子资料侧重于对温、湿量场的调整, 使降雨落区和强度预报都有所提高; 在ADAS系统中, 雷达径向风和反射率因子资料对初始场调整有不同影响, 径向风资料侧重于对风场的调整, 而反射率因子资料侧重于对温、湿量场的调整, 两个个例的试验表明, 加入雷达径向风资料的模拟试验能够得到较好评分, 加入雷达反射率因子资料或同时加入这两种雷达资料也能够在一定程度上提高模拟的准确性。

关键词: 中尺度模式复杂云分析多普勒天气雷达中尺度系统

Impacts of Chinese Doppler Radar on the Severe Heavy Rainfall Forecast During Meiyu Season

Xu Guangkuo^1,2, Sun Jianhua¹, Lei Ting¹, Zhao Sixiong¹

1. Institute of Atmosphere Physics, Chinese Academy of Science, Beijing 100029;
2. Graduate University of Chinese Academy of Science, Beijing 100049

Abstract: CINRAD/SA Doppler radar data and ARPS data analysis system (ADAS) are used to adjust the initial field, then the adjusted initial field is inputted into the mesoscale model WRF (The Weather Research and Forecasting Model) to simulate two rainstorm processes. The two rainstorm processes produce a flash flooding over Huaihe River Basin during Meiyu of 2003. According to the difference of initial data to be used in the numerical simulation, four experiments are designed and conducted in the study. The initial field obtained without use of radar data in control run (Exp CNTL), with use of radial velocity in Exp RADAR-V, with use of radar reflectivity in Exp RADAR-V, with both radar reflectivity and radial velocity in Exp RADAR-RV. The simulated outputs of these four experiments are compared and verified. The results show that after the adjustment of initial field using radar data through the ARPS complex cloud analysis scheme, both wind field and moisture field are adjusted at the region of radar observation, and the initial fields carries more information about moisture, cloud, latent heat, meso-scale circulation, and so on. At the same time, the simulation results also show that the spin-up time of meso-scale model is shortened and accuracy of rainstorm simulation is improved. Through the quantitative verification of the simulation results, both the ETS and the HSS of experiments simulating the radar data in initial fields are proved higher than those of experiments not simulating the radar data in initial fields, and the BS verification score for the former experiments is more closer to 1.Based on the comparing of the results of these four experiments, it can concluded that the impacts of Doppler radar data assimilation on initial field are different between Exp RADAR-V and RADAR-R. In ADAS system, radar radial velocity observations are used to adjust the wind field, but radar reflectivity observations are used to adjust the thermal and moisture fields. The significant differences exist between simulation results of four experiments. On the basis of the quantitative verification, the Exp RADAR-V, which uses radar radial velocity, gets the highest score and is able to simulate meso-scale convective system and its rainfall more accurately. However, it is noticed that the other experiment, such as Exp RADAR-R and Exp RADAR-RV, also can improve the accuracy of rainfall simulation at a certain extent, though not as good as the results of Exp RADAR-V. In addition, the improvements of precipitation prediction are notable in the first six-hour simulation.

Key words: meso-scale numerical model complex cloud analysis scheme Doppler radar meso-scale convective system

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图 1. 2003年6月29日00:00—30日00:00 24h累积降水量模拟结果检验 (a) ETS评分, (b) BS评分, (c) HSS评分 Fig 1. The verification of simulated precipitation during 00:00 29 Jun to 00:00 30Jun, 2003 (a) ETS, (b) BS, (c) HSS


图 2. 2008年7月4日12:00—18:00降水量模拟结果 (实线) 与实况 (阴影) (单位:mm) (a) 试验CNTL, (b) 试验RADAR-V, (c) 试验RADAR-R, (d) 试验RADAR-RV Fig 2. The simulated precipitation (solid line) and observation (shaded) during 12:00 to 18:00 on Jul4, 2003(unit:mm) (a) Exp CNTL, (b) Exp RADAR-V, (c) Exp RADAR-R, (d) Exp RADAR-RV


图 3. 2003年7月4日12:00—5日12:00 24h累积降水量模拟结果检验 (a) ETS评分, (b) BS评分, (c) HSS评分 Fig 3. The verification of simulated precipitation during 12:00 4 Jul to 12:00 5Jul, 2003 (a) ETS, (b) BS, (c) HSS


图 4. 个例一中加入雷达资料后初始场云水、雨水差异沿31.9°N的纬向-高度剖面图 (单位:g/kg) Fig 4. The cross-section along 31.9°N of the difference of cloud water, rain water between experiments which radar data is used and unused of Case one (unit:g/kg)


图 5. 个例二试验RADAR-V与试验CNTL的初始风场之差沿31.9°N的纬向-高度剖面图 (单位:m/s) Fig 5. The difference of initial wind between Exp RADAR-V and Exp CNTL along 31.9°N of Case two (unit:m/s)


图 6. 个例二不同高度上试验RADAR-V与试验CNTL初始风场差异 (单位:m/s) (a) 750m, (b) 3750m, (c) 5750m, (d) 9750m Fig 6. The difference of initial wind between Exp RADAR-V and Exp CNTL at different height of Case two (unit:m/s) (a) 750m, (b) 3750m, (c) 5750m, (d) 9750m


图 7. 2003年7月4日850hPa高度上试验RADAR-V与试验CNTL的环流差异 (矢量, 单位:m/s) 与试验RADAR-V逐小时降水量模拟 (阴影, 单位:mm) Fig 7. The difference of circulation at 850 hPa between Exp RADAR-V and Exp CNTL (vectors, unit:m/s) and hourly rainfall simulated by Exp RADAR-V (shaded, unit:mm) on 4 Jul 2003 of Case two