| EnSRF雷达资料同化对一次强对流天气模拟的影响研究 |
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| 引用本文： | 黄丹莲,高士博,闵锦忠.EnSRF雷达资料同化对一次强对流天气模拟的影响研究[J].气象科学,2017,37(5):567-578. |
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| 作者姓名： | 黄丹莲 高士博 闵锦忠 |
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| 作者单位： | 南京信息工程大学 气象灾害预报预警与评估协同创新中心, 南京 210044;南京信息工程大学 气象灾害教育部重点实验室, 南京 210044,南京信息工程大学 气象灾害预报预警与评估协同创新中心, 南京 210044;南京信息工程大学 气象灾害教育部重点实验室, 南京 210044,南京信息工程大学 气象灾害预报预警与评估协同创新中心, 南京 210044;南京信息工程大学 气象灾害教育部重点实验室, 南京 210044 |
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| 基金项目： | 国家重点基础研究发展计划（973计划）项目（2013CB43013）；江苏省普通高校研究生科研创新计划项目（KYLX_0844）；江苏省普通高校研究生科研创新计划项目（KYLX_0829） |
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| 摘 要： | 利用ARPS(Advanced Regional Prediction System)模式和具有流依赖背景误差协方差的集合均方根滤波(Ensemble Square Root Filter,简称En SRF)方法,通过同化多部多普勒雷达资料,对2013年6月23日的强对流天气过程进行了研究。首先对比同化试验和观测的组合反射率因子,检验了同化效果。通过计算均方根误差和离散度,进一步定量评估了同化结果。再对比模式变量,综合分析了En SRF雷达资料同化对模式热力、动力、湿度和微物理量等变量的影响。最后对集合平均场进行1 km的高分辨率数值模拟。结果表明:En SRF能够同化出与观测类似的对流系统,且减弱了南北部的虚假回波。径向风和反射率因子的均方根误差明显减少。En SRF雷达同化能够明显优化模式的初始场,同化试验的回波在垂直方向上范围增加,强度偏弱。在强对流区域,低层的冷池温度最多降低6 K,相对湿度最多增加30%。对流区域的雨水、冰晶和雪的混合比均有明显增加。模拟发现同化试验能够较好地模拟出对流系统的结构和位置。
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| 关 键 词： | 强对流 组合反射率因子 集合均方根滤波 雷达资料同化 |
| 收稿时间： | 2016/8/29 0:00:00 |
| 修稿时间： | 2016/10/8 0:00:00 |
Impact of EnSRF radar data assimilation on the simulation of a severe convection |
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| HUANG Danlian,GAO Shibo and MIN Jinzhong.Impact of EnSRF radar data assimilation on the simulation of a severe convection[J].Scientia Meteorologica Sinica,2017,37(5):567-578. |
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| Authors: | HUANG Danlian GAO Shibo and MIN Jinzhong |
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| Institution: | Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science & Technology, Nanjing 210044, China,Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science & Technology, Nanjing 210044, China and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science & Technology, Nanjing 210044, China |
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| Abstract: | By using the Advanced Regional Prediction System (ARPS) and Ensemble Square Root Filter (EnSRF) method with flow dependent background error covariance, through assimilating multiple Doppler radar data, the strong convective weather occurred on June 23, 2013 was analyzed. Firstly, the composite radar reflectivity in assimilation tests and observation were compared to verify assimilation effects, moreover, by calculating the Root Mean Square Error (RMSE) and spread, the assimilation results were further evaluated quantitatively. Secondly, the impacts of EnSRF radar assimilation on thermal, dynamical, humidity and microphysical variables were investigated. Finally, the ensemble mean was simulated at a high resolution of 1 km. Results show that EnSRF can assimilate convective system similar to the observations and suppress the false echo. The RMSE of radial velocity and reflectivity reduce significantly. The assimilation experiment has larger range of radar reflectivity in vertical direction and has weaker intensity than that of the control experiment. In the convective region, the strength of surface perturbation potential temperature can decrease by 6 K and the relative humidity can increase by 30%. The rain, ice and snow mixing ratios increase significantly in the convective area. The simulation with the final analysis results can better simulate the severe storm. |
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| Keywords: | Convection Composite radar reflectivity EnSRF Radar data assimilation |
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