基于对流尺度集合预报的飑线结构特征模拟与改善
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摘要
对流尺度集合预报是研究飑线等强对流天气的新方向。当前对飑线系统结构的研究主要采用卫星和雷达资料结合高分辨率确定性预报的方法,而本文从集合预报技术的角度分析飑线结构特征。针对2014年7月30日中国江淮地区的一次强飑线过程,利用WRF模式开展了对流尺度集合预报试验,采用概率匹配平均法对集合预报结果进行综合处理,重点考察集合预报对飑线结构特征的模拟能力。结果表明:对流尺度集合预报能够模拟出飑线系统的基本结构特征。集合平均和概率匹配平均法相比控制预报而言,对飑线回波、热力场、动力场和微物理量场结构有明显的改善作用。同时模拟出了飑线系统近地面冷池和环境垂直风切变的相互作用,与RKW理论相一致。概率匹配平均法在回波强度上较集合平均更接近实况,应用于对流尺度集合预报研究极端天气事件具有指示意义。
The convection-allowing ensemble forecast is a new direction for studying strong convective weather,such as squall lines. The current research on the structural characteristics of squall systems is mainly based on the high-resolution deterministic forecast combined with the satellite and radar data. In this paper,the structure of the squall line was analyzed from the perspective of ensemble forecast technology. A convection-allowing ensemble forecast experiment based on the Weather Research and Forecasting(WRF) model was conducted for a strong squall line in eastern China on July 30,2014. The probability matched mean(PMM) method was used to analyze synthetically the modelling results and verify the ability to simulate structural characteristics of the squall line. The results indicated that the convection-allowing ensemble forecast is able to simulate the basic structural characteristics of the squall line system. Compared with control prediction,the ensemble mean(EM) and PMM methods can improve significantly the structure of echo,a thermal field,dynamic field and microphysical field for the squall line. The modelling results also reflect the interaction between the near-surface cold pool and the vertical wind shear in the squall line system,which is consistent with the RKW theory. The echo intensity obtained from the PMM method is more close to the observations than that by the EM method,which means that it has a guiding significance to use the PMM method to study extreme weather events in the convection-allowing ensemble forecast.
The convection-allowing ensemble forecast is a new direction for studying strong convective weather,such as squall lines. The current research on the structural characteristics of squall systems is mainly based on the high-resolution deterministic forecast combined with the satellite and radar data. In this paper,the structure of the squall line was analyzed from the perspective of ensemble forecast technology. A convection-allowing ensemble forecast experiment based on the Weather Research and Forecasting(WRF) model was conducted for a strong squall line in eastern China on July 30,2014. The probability matched mean(PMM) method was used to analyze synthetically the modelling results and verify the ability to simulate structural characteristics of the squall line. The results indicated that the convection-allowing ensemble forecast is able to simulate the basic structural characteristics of the squall line system. Compared with control prediction,the ensemble mean(EM) and PMM methods can improve significantly the structure of echo,a thermal field,dynamic field and microphysical field for the squall line. The modelling results also reflect the interaction between the near-surface cold pool and the vertical wind shear in the squall line system,which is consistent with the RKW theory. The echo intensity obtained from the PMM method is more close to the observations than that by the EM method,which means that it has a guiding significance to use the PMM method to study extreme weather events in the convection-allowing ensemble forecast.
引文
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[23]Berenguer M,Surcel M,Zawadzki I,et al.The diurnal cycle of precipitation from continental radar mosaics and numerical weather prediction models.Part Ⅱ:Intercomparison among Numerical Models and with Nowcasting[J].Monthly Weather Review,2012,140(8):2689-2705.
[24]徐姝,尉英华,熊明明,等.频率匹配法在海河流域ECMWF集合预报融合产品中的应用研究[J].气象与环境学报,2018,34(4):11-17.
[25]李娜,冉令坤,高守亭.华东地区一次飑线过程的数值模拟与诊断分析[J].大气科学,2013,37(3):595-608.
[26]Ebert E E.Ability of a poor man's ensemble to predict the probability and distribution of precipitation[J].Monthly Weather Review,2001,129(10):2461-2480.
[2]丁一汇,李鸿洲,章名立,等.我国飑线发生条件的研究[J].大气科学,1982,6(1):18-27.
[3]Rotunno R,Klemp J B,Weisman M L.A Theory for Strong,Long-Lived Squall Lines[J].Journal of the Atmospheric Science,1988,45(3):463-485.
[4]Weisman M L,Klemp J B,Rotunno R.Structure and evolution of numerically simulated squall lines[J].Journal of the Atmospheric Science,1988,45(14):1990-2013.
[5]Weisman M L.The genesis of severe,long-lived bow echoes[J].Journal of the Atmospheric Science,1993,50(4):645-645.
[6]陈明轩,王迎春.低层垂直风切变和冷池相互作用影响华北地区一次飑线过程发展维持的数值模拟[J].气象学报,2012,70(3):371-386.
[7]刘香娥,郭学良.灾害性大风发生机理与飑线结构特征的个例分析模拟研究[J].大气科学,2012,36(6):1150-1164.
[8]缪子青,何宏让,白仕刚,等.2014年3月广东一次飑线过程观测及数值模拟分析[J].气象与减灾研究,2014,37(4):7-17.
[9]缪子青,何宏让,张云,等.一次飑线过程雷达回波特征及环境条件分析[J].气象科学,2016,36(1):71-79.
[10]高士博,闵锦忠,黄丹莲.EnSRF雷达资料同化在一次飑线过程中的应用研究[J].大气科学,2016,40(6):1127-1142.
[11]张涵斌,智协飞,陈静,等.区域集合预报扰动方法研究进展综述[J].大气科学学报,2017,40(2):145-157.
[12]陈宇,王小桃,王瀛,等.基于中尺度集合预报的“8.16”抚顺地区特大暴雨过程分析[J].气象与环境学报,2015,31(6):01-08.
[13]王太微,陈德辉,吴曼丽.GRAPES-EPS系统的初值生成方法与对比试验研究[J].气象与环境学报,2014,30(2):23-30.
[14]王太微,王勇,陈德辉,等.基于聚类分析法区域集合预报模式的初边值试验研究[J].气象与环境学报,2015,31(6):18-26.
[15]王孝慈,李双君,闵锦忠.SLAF方法的改进及其对广东地区一次飑线过程集合预报研究[J].气象与环境学报,2015,31(5):31-38.
[16]高峰,闵锦忠,孔凡铀.基于增长模繁殖法的风暴尺度集合预报试验[J].高原气象,2010,29(2):429-436.
[17]庄潇然,闵锦忠,王世璋,等.风暴尺度集合预报中的混合初始扰动方法及其北京2012年“7.21”暴雨预报中的应用[J].大气科学,2017,41(1):30-42.
[18]蔡沅辰,闵锦忠,庄潇然.不同随机物理扰动方案在一次暴雨集合预报中的对比研究[J].高原气象,2017,36(2):407-423.
[19]Schwartz C S,Romine G S,Smith K R,et al.Characterizing and optimizing precipitation forecasts from a convectionpermitting ensemble initialized by a mesoscale ensemble kalman filter[J].Weather and Forecasting,2014,29(6):1295-1318.
[20]Schwartz C S,Romine G S,Sobash R A,et al.NCAR's experimental real-time convection-allowing ensemble prediction system[J].Weather and Forecasting,2015,30(5):1645-1654.
[21]Clark A J,Gallus W,Xue M,et al.A comparison of precipitation forecast skill between small convection-allowing and large convection-parameterizing ensembles[J].Weather and Forecasting,2009,24(4):1121-1140.
[22]Kong F,Droegemeier K K,Hickmon N L.Multiresolution ensemble forecasts of an observed tornadic thunderstorm system.Part I:Comparsion of coarse-and fine-grid experiments[J].Monthly Weather Review,2006,134(3):807-833.
[23]Berenguer M,Surcel M,Zawadzki I,et al.The diurnal cycle of precipitation from continental radar mosaics and numerical weather prediction models.Part Ⅱ:Intercomparison among Numerical Models and with Nowcasting[J].Monthly Weather Review,2012,140(8):2689-2705.
[24]徐姝,尉英华,熊明明,等.频率匹配法在海河流域ECMWF集合预报融合产品中的应用研究[J].气象与环境学报,2018,34(4):11-17.
[25]李娜,冉令坤,高守亭.华东地区一次飑线过程的数值模拟与诊断分析[J].大气科学,2013,37(3):595-608.
[26]Ebert E E.Ability of a poor man's ensemble to predict the probability and distribution of precipitation[J].Monthly Weather Review,2001,129(10):2461-2480.