准线形对流系统中强度—速度负相关性的特征研究

Research of negative correlativity of reflectivity and radial velocity in quasi linear convective system

  • 摘要: 准线形对流系统,如飑线、弓形回波,是常见的强对流性系统,伴随它出现的一般是大风、旋风甚至冰雹等严重的灾害性天气现象。弓形回波有的是由一个单体产生的,也有嵌套在飑线或其他线形系统中,作为整个线形回波的一个部分。弓形回波能在很长的带上产生灾害性的直线风。Fujita给出了弓形回波演变的概念模型,并提出大风发生在弓形回波的顶部,他对弓形回波的描述对其后关于弓形回波的研究有重要的意义。Johns曾对发生在美国的70多个derecho(生命期较长和尺度较大的由对流引发的暴风)个例进行统计分析,得出一些适宜对derecho进行预报的参数,如500hPa气流方向、850hPa对流尺度、500hPa12小时最大变高、对流层中层风速等等,这些量测量大都比较复杂,并且很难通过一种观测手段测量出来。在我们的研究中发现,在准线形对流系统中,反射率因子(R)和径向速度(V)之间存在一定的负相关性,本文通过对发生在中国东部地区(经度范围116.01?E~119.52?E,纬度范围24.5?N~34.29?N)的16个个例进行统计分析,发现在这些系统中都存在这种R-V负相关的特征,负相关的程度随高度有规律性的变化。通过对2006年6月29日个例的风场分析证实这种特征确实存在。对流系统与雷达射线方向接近垂直时,R-V负相关特征明显,这是因为该方向上,观测到的径向速度近乎等于实际风速,数值最大;而因垂直运动造成的水平风速减小并不因探测位置的不同而有很大变化。通过本文的分析,推断R-V的这种负相关性与准线形系统中对流的强弱、中层径向辐合的强弱以及后向入流都有很大的关系。本文提出R-V的负相关特征,希望能有助于对准线形对流系统的结构分析和预报。

     

    Abstract: A dataset consisting of 16 quasi-linear convective system (QLCS) cases has been developed in east China(116.01?E-119.52?E, 24.5?N-34.29?N ). Statistical analyses of this dataset reveal that radar reflectivity and radial velocity presented a negative correlativity in the leading edge of QLCSs, and the degree of negative correlation changed regularly with heights. Analyses of a QLCS case in Nanjing on 29 June, 2006 show in detail the existence of the negative correlativity between reflectivity and radial velocity. When the QLCS was perpendicular to the radar radial, the degree of negative correlation was most distinct, because, the observed radial velocity in this circumstance approximately equals to the actual wind speed (i.e. maximum radial velocity), while the reduction in horizontal wind resulted from the vertical motion does not change with different detect directions. In this paper, we deduce that the negative correlativity of reflectivity-velocity is associated with convective intensity, mid-altitude radial convergence and rear-inflow jet. The negative correlativity between reflectivity and radial velocity presented here is hoped to be useful for the structure analysis, identification and prediction of QLCSs.

     

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