对流涡度矢量和湿涡度矢量在暴雨诊断分析中的应用研究

Application of convective and moist vorticity vectors in the analysis of a heavy rainfall event

利用对流涡度矢量(CVV,(ζa×θe)/ρ)和湿涡度矢量(MVV,(ζa×qv)/ρ)对华北地区一次大范围的大到暴雨天气过程进行了诊断研究。结果表明,CVV和MVV垂直分量与云和降水密切相关,暴雨区区域平均和垂直积分的CVV和MVV垂直分量与云中水凝物混合比的相关系数分别为0.92和0.95,与降水率的相关系数分别为0.71和0.47。云中水凝物分为液态水凝物和固态水凝物,虽然固态水凝物的含量相对较少,但它在云的变化中起着更重要的作用。滞后相关分析表明,降水率的峰值到来之前4—5 h云中水凝物含量最少,降水率的峰值到来之后1—2 h,云中水凝物含量最多。云中水凝物与降水率的滞后相关系数主要是由液态水凝物与降水率的滞后相关系数决定的,只有约1/4的滞后相关系数是由固态水凝物与降水率的滞后相关系数贡献的。CVV和MVV的垂直分量与云中水凝物具有非常好的相关性(同时及滞后),与降水率的相关也较好,可以代表云和对流系统的发展。CVV和MVV垂直分量的局地变化超前降水率3 h左右,可以作为降水发生的先兆,对降水的预报有潜在的意义。CVV垂直分量的局地变化与降水率的相关系数大于MVV垂直分量的局地变化与降水率的相关系数,因此在实际预报中可以利用CVV垂直分量的局地变化来估计未来降水的变化。

Convective vorticity vector （CVV,（ξa×△θe）/ρ） and moist vorticity vector （MVV,ξa×△qv）/ρ） introduced by Gao et al. in 2004, 2005, and 2007 are used to study a heavy rainfall event in North China. The result shows that vertical components of the CVV and the MVV are closely associated with clouds and precipitation. Analysis of domain-averaged and mass-integrated quantities shows that the linear correlation coefficients between the vertical component of the CVV （MVV） and the sum of mixing ratio of cloud hydrometeors is 0.92 （0.95）, and that between the vertical component of the CVV （MVV） and precipitation rate is 0.71 （0.47）. Cloud hydrometeors can be further broken into ice hydrometeor and water hydrometeors. Although ice hydrometeors are little, they contribute more to the evolution of clouds. Analysis of lag correlation suggests that minimum cloud hydrometeor leads the maximum precipitation rate by 4 - 5 h, and maximum cloud hydrometeor lags maximum precipitation rate by 1 2 h. The lag correlation coefficient between cloud hydrometeors and precipitation rate is mainly determined by the weighted lag correlation coefficient between water hydrometeors and surface rain rate, only one fourth of the lag correlation coefficient is contributed to the weighted lag correlation coefficients between ice hydrometeors and surface rain rate. Vertical components of CVV and MVV are well correlated with cloud hydrometeors （in phase or lag correlation） and precipitation rate, and they may represent the development of clouds and convective system. The local changes of Cz and Mz lead surface rain rate by 3 h, which may be a precursor for rainfall and has potential significance for rainfall prediction. The linear correlation coefficient between the local change of Cz and surface rain rate is larger than that between the local change of Mz and surface rain rate. Therefore, the local change of Cz can be used to estimate the change of surface rain rate in operational forecast.