动力因子对2006“碧利斯”台风暴雨的诊断分析

本文利用2006年登陆台风"碧利斯"暴雨过程高分辨率数值模拟资料, 结合湿热力平流参数、广义对流涡度矢量垂直分量、水汽螺旋度、热力螺旋度、散度垂直通量、热力散度垂直通量、热力切变平流参数和 Q *矢量散度等8个动力因子, 对"碧利斯"台风暴雨进行诊断分析。结果指出:(1)8个动力因子在"碧利斯"台风强降水区均表现为强信号, 其中, 水汽螺旋度、热力螺旋度、散度垂直通量、热力散度垂直通量等动力因子与降水强度的相关系数均达0.99以上, 与总云水物质的相关系数也均达0.97以上, 而热力切变平流参数与上述二者的相关系数最低, 达0.5左右;(2)8个动力因子中, Q *矢量散度随降水强度先增大后减小, 与"霰融化成雨水造成雨水增长"微物理过程随降水强度的变化相似, 热力切变平流参数随降水强度呈现"增大—减小—再增大"的变化特征, 而其他6个动力因子均呈现单调增长趋势, 与"雨水碰并云水造成雨水增长"微物理过程随降水强度的变化相类似;(3)总体看来, 水汽螺旋度、热力螺旋度、散度垂直通量、热力散度垂直通量4个动力因子与降水强度及雨水收支相关的总的云微物理过程转化率对应更好, 因此, 对降水的指示意义也更好。

Diagnosis of Dynamical Parameters in Torrential Rain Associatedwith Typhoon "Bilis" in 2006

High-resolution numerical simulation data of typhoon Bilis in 2006 was used for diagnostic analysis of eight dynamical parameters in a torrential rain event associated with Bilis. The eight parameters are moist thermodynamic advection parameter (G), the vertical component of the generalized convective vorticity vector (CVZ*), moisture helicity (H_m), thermal helicity (H_t), divergence vertical flux (Γ), thermal divergence vertical flux (Γ_t), thermodynamic shear advection parameter (J), and generalized Q -vector divergence (Q*_d). The results show that the following. (1) All eight dynamical parameters show strong signals in torrential rainfall regions. The correlation coefficients of the rain rate and H_m, H_t, Γ, Γ_t are all larger than 0.99, while the correlation coefficients of the total cloud hydrometeors and the four parameters above are all larger than 0.97. The correlation coefficients between J and rain rate, and J and total hydrometeors are both about 0.5, which is the lowest. (2) Q*_d first increases and then decreases with an increase in rainfall intensity, sharing the same variation as the melting of graupel. J shows an increasing-decreasing-increasing pattern, while the other six parameters always increase with an increase in rainfall intensity, sharing the same variation pattern as the accretion of cloud water by rain water. (3) Overall, H_m, H_t, Γ and Γ_t correspond better with the rain rate and total cloud-microphysical processes associated with rain water. Thus, they are more indicative of strong precipitation.