摘要
利用多种气象观测资料和高分辨率的数值模拟结果,对2020年5月11日华南地区一次飑线的初生、增强、成熟和衰亡等4个阶段的对流组织特征和模态的演变及机理进行了分析.结果表明:该飑线发生于高空急流入口右侧的高空辐散区,伴随着南支槽的加深东移,低层暖湿平流以及地面的中尺度辐合线为其提供了有利的水汽、热力和抬升触发条件.初始阶段,飑线呈断线型发展,在较大的环境热力条件下具有中到强的对流有效位能和最大的对流抑制.成熟期形成拖尾层状云型飑线,低层风切变和冷池强度逐渐达到平衡状态.在衰亡阶段,飑线的组织模态发生转变,其中环境热力条件是后向新生型对流单体发生的主要原因,且低层不同的水汽和风切变条件也对模态的变异存在一定作用.在华南地区,以断线型模态生成拖尾层状云型模态的飑线所需的对流有效位能更高,且飑线的维持也需要更强的热力条件.对流有效位能、对流抑制能量、粗理查森数、风暴相对螺旋度等在对流单体形成的种类和组织模态方面均有一定的指示意义.
Abstract
Based on meteorological observation data and high-resolution numerical simulation results,the evolution and mechanism of convective organization and modes in a squall line over South China on May 11,2020,were analyzed in four stages:nascent stage,enhanced stage,mature stage,and decay stage.The results show that the squall line occurred in the strong divergence zone of the upper jet stream.With the deepening and eastward moving of the south branch of the trough,the warm and wet advection in the low layer and mesoscale convergence line on the ground provided favorable conditions of water vapor,heat,and uplift triggering.In the nascent stage,the squall developed in a manner of Bro-ken Lines with medium to strong convective available potential energy and maximum convective inhibi-tion,in the environment of the maximum thermal condition.In the mature stage,a trailing stratiform squall was formed,and the low-level wind shear and cold pool intensity gradually reached a balanced state.During the decay stage,the phase mode of the squall line changed,mainly affected by the thermal condition caused Back Building mode convective cells,and also by different water vapor and wind shear conditions in the lower layer.In South China,it requires high convective effective potential energy to generate a squall line of stratiform cloud mode with trailing tail strong thermal conditions to maintain the squall line.The convective available potential energy,convective inhibition,Bulk Richardson num-ber,and storm-relative helicity can indicate the type and structure mode of convective monomer forma-tion.
国家科技期刊平台
NSTL
维普
万方数据