中文摘要：

2011年5月10-12日,广西出现了全区性的暴雨过程,暴雨区分布呈现3条“西南-东北”向的“强-弱-强”降雨带相间隔的特点,即桂西-桂东北强降雨带,桂西南-桂东北弱降雨带,桂东南-桂东强降雨带.文中利用卫星和自动站等非常规观测资料分析发现,造成这次强降雨过程特点的成因,主要是从云贵高原南移准静止锋,与从中南半岛北部向东北移的中尺度涡旋云系相互作用,触发形成中尺度对流系统而造成的,具有明显的中、低纬度天气系统相互作用特征.分析发现,强降雨过程可分为3个阶段：（1）5月10日20时-11日6时,南移准静止锋上发展成一个MCS,并移到桂西北造成了桂西北暴雨区,此后MCC减弱并沿副高脊北边的西南气流向东北移,对广西的影响过程基本结束；（2）5月11日下午,准静止锋西段南移到桂西北,中尺度涡旋云系移近桂西,两者相互作用在桂西触发形成中尺度对流系统,造成了桂西暴雨区；（3）5月12日中-下午,准静止锋桂东段南移,与继续东移的中尺度涡旋云系在桂东相遇,触发中尺度对流系统,造成了桂东南到桂东暴雨区.应用表明,在常规观测资料稀缺的高原和低纬地区,卫星资料在分析中尺度天气系统中可发挥重要作用.

英文摘要：

Based on the unconventional observation data from satellites and automatic weather stations of a regional rainstorm in Guangxi during 10-12th May, 2011, it is found that the cause of the rainstorm is the Middle -Low latitude weather systems, which was triggered by the interaction between Quasi- stationary front which moved southward from Yunnan-Guizhou Plateau and the Mesoscale-vortex cloud which moved northeastward from northern Indochina. The result shows that heavy rainfall can be divided into three stages： （1） from BT 20：00 May 10th to BT 6：00 May llth ,the southward Quasi-stationary front generates an MCS, and moving to northwestern Guangxi cause a rainstorm, and then the weakened MCC along the southwest airflow of north of subtropical ridge move to northeast, the impact to Guangxi basically end; （2） p.m. 1 lth May, the western Quasi-stationary front move southward to the northwestern Guangxi, Mesoscale-vortex cloud move closer to western Guangxi, the interaction between trigger the formation of MCS in western Guangxi, resulting rainstorm in western Guangxi; （3） 12th May noon to afternoon, the eastern Quasi-stationary front moved southward, encounter the Mesoscale-vortex clouds which continuously move eastward in eastern Guangxi, the interaction between trigger the formation of MCS, resulting rainstorm from southeastern Guangxi to eastern Guangxi. It shows that satellite data can play an important role in the analysis for mesoscale weather systems in the highlands and low latitudes area which lack of conventional observations data.