标题:
甘肃河东地区一次倒槽作用下的致灾强降雪过程诊断分析Diagnosis Analysis of a Heavy Snow Caused by Inverted Trough in He-Dong of Gansu Province
作者:
夏权, 吴芳蓉, 马敏劲
关键字:
甘肃河东, 强降雪, 倒槽, 回流, 温度平流, 涡度平流He-Dong of Gansu Province, Heavy Snow, Inverted Trough, Returning Current, Temperature Advection, Vorticity Advection
期刊名称:
《Climate Change Research Letters》, Vol.4 No.2, 2015-03-27
摘要:
利用常规高空、地面观测资料及物理量场资料，对2014年2月15~17日甘肃河东地区大到暴雪天气过程进行诊断分析，结果表明：此次强降雪过程是地面倒槽、东风回流与高原东移短波槽共同作用下产生的，东风回流起到冷垫作用，使得短波槽前暖湿气流沿冷垫爬升为强降雪的产生提供了动力抬升条件。过程中热力不稳定条件较弱，但存在较强的动力不稳定，中层0~6 km风矢量差为21.0 m∙s−1左右。500 hPa高原短波槽前西南暖湿气流是本次强降雪过程的主要水汽来源，同时低层东风回流湿度较高，配合强水汽辐合中心，有利于水汽的垂直输送。500 hPa正涡度平流和强暖平流是导致低层辐合、高层辐散和垂直上升运动的最根本动力因子，并且促使了地面倒槽不断发展、辐合线加强。低层东风回流和中层槽前暖湿气流叠置的时间可以用来判断此类过程降雪发生的时段，与高空槽前西南暖湿气流相对应的水汽通量强度以及高空涡度平流和温度平流强度对过程降雪量级有很好的指示意义。By using the data of upper-air sounding and surface observations, an analysis was performed on heavy snow process taking place in He-Dong of Gansu province from 15 to 17 February, 2014. The results showed that this heavy snow process is a combined consequence of surface inverted trough, eastward returning current and Plateau short-wave trough; the eastward returning current provided a cooling cushion to southwest warm and wet current. In the snow process, the thermal instability condition was weaker, but there was strong dynamic instability, and the difference of wind vector in middle level was about 21.0 m∙s−1. The main water vapor source of this snow process was southwest warm and wet current in front of Plateau trough; meanwhile, in lower level there was a water vapor convergence center and the returning current was moist air, so it helped vertical transport of water vapor. The positive vorticity advection and strong warm advection of 500 hPa were the direct dynamic factors that led to convergence in low level, divergence in upper level and vertical ascending motion; these factors promoted surface inverted trough’s continuously development and convergence line was to strengthen. The superposed time of eastward returning current and southwest warm and wet current can be used to forecast the occurring time of this kind of snow process. There were three physics characteristics providing good indicators to snow magnitude: water vapor flux, vorticity advection and temperature advection of 500 hPa.