Mesoscale and Doppler Radar Observation Analyses on a Severe Convective Weather Process in Middle Shaanxi Province in September 2010
Using the mesoscale weather chart analysis technique and Doppler radar observation data, the mesoscale features of severe convective weather process in middle Shaanxi Province on 1 September 2010 are analyzed. The obtained results are as follows: (1) The synoptic-scale analysis can't well confirm the potential conditions of severe convective weather under the influence of weak synoptic-scale weather system. (2) The mesoscale and comprehensive analysis of radiosonde data can clearly reflect temperature advection, dry line, moisture tongue, significantly streamline, which is an effective means of analysis of severe convective weather. (3)The surface and dew point temperature at 08:00 can well indicate potential conditions of severe convective weather trigger in Loess Plateau in the north of Shaanxi, while the position of surface cold front and intersection region of clod and warm air or wet and dry air can be well shown by analyzing 14:00 surface data, which can help to determine the exact region of severe convective trigger. (4) Dry line and terrain have significant effects on convective cloud initiation, which mainly lies near underlying. Although more convection cloud triggered in southwestern Shaanxi, but cloud top height is lower than other region, so it has little possibility that lightning, hailstorm and thunderstorm are triggered. (5) The formated radar echo in the process of convection cloud developing plays an important role in severe weather warning. There is 'V - shaped gap, echo fornix and overshooting cloud top in process of the hail cloud development, and the central horizontal displacement between the middle level strong echo and the low level one is more than 1 km. The 45 dBz strong echo extended height in the storm is over 7. 0 km. All of these metrics above are good indications of the severe convective weather warning.
Severe convective weatherHailstormMesoscale composite chartRadar observation
NETL
NSTL
万方数据
维普
