Characteristics of Doppler Radar Radial Velocity Images for Heavy Rainfall Events in Xining
Article
Figures
Metrics
Preview PDF
Reference
Related
Cited by
Materials
Abstract:
The characteristics of heavy rainfall events on the Doppler weather radar velocity images and their early warning indicators in Xining from 2010 to 2016 are analyzed. The results show that the adverse wind region (AWR) on radial velocity images often occurs in the case of heavy rainfall events in Xining. TypeⅠAWR is slightly more for the mixed heavy rainfall and typeⅡAWR is mostly for the convective heavy rainfall during the directly affected heavy rainfall events. The AWR moves mostly northeastward in general. The occurring times of the AWR have certain lead times before the beginning of heavy rainfall events, and heavy rainfall falls near the AWR and its moving path, that is, the AWR is not only a timebased criterion for issuing early warnings of heavy precipitation but also a useful criterion for identifying falling areas of heavy rainfall. When the shear flow field in the AWR is convergent (divergent), it will enhance (weaken) the development of heavy rainfall, and the time of the convergence (divergence) is ahead of schedule the beginning (end) of heavy rainfall. At the time 1 h before the beginning of heavy rainfall, the vertical wind shear is the largest in low level and the smallest in middle level of the mixed heavy rainfall. However, it is obviously large in all the levels during convective heavy rainfall. The changes in wind direction mainly show deep and warm advection for the mixed heavy rainfall, while they are not obvious or there is warm advection in the low and middle levels for the convective heavy rainfall. The maximum echo heights and zero speed layers are higher for the convective heavy rainfall than for the mixed heavy rainfall, but there are smaller differences on the whole for the convective heavy rainfall. The indicators for early warning of heavy rainfall by comprehensive application of the radial velocity are obtained, and the accuracy rate reaches 78.6%.