Abstract
The velocity ambiguity in Doppler weather radars has inhibited the application of wind field data for long time. One effective solution is software-based velocity dealiasing algorithm. In this paper, in order to better design, optimize and validate velocity dealiasing algorithms for CINRAD-SA, data from operational radars were used to statistically characterize velocity ambiguity. The analyzed characteristic parameters included occurrence rate, and inter-station, inter-type, temporal, and spatial distributions. The results show that 14.9% of cloud-rain files and 0.3% of clear-air files from CINRADSA radars are ambiguous. It is also found that echoes of weak convections have the highest occurrence rate of velocity ambiguity than any other cloud types, and the probability of ambiguity is higher in winter than in summer. A detailed inspection of the occurrence of ambiguity in various cases indicates that ambiguous points usually occur in areas with an elevation angle of 6.0°, an azimuth of 70° or 250°, radial distance of 50–60 km, and height of 5–6 km, and that 99.4% of ambiguous points are in the 1st-folding interval. Suggestions for performing dealiasing at different locations and different time points are provided.
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