Automatic radial velocity dealiasing algorithm for S-band Doppler weather radar

Radial velocity ambiguity limits the application of radar velocity data. To address the issues of the ambiguity of isolated echo or echo isolated by distance ambiguity and clutter interference as well as the problem in traditional method that takes radial straight line as initial reference in velocity dealiasing algorithm, a new automated Doppler radar velocity dealiasing algorithm is proposed. (1) Two zero velocity curves are obtained by finding the zero velocity junction point to roughly partition positive and negative velocity regions. After the positive and negative zoning, the clutter interference area and non clutter interference area are identified. For the clutter interference area, whether it meets multiple conditions with ambiguity characteristics is determined point by point. For the non clutter interference area, the ambiguity boundary is determined to delineate the ambiguity area block for dealiasing, which is conducted at the remaining points. (2) If the zero velocity curves cannot be determined, either the zero velocity curves information recorded in the upper layer is used or the qualified radial linear zero velocity line is searched. (3) If the zero speed line still cannot be determined, whether it meets multiple conditions with ambiguity characteristics will then be determined point by point. The algorithm is verified by using 3407 velocity ambiguity volume scan data of 11 cases such as squall lines, hails and strong typhoons observed by S-band radar, and the overall accuracy is higher than 98%. Using the zero velocity curves to determine the positive and negative zones, identifying the ambiguity area blocks and considering the extended neighborhood search in point by point judgment are conducive to the dealiasing processing of isolated echoes and echoes isolated by distance ambiguity. This method is more effective than the operational method. For the hail case that occurred on 4 March 2018, the accuracy is 10% higher than that by the operational method. Using the method of determining whether it meets multiple ambiguity feature conditions point by point for the clutter interference area, the ambiguity points can be successfully removed without being affected by the clutter. Comprehensive consideration of the upper zero velocity line and relevant information in the image that is helpful to determine the zero velocity curves and strict examination and test can ensure the accuracy of the zero velocity curve, which is conducive to the successful processing of velocity dealiasing.