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The ability of a fuzzy logic classifier to dynamically identifynon-meteorological radar echoes is demonstrated using data from the NationalCentre for Atmospheric Science dual polarisation, Doppler, X-band mobileradar. Dynamic filtering of radar echoes is required due to the variablepresence of spurious targets, which can include insects, ground clutter andbackground noise. The fuzzy logic classifier described here uses novelmulti-vertex membership functions which allow a range of distributions to beincorporated into the final decision. These membership functions are derivedusing empirical observations, from a subset of the available radar data. Theclassifier incorporates a threshold of certainty (25 % of the totalpossible membership score) into the final fractional defuzzification toimprove the reliability of the results. It is shown that the addition oflinear texture fields, specifically the texture of the cross-correlationcoefficient, differential phase shift and differential reflectivity, to theclassifier along with standard dual polarisation radar moments enhances theability of the fuzzy classifier to identify multiple features. Examples fromthe Convective Precipitation Experiment (COPE) show the ability of the filterto identify insects (18 August 2013) and ground clutter in the presence ofprecipitation (17 August 2013). Medium-duration rainfall accumulations acrossthe whole of the COPE campaign show the benefit of applying the filter priorto making quantitative precipitation estimates. A second deployment ata second field site (Burn Airfield, 6 October 2014) shows the applicabilityof the method to multiple locations, with small echo features, includingpower lines and cooling towers, being successfully identified by theclassifier without modification of the membership functions from the previousdeployment. The fuzzy logic filter described can also be run in near realtime, with a delay of less than 1 min, allowing its use on future fieldcampaigns

Fuzzy logic filtering of radar reflectivity to remove non-meteorological echoes using dual polarization radar moments