Abstract
Using China New Generation Weather Radar (CINRAD) level-II data, the original algorithms for removing isolated non-meteorological echoes and ground clutters in radar data, which have been applied to Weather Surveillance Radar-1988 Doppler (WSR-88D) in the USA and Severe Weather Automatic Nowcast (SWAN) system in China, are modified and improved. To remove isolated non-meteorological echoes, the new algorithm introduces a constraint parameter (Po) to distinguish whether a window of 5 × 5 points is isolated as external echoes. A statistical analysis of 150 radar scans (5 cases, with each case comprising 30 scans) under three different echo types (small-scale convection, typhoon, and large-scale synoptic system) shows that the constraint parameter Po ⩽ 0.167 is suitable for removing isolated non-meteorological echoes while preserving the edge of meteorological echoes. A new parameter, NDZ, which promotes the ability of the algorithm to identify the ground clutters appearing at two adjacent elevation angles, is constructed based on the vertical continuity of reflectivity. These improved algorithms are tested for four cases (three cases of isolated non-meteorological echoes and one case of ground clutters). Based on the statistics of 232 volume scans of radar data (on a temporal resolution of 1 h) measured at Nanchang station from 0000 UTC 5 to 1600 UTC 14 March 2015, it is found that the improved algorithms not only eliminate most (over 95% under clear-sky conditions) of the isolated non-meteorological echoes and ground clutters (including those appearing at two adjacent elevation angles), but also well preserve the structure of meteorological echoes (storms). Key words: radar, isolated non-meteorological echoes, ground clutter, quality control
Highlights
Doppler weather radar data have high temporal and spatial resolutions and have been widely applied in operational forecasts and research on mesoscale weather phenomena (Anagnostou and Krajewski, 1999; Alfieri et al, 2010; Pan et al, 2010; Qin et al, 2014; Liu et al, 2016), presenting significant advantages compared with other observational data (Serafin and Wilson, 2000; Zheng et al, 2004; Xiao et al, 2008)
The present study proposes improvements to two algorithms commonly used for removing isolated non-meteorological echoes and ground clutters from single-polarization, level-II radar data
In view of the shortcomings of the original methods, which can remove the edges of meteorological echoes but cannot identify ground clutters appearing at two adjacent elevation angles, the current algorithms offer improvements in these respects
Summary
Doppler weather radar data have high temporal and spatial resolutions and have been widely applied in operational forecasts and research on mesoscale weather phenomena (Anagnostou and Krajewski, 1999; Alfieri et al, 2010; Pan et al, 2010; Qin et al, 2014; Liu et al, 2016), presenting significant advantages compared with other observational data (Serafin and Wilson, 2000; Zheng et al, 2004; Xiao et al, 2008). Our main goal here is to improve these algorithms such that they can remove isolated non-meteorological echoes whilst preserving the edges of meteorological echoes, as well as identify ground clutters (especially those appearing at two adjacent tilts) on the overall azimuth–range plane.
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