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Improved Algorithms for Removing Isolated Non-Meteorological Echoes and Ground Clutters in CINRAD.
- Source :
- Journal of Meteorological Research; Aug2018, Vol. 32 Issue 4, p584-597, 14p
- Publication Year :
- 2018
-
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 (P<subscript>o</subscript>) 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 P<subscript>o</subscript> ⩽ 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 [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20956037
- Volume :
- 32
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Journal of Meteorological Research
- Publication Type :
- Academic Journal
- Accession number :
- 131619359
- Full Text :
- https://doi.org/10.1007/s13351-018-7176-9