Clutter Elimination Algorithm for Non-Precipitation Echo of Radar Data Considering Meteorological and Observational Properties in Polarimetric Measurements

Abstract

Non-precipitation echoes due to ground and sea clutter, chaff, anomalous propagation, biological targets, and interference in weather radar observations are major issues causing a decline in the accuracy of meteorological and hydrological applications based on radar data. Statistically based quality control techniques using polarimetric variables have improved the accuracy of radar echo classification, however their performance is affected by attenuation, nonuniform beam filling, and hydrometeor diversity as well as terrain blockage, beam broadening, and noise correction issues due to the quality degradation of polarimetric measurements. To address this, a new quality control algorithm, named clutter elimination algorithm for non-precipitation echo of radar data (CLEANER), was designed by employing independent feature parameters and variable classification conditions with spatial and temporal observation environments to adapt to these meteorological artifacts and observational limitations. CLEANER was applied to several precipitation cases with various non-precipitation echoes, showing improved performance compared with results from the fuzzy logic-based quality control algorithm in terms of non-precipitation echo removal as well as in precipitation echo conservation. In addition, CLEANER shows better computational efficiency and robustness, as well as an excellent expandability for different radar networks.

Kinematic and Dynamic Structure of the 18 May 2020 Squall Line over South Korea

“…The horizontal and vertical resolution of the data are 500 m and 50 m, respectively. For further details on the locations, scanning strategies, and specifications of these radars, refer to [32,33]. The Wind Synthesis System Using Doppler Measurements (WISSDOM) is employed to represent the wind field component, and its application in the Korea region has been documented by [29].…”

The Use of Weather Radar Data: Possibilities, Challenges and Advanced Applications

“…The electromagnetic interference negatively affects the quantitative precipitation estimation and can lead to a biased hydrometeor classification [36]. Oh et al [37] proposed a clutter elimination algorithm for the non-precipitation echo of radar data, such as anomalous propagation and interference, biological target and sea clutter.…”