Sensitivity Analysis of Sampling Number on Quality of Polarmetric Measurements from S-band Dual-Polarization Radar
Abstract
The data quality of dual-polarimetric weather radar is subject to radar scanning strategies such as pulse length, pulse repetition frequency (PRF), antenna scan speed, and sampling number. In terms of sampling number, the quality of radar moment data increases with the increasing of sampling number at the given PRF and pulse length while the feasible number of elevation angles decreases for the given time or the time required for radar volume scan increases with the relatively high sampling number. For operational weather radar, the sampling number is subjectively determined by the proficient radar operator. The determination of suitable sampling number is still challengeable for operational dual-polarimetric weather radar.In this study, we analyzed the sensitivity of polarimetric measurements to sampling number based on special radar experiment for rainfall and snowfall events using S-band dual-polarimetric radar (YIT) at Yong-In test bed. For this experiment, YIT radar transmitted a simultaneously polarized beam in horizontal and vertical with pulse length of 1.0 μs and single PRF of 600Hz. The beam width and gate size were 1.0° and 250m, respectively. The volume scan was composed of three PPI scans with three sampling numbers (antenna scan speed) of 40 (15°s-1), 60(10°s-1), and 85(7°s-1) at same elevation angle (=0.2°). We first investigated the spatial fluctuation of the polarimetric measurements according to three sampling numbers using radial texture. As the sampling number increases, the radial fluctuations of polarimetric measurements decrease. Second, we also examined the sensitivity to fuzzy logic based quality control algorithm for dual-polarimetric radar (Ye et al. 2015). The probability density functions (PDFs) of fuzzy logic feature parameters between ground clutter and meteorological echo area were compared. For overlapping area in both PDFs between ground clutter and meteorological echo increases with decreasing the sampling number. As the overlapping area increases, the classification of ground clutter (or meteorological echo) in fuzzy logic classifier is more difficult due to similar characteristics between ground clutter and meteorological echoes.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.A11H0113K
- Keywords:
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- 1816 Estimation and forecasting;
- HYDROLOGYDE: 4303 Hydrological;
- NATURAL HAZARDSDE: 6952 Radar atmospheric physics;
- RADIO SCIENCEDE: 6969 Remote sensing;
- RADIO SCIENCE