Development of Dual-Polarization Radar Algorithm for Melting Layer Signatures Detection in Northern Taiwan

A melting layer (ML) detection algorithm with polarimetric radar measurements was developed and applied to four years of S-band dual-polarization radar data. The algorithm takes advantage of the ML signatures of polarimetric radar measurements at high elevation angles (>6º), in particular, the cross-correlation coefficient (ρhv), differential reflectivity (Zdr), and reflectivity (Z). It uses radial profiles of ρ_hv, Zdr, and Z to determine the features of ML such as intensity, thickness, and the height of the peak (Hp) in the ML, top and bottom boundaries of the ML. This ML detection algorithm exhibits robust performance for different azimuth and elevation angles for the plan position indicator (PPI) scanning strategy. A case study of March 31, 2017 (10 to 22 UTC) is selected and tested in this study. The result shows that the Hp of all observed radar variables dropped slowly to about 2.5 km at 1830 UTC from about 4 km at 1000 UTC, which has good agreement with the method of Giangrande et al. (2008). Moreover, the thickness can be well detected and varies from a few hundred meters to about 1.5 km. Furthermore, the Hp of ML has a good agreement with the sounding data, lending further validity to this ML detection algorithm. This algorithm can provide the spatial features of the ML and also different azimuth and elevation angles, which can help to improve the quantitative precipitation estimation (QPE), hydrometeor classification algorithms, etc.

Keywords: melting layer; dual-polarized radar observations; height; thickness; intensity

6º), in particular, the cross-correlation coefficient (ρhv), differential reflectivity (Zdr), and reflectivity (Z). It uses radial profiles of ρ_hv, Zdr, and Z to determine the features of ML such as intensity, thickness, and the height of the peak (Hp) in the ML, top and bottom boundaries of the ML. This ML detection algorithm exhibits robust performance for different azimuth and elevation angles for the plan position indicator (PPI) scanning strategy. A case study of March 31, 2017 (10 to 22 UTC) is selected and tested in this study. The result shows that the Hp of all observed radar variables dropped slowly to about 2.5 km at 1830 UTC from about 4 km at 1000 UTC, which has good agreement with the method of Giangrande et al. (2008). Moreover, the thickness can be well detected and varies from a few hundred meters to about 1.5 km. Furthermore, the Hp of ML has a good agreement with the sounding data, lending further validity to this ML detection algorithm. This algorithm can provide the spatial features of the ML and also different azimuth and elevation angles, which can help to improve the quantitative precipitation estimation (QPE), hydrometeor classification algorithms, etc.\n\nKeywords: melting layer; dual-polarized radar observations; height; thickness; intensity\n"}" data-sheets-userformat="{"2":515,"3":{"1":0},"4":{"1":2,"2":14281427},"12":0}">