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- W3034843478 abstract "A method was proposed for correcting the attenuation of C-band weather radar reflectivity data based on a 2-D video disdrometer. The relationship between the C-band weather radar reflectivity attenuation rate k and radar reflectivity factor Z was derived using radar meteorological equations. A video disdrometer was used to correct the deformation of large (1 to 9 mm) raindrops, and the coefficients a and b of the k − Z relationships for different precipitation types under Rayleigh scattering and Mie scattering conditions were inverted separately. Data from a weather detection instrument and rain gauge were combined with Newton’s iteration method for database-by-database accumulative corrections of the C-band radar reflectivity factor. Observed C-band weather radar data recorded in Xichang city and video disdrometer data from Xichang, Dechang, Mianning, and Xide counties during 2016 and 2017 were selected (all areas are in Liangshan Prefecture, Sichuan Province). The relationships between the raindrop size distribution and the radar reflectivity factor and attenuation rate in stratiform and convective cloud precipitation were analyzed, and the k − Z relationships under different precipitation types in Liangshan were presented. Additionally, radar reflectivity attenuation correction errors were analyzed using observed C-band weather radar data under strong convective storm precipitation. The proposed method achieves far smaller root mean square errors of the radar reflectivity factor than traditional attenuation correction methods in both the radial and the vertical directions. Overall, the proposed method has a better attenuation correction effect for C-band weather radar reflectivity data than traditional attenuation correction methods, which may enable the popularization and application of the proposed method elsewhere." @default.
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- W3034843478 date "2020-06-12" @default.
- W3034843478 modified "2023-09-24" @default.
- W3034843478 title "Improving C-band weather radar reflectivity attenuation based on two-dimensional video disdrometer data" @default.
- W3034843478 doi "https://doi.org/10.1117/1.jrs.14.024521" @default.
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