Articles | Volume 18, issue 3
https://doi.org/10.5194/amt-18-793-2025
https://doi.org/10.5194/amt-18-793-2025
Research article
 | 
13 Feb 2025
Research article |  | 13 Feb 2025

Benchmarking KDP in rainfall: a quantitative assessment of estimation algorithms using C-band weather radar observations

Miguel Aldana, Seppo Pulkkinen, Annakaisa von Lerber, Matthew R. Kumjian, and Dmitri Moisseev

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Cited articles

Al-Sakka, H., Boumahmoud, A.-A., Fradon, B., Frasier, S. J., and Tabary, P.: A New Fuzzy Logic Hydrometeor Classification Scheme Applied to the French X-, C-, and S-Band Polarimetric Radars, J. Appl. Meteorol. Clim., 52, 2328–2344, https://doi.org/10.1175/JAMC-D-12-0236.1, 2013. a
Aldana, M.: Datasets used in the manuscript “Benchmarking KDP in Rainfall: A Quantitative Assessment of Estimation Algorithms Using C-band Weather Radar Observations” by Aldana et al, submitted to AMT, Copernicus, Finnish Meteorological Institute [data set], https://doi.org/10.57707/fmi-b2share.4126c5db27d24ddeae10d5c3163ff95a, 2024. a, b
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Short summary
Accurate KDP estimates are crucial in radar-based applications. We quantify the uncertainties of several publicly available KDP estimation methods for multiple rainfall intensities. We use C-band weather radar observations and employed a self-consistency KDP, estimated from reflectivity and differential reflectivity, as a framework for the examination. Our study provides guidance for the performance, uncertainties, and optimisation of the methods, focusing mainly on accuracy and robustness.
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