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https://doi.org/10.5194/egusphere-2023-2220
https://doi.org/10.5194/egusphere-2023-2220
13 Nov 2023
 | 13 Nov 2023

Drop Size Distribution Retrieval Using Dual Frequency Polarimetric Weather Radars

Daniel Durbin, Yadong Wang, and Pao-Liang Chang

Abstract. Having knowledge of the drop size distribution (DSD) is of particular interest to researchers as it is widely applied to quantitative precipitation estimation (QPE) methods. Polarimetric radar measurements have previously been utilized to derive DSD curve characteristics frequently modeled as a gamma distribution. Likewise, approaches using dual frequency measurements have shown positive results. Both cases have relied on the need to constrain the relationship between the DSD parameters based on prior knowledge or assumptions of the collected data. This paper presents a methodology for retrieving the DSD parameters using the dual frequency and polarimetric nature of measurements from a unique data set taken at co-located S-band and C-band dual polarization radars. Using the reflectivity and differential phase measurements from each radar, an optimization routine employing particle swarm optimization (PSO) and T-Matrix computation of radar parameters is able to accurately retrieve the gamma distribution parameters without the constraints required in previous methods. Retrieved results are compared to known truth data collected using a network of OTT PARSIVEL disdrometers in Taiwan in order to assess the success of this procedure.

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Journal article(s) based on this preprint

12 Sep 2024
Drop size distribution retrieval using dual-polarization radar at C-band and S-band
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024,https://doi.org/10.5194/amt-17-5397-2024, 2024
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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A method for determining Drop Size Distributions (DSDs) for rain using radar measurements from...
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