The Precipitation Rate Retrieval Algorithms for the GPM Dual-frequency Precipitation Radar
In this paper, precipitation rate retrieval algorithms for the Global Precipitation Measurement mission's Dual-frequency Precipitation Radar (DPR) are developed. The DPR consists of a Ku-band radar (KuPR; 13.6 GHz) and a Ka-band radar (KaPR; 35.5 GHz). For the KuPR, an algorithm similar to the...
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Published in | Journal of the Meteorological Society of Japan. Ser. II p. 2021-011 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Meteorological Society of Japan
2021
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Subjects | |
Online Access | Get full text |
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Summary: | In this paper, precipitation rate retrieval algorithms for the Global Precipitation Measurement mission's Dual-frequency Precipitation Radar (DPR) are developed. The DPR consists of a Ku-band radar (KuPR; 13.6 GHz) and a Ka-band radar (KaPR; 35.5 GHz). For the KuPR, an algorithm similar to the Tropical Rainfall Measuring Mission's Precipitation Radar algorithm is developed, with the relation between precipitation rate R and mass-weighted mean diameter Dm (R–Dm relation) replacing the relation between the specific attenuation k and effective radar reflectivity factor Ze. The R–Dm relation can also be applied to the KaPR and dual-frequency algorithms. In both the single-frequency and dual-frequency algorithms, the forward retrieval method is applied with an assumed adjustment factor for the R–Dm relation (ε) and the results are evaluated to select the best value of ε. The advantages of the dual-frequency algorithm are the availability of the dual-frequency surface reference technique and the ZfKa method, which is a method to use the attenuation-corrected radar reflectivity factor Zf of KaPR, to select ε as well as the possibility to selectively use measurements from KuPR or KaPR. This paper also describes the derivation of the scattering table and the R–Dm relation as well as the procedure for non-uniform beam filling correction in detail. The outputs are then statistically analyzed to demonstrate algorithm performance. |
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ISSN: | 0026-1165 2186-9057 |
DOI: | 10.2151/jmsj.2021-011 |