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[IEEE 2019 IEEE International Ultrasonics Symposium (IUS) - Glasgow, United Kingdom (2019.10.6-2019.10.9)] 2019 IEEE International Ultrasonics Symposium (IUS) - Simultaneous dictionary learning and reconstruction from subsampled data in photoacoustic microscopy

DOI:10.1109/ULTSYM.2019.8925747 出版年份:2019 更新时间:2025-09-19 17:13:59
摘要: The Global Precipitation Measurement (GPM) Core Observatory will carry a Dual-frequency Precipitation Radar (DPR) consisting of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR). In this study, “at-launch” codes of DPR precipitation algorithms, which will be used in GPM ground systems at launch, were evaluated using synthetic data based upon the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data. Results from the codes (Version 4.20131010) of the KuPR-only, KaPR-only, and DPR algorithms were compared with “true values” calculated based upon drop size distributions assumed in the synthetic data and standard results from the TRMM algorithms at an altitude of 2 km over the ocean. The results indicate that the total precipitation amounts during April 2011 from the KuPR and DPR algorithms are similar to the true values, whereas the estimates from the KaPR data are underestimated. Moreover, the DPR estimates yielded smaller precipitation rates for rates less than about 10 mm/h and greater precipitation rates above 10 mm/h. Underestimation of the KaPR estimates was analyzed in terms of measured radar re?ectivity ( ) of the KaPR at an altitude of 2 km. The underestimation of the KaPR data was most pronounced during strong precipitation events of (high attenuation cases) over heavy precipitation areas in the Tropics, whereas the underestimation was less pronounced when the (moderate attenuation cases). The results suggest that the underestimation is caused by a problem in the attenuation correction method, which was veri?ed by the improved codes.
作者: Takuji Kubota,Naofumi Yoshida,Shinji Urita,Toshio Iguchi,Shinta Seto,Robert Meneghini,Jun Awaka,Hiroshi Hanado,Satoshi Kida,Riko Oki
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To evaluate the 'at-launch' codes of the GPM/DPR precipitation algorithms using synthetic data based on TRMM/PR observations to assess their accuracy in estimating precipitation rates.

The KuPR and DPR algorithms showed similar total precipitation amounts to the true values, while the KaPR algorithm underestimated precipitation. The underestimation was most pronounced in high attenuation cases during strong precipitation events in the Tropics. Improvements in the attenuation correction method were verified to address the underestimation issue.

The study focused on over-ocean estimates due to potential issues with surface echo simulation at Ka-band over land. The DSD parameter μ was assumed to be 3, consistent with current DPR-L2 algorithms, which may not capture all variability in real-world conditions.

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