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Long Wen, Kun Zhao, Guifu Zhang, Su Liu, and Gang Chen

Abstract

Instrumentation limitations on measured raindrop size distributions (DSDs) and their derived relations and physical parameters are studied through a comparison of the DSD measurements during mei-yu season in east China by four collocated instruments, that is, a two-dimensional video disdrometer (2DVD), a vertically pointing Micro Rain Radar (MRR), and two laser-optical OTT Particle Size Velocity (PARSIVEL) disdrometers (first generation: OTT-1; second generation: OTT-2). Among the four instruments, the 2DVD provides the most accurate DSD and drop velocity measurements, so its measured rainfall amount has the best agreement with the reference rain gauge. Other instruments tend to miss more small drops (D < 1 mm), leading to inaccurate DSDs and a lower rainfall amount. The low rainfall estimation becomes significant during heavy rainfall. The impacts of instrument limitations on the microphysical processes (e.g., evaporation and accretion rates) and convective storm morphology are evaluated. This is important especially for mei-yu precipitation, which is dominated by a high concentration of small drops. Hence, the instrument limitations need to be taken into account in both QPE and microphysics parameterization.

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Hao Huang, Guifu Zhang, Kun Zhao, Su Liu, Long Wen, Gang Chen, and Zhengwei Yang

Abstract

Drop size distribution (DSD) is a fundamental parameter in rain microphysics. Retrieving DSDs from polarimetric radar measurements extends the capabilities of rain microphysics research and quantitative precipitation estimation. In this study, issues in rain DSD retrieval were studied with simulated and measured data. It was found that a three-parameter gamma distribution model was not suitable for directly retrieving DSD from polarimetric radar measurements. A statistical constraint, such as the shape–slope relation used in the constrained-gamma (C-G) distribution model, helped to reduce the uncertainties and errors in the retrieval. The inclusion of specific differential phase (K DP) measurements resulted in more accurate DSD retrieval and rain physical parameter estimation if the measurement errors were properly characterized in the error minimization analysis (EMA), which was verified using two real precipitation events. The study demonstrated the potential of using full polarimetric radar measurements to improve rain DSD retrieval.

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Hao Huang, Kun Zhao, Guifu Zhang, Qing Lin, Long Wen, Gang Chen, Zhengwei Yang, Mingjun Wang, and Dongming Hu

Abstract

Quantitative precipitation estimation (QPE) with polarimetric radar measurements suffers from different sources of uncertainty. The variational approach appears to be a promising way to optimize the radar QPE statistically. In this study a variational approach is developed to quantitatively estimate the rainfall rate (R) from the differential phase (ΦDP). A spline filter is utilized in the optimization procedures to eliminate the impact of the random errors in ΦDP, which can be a major source of error in the specific differential phase (K DP)-based QPE. In addition, R estimated from the horizontal reflectivity factor (Z H) is used in the a priori with the error covariance matrix statistically determined. The approach is evaluated by an idealized case and multiple real rainfall cases observed by an operational S-band polarimetric radar in southern China. The comparative results demonstrate that with a proper range filter, the proposed variational radar QPE with the a priori included agrees well with the rain gauge measurements and proves to have better performance than the other three approaches, that is, the proposed variational approach without the a priori included, the variational approach proposed by Hogan, and the conventional power-law estimator-based approach.

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