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Improving Polarimetric C-Band Radar Rainfall Estimation with Two-Dimensional Video Disdrometer Observations in Eastern China
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Improving Polarimetric C-Band Radar Rainfall Estimation with Two-Dimensional Video Disdrometer Observations in Eastern China
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Improving Polarimetric C-Band Radar Rainfall Estimation with Two-Dimensional Video Disdrometer Observations in Eastern China
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Journal Article
Improving Polarimetric C-Band Radar Rainfall Estimation with Two-Dimensional Video Disdrometer Observations in Eastern China
2017
Overview
In this study, the capability of using a C-band polarimetric Doppler radar and a two-dimensional video disdrometer (2DVD) to estimate monsoon-influenced summer rainfall during the Observation, Prediction and Analysis of Severe Convection of China (OPACC) field campaign in 2014 and 2015 in eastern China is investigated. Three different rainfall R estimators, for reflectivity at horizontal polarization [R(Z
h)], for reflectivity at horizontal polarization and differential reflectivity factor [R(Z
h, Z
dr)], and for specific differential phase [R(K
DP)], are derived from 2-yr 2DVD observations of summer precipitation systems. The radar-estimated rainfall is compared to gauge observations from eight rainfall episodes. Results show that the two polarimetric estimators, R(Z
h, Z
dr) and R(K
DP), perform better than the traditional Z
h–R relation [i.e., R(Z
h)]. The K
DP-based estimator [i.e., R(K
DP)] produces the best rainfall accumulations. The radar rainfall estimators perform differently across the three organized convective systems (mei-yu rainband, typhoon rainband, and squall line). Estimator R(Z
h) overestimates rainfall in the mei-yu rainband and squall line, and R(Z
h, Z
dr) mitigates the overestimation in the mei-yu rainband but has a large bias in the squall line. QPE from R(K
DP) is themost accurate among the three estimators, but it possesses a relatively large bias for the squall line compared to the mei-yu case. The high variability of drop size distribution (DSD) related to the precipitation microphysics in different types of rain is largely responsible for the case-dependent QPE performance using any single radar rainfall estimator. The squall line has a distinct ice-phase process with a large mean size of raindrops, while the mei-yu rainband and typhoon rainband are composed of smaller raindrops. Based on the statistical QPE error in the Z
H–Z
DR space, a new composite rainfall estimator is constructed by combining R(Z
h), R(Z
h, Z
dr), and R(K
DP) and is proven to outperform any single rainfall estimator.
