Abstract
To assess the performance of rainfall estimation using specific differential phase observed by Bislsan radar, the first polarimetric radar in Korea, three rainfall cases occurring in 2011 were selected, each caused by different conditions: the first is the Changma front and typhoon, the second is only the Changma front, and the third is only a typhoon. For quantitative use of specific differential phase (KDP), a data quality algorithm was developed for differential phase shift (ΦDP), composed of two steps; the first involves removal of scattered noise and the second is unfolding ofΦDP. This order of the algorithm is necessary so as not to remove unfolded areas, which are the real meteorological target. All noise was removed and the foldedΦDPwere unfolded successfully for this study.RKDPrelations for S-band radar were calculated for 84,754 samples of observed drop size distribution (DSD) using different drop shape assumptions. The relation for the Bringi drop shape showed the best statistics: 0.28 for normalized error, and 6.7 mm for root mean square error for rainfall heavier than 10 mm h-1. Because the drop shape assumption affects the accuracy of rainfall estimation differently for different rainfall types, such characteristics should be taken into account to estimate rainfall more accurately using polarimetric variables.
Highlights
Weather radar is a very useful remote sensing tool for estimating rainfall amount because of its high spatial and time resolution compared with other instruments
This paper discusses how the accuracy of rainfall estimation can be improved using specific differential phase measured by the first polarimetric radar installed in Korea
There could be many sources of error, but the differing accuracy of the different rainfall relations was first examined by using the tropical R(Z) relation used in generation radar (NEXRAD) in USA: R = 1.21 × 10−2Z0.833
Summary
Weather radar is a very useful remote sensing tool for estimating rainfall amount because of its high spatial and time resolution compared with other instruments. Measurements of rainfall by radar are generally based on the relationship between the reflectivity factor (Z) and rain rate (R), termed the Z-R relation (hereafter R(Z)). Measured DSDs have been extensively used to calculate both radar reflectivity and rain rate [1]. Many researchers have noted that radar rainfall estimation is contaminated by a number of uncertainties such as hardware calibration, partial beam filling, rain attenuation, bright band, and nonweather echoes [3, 4]. Several studies in Korea have calculated the R(Z) relationship using disdrometer data for different rainfall types and calirated rainfall amount with rain gages for operational Doppler weather radars [5,6,7]
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