• Journal of Korea Water Resources Association
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• v.42 no.8
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• pp.607-617
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• 2009

Radar beam blocking which is partially or entirely interrupted by obstacles like a mountain causes underestimation of the rainfall. In this paper, partially blocked radar reflectivity is retrieved using the ARM(Accumulated Reflectivity Map). ARM is made by accumulation of the radar reflectivity and very useful product to analyze the beam blockage. The blockage correcting map could be obtained by assuming the spatially uniform reflectivity field in the ARM. This method is applied to the cases of typhoon and Changma, and we obtain the MFE(Mean Fractional Error) from two radar data, the one is objective radar data which is affected by blockage and the other is comparative radar data which is not affected by blockage. Before blocking correction, MFE is 20-35%. However, after correction, MFE decreases to 7-10%.

• Journal of the Korean earth science society
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• v.36 no.1
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• pp.109-124
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• 2015

A novel approach, hybrid surface rainfall (KNU-HSR) technique developed by Kyungpook Natinal University, was utilized for improving the radar rainfall estimation. The KNU-HSR technique estimates radar rainfall at a 2D hybrid surface consistings of the lowest radar bins that is immune to ground clutter contaminations and significant beam blockage. Two HSR techniques, static and dynamic HSRs, were compared and evaluated in this study. Static HSR technique utilizes beam blockage map and ground clutter map to yield the hybrid surface whereas dynamic HSR technique additionally applies quality index map that are derived from the fuzzy logic algorithm for a quality control in real time. The performances of two HSRs were evaluated by correlation coefficient (CORR), total ratio (RATIO), mean bias (BIAS), normalized standard deviation (NSD), and mean relative error (MRE) for ten rain cases. Dynamic HSR (CORR=0.88, BIAS= $-0.24mm\;hr^{-1}$, NSD=0.41, MRE=37.6%) shows better performances than static HSR without correction of reflectivity calibration bias (CORR=0.87, BIAS= $-2.94mm\;hr^{-1}$, NSD=0.76, MRE=58.4%) for all skill scores. Dynamic HSR technique overestimates surface rainfall at near range whereas it underestimates rainfall at far ranges due to the effects of beam broadening and increasing the radar beam height. In terms of NSD and MRE, dynamic HSR shows the best results regardless of the distance from radar. Static HSR significantly overestimates a surface rainfall at weaker rainfall intensity. However, RATIO of dynamic HSR remains almost 1.0 for all ranges of rainfall intensity. After correcting system bias of reflectivity, NSD and MRE of dynamic HSR are improved by about 20 and 15%, respectively.