Inter-comparison of radar rainfall rate using Constant Altitude Plan Position Indicator and hybrid surface rainfall maps

- We develop a hybrid surface rainfall map (HSR).
- The HSR map selectively chooses the lowest observable precipitation pixels.
- The technique is compared with the rainfall rate estimated by CAPPI.
- The HSR is more successful in the algorithms using differential reflectivity.
- The HSR shows significant improvement of rainfall estimation at beam blockage areas.

SummaryGround clutter and beam blockage caused by complex terrain deteriorates the accuracy of radar quantitative precipitation estimations (QPE). To improve radar QPE, we have developed a technique for radar rainfall estimation, the Kyungpook National University Hybrid Surface Rainfall (KHSR), based on a two-dimensional hybrid surface consisting of the lowest radar bins that are immune to ground clutter, beam blockage, and non-meteorological echoes. The KHSR map is a composite of a ground echo mask, a beam blockage mask, and a rain echo mask, and it was applied to an operational S-band dual-polarimetric radar that scans six PPIs at a low elevation angle every 2.5 min. By using three rainfall estimators, R(ZH), R(ZH, ZDR), and R(ZH, ξDR), this technique was compared with an operational Constant Altitude Plan Position Indicator (CAPPI) QPE of the Korea Meteorological Administration during a summer season from June-August 2012. In comparison with CAPPI, KHSR shows improved rainfall estimates for three algorithms, and it was more effective with dual-polarimetric rainfall algorithms than with single polarimetric rainfall algorithms. Error increased with increasing range from radar, but this increase was more rapid using CAPPI than using KHSR. KHSR using the R(ZH, ZDR) algorithm was the most accurate long range (>100 km from the radar) estimator.