On quality of radar rainfall with respect to temporal and spatial resolution for application to urban areas

Abstract

In this study the quality of radar rainfall with respect to temporal and spatial resolution was examined. Gwangdeoksan Radar and the Korea Institute of Civil Engineering and Building Technology (KICT) Radar were used for this purpose, along with the automatic weather systems data within Seoul. In addition, several quantitative quality measures were applied to examine the resolution. A negative bias of more than 40% in the radar rainfall of Gwangdeoksan Radar occurred with changes in the temporal and spatial resolution. However, the negative bias in the radar rainfall of KICT Radar was less than 10%. The mean square error in the radar rainfall of Gwangdeoksan Radar ranged from 5.5 to 0.4 mm2 h−2 and the mean square error in the radar rainfall of KICT Radar ranged from 30.2 to 1.5 mm2 h−2. The correlation co‐efficient of the accumulated time of 30 min was more than 0.7, which increased by 30% from the correlation co‐efficient of the accumulated time of 10 min. The bias in the radar rainfall of Gwangdeoksan Radar was still large with changes in the temporal and spatial resolution. However, the radar rainfall of KICT Radar was quantitatively similar to the gauge rainfall, and so the radar rainfall did not need any further quantitative correction.

The Role of Weather Radar in Rainfall Estimation and Its Application in Meteorological and Hydrological Modelling—A Review

“…Reduced temporal resolution has more impact on the hydrological modelling accuracy than decreasing spatial resolution [12,19]. In the study by Yoon et al [19], the root mean square error and correlation coefficient increased as the accumulated time and radar bin size increased, and the correlation coefficient was found to be much more sensitive to temporal resolution than spatial resolution.…”

“…Reduced temporal resolution has more impact on the hydrological modelling accuracy than decreasing spatial resolution [12,19]. In the study by Yoon et al [19], the root mean square error and correlation coefficient increased as the accumulated time and radar bin size increased, and the correlation coefficient was found to be much more sensitive to temporal resolution than spatial resolution. An assessment of the impact of the temporal resolution of rainfall data on rainfall-runoff modelling was performed by, among others, Ochoa-Rodriguez et al [17], who confirmed that the influence of temporal accumulation of radar rainfall data is higher than that of spatial resolution, especially in small drainage areas.…”

Attenuation Correction of X-Band Radar Reflectivity Using Adjacent Multiple Microwave Links

“…The attenuation correction can account for spatiotemporal differentiation depending on the rainfall type, and it also recovers the physical structure of the rainfall in accordance with the rapidly changing spatial and temporal variations as well as the spatial heterogeneity. Chandrasekar et al [14] reported that under Rayleigh scattering assumptions, radar reflectivity will not change in accordance with the radar frequency. However, the Rayleigh scattering assumptions are not strictly valid with respect to X-band.…”

Quantification of Error in Reflectivity for Improving the Accuracy of the Radar Rainfall Estimated from Single Polarization Radar

“…이에 비해 기상 분야에서는 호우의 종류에 따른 강우 크기 입자분포의 변동성과 레이더 강수 추정 알고리즘의 매개변수 등을 주요 오차 원인으로 바라보고 있다 (Gosset et al, 2010). 이러한 전자, 통신, 기상 분야에서의 오차 원인을 파악하고 제거하였다 할지라도 레이더 강우를 수문분석에 활용하는 수문 전문가들에게는 여전히 레이더 강우에 오차 가 존재한다는 문제점을 제기하여 왔다 (Seo and Krajewski, 2011;Yoon, Choi, et al, 2016;Yoon et al, 2017).…”