[논문]강우레이더 강수량 관측의 공간적 오차 발생 특성 연구

황석환; 윤정수; 강나래

doi:10.3741/jkwra.2022.55.12.1105

강우레이더 강수량 관측의 공간적 오차 발생 특성 연구
A study on spatial error occurrence characteristics of precipitation estimation of rainfall radar 원문보기

Journal of Korea Water Resources Association = 한국수자원학회논문집, v.55 no.12, 2022년, pp.1105 - 1114

황석환 (한국건설기술연구원 수자원하천연구본부) , 윤정수 (한국건설기술연구원 수자원하천연구본부) , 강나래 (한국건설기술연구원 수자원하천연구본부)

초록
AI-Helper

홍수예보에 활용하기 위해 강우레이더의 시공간적 관측 장점을 살려 지상강우량과 정합성 높은 QPE 추정을 위한 지형적, 수문학적 관측 환경의 한계를 극복하기 위한 방법에 대한 연구와 이러한 한계 조건으로 인해 집중호우 관측의 정량적 불확실도를 홍수해석 측면에서 규명하여야 한다. 이러한 배경에서 본 연구에서는 비슬산(BSL), 소백산(SBS), 가리산(GRS), 모후산(MHS), 서대산(SDS) 강우레이더 각각에 대하여 2016년 22개 주요 호우사상을 분석하여 관측 거리와 고도에 따른 관측의 불확실도를 정량화하고 오차지도를 유도하였다. 분석결과 강우레이더 평균적으로 100 km까지는 대략 10% 이하, 150 km 이상에서는 30%를 초과하는 것으로 나타났다. 고도에 대한 오차는 레이더 운영 고도각 평균을 기준으로 2번째 고도각까지는 대략 10% 이하, 3번째 이상에서는 20%, 4번째 고도각 이상에서는 50% 초과하는 것으로 나타났다.

Abstract ▼ AI-Helper

A study on a method to overcome the limitations of the topographical and hydrological observation environment for estimating the QPE with high consistency with the ground rainfall by utilizing the spatiotemporal observation advantages of the rainfall radar for use in flood forecasting, and quantitative observations of localized rainfall due to these limiting conditions Uncertainty should be identified in terms of flood analysis. Against this background, in this study, 22 major heavy rain events in 2016 were analyzed for each of Mt. Biseul (BSL), Mt. Sobaek (SBS), Mt. Gari (GRS), Mt. Mohu (MHS), and Mt. Seodae (SDS) to determine the observation distance and altitude. The uncertainty of observation was quantified and an error map was derived. As a result of the analysis, it was found that, on average, the rainfall radar exceeded 10% up to 100 km and 30% over 150 km. Based on the average radar operating altitude angle, it was found that the error for the altitude was approximately 10% or less up to the second altitude angle, 20% at the third or higher altitude angle, and more than 50% at the fourth altitude angle or higher.

주제어

표/그림 (12)

그림 Fig. 1. Rainfall radar networks of Ministry of Environment Flood Control Office
표 Table 1. Rain events used to derive error according to distance and altitude of rainfall radar observation
그림 Fig. 2. Beam propagation and blocking diagram according to distance and altitude
그림 Fig. 3. Schematic diagram of change in reflectivity according to altitude
표 Table 2. Quantitative Precipitation Estimation (QPE) algorithm used for analysis
표 Table 3. NE of R(JPL) as a function of beam distance from radar
표 Table 4. NE of R(Z) as a function of beam distance from radar
표 Table 5. NE of R(KDP) as a function of beam distance from radar
그림 Fig. 4. Standard Errors for distance at each elevation angle. Thin dotted line (EA1), solid red line (EA2), solid blue line (EA3), solid black line (EA4), black dotted line (EA5), thick black dotted line (EA6)
그림 Fig. 5. Distribution of Standard Error (NE) of QPE by Distance from the radar and elevation angle (HRFCO and MLIT, 2017; HRFCO and ME 2018, 2019, 2020, 2021)
그림 Fig. 6. Distance and altitude error of QPE for each standard basin based on measurements (HRFCO and MLIT, 2017; HRFCO and ME 2018, 2019, 2020, 2021)
그림 Fig. 7. Distance and altitude error of QPE for each Standard basin estimated from 5 rainfall radars

참고문헌 (21)

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