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Development of radar-based quantitative precipitation forecasting using spatial-scale decomposition method for urban flood management

도시홍수예보를 위한 공간규모분할기법을 이용한 레이더 강우예측 기법 개발

  • 윤성심 (한국외국어대학교 차세대도시농림융합기상사업단)
  • Received : 2017.03.09
  • Accepted : 2017.04.19
  • Published : 2017.05.31

Abstract

This study generated the radar-based forecasted rainfall using spatial-scale decomposition method (SCDM) and evaluated the hydrological applicability with forecasted rainfall by KMA (MAPLE, KONOS) in terms of urban flood forecasting. SCDM is to separate the small-scale field (convective cell) and large-scale field (straitform cell) from radar rainfield. And each separated field is forecasted by translation model and storm tracker nowcasting model for improvement of QPF accuracy. As the evaluated results of various QPF for three rainfall events in Seoul and Metropolitan area, proposed method showed better prediction accuracy than MAPLE and KONOS considering the simplicity of the methodology. In addition, this study assessed the urban hydrological applicability for Gangnam basin. As the results, KONOS simulated the peak of water depth more accurately than MAPLE and SCDM, however cannot simulated the timeseries pattern of water depth. In the case of SCDM, the quantitative error was larger than observed water depth, but the simulated pattern was similar to observation. The SCDM will be useful information for flood forecasting if quantitative accuracy is improved through the adjustment technique and blending with NWP.

본 연구에서는 공간규모분할 기법(SCDM)을 적용하여 레이더 예측강우를 산정하고, 도시홍수예보 관점에서 기상청 현업 레이더 예측강우(MAPLE 및 KONOS)와 함께 수문학적 활용성을 평가하였다. 본 연구에서 제시한 공간규모분할 기법은 강우를 층운형과 대류성 강우로 분리하여 각각의 이동속도를 고려하여 개별예측 및 재합성하는 것이다. 수도권 영역의 세 호우 사례를 대상으로 기상청 MAPLE 및 KONOS와의 예측강우 정확도를 평가한 결과, 본 연구에서 적용한 예측기법은 기법의 단순함에 비해 양호한 예측 정확도를 보였다. 또한, 강남유역을 대상으로 각 예측강우의 수심모의 정확도를 평가한 결과, MAPLE 및 SCDM에 비하여 KONOS가 첨두수심을 보다 정확하게 모의하였으나, 호우의 시간적 패턴 구현의 정확도가 높지 않았다. SCDM의 경우 정량적인 오차는 다소 크게 나타났지만, 전체적으로 관측수심과 유사한 모의 양상을 보였다. 추후 부족한 정량적 정확도를 보정 기법 및 수치예보자료와의 결합을 통해 개선한다면 SCDM의 예측강우가 홍수예보를 위한 입력자료로 유용하게 활용될 수 있을 것으로 판단된다.

Keywords

References

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