한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제53권11호
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  • Pages.1025-1037
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  • 2020
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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강우앙상블 예측자료의 공간적 특성 및 적용성 평가

Appraisal of spatial characteristics and applicability of the predicted ensemble rainfall data

  • 이상협 (경북대학교 미래과학기술융합학과) ;
  • 성연정 (경북대학교 미래과학기술융합학과) ;
  • 김경탁 (한국건설기술연구원) ;
  • 정영훈 (경북대학교 미래과학기술융합학과)
  • Lee, Sang-Hyeop (Department of Advanced Science and Technology Convergence, Kyungpook National University) ;
  • Seong, Yeon-Jeong (Department of Advanced Science and Technology Convergence, Kyungpook National University) ;
  • Kim, Gyeong-Tak (Korea Institute of Civil Engineering and Building Technology) ;
  • Jeong, Yeong-Hun (Department of Advanced Science and Technology Convergence, Kyungpook National University)
  • 투고 : 2020.09.17
  • 심사 : 2020.10.05
  • 발행 : 2020.11.30
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초록

본 연구는 호우경보에 사용되는 Limited area ENsemble prediction System (LENS) 강우예측자료에 대한 공간적 특성 및 적용성을 평가하였다. LENS는 13개의 강우앙상블 멤버를 가지고 있어 호우경보를 발령하는데 있어 확률적인 방법을 활용할 수 있다. 그러나 LENS의 자료의 접근성은 매우 낮아 강우예측자료의 적용성에 대한 연구가 미흡한 실정이다. 본 연구에서는 행정구역별로 활용되는 호우경보 시스템에 따라 하나의 지점값과 면적평균값을 관측값과 비교하여 평가지수를 산정하였다. 또한, LENS의 발령시간에 따르는 각 앙상블 멤버들의 정확성을 평가하였다. LENS는 멤버별로 과대 혹은 과소 예측의 불확실성을 보여줬다. 면적단위의 예측이 지점단위의 예측보다 더 높은 예측성을 보여주었다. 또한, 다가오는 72시간의 강우를 예측하는 LENS 자료는 수재해의 영향성이 있을 수 있는 강우 사상에 대하여 예측성능이 좋은 것으로 평가되었다. 추후 국지강우앙상블시스템(LENS) 자료는 행정구역 또는 유역면적 단위의 홍수 대비에 기초자료로 활용될 수 있을 것으로 기대된다.

This study attempted to evaluate the spatial characteristics and applicability of the predicted ensemble rainfall data used for heavy rain alarms. Limited area ENsemble prediction System (LENS) has 13 rainfall ensemble members, so it is possible to use a probabilistic method in issuing heavy rain warnings. However, the accessibility of LENS data is very low, so studies on the applicability of rainfall prediction data are insufficient. In this study, the evaluation index was calculated by comparing one point value and the area average value with the observed value according to the heavy rain warning system used for each administrative district. In addition, the accuracy of each ensemble member according to the LENS issuance time was evaluated. LENS showed the uncertainty of over or under prediction by member. Area-based prediction showed higher predictability than point-based prediction. In addition, the LENS data that predicts the upcoming 72-hour rainfall showed good predictive performance for rainfall events that may have an impact on a water disaster. In the future, the predicted rainfall data from LENS are expected to be used as basic data to prepare for floods in administrative districts or watersheds.

키워드

참고문헌

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