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Korean Meteorological Society (한국기상학회)
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Development and Wind Speed Evaluation of Ultra High Resolution KMAPP Using Urban Building Information Data

도시건물정보를 반영한 초고해상도 규모상세화 수치자료 산출체계(KMAPP) 구축 및 풍속 평가

  • Kim, Do-Hyoung (Research Applications Department, National Institute of Meteorological Sciences) ;
  • Lee, Seung-Wook (Research Applications Department, National Institute of Meteorological Sciences) ;
  • Jeong, Hyeong-Se (Research Applications Department, National Institute of Meteorological Sciences) ;
  • Park, Sung-Hwa (Research Applications Department, National Institute of Meteorological Sciences) ;
  • Kim, Yeon-Hee (Numerical Modeling Center, Korea Meteorological Administration)
  • 김도형 (국립기상과학원 기상응용연구부) ;
  • 이승욱 (국립기상과학원 기상응용연구부) ;
  • 정형세 (국립기상과학원 기상응용연구부) ;
  • 박성화 (국립기상과학원 기상응용연구부) ;
  • 김연희 (기상청 수치모델링센터)
  • Received : 2022.01.11
  • Accepted : 2022.07.18
  • Published : 2022.09.30
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Abstract

The purpose of this study is to build and evaluate a high-resolution (50 m) KMAPP (Korea Meteorological Administration Post Processing) reflecting building data. KMAPP uses LDAPS (Local Data Assimilation and Prediction System) data to detail ground wind speed through surface roughness and elevation corrections. During the detailing process, we improved the vegetation roughness data to reflect the impact of city buildings. AWS (Automatic Weather Station) data from a total of 48 locations in the metropolitan area including Seoul in 2019 were used as the observation data used for verification. Sensitivity analysis was conducted by dividing the experiment according to the method of improving the vegetation roughness length. KMAPP has been shown to improve the tendency of LDAPS to over simulate surface wind speeds. Compared to LDAPS, Root Mean Square Error (RMSE) is improved by approximately 23% and Mean Bias Error (MBE) by about 47%. However, there is an error in the roughness length around the Han River or the coastline. Accordingly, the surface roughness length was improved in KMAPP and the building information was reflected. In the sensitivity experiment of improved KMAPP, RMSE was further improved to 6% and MBE to 3%. This study shows that high-resolution KMAPP reflecting building information can improve wind speed accuracy in urban areas.

Keywords

Acknowledgement

이 연구는 기상청 국립기상과학원 「고해상도 도시 기상서비스 기술개발(KMA2018-00627)」의 일환으로 수행되었습니다.

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