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Jan., 2005

The Regional R&D Framework for Ensemble Prediction of Rapidly Developing S.W.P. based on HPN & GRID Technology. Jan., 2005. Jai Ho Oh jhoh@pknu.ac.kr Pukyong National University, Busan, Korea http:// climate.pknu.ac.kr /. Back Ground. 1. Traditional Forecasting. T. r. u. t. h. I.

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Jan., 2005

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  1. The Regional R&D Framework for Ensemble Prediction of Rapidly Developing S.W.P. based on HPN & GRID Technology Jan., 2005 Jai Ho Oh jhoh@pknu.ac.kr Pukyong National University, Busan, Korea http://climate.pknu.ac.kr/

  2. Back Ground 1. Traditional Forecasting T r u t h I n i t i a l S t a t e U n c e r t a i n t y F o r e c a s t Briefing and Discussion

  3. Initial State Uncertainty t critical Deterministic Stochastic 2. Ensemble Forecasting

  4. Probability forecast

  5. 3. Example of Ensemble Forecast for Typhoon “Ramasoon” 200207040900 200207041200 200207041500 200207041800 200207042100 200207050000 이미지 누락 이미지 누락 20.5mm 100mm 97mm 3시간간격의 관측치, 앙상블 강수량, 강수확률 비교

  6. 3. Example of Ensemble Forecast for Typhoon “Ramasoon” 200207050300 200207050600 200207050900 200207051200 200207051500 200207051800 98mm 105mm 124mm 3시간간격의 관측치, 앙상블 강수량, 강수확률 비교

  7. 3. Example of Ensemble Forecast for Typhoon “Ramasoon” 200207052100 200207060000 200207060300 200207060600 82.8mm 3시간간격의 관측치, 앙상블 강수량, 강수확률 비교

  8. 4. Multi-ensemble forecast in USA

  9. 5. Benefit of Multi-ensemble Prediction 多 多 益 善

  10. GOAL Establishment of GRID based Research Framework on Severe Weather Prediction

  11. GRID and Atmos. Sci. in KOREA Significant Comp. Resources 다학제간 기상연구협업 Great Amount of Data Interdisciplinary works Probable Approaches Limited Human and Computational Resources Accomplish the Goal with GRID

  12. About GRID based Research Framework The concept of virtual lab. for super ensemble prediction of severe weather phenomena • Access Grid : Cooperative meteorological research environment • Computational Grid : Distributed high performance computing • - Data Grid : Virtual server for large meteorological data GRID Web - Portal GRID concept is essential for C-J-K Research Framework

  13. Major Components of C-J-K Framework Real-time C-J-K. collaboration with Access GRID Distributed high performance computing with Computational GRID Web-portal for data GRID

  14. 1차년도 : C-J-K research Framework Installation

  15. 2차년도 : C-J-K research Framework Pilot Testing IC BC MO NEW IC Obs. NEW BC IC BC IC BC MODEL OUT MO Obs. Obs. MO

  16. 3차년도 : C-J-K research Framework Operation Observation Data-set KMA Observation Data-set Observation Data-set JMA CMA

  17. KT Cluster PKNU Storage KISTI Cluster NCAM Storage Collabortion among C-J-K Shearing Comp. Res. Shearing Ensemble Forecast Shearing Obs. Data KOREA C-J-K Research Framework CHINA JAPAN

  18. Web PortalforData Grid • Data Grid: Web 기반 기상 그리드 포털 구축 및 운영 (GTK 3.0)

  19. 공동연구를 위한 국내 네트웍 현황 초고속 선도망 이용기관은 현재 해외와 연결된 시험망 자동 이용

  20. 공동연구를 위한 해외 네트웍 현황 초고속 선도망과 연동되는 해외망에 대한 TOPOLOGY. KOREA light network & GLORIAD network. 해외 연동망을 활용한 기술 발전 방향 - 한·중간 연구전산망 연동을 통해 슈퍼컴퓨팅, 그리드 등을 비롯한 첨단 응용연구 활성화 - 세계적인 과학기술 망인 글로리아드 (GLORIAD) 연구망에 한국의 주도적 참여 기대 - 초고속연구망 (KREONET)와 과학기술연구망 (CSTNET)을 통한 국내외 연구 활동 증진

  21. 공동연구 인력 및 정보 교류방안 월간회의 : Access Grid 실시간 화상회의시스템을 이용한 월 1회 이상 실시 KOREA C-J-K Coresearch Framework CHINA JAPAN 년 2회 이상의 C-J-K Workshop 연 2회 이상의 C-J-K User Tutorials

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