Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
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The Improvement of Computational Efficiency in KIM by an Adaptive Time-step Algorithm

적응시간 간격 알고리즘을 이용한 KIM의 계산 효율성 개선

  • Hyun Nam (Korea Institute of Atmospheric Prediction Systems (KIAPS)) ;
  • Suk-Jin Choi (Department of Atmospheric Environmental Sciences, Gangneung-Wonju National University)
  • 남현 ((재)차세대수치예보모델개발사업단) ;
  • 최석진 (강릉원주대학교 대기환경과학과)
  • Received : 2023.04.04
  • Accepted : 2023.06.13
  • Published : 2023.08.31
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Abstract

A numerical forecasting models usually predict future states by performing time integration considering fixed static time-steps. A time-step that is too long can cause model instability and failure of forecast simulation, and a time-step that is too short can cause unnecessary time integration calculations. Thus, in numerical models, the time-step size can be determined by the CFL (Courant-Friedrichs-Lewy)-condition, and this condition acts as a necessary condition for finding a numerical solution. A static time-step is defined as using the same fixed time-step for time integration. On the other hand, applying a different time-step for each integration while guaranteeing the stability of the solution in time advancement is called an adaptive time-step. The adaptive time-step algorithm is a method of presenting the maximum usable time-step suitable for each integration based on the CFL-condition for the adaptive time-step. In this paper, the adaptive time-step algorithm is applied for the Korean Integrated Model (KIM) to determine suitable parameters used for the adaptive time-step algorithm through the monthly verifications of 10-day simulations (during January and July 2017) at about 12 km resolution. By comparing the numerical results obtained by applying the 25 second static time-step to KIM in Supercomputer 5 (Nurion), it shows similar results in terms of forecast quality, presents the maximum available time-step for each integration, and improves the calculation efficiency by reducing the number of total time integrations by 19%.

Keywords

Acknowledgement

이 논문은 기상청 출연사업인 (재)차세대수치예보모델개발사업단의 가변격자체계 기반 통합형수치예보모델 개발(KMA2020-02212) 및 2023년도 강릉원주대학교 학술연구조성비 지원에 의하여 수행되었음을 밝힙니다.

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