• Title/Summary/Keyword: Stochastic Typhoon Simulation

Search Result 5, Processing Time 0.02 seconds

GCM Scenario Downcsaling Method using Multi-Artificial Neural Network and Stochastic Typhoon Model (다지점 인공신경망과 추계학적 태풍모의를 통한 GCM 시나리오 상세화기법)

  • Moon, Su-Jin;Kim, Jung-Joong;Kang, Boo-Sik
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2012.05a
    • /
    • pp.276-276
    • /
    • 2012
  • 일반적으로 기후변화영향에 관한 연구수행을 위해 전지구기후모형(GCM; Global Climate Model)이 사용되고 있다. 하지만 GCM은 공간해상도(Spatial resolution)가 거칠기 때문에 수문학 분야에서 주로 사용되는 유역규모의 지역적인 스케일특성과 물리적 특징을 표현하는데 한계가 있다. 또한 GCM 기후변수들 중 강수량의 경우 한반도 지역의 6월과 10월 사이에 연강수량의 67% 이상이 집중되는 계절성을 반영하지 못하고 있으며, 높은 불확실성을 보이고 있다. 본 연구에서는 GCM 기반의 다지점 인공신경망기법을 적용한 상세화(Downscaling)를 실시하였다. GCM의 24개 2D변수에 대한 주성분분석을 실시하여 신경망의 학습인자로 사용하였으며, 학습, 검증 및 예측기간은 각각 1981~1995년, 1996~2000년, 2011~2100년으로 A1B 시나리오를 대상으로 상세화를 실시하였다. 또한, 여름철 태풍사상을 모의하기 위한 Stochastic Typhoon Simulation기법과 Baseline과 Projection 사이의 강수량 보정을 위한 Dynamic Quantile Mapping 기법을 적용하여, 강수량의 불확실성을 최소화 하고자 하였다.

  • PDF

Wind-excited stochastic vibration of long-span bridge considering wind field parameters during typhoon landfall

  • Ge, Yaojun;Zhao, Lin
    • Wind and Structures
    • /
    • v.19 no.4
    • /
    • pp.421-441
    • /
    • 2014
  • With the assistance of typhoon field data at aerial elevation level observed by meteorological satellites and wind velocity and direction records nearby the ground gathered in Guangzhou Weather Station between 1985 and 2001, some key wind field parameters under typhoon climate in Guangzhou region were calibrated based on Monte-Carlo stochastic algorithm and Meng's typhoon numerical model. By using Peak Over Threshold method (POT) and Generalized Pareto Distribution (GPD), Wind field characteristics during typhoons for various return periods in several typical engineering fields were predicted, showing that some distribution rules in relation to gradient height of atmosphere boundary layer, power-law component of wind profile, gust factor and extreme wind velocity at 1-3s time interval are obviously different from corresponding items in Chinese wind load Codes. In order to evaluate the influence of typhoon field parameters on long-span flexible bridges, 1:100 reduced-scale wind field of type B terrain was reillustrated under typhoon and normal conditions utilizing passive turbulence generators in TJ-3 wind tunnel, and wind-induced performance tests of aero-elastic model of long-span Guangzhou Xinguang arch bridge were carried out as well. Furthermore, aerodynamic admittance function about lattice cross section in mid-span arch lib under the condition of higher turbulence intensity of typhoon field was identified via using high-frequency force-measured balance. Based on identified aerodynamic admittance expressions, Wind-induced stochastic vibration of Xinguang arch bridge under typhoon and normal climates was calculated and compared, considering structural geometrical non-linearity, stochastic wind attack angle effects, etc. Thus, the aerodynamic response characteristics under typhoon and normal conditions can be illustrated and checked, which are of satisfactory response results for different oncoming wind velocities with resemblance to those wind tunnel testing data under the two types of climate modes.

Prediction of Long-term Runoff for Hapcheon Dam Watershed through Multi-Artificial Neural Network Downscaling of KMA's RCM (기상청 RCM전망의 다지점 인공신경망 상세화를 통한 합천댐 유역의 장기유출 전망)

  • Kang, Boo-Sik;Moon, Su-Jin;Kim, Jung-Joong
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2012.05a
    • /
    • pp.948-948
    • /
    • 2012
  • 합천댐유역에 대한 기후변화에 따른 수문학적 영향을 정량적으로 분석하기 위해, 기상청에서 제공하는 공간해상도 27km의 MM5 RCM(Regional Climate Model)을 사용하였다. RCM의 기상변수들은 공간적 스케일의 상이성과 RCM 기후변수들의 불확실성 때문에 유출모형인 SWAT의 입력자료로 사용하기에는 어려움이 있다. 특히, RCM 변수들 중 강수량의 경우 한반도 지역의 6월과 10월 사이에 연강수량의 67%이상이 집중되는 계절성을 반영하지 못하고 있는 실정이기 때문에 국내 유역의 유출량 산정에 사용하기 위해서는 지역적 상세화(Downscaling)가 필요하다. 본 연구에서는 RCM 기후변수에 내포된 공간적 스케일의 상이성과 불확실성을 최소화하기 위해 강우관측소 지점을 단위로 한 다지점 인공신경망 기법을 적용하여 강수량, 습도, 최고기온 및 최저기온에 대한 상세화를 실시하였다. 강수의 경우 여름철 태풍사상을 모의하기 위한 Stochastic Typhoon Simulation기법과 Baseline(1991~2010)과 Projection(2011~2100) 사이의 강수량 보정을 위한 Dynamic Quantile Mapping 기법을 적용하여, 강수량의 불확실성을 최소화 하고자 하였다. 상세화된 기후자료를 이용한 SWAT 모형의 일(Daily) 단위 강우-유출 모의결과를 2011~2040년, 2041~2070년, 2071~2100년으로 구분하여 추세분석을 실시하였다.

  • PDF

Representation of Model Uncertainty in the Short-Range Ensemble Prediction for Typhoon Rusa (2002) (단기 앙상블 예보에서 모형의 불확실성 표현: 태풍 루사)

  • Kim, Sena;Lim, Gyu-Ho
    • Atmosphere
    • /
    • v.25 no.1
    • /
    • pp.1-18
    • /
    • 2015
  • The most objective way to overcome the limitation of numerical weather prediction model is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterization of unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast to represent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastic kinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), we assessed the performance level of the two schemes. The both schemes produced better results than the control run did in the ensemble mean forecast of the track. The results using PHYS improved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors of the both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreads increased gradually during integration. The results based on SKEBS represented model errors very well during the forecast time of 96 hrs. After the period, it produced an under-dispersive pattern. The simulation based on PHYS overestimated the ensemble mean error during integration and represented the real situation well at the forecast time of 120 hrs. The displacement speed of the typhoon based on PHYS was closest to the best track, especially after landfall. In the sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitive to the physics parameterization. By adjusting the forcing parameter of SKEBS, the default experiment improved in the ensemble spread, ensemble mean errors, and moving speed.

Estimation of Extreme Wind Speeds in Korean Peninsula using Typhoon Monte Carlo Simulation (태풍 시뮬레이션을 통한 한반도 극한풍속 추정)

  • Lee, Sungsu;Kim, Ga Young
    • Journal of the Computational Structural Engineering Institute of Korea
    • /
    • v.29 no.2
    • /
    • pp.141-148
    • /
    • 2016
  • The long-span bridges such as Incheon Bridge and Seohae Grand Bridge are located on the coastal region effected frequently by strong wind of typhoons. In order to ensure the wind-resistant performance of the structure, estimation of the proper design wind speed is very important. In this study, stochastic estimation of design wind speed incurred by typhoons is carried out. For this purpose, we first established probability distribution of climatological parameters such as central pressure depth, distance of closest approach, translation speed and heading to build statistical model of typhoons, which are employed in Monte Carlo simulation for hypothetical typhoons. Once a typhoon is generated with statistically justified parameters, wind speeds are estimated along its path using wind field model. Thousands of typhoons are generated and their peak wind speeds are utilized to establish the extreme wind speeds for different return period. The results are compared with design basic wind speeds in Korean Highway Bridge Design Code, showing that the present results agree well with similar studies while the existing code suggests higher design wind speed.