• Title/Summary/Keyword: nonhydrostatic effects

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Numerical Simulations of Dam-Break Flows and Inundation considering Nonhydrostatic Pressure and Dispersive Effects (동수압 및 분산 효과를 고려한 댐붕괴파와 범람 수치모의)

  • Kim, Dae-Hong;Lynett, Patrick
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.213-217
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    • 2010
  • 댐붕괴파 (dam-break flow)나 지진해일에 의해 발생하는 undular bore와 충격파 (shock) 현상을 동수압 및 분산효과를 고려하여 수치모의를 수행하였다. 완전비선형 Boussinesq-type equations 모형을 이용하여, 동수압 및 분산 효과를 고려하였다. 방정식은 4차 정확도의 유한체적법을 이용하여 해석하였고, 시간적으로도 4차정확도의 기법을 이용하여 고차미분항에 대한 수치분산을 억제하였다. 다양한 경우의 1차원과 2차원 공간에서의 수치모의를 수행하고 검증을 수행하였다. 그 결과, 완전비선형 Boussinesq-type equations 모형은 천수방정식 (shallow water equations) 기반의 모형에서 재현이 불가능한 undular bore 등을 재현 하는 등, 전반적으로 천수방정식 기반의 모형 보다 물리적으로도 타당하고 정량적으로도 실험결과와 잘 일치하는 경향을 보였다. 즉, 댐붕괴파나 지진해일 등에 의한 범람 모의에 있어 동수압과 분산 효과의 중요성이 공학적으로도 매우 중요한 고려사항 임이 나타났다.

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Nonhydrostatic Effects on Convectively Forced Mesoscale Flows (대류가 유도하는 중규모 흐름에 미치는 비정역학 효과)

  • Woo, Sora;Baik, Jong-Jin;Lee, Hyunho;Han, Ji-Young;Seo, Jaemyeong Mango
    • Atmosphere
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    • v.23 no.3
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    • pp.293-305
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    • 2013
  • Nonhydrostatic effects on convectively forced mesoscale flows in two dimensions are numerically investigated using a nondimensional model. An elevated heating that represents convective heating due to deep cumulus convection is specified in a uniform basic flow with constant stability, and numerical experiments are performed with different values of the nonlinearity factor and nonhydrostaticity factor. The simulation result in a linear system is first compared to the analytic solution. The simulated vertical velocity field is very similar to the analytic one, confirming the high accuracy of nondimensional model's solutions. When the nonhydrostaticity factor is small, alternating regions of upward and downward motion above the heating top appear. On the other hand, when the nonhydrostaticity factor is relatively large, alternating updraft and downdraft cells appear downwind of the main updraft region. These features according to the nonhydrostaticity factor appear in both linear and nonlinear flow systems. The location of the maximum vertical velocity in the main updraft region differs depending on the degrees of nonlinearity and nonhydrostaticity. Using the Taylor-Goldstein equation in a linear, steady-state, invscid system, it is analyzed that evanescent waves exist for a given nonhydrostaticity factor. The critical wavelength of an evanescent wave is given by ${\lambda}_c=2{\pi}{\beta}$, where ${\beta}$ is the nonhydrostaticity factor. Waves whose wavelengths are smaller than the critical wavelength become evanescent. The alternating updraft and downdraft cells are formed by the superposition of evanescent waves and horizontally propagating parts of propagating waves. Simulation results show that the horizontal length of the updraft and downdraft cells is the half of the critical wavelength (${\pi}{\beta}$) in a linear flow system and larger than ${\pi}{\beta}$ in a weakly nonlinear flow system.

A Suggestion for Data Assimilation Method of Hydrometeor Types Estimated from the Polarimetric Radar Observation

  • Yamaguchi, Kosei;Nakakita, Eiichi;Sumida, Yasuhiko
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.2161-2166
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    • 2009
  • It is important for 0-6 hour nowcasting to provide for a high-quality initial condition in a meso-scale atmospheric model by a data assimilation of several observation data. The polarimetric radar data is expected to be assimilated into the forecast model, because the radar has a possibility of measurements of the types, the shapes, and the size distributions of hydrometeors. In this paper, an impact on rainfall prediction of the data assimilation of hydrometeor types (i.e. raindrop, graupel, snowflake, etc.) is evaluated. The observed information of hydrometeor types is estimated using the fuzzy logic algorism. As an implementation, the cloud-resolving nonhydrostatic atmospheric model, CReSS, which has detail microphysical processes, is employed as a forecast model. The local ensemble transform Kalman filter, LETKF, is used as a data assimilation method, which uses an ensemble of short-term forecasts to estimate the flowdependent background error covariance required in data assimilation. A heavy rainfall event occurred in Okinawa in 2008 is chosen as an application. As a result, the rainfall prediction accuracy in the assimilation case of both hydrometeor types and the Doppler velocity and the radar echo is improved by a comparison of the no assimilation case. The effects on rainfall prediction of the assimilation of hydrometeor types appear in longer prediction lead time compared with the effects of the assimilation of radar echo only.

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