• Journal of Astronomy and Space Sciences
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• v.29 no.2
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• pp.115-121
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• 2012

Existing but largely unused binary star model capabilities are examined. An easily implemented scheme is parameterization of starspot growth and decay that can stimulate work on outer convection zones and their dynamos. Improved precision in spot computation now enhances analysis of very precise data. An existing computational model for blended spectral line profiles is accurate for binary system effects but needs to include damping, thermal Doppler, and other intrinsic broadening effects. Binary star ephemerides had been found exclusively from eclipse timings until recently, but now come also from whole light and radial velocity curves. A logical further development will be to expand these whole curve solutions to include eclipse timings. An attenuation model for circumstellar clouds, with several absorption and scattering mechanisms, has been applied only once, perhaps because the model clouds have fixed locations. However the clouds could be made to move dynamically and be combined into moving streams and disks. An area of potential interest is polarization curve analysis, where incentive for modeling could follow from publication of observed polarization curves. Other recent advances include direct single step solutions for temperatures of both stars of an eclipsing binary and third body kinematics from combined light and velocity curves.

• Atmosphere
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• v.15 no.2
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• pp.91-99
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• 2005

This study compares the summer monsoon circulations during a heavy rainfall period over the Korean peninsular from 11 to 18 July 2004, simulated by three widely used regional models; WRF, MM5, and RSM. An identical model setup is carried out for all the experiments, except for the physical option differences in the RSM. The three models with a nominal resolution of about 50 km over Korea are nested by NCEP-DOE reanalysis data. Another RSM experiment with the same cumulus parameterization scheme as in the WRF and MM5 is designed to investigate the importance of the representation of subgrid-scale parameterized convection in reproducing monsoonal circulations in East Asia. All thee models are found to be capable of reproducing the general distribution of monsoonal precipitation, extending northeastward from south China across the Korean peninsula, to northern Japan. The results from the WRF and MM5 are similar in terms of accumulated precipitation, but a slightly better performance in the WRF than in the MM5. The RSM improves the bias for precipitation as compared to those from the WRF and MM5, but the pattern correlation is degraded due to overestimation of precipitation in northern China. In the comparison of simulated synoptic scale features, the RSM is found to reproduce the large-scale features well compared to the results from the MM5 and WRF. On the other hand, the simulated precipitation from the RSM with the convection scheme used in the MM5 and WRF is closer to that from the WRF and MM5 simulations, indicating the significant dependency of simulated precipitation in East Asia on the cumulus parameterization scheme.

• Atmosphere
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• v.19 no.2
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• pp.127-143
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• 2009

This study investigates characteristics of wintertime simulation conducted by METRI AGCM utilizing new radiation parameterization scheme. New radiation scheme is based on the method of Chou et al., and is utilized in the METRI AGCM recently. In order to analyze characteristics of seasonal simulation in boreal winter, hindcast dataset from 1979 to 2005 is produced in two experiments - control run (CTRL) and new model's run (RADI). Also, changes in performance skill and predictability due to implementation of new radiation scheme are examined. In the wintertime simulation, the RADI experiment tends to reduce warm bias in the upper troposphere probably due to intensification of longwave radiative cooling over the whole troposphere. The radiative cooling effect is related to weakening of longitudinal temperature gradient, leading to weaker tropospheric jet in the upper troposphere. In addition, changes in vertical thermodynamic structure have an influence on reduction of tropical precipitation. Moreover, the RADI case is less sensitive to variation of tropical sea surface temperature than the CTRL case, even though the RADI case simulates the mean climate pattern well. It implies that the RADI run does not have significant improvement in seasonal prediction point of view.

• Journal of Radiation Protection and Research
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• v.48 no.1
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• pp.28-43
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• 2023

Background: High-fidelity meteorological data is a prerequisite for the realistic simulation of atmospheric dispersion of radioactive materials near nuclear power plants (NPPs). However, many meteorological models frequently overestimate near-surface wind speeds, failing to represent local meteorological conditions near NPPs. This study presents a new high-resolution (approximately 1 km) meteorological downscaling method for modeling short-range (< 100 km) atmospheric dispersion of accidental NPP plumes. Materials and Methods: Six considerations from literature reviews have been suggested for a new dynamic downscaling method. The dynamic downscaling method is developed based on the Weather Research and Forecasting (WRF) model version 3.6.1, applying high-resolution land-use and topography data. In addition, a new subgrid-scale topographic drag parameterization has been implemented for a realistic representation of the atmospheric surface-layer momentum transfer. Finally, a year-long simulation for the Kori and Wolsong NPPs, located in southeastern coastal areas, has been made for 2016 and evaluated against operational surface meteorological measurements and the NPPs' on-site weather stations. Results and Discussion: The new dynamic downscaling method can represent multiscale atmospheric motions from the synoptic to the boundary-layer scales and produce three-dimensional local meteorological fields near the NPPs with a 1.2 km grid resolution. Comparing the year-long simulation against the measurements showed a salient improvement in simulating near-surface wind fields by reducing the root mean square error of approximately 1 m/s. Furthermore, the improved wind field simulation led to a better agreement in the Eulerian estimate of the local atmospheric dispersion. The new subgrid-scale topographic drag parameterization was essential for improved performance, suggesting the importance of the subgrid-scale momentum interactions in the atmospheric surface layer. Conclusion: A new dynamic downscaling method has been developed to produce high-resolution local meteorological fields around the Kori and Wolsong NPPs, which can be used in short-range atmospheric dispersion modeling near the NPPs.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.150-150
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• 2018

The Numerical Weather Prediction (NWP) models provide information for weather forecasts. The highly nonlinear and complex interactions in the atmosphere are simplified in meteorological models through approximations and parameterization. Therefore, the simplifications may lead to biases and errors in model results. Although the models have improved over time, the biased outputs of these models are still a matter of concern in meteorological and hydrological studies. Thus, bias removal is an essential step prior to using outputs of atmospheric models. The main idea of statistical bias correction methods is to develop a statistical relationship between modeled and observed variables over the same historical period. The Model Output Statistics (MOS) would be desirable to better match the real time forecast data with observation records. Statistical post-processing methods relate model outputs to the observed values at the sites of interest. In this study three methods are used to remove the possible biases of the real-time outputs of the Weather Research and Forecast (WRF) model in Imjin basin (North and South Korea). The post-processing techniques include the Linear Regression (LR), Linear Scaling (LS) and Power Scaling (PS) methods. The MOS techniques used in this study include three main steps: preprocessing of the historical data in training set, development of the equations, and application of the equations for the validation set. The expected results show the accuracy improvement of the real-time forecast data before and after bias correction. The comparison of the different methods will clarify the best method for the purpose of the forecast skill enhancement in a real-time case study.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.244-252
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• 2021

Wind plays an important role in cases of unexpected radioactive pollutant dispersion, deciding distribution and concentration of the leaked substance. The accurate prediction of wind has been challenging in numerical weather prediction models, especially near the surface because of the complex interaction between turbulent flow and topographic effect. In this study, we investigated the characteristics of atmospheric dispersion of radioactive material (i.e. ¹³⁷Cs) according to the simulated boundary layer around the HANARO research nuclear reactor in Korea using the Weather Research and Forecasting (WRF)-Mesoscale Model Interface (MMIF)-California Puff (CALPUFF) model system. We examined the impacts of orographic drag on wind field, stability calculation methods, and planetary boundary layer parameterizations on the dispersion of radioactive material under a radioactive leaking scenario. We found that inclusion of the orographic drag effect in the WRF model improved the wind prediction most significantly over the complex terrain area, leading the model system to estimate the radioactive concentration near the reactor more conservatively. We also emphasized the importance of the stability calculation method and employing the skillful boundary layer parameterization to ensure more accurate low atmospheric conditions, in order to simulate more feasible spatial distribution of the radioactive dispersion in leaking scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.69-69
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• 2021

From the unprecedented 2011 spring flood, the residens reside by Lake Champlain and Richelieu River encountered enormous damages. The International Joint Committee (IJC) released the Lake Champlain-Richelieu River (LCRR) Plan of Study (PoS). One of the major tasks for the PoS is to investigate the possible scenarios that might happen in the LCRR basin based on the stochastic simulation of the Net Basin Supplies that calculates the amount of flow into the lake and the river. Therefore, the current study proposed a novel apporach that simulate the annual NBS teleconnecting the climate index. The proposed model employed the bivariate empirical decomposition to contamporaneously model the long-term evolution of nonstationary oscillation embeded in the annual NBS and the climate signal (here, Artic Oscillation: AO). In order to represent the variational behavior of NBS correlation structure along with the temporal revolution of the climate index, a new nonstationary parameterization concept is proposed. The results indicate that the proposed model is superior performance in preserving long and short temporal correlation. It can even preserve the hurst coefficient better than any other tested models.

• Journal of Ocean Engineering and Technology
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• v.11 no.4
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• pp.111-121
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• 1997

The spectral energy balance model is composed and the nonlinear interaction is approximated by the discrete interaction parameterization as in WAM model. The numerical results of durational limited growth test agree very well with those of the exact model, EXACT-NL. The response of a wave spectrum to a change in wind direction is investigated numerically for a sequence of direction changes 30$^{\circ}$ , 45$^{\circ}$ , 60$^{\circ}$ , 90$^{\circ}$ . The high frequency components relax more repidly to the new wind direction than the low frequency components and the relaxation process also depends on the wave age. For wind direction changes less than 60$^{\circ}$ , the coupling by nonlinear interaction is so strong that the secondary peak in input source distribution is counteracted by the negative lobe of the nonlinear interaction. For wind direction changes grater than 60$^{\circ}$ , a second independent wind-sea spectrum is generated in the new wind direction, while the old spectrum gradually decays as swell.

• Atmosphere
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• v.22 no.4
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• pp.429-436
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• 2012

The performances of the Seoul National University Urban Canopy Model (SNUUCM) under different meteorological conditions (clear, cloudy, and rainy conditions) in summertime are compared using observation dataset obtained at an urban site. The daily-averaged net radiation, sensible heat flux, and storage heat flux are largest in clear days and smallest in rainy days, but the daily-averaged latent heat flux is similar among clear, cloudy, and rainy days. That is, the ratio of latent heat flux to net radiation increases in order of clear, cloudy, and rainy conditions. In general, the performance of the SNUUCM is better in clear days than in cloudy or rainy days. However, the performance in simulating sensible heat flux in clear days is as poor as that in rainy days. For all the meteorological conditions, the performance in simulating latent heat flux is worst among the performances in simulating net radiation, sensible heat flux, and latent heat flux. The normalized mean error for latent heat flux is largest in rainy days in which the relative importance of latent heat flux in the surface energy balance becomes greatest among the three conditions. This study suggests that improvements to the parameterization of processes that are related to latent heat flux are particularly needed.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.79-89
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• 2022

Soil moisture is significantly related to crop growth and plays an important role in irrigation management. To predict soil moisture, various process-based model has been developed and used in the world. Various models (Land surface model) may have different performance depending on the model parameters and structures that causes the different model output for the same modeling condition. In this study, the three land surface models (Noah Land Surface Model, Soil Water Atmosphere Plant, Community Land Model) were used to compare the model performance (soil moisture prediction) and develop the multi-model simulation. At first, the genetic algorithm was used to estimate the optimal soil parameters for each model, and the parameters were used to predict soil moisture in the study area. Then, we used the multi-model approach based on Bayesian model averaging (BMA). The results derived from this approach showed a better match to the measurements than the results from the original single land surface model. In addition, identifying the strengths and weaknesses of the single model and utilizing multi-model methods can help to increase the accuracy of soil moisture prediction.