• Ocean and Polar Research
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• v.43 no.1
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• pp.1-14
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• 2021

In this study, extreme wind speeds in the Western North Pacific (WNP) were estimated using reanalysis wind fields synthesized with an empirical typhoon vortex model. Reanalysis wind data used is the Fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) data, which was deemed to be the most suitable for extreme value analysis in this study. The empirical typhoon vortex model used has the advantage of being able to realistically reproduce the asymmetric winds of a typhoon by using the gale/storm-forced wind radii information in the 4 quadrants of a typhoon. Using a total of 39 years of the synthesized reanalysis wind fields in the WNP, extreme value analysis is applied to the General Pareto Distribution (GPD) model based on the Peak-Over-Threshold (POT) method, which can be used effectively in case of insufficient data. The results showed that the extreme analysis using the synthesized wind data significantly improved the tendency to underestimate the extreme wind speeds compared to using only reanalysis wind data. Considering the difficulty of obtaining long-term observational wind data at sea, the result of the synthesized wind field and extreme value analysis developed in this study can be used as basic data for the design of offshore structures.

• Structural Engineering and Mechanics
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• v.69 no.1
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• pp.105-120
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• 2019

In this paper, a new efficient method for structural modal reanalysis is proposed, which can handle large finite element (FE) models requiring frequent design modifications. The global FE model is divided into a residual part not to be modified and a target part to be modified. Then, an automated matrix permutation and substructuring algorithm is applied to these parts independently. The reduced model for the residual part is calculated and saved in the initial analysis, and the target part is reduced repeatedly, whenever design modifications occur. Then, the reduced model for the target part is assembled with that of the residual part already saved; thus, the final reduced model corresponding to the new design is obtained easily and rapidly. Here, the formulation of the proposed method is derived in detail, and its computational efficiency and reanalysis ability are demonstrated through several engineering problems, including a topological modification.

• Journal of Industrial Technology
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• v.35
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• pp.95-102
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• 2015

Two extreme wind speed prediction models, the EWM(Extreme wind speed model) in IEC61400-1 and the Gumbel method were compared in this study. The two models were used to predict extreme wind speeds of six different sites in Korea and the results were compared with long term wind data. The NCAR reanalysis data were used for inputs to two models. Various periods of input wind data were tried from 1 year to 50 years and the results were compared with the 50 year maximum wind speed of NCAR wind data. It was found that the EWM model underpredicted the extreme wind speed more than 5 % for two sites. Predictions from Gumbel method overpredicted the extreme wind speed or underpredicted it less than 5 % for all cases when the period of the input data is longer than 10 years. The period of the input wind data less than 3 years resulted in large prediction errors for Gumbel method. Predictions from the EWM model were not, however, much affected by the period of the input wind data.

• Ocean and Polar Research
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• v.41 no.4
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• pp.213-232
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• 2019

This study evaluates the accuracy of four satellite-composite (OSTIA, AVHRR, G1SST, FNMONC-S) and three model-reanalysis (HYCOM, JCOPE2, FNMOC-M) daily sea surface temperature (SST) data around the Korean Peninsula (KP) using ocean buoy data from 2011-2016. The results reveal that OSTIA has the lowest root mean square error (RMSE; 0.68℃) and FNMOC-S/M has the highest correction coefficients (r = 0.993) compared with observations, while G1SST, JCOPE2, and AVHRR have relatively larger RMSEs and smaller correlations. The large RMSEs were found in the western coastal regions of the KP where water depth is shallow and tides are strong, such as Chilbaldo and Deokjeokdo, while low RMSEs were found in the East Sea and open oceans where water depth is relatively deep such as Donghae, Ulleungdo, and Marado. We found that the main sources of the large RMSEs, sometimes reaching up to 5℃, in SST data around the KP, can be attributed to rapid SST changes during events of strong tidal mixing, upwelling, and typhoon-induced mixing. The errors in the background SST fields which are used in data assimilations and satellite composites and the missing in-situ observations are also potential sources of large SST errors. These results suggest that both satellite and reanalysis SST data, which are believed to be true observation-based data, sometimes, can have significant inherent errors in specific regions around the KP and thus the use of such SST products should proceed with caution particularly when the aforementioned events occur.

• Atmosphere
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• v.30 no.1
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• pp.91-102
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• 2020

MERRA-2 ozone and atmospheric data are utilized to test the usefulness of reanalysis-based tracer transport analysis for ozone in the tropical tropopause layer (TTL). Transport and mixing processes related to the seasonal variation of TTL ozone are examined using the tracer transport equation based on the transformed Eulerian mean, and the results are compared to previously proposed values from model analyses. The analysis shows that the seasonal variability of TTL ozone is mainly determined by two processes: vertical mean transport and horizontal eddy mixing of ozone, with different contributions in the Northern and Southern Hemispheres. The horizontal eddy mixing process explains the major portion of the seasonal cycle in the northern TTL, while the vertical mean transport dominates in the southern TTL. The Asian summer monsoon likely contributes to this observed difference. The ozone variability and related processes in MERRA-2 reanalysis show qualitatively similar features with satellite- and model-based analyses, and it provides advantages of fine-scale analyses. However, it still shows significant quantitative biases in ozone budget analysis.

• The Korean Journal of Quaternary Research
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• v.22 no.1
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• pp.13-22
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• 2008

The Indian summer monsoon behaved in an abnormal way in 2002 and as a result there was a large deficiency in precipitation (especially in July) over a large part of the Indian subcontinent. For the study of deficient monsoon of 2002, a recent version of the NCAR regional climate model (RegCM3) has been used to examine the important features of summer monsoon circulations and precipitation during 2002. The main characteristics of wind fields at lower level (850 hPa) and upper level (200 hPa) and precipitation simulated with the RegCM3 over the Indian subcontinent are studied using different cumulus parameterization schemes namely, mass flux schemes, a simplified Kuo-type scheme and Emanuel (EMU) scheme. The monsoon circulation features simulated by RegCM3 are compared with the NCEP/NCAR reanalysis and simulated precipitation is validated against observation from the Global Precipitation Climatology Centre (GPCC). Validation of the wind fields at lower and upper levels shows that the use of Arakawa and Schubert (AS) closure in Grell convection scheme, a Kuo type and Emanuel schemes produces results close to the NCEP/NCAR reanalysis. Similarly, precipitation simulated with RegCM3 over different homogeneous zones of India with the AS closure in Grell is more close to the corresponding observed monthly and seasonal values. RegcM3 simulation also captured the spatial distribution of deficient rainfall in 2002.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.3
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• pp.409-420
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• 2002

This paper proposed a technique of structural re-analysis for the evaluation of dynamic responses of bridge structure under moving loads using experimental modal results. For successful structural re-analysis, it is required to have accurate estimation techniques of the modal characteristics of bridge structures. The natural frequencies and mode shapes were identified by direct fourier analysis techniques and damping ratios by the random decrement method, respectively. An interpolation method was also proposed for the extension of mode shape measured on limited DOFs. Second, the structural reanalysis was performed using moving mass model and identified modal parameters. The results from the reanalysis show that the proposed technique is very reasonable to evaluate the actual behavior of bridge structures under moving loads.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.49-56
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• 2004

Model updating is a very active research field, in which significant efforts has been invested in recent years. Model updating methodologies are invariably successful when used on noise-free simulated data, but tend to be unpredictable when presented with real experimental data that are-unavoidably-corrupted with uncorrected noise content. In this paper, Reanalysis using frequency response functions for correlating and updating dynamic systems is presented. A transformation matrix is obtained from the relationship between the complex and the normal frequency response functions of a structure. The transformation matrix is employed to calculate the modified damping matrix of the system. The modified mass and stiffness matrices are identified from the normal frequency response functions by using the least squares method. One simulated system is employed to illustrate the applicability of the proposed method. The result indicate that the damping matrix of correlated finite element model can be identified accurately by the proposed method. In addition, the robustness of the new approach uniformly distributed measurement noise Is also addressed.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.421-424
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• 2004

Model updating is a very active research field, in which significant efforts has been invested in recent years. Model updating methodologies are invariably successful when used on noise-free simulated data, but tend to be unpredictable when presented with real experimental data that are-unavoidably-corrupted with uncorrelated noise content. In this paper, Reanalysis using frequency response functions for correlating and updating dynamic systems is presented. A transformation matrix is obtained from the relationship between the complex and the normal frequency response functions of a structure. The transformation matrix is employed to calculate the modified damping matrix of the system. The modified mass and stiffness matrices are identified from the normal frequency response functions by using the least squares method. Full scale pseudo dynamic pier test is employed to illustrate the applicability of the proposed method. The result indicate that the damping matrix of correlated finite element model can be identified accurately by the proposed method. In addition, the robustness of the new approach uniformly distributed measurement noise is also addressed.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.118-118
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• 2020

This study investigates the change of flow characteristics over 10 Asian river basins in the past 30 years (1976-2005). The variation is estimated from The Soil and Water Assessment Tool (SWAT) model outputs based on reanalysis data which was bias-corrected for Asian monsoon reagion. The model was firstly calibrated and validated using observed data for daily streamflow. Four statistical criteria were applied to evaluate the model performance, including Coefficient of determination (R2), Nash - Sutcliffe model efficiency coeffi cient (NSE), Root mean square error-observations standard deviation ratio (RSR), and Percentage Bias (PBIAS). Then parameters of the model were applied for the historical period 1976-2005. The estimates show a temporal non-considerable increasing rate of daily streamflow in most of the basins over the past 30 years. The difference of monthly discharge becomes more significant during the months in the wet season (June to September) in all basins. The seasonal runoff shows significant difference in Summer and Autumn, when the rainfall intensity is higher. The line showing averaged runoff/rainfall ratio in all basins is sharp, presenting high variation of seasonal runoff/rainfall ratio from season to season.