• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.221-230
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• 2011

The climate change has been observed in Korea as well as in the entire world recently. The rainstorm has been gradually increased and then the damage has been grown. It is getting important to predict short-term rainfall. The Korea Meteorological Administration (KMA) generates numerical model outputs which are computed by Global Data Assimilation and Prediction System (GDAPS) and Regional Data Assimilation and Prediction System (RDAPS). The KMA predicts rainfall using RDAPS results. RDAPS model generates 48 hours data which is organized 3 hours data accumulated at 00UTC and 12UTC. RDAPS results which are organized 3 hours time scale are converted into daily rainfall to compare observed daily rainfall. In this study, 9 cases are applied to convert RDAPS results to daily rainfall data. The MAP (mean areal precipitation) in Geum river basin are computed by using KMA which are 2005 are used. Finally, the best case which gives the close value to the observed rainfall data is obtained using the average absolute relative error (AARE) especially for the Geum River basin.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.2
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• pp.177-189
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• 2010

In order to incorporate correctly the large or local scale circulation in an atmospheric model, a nudging term is introduced into the equation of motion. The MM5 model was used to assess the meteorological values differences in each case, during ozone episode days in Gwangyang bay. The main objective of this study is to investigate the effect of horizontal and vertical flow fields according to the surface and vertical observation data assimilation by upper wind conditions. Therefore, we carried out several numerical experiments with various parameterization methods for nudging coefficient considering the upper wind conditions (synoptic or asynoptic condition). Nudging considering the synoptic and asynoptic nudging coefficient does have a clear advantage over dynamic initialization, therefore appropriate limitation of these nudging coefficient values on its upper wind conditions is necessary before making an assessment. Obviously, under the weak synoptic wind, there was apparent advantage associated with nudging coefficient by the regional difference. The accuracy for the prediction of the meteorological values has been improved by applying the appropriate PBL (Planetary Boundary Layer) limitation of circulation.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.377-382
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• 2010

For business purposes, it is important to identify diffusion power users, a group of users who have big influence on other users in diffusing content. In this paper, we use the independent cascade model for determining diffusion power users, and to do so, we need a method for calculating the assimilation probability between users. This paper proposes the concepts of user delivery power and a way to quantifying the value of this. User delivery power is used to compute the assimilation probability with user content power. We analyze the proposed method by comparing its performance with those of existing methods through experiments using a real blog network data.

• Journal of Korean Society on Water Environment
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• v.32 no.1
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• pp.60-69
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• 2016

In this study, we estimated root zone soil moisture dynamics using remotely sensed (RS) data. A soil moisture data assimilation scheme was used to derive the soil and root parameters from MODerate resolution Imaging Spectroradiometer (MODIS) data. Based on the estimated soil/root parameters and weather forcings, soil moisture dynamics were simulated at spatio-temporal scales based on a hydrological model. For calibration/validation, the Little Washita (LW13) in Oklahoma and Chungmi-cheon/Seolma-cheon sites were selected. The derived water retention curves matched the observations at LW 13. Also, the simulated soil moisture dynamics at these sites was in agreement with the Time Domain Reflectrometry (TDR)-based measurements. To test the applicability of this approach at ungauged regions, the soil/root parameters at the pixel where the Seolma-cheon site is located were derived from the calibrated MODIS-based (Chungmi-cheon) soil moisture data. Then, the simulated soil moisture was validated using the measurements at the Seolma-cheon site. The results were slightly overestimated compared to the measurements, but these findings support the applicability of this proposed approach in ungauged regions with predictable uncertainties. These findings showed the potential of this approach in Korea. Thus, this proposed approach can be used to assess root zone soil moisture dynamics at spatio-temporal scales across Korea, which comprises mountainous regions with dense forest.

• Journal of the Korean earth science society
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• v.26 no.1
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• pp.66-77
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• 2005

Aerological observation at Heuksando located in south-western part of Koran Peninsula has been started at 1 June 2003. In order to clarify the improvement of meteorological prediction quality. it is necessary to compare between aerological data observed at Gawngju and Heuksando and to make clear the influence of Heuksando data assimilation. Therefore numerical simulations were carried out with High resolution meterological prediction system based on MM5(The 5th Generation Mesoscale Model). The pattern of wind and temperature field observed at Heuksando and Gwangju are different due to land surface friction End Sensible heat flux at surface and the wind field Simulated With Gwangju and Heuksando aerological data agree well with observation wind field. Although the amount of precipitation in these experiments is underestimated. the area and starting time of precipitation around Honam province in case with Heuksando data is more reliable that without the data.

• Atmosphere
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• v.26 no.4
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• pp.523-540
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• 2016

The effects of satellite observations on large-scale atmospheric circulations in the reanalysis data are investigated by comparing the latest Japanese Meteorological Association's reanalysis data (JRA-55) and its family data, JRA-55 Conventional (JRA-55C). The latter is identical to the former except that satellite observations are excluded during the data assimilation process. Only conventional datasets are assimilated in JRA-55C. A simple comparison revealed a considerable difference in temperature and zonal wind fields in both the stratosphere and troposphere. Such differences are particularly large in the Southern Hemisphere and whole stratosphere where conventional ground-based measurements are limited. The effects of satellite observations on the zonal-mean tropospheric circulations are further examined in terms of the Hadley cell, eddy-driven jet, and mid-latitude storm tracks. In both hemispheres, JRA-55C exhibits slightly weaker and narrower Hadley cell than JRA-55. This is consistent with a weaker diabatic heating in JRA-55C. The eddy-driven jet shows a small difference in its latitudinal location only in the Southern Hemisphere. Likewise, while the Northern-Hemisphere storm tracks are quantitatively similar in the two datasets, Southern-Hemisphere storm tracks are relatively weaker in JRA-55C than in JRA-55. Their difference is comparable to the uncertainty between reanalysis datasets, indicating that satellite data assimilation could yield significant corrections in the zonal-mean circulation in the Southern Hemisphere.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2005.09a
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• pp.37-40
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• 2005

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.681-692
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• 2008

This study investigated the application of the successive correction method(SCM), a simple data assimilation method, for synthesizing the radar and rain gauge data. First, the number of iteration and influence radius for the SCM application were decided based on their sensitivity analysis. Also, for the evaluation of synthetic rainfall, the distributed rainfall field using the dense rainfall gauge network was assumed to be the true one. The synthetic rainfall field based on the SCM was also compared quantitatively with the one based on the co-Kriging frequently used nowadays. As the results, the SCM, a simple and economical data assimilation method, was found to secure the accuracy and statistical characteristics of the co-Kriging application.

• Atmosphere
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• v.20 no.3
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• pp.287-306
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• 2010

An ensemble Kalman filter (EnKF) with Weather Research and Forecasting (WRF) Model is applied for Typhoon Wukong (200610) to investigate the performance of ensemble forecasts depending on experimental configurations of the EnKF. In addition, the ensemble sensitivity analysis is applied to the forecast and analysis ensembles generated in EnKF, to investigate the possibility of using the ensemble sensitivity analysis as the adaptive observation guidance. Various experimental configurations are tested by changing model error, ensemble size, assimilation time window, covariance relaxation, and covariance localization in EnKF. First of all, experiments using different physical parameterization scheme for each ensemble member show less root mean square error compared to those using single physics for all the forecast ensemble members, which implies that considering the model error is beneficial to get better forecasts. A larger number of ensembles are also beneficial than a smaller number of ensembles. For the assimilation time window, the experiment using less frequent window shows better results than that using more frequent window, which is associated with the availability of observational data in this study. Therefore, incorporating model error, larger ensemble size, and less frequent assimilation window into the EnKF is beneficial to get better prediction of Typhoon Wukong (200610). The covariance relaxation and localization are relatively less beneficial to the forecasts compared to those factors mentioned above. The ensemble sensitivity analysis shows that the sensitive regions for adaptive observations can be determined by the sensitivity of the forecast measure of interest to the initial ensembles. In addition, the sensitivities calculated by the ensemble sensitivity analysis can be explained by dynamical relationships established among wind, temperature, and pressure.