• Journal of Korea Water Resources Association
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• v.49 no.7
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• pp.625-634
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• 2016

Three leading agencies under different ministries - Korea Meteorological Administration (KMA) in the ministry of Environment, Han river control office in the Ministry of Land, Infrastructure and Transport (MOLIT) and Weather Group of ROK Air Force in the Ministry of National Defense (MND) - have been operated radars in the purpose of observing weather, hydrology and military operational weather in Korea. Eight S-band dual-pol. radars have been newly installed or replaced by these ministries over different places by 2015. However each ministry has different aims of operating radars, observation strategies, data processing algorithms, etc. Due to the differences, there is a wide level of accuracy on observed radar data as well as the composite images made of the cross governmental radar measurement. Gaining fairly high level of accuracy on radar data obtained by different agencies has been shared as a great concern by the ministries. Thus, "an agreement of harmonizing weather and hydrological radar products" was made by the three ministries in 2010. Particularly, this is very important to produce better rainfall estimation using the cross governmental radar measurement. Weather Radar Center(WRC) in KMA has been developed an empirical method using measurements observed by Yongin testbed radar. This study is aiming to examine the efficiency of the empirical method to improve the accuracies of radar rainfalls estimated from cross governmental dual-pol. radar measurements. As a result, the radar rainfalls of three radars (Baengnyeongdo, Biseulsan, and, Sobaeksan Radar) were shown improvement in accuracy (1-NE) up to 70% using data from May to October in 2015. Also, the range of the accuracies in radar rainfall estimation, which were from 30% to 60% before adjusting polarimetric variables, were decreased from 65% to 70% after adjusting polarimetric variables.

• Atmosphere
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• v.32 no.1
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• pp.27-37
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• 2022

The Korean Integrated Model (KIM) forecast system was extended to assimilate Horizontal Line-Of-Sight (HLOS) wind observations from the Atmospheric Laser Doppler Instrument (ALADIN) on board the Atmospheric Dynamic Mission (ADM)-Aeolus satellite. Quality control procedures were developed to assess the HLOS wind data quality, and observation operators added to the KIM three-dimensional variational data assimilation system to support the new observed variables. In a global cycling experiment, assimilation of ALADIN observations led to reductions in average root-mean-square error of 2.1% and 1.3% for the zonal and meridional wind analyses when compared against European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) analyses. Even though the observable variable is wind, the assimilation of ALADIN observation had an overall positive impact on the analyses of other variables, such as temperature and specific humidity. As a result, the KIM 72-hour wind forecast fields were improved in the Southern Hemisphere poleward of 30 degrees.

• Journal of Korean Society of Water and Wastewater
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• v.14 no.3
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• pp.281-290
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• 2000

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. ANFIS, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an application of network-based fuzzy inference system(ANFIS) for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water which supplied in Kwangju city. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supply, (b) the mean temperature, and (c) the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.46% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.1
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• pp.51-63
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• 1997

Total suspended particulate matters in the ambient air were analyzed for eight chemical elements (Ca, Co, Cu, Fe, Mn, Pb, Si, and Zn) using an x-ray fluorescence spectrometry (XRF) at the Kyung Hee University - Suwon Campus during 1989 to 1994. To use these data as basis for source identification study, membership of each sample was selected to represent one of the well defined sample groups. The data sets consisting of 83 objects and 8 variables were initially separated into two groups, fine (d$_{p}$<3.3 ${\mu}{\textrm}{m}$) and coarse particle groups (d$_{p}$>3.3 ${\mu}{\textrm}{m}$). A hierarchical clustering method was examined to obtain possible member of homogeneous sample classes for each of the two groups by transforming raw data and by applying various distances. A disjoint principal component analysis was then used to define homogeneous sample classes after deleting outliers. Each of five homogeneous sample classes was determined for the fine and the coarse particle group, respectively. The data were properly classified via an application of logarithmic transformation and Euclidean distance concept. After determining homogeneous classes, correlation coefficients among eight chemical variables within all the homogeneous classes for calculated and meteorological variables (temperature. relative humidity, wind speed, wind direction, and precipitation) were examined as well to intensively interpret environmental factors influencing the characteristics of each class for each group. According to our analysis, we found that each class had its own distinct seasonal pattern that was affected most sensitively by wind direction.ion.

• Journal of Environmental Science International
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• v.26 no.6
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• pp.741-750
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• 2017

A model coupling a meteorological predictive model and a vegetation photosynthesis and respiration model was used to simulate $CO_2$ concentrations over coastal basin areas, and modeling results were estimated with aircraft observations during a massive sampling campaign. Along with the flight tracks, the model captured the meteorological variables of potential temperature and wind speed with mean bias results of $0.8^{\circ}C$, and 0.2 m/s, respectively. These results were statistically robust, which allowed for further estimation of the model's performance for $CO_2$ simulations. Two high-resolution emission data sets were adopted to determine $CO_2$ concentrations, and the results show that the model underestimated by 1.8 ppm and 0.9 ppm at higher altitude over the study areas during daytime and nighttime, respectively, on average. Overall, it was concluded that the model's $CO_2$ performance was fairly good at higher altitude over the study areas during the study period.

• Atmosphere
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• v.25 no.2
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• pp.193-203
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• 2015

A large aperture scintillometer (LAS) was deployed with an optical path length of 2.1 km to estimate turbulent sensible heat flux (${\mathcal{Q}}_H$) over a highly heterogeneous urban area. Scintillation measurements were conducted during cold season in November and December 2013, and the daytime data of 14 days were used in the analysis after quality control processes. The LAS-derived ${\mathcal{Q}}_H$ show reasonable temporal variation ranging $20{\sim}160W\;m^{-2}$ in unstable atmospheric conditions, and well compare with the measured net radiation. The LAS footprint analysis suggests that ${\mathcal{Q}}_H$ can be relatively high when the newly built-up urban area has high source contribution of the turbulent flux in the study area ('northwesterly winds'). Sensitivity tests show that the LAS-derived ${\mathcal{Q}}_H$ are highly sensitive to non-dimensional similarity function for temperature structure function parameter, but relatively less sensitive to surface aerodynamic parameters and meteorological variables (temperature and wind speed). A lower Bowen ratio also has a significant influence on the flux estimation. Overall uncertainty of the estimated daytime ${\mathcal{Q}}_H$ is expected within about 20% at an upper limit for the analysis data. It is also found that stable atmospheric conditions can be poorly determined when the scintillometry technique is applied over the highly heterogeneous urban area.

• Wind and Structures
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• v.5 no.2_3_4
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• pp.115-126
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• 2002

A mesoscale meteorological model is applied to simulate turbulent airflow and eddy shedding over the Isle of Arran, SW Scotland, UK. Under conditions of NW flow, the mountain ridge of Kintyre, located upwind of Arran, induces gravity waves that also affect the airflow over the island. The possibility to nest domains allows description of the airflow over Arran with a very high resolution grid, while also including the effects of the surrounding mainland of Scotland, in particular of the mountain ridge of Kintyre. Initialised with a stably stratified NW flow, the mesoscale model simulates quasi-stationary gravity waves over the island induced by Kintyre. Embedded in the larger scale wave trains there is continuous development of small-scale transient eddies, created at the Arran hill tops, that move downstream through the stationary wave field. Although the transient eddies are more frequently simulated on the northern island where the terrain is more pronounced, they are also produced over Tighvein, a hill of 458 m on the southern island where measurements of surface pressure and 2 m meteorological variables have been recorded at intermittent intervals between 1996 and 2000. Comparison between early observations and simulations so far show qualitatively good agreement. Overall the computations demonstrate that turbulent flow can be modelled with a horizontal resolution of 70 m, and describe turbulent eddy structure on wavelength of only a few hundred metres.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.61-64
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• 2003

This study was conducted to investigate the chemical characteristics of $PM^{10}$ at Anmyeon-do during the periods from January 1998 to December 2001. The $PM^{10}$ samples ($PM^{10}$) were collected by High Volume Air sampler (HVAS). The measured items were mass concentration of $PM^{10}$ with the major ions ($Cl^{-}$, ${SO_{4}}^{2-}$, ${NO_3}^{-}$, ${Mg}^{2+}$, ${Ca}^{2+}$, ${K}^{+}$etc.) and metallic elements (AI, Fe, Mn, Cr, Zn, Pb etc.). The chemical analysis of major ion components were made by Ion Chromatography (DX-500) and that of metallic elements were made by Inductively Coupled Plasma Spectrometer (ICP-AES, ICP-Mass). The average mass concentration of $PM^{10}$ increased substantially during the heavy dust periods (Asian Dust cases). For water-soluble ions, concentrations of ${Ca}^{2+}$, ${SO_{4}}^{2-}$ and ${NO_3}^{-}$ were remarkably enhanced. Concentrations and mass fraction of crustal elements such as Na, Mg, Ca, Fe, Mn were highly elevated, but those of pollution-derived heavy metals were appreciably decreased. The factor analysis was conducted in order to make the large and diverse data set as manageable levels and to qualitatively examine the relationship between the variables.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.274-277
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• 2008

To evaluate high-resolution wind resources for local and coastal area with complex terrain was attemped to combine the prognostic MM5 mesoscale model with CALMET diagnostic modeling this study. Firstly, MM5 was simulated for 1km resolution, nested fine domain, with FDDA using QuikSCAT seawinds data was employed to improve initial meteorological fields. Wind field and other meteorological variables from MM5 with all vertical levels used as initial guess field for CALMET. And 5 surface and 1 radio sonde observation data is performed objective analysis whole domain cells. Initial and boundary condition are given by 3 hourly RDAPS data of KMA in prognostic MM5 simulation. Geophysical data was used high-resolution terrain elevation and land cover(30 seconds) data from USGS with MM5 simulation. On the other hand SRTM 90m resolution and EGIS 30m landuse was adopted for CALMET diagnostic simulation. The simulation was performed on whole year for 2007. Vertical wind field a hour from CALMET and latest results of MM5 simulation was comparison with wind profiler(KEOP-2007 campaign) data at HAENAM site.

• 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.