• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.922-934
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• 2015

In this paper, The classification between precipitation echo(PRE) and non-precipitation echo(N-PRE) (including ground echo and clear echo) is carried out from weather radar data using neuro-fuzzy algorithm. In order to classify between PRE and N-PRE, Input variables are built up through characteristic analysis of radar data. First, the event classifier as the first classification step is designed to classify precipitation event and non-precipitation event using input variables of RBFNNs such as DZ, DZ of Frequency(DZ_FR), SDZ, SDZ of Frequency(SDZ_FR), VGZ, VGZ of Frequency(VGZ_FR). After the event classification, in the precipitation event including non-precipitation echo, the non-precipitation echo is completely removed by the echo classifier of the second classifier step that is built as Type-2 FCM based RBFNNs. Also, parameters of classification system are acquired for effective performance using PSO(Particle Swarm Optimization). The performance results of the proposed echo classifier are compared with CZ. In the sequel, the proposed model architectures which use event classifier as well as the echo classifier of Interval Type-2 FCM based RBFNN show the superiority of output performance when compared with the conventional echo classifier based on RBFNN.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.265-271
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• 2020

Automotive radar that is one of the most important equipment in high-tech vehicles, is commonly used to detect the speed and range of objects such as cars. In this paper, in addition to objects detection, a method of retrieving precipitation information using the automotive radar data is proposed. The proposed method is based on the fact that the degree of attenuation of the returned radar signal differs depending on the precipitation intensity and the assumption that the distribution of precipitation is constant in short spatial and temporal observation. The purpose of this paper is to assesses the possibility of retrieving precipitation information using a vehicle radar. To verify the feasibility of the proposed method during actual driving, a method of estimating precipitation information for each time segment of various precipitation events was applied. From the results of driving field experiments, it was found that the proposed method is suitable for estimating precipitation information in various rainfall types.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.39-47
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• 2017

Precipitation is an important component for hydrological and water control study. In general, AWS data provides more accurate but low dense information for precipitation while radar data gives less accurate but high dense information. The objective of this study is to construct adjusted precipitation field based on hierarchical spatial model combining radar data and AWS data. Here, we consider a Bayesian hierarchical model with spatial structure for hourly accumulated precipitation. In addition, we also consider a redistribution of hourly precipitation to 2.5 minute precipitation. Through real data analysis, it has been shown that the proposed approach provides more reasonable precipitation field.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.483-492
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• 2017

Precipitation is one of key components in hydrological modeling and water balance studies. A comprehensive, optimized and sustainable water balance monitoring requires the availability of accurate precipitation data. The amount of precipitation measured in a gauge is less than the actual precipitation reaching the ground. The objective of this study is to determine the wind-induced under-catch of solid precipitation and develop a continuous adjustment function for measurements of all types of winter precipitation (from rain to dry snow), which can be used for operational measurements based on data available at standard automatic weather stations. This study provides Bayesian analysis for the systematic structure of catch ratio in precipitation measurement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.265-276
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• 2011

Precipitation data and groundwater level data were collected for Korean peninsular and Jeju island. The relationship between precipitation and groundwater level and the correlation between the moving average of precipitation and goundwater level were analyzed. Critical infiltration, which is the spatially averaged maximum daily infiltration depth over interested region, is considered when the precipitation data was modified for moving average process and correlation between the moving average of modified precipitation and groundwater level. High correlation regions, which have greater than 0.6 correlation coefficients, were selected after the analysis with ciritical infiltration. Twenty-six regions were selected for high correlation regions. If we divide the regions by administrative district, there are nine regions for Gyungsang-Do, five regions for Chunchung-Do, four regions for Gyunggi-Do and Gangwon-Do, three regions for Jolla-Do, and one region for Jeju island. The groundwater level data for high correlation regions shows obvious response after precipitation event and there are few cases with abrupt change in groundwater level without precipitation-related event.

• Atmosphere
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• v.27 no.1
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• pp.105-118
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• 2017

This study assesses the performance of the Weather Research and Forecasting (WRF) model in reproducing regional climate over CORDEX-East Asia Phase 2 domain with different cumulus parameterization schemes [Kain-Fritch (KF), Betts-Miller-Janjic (BM), and Grell-Devenyi-Ensemble (GD)]. The model is integrated for 27 months from January 1979 to March 1981 and the initial and boundary conditions are derived from European Centre for Medium-Range Weather Forecast Interim Reanalysis (ERA-Interim). The WRF model reasonably reproduces the temperature and precipitation characteristics over East Asia, but the regional scale responses are very sensitive to cumulus parameterization schemes. In terms of mean bias, WRF model with BM scheme shows the best performance in terms of summer/winter mean precipitation as well as summer mean temperature throughout the North East Asia. In contrast, the seasonal mean precipitation is generally overestimated (underestimated) by KF (GD) scheme. In addition, the seasonal variation of the temperature and precipitation is well simulated by WRF model, but with an overestimation in summer precipitation derived from KF experiment and with an underestimation in wet season precipitation from BM and GD schemes. Also, the frequency distribution of daily precipitation derived from KF and BM experiments (GD experiment) is well reproduced, except for the overestimation (underestimation) in the intensity range above (less) then $2.5mm\;d^{-1}$. In the case of the amount of daily precipitation, all experiments tend to underestimate (overestimate) the amount of daily precipitation in the low-intensity range < $4mm\;d^{-1}$ (high-intensity range > $12mm\;d^{-1}$). This type of error is largest in the KF experiment.

• Atmosphere
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• v.20 no.3
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• pp.229-238
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• 2010

The 1,000~500 hPa thickness and the $0^{\circ}C$ isotherm at 850 hPa have been used as the traditional predictors for wintertime precipitation-type forecasts. New approaches are taking on added significance as preexistence method of determination for wintertime precipitation-type exhibits more or less prevalent false alarms. Moreover thicknesses and thermodynamic profiles from ordinary upper-air observation were not adequate to monitor the atmospheric structure. In this regard, Microwave radiometric profiler microwave radiometer is useful in wintertime precipitation-type forecasts because radiometric measurements provide soundings at high temporal resolution. In this study, the determination and the predictability of wintertime precipitation-type were examined by using the calculated thicknesses, temperature of 850 hPa (T850) from a microwave radiometer, and surface observation at National Center for Intensive Observation of severe weather (NCIO) located at Haenam, Korea. The critical values for traditional predictors (thickness of 1000~500 hPa and T850) were evaluated and adjusted to Haenam region because snow rarely occurred with a 1000-500 hPa thickness > 5,300 m and T850 > $-10^{\circ}C$. Three thicknesses (e.g., 1,000~850, 1000~700, and 850~700 hPa thickness), T850, surface air temperature, and wet-bulb temperature were also evaluated as the additional predictors. A simple nomogram and a flow chart were finally designed to determine the wintertime precipitation-type using the microwave radiometer. The skill scores for the predictability of precipitation-type determination are considerably improved and the predictors showed the temporal variations in 12 hours before precipitation. We can monitor the hit and run snowfall in winter successful by realtime watch of the predictors, especially in commutes of big cities.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.99-109
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• 2009

In this study, often the spatial distribution of precipitation was analyzed using the quantile with regional frequency analysis and spatial analysis to find out the detail distribution of extreme precipitation for preventing the disaster in the region of Gangwon. The hourly precipitation data of 66 stations in Gangwon were used. As the results of regional frequency analysis, it shows that the generalized logistic (GLO) distribution is the best for the region of Gangwon. As the results of spatial analysis, the quaniles have high vaules nearby Seolakdong, Daegwallyeong and Cheongil as the duration of precipitation increase, and the change of spatial distribution occurs severely according to the duration of precipitation. The spatial characteristics of precipitation appears clearly as the return period of quantile increases. As the results of the spatial distribution of precipitation in Gangwon heavy quantiles usually are appeared in Yongdong, and the spatial distributions of quantile in Yongseo are various according to the duration and the return period of quantile. Therefore, to estimate more accurate quantiles in Gangwon, various geographical and weather conditions are considered additionally for the regional precipitation frequency analysis.

• Journal of Environmental Science International
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• v.23 no.4
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• pp.553-560
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• 2014

The rainfall-runoff characteristics in Jeju Island significantly differ from those in inland, due to highly permeable geologic features driven by volcanic island. Streams are usually sustained in the dry conditions and thereby the rainfall-runoff characteristics changes in terms of initiating stream discharge and its types, depending highly on the antecedent precipitation. Among various the rainfall-runoff characteristics, lag time mainly used for flood warning system in river and direct runoff ratio for determining water budget to estimate groundwater recharge quantity are practically crucial. They are expected to vary accordingly with the given antecedent precipitation. This study assessed the lag time in the measured hydrograph and direct runoff ratio, which are especially in the upstream watershed having the outlet as $2^{nd}$ Dongsan bridge of Han stream, Jeju, based upon several typhoon events such as Khanun, Bolaven, Tembin, Sanba as well as a specific heavy rainfall event in August 23, 2012. As results, considering that the lag time changed a bit over the rainfall events, the averaged lag time without antecedent precipitation was around 1.5 hour, but it became increased with antecedent precipitation. Though the direct run-off ratio showed similar percentages (i.e., 23%)without antecedent precipitation, it was substantially increased up to around 45% when antecedent precipitation existed. In addition, the direct run-off ration without antecedent precipitation was also very high (43.8%), especially when there was extremely heavy rainfall event in the more than five hundreds return period such as typhoon Sanba.

• Microbiology and Biotechnology Letters
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• v.42 no.1
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• pp.25-31
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• 2014

Fractional precipitation is a simple method for purifying (+)-dihydromyricetin extracted from biomass. However, the fractional precipitation process has been inherently problematic due to the lengthy precipitation time that is required. The fractional precipitation time was shortened and (+)-dihydromyricetin yield was improved by increasing the surface area per working volume (S/V) of the reacting solution through the addition of a cation exchange resin (Amberlite 200, Amberlite IR 120Na, Amberlite IR 120H, or Amberlite IRC 50). Most of the (+)-dihydromyricetin (>90%) could be obtained after about 16 h of fractional precipitation using Amberlite 200. Since high-purity (+)-dihydromyricetin can be obtained at a high yield and the precipitation time can be reduced by increasing the surface area available for precipitation, this improved method is expected to minimize solvent usage and the size and complexity of the high performance liquid chromatography operation required for (+)-dihydromyricetin purification.