• Atmosphere
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• v.25 no.4
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• pp.623-637
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• 2015

The accurate analysis of water vapor in initial of numerical weather prediction (NWP) model is required as one of the necessary conditions for the improvement of heavy rainfall prediction and reduction of spin-up time on a very-short-range forecast. To study this effect, the impact of a ground-based Global Positioning System (GPS)-Precipitable Water Vapor (PWV) on very-short-range forecast are examined. Data assimilation experiments of GPS-PWV data from 19 sites over the Korean Peninsula were conducted with Advanced Storm-scale Analysis and Prediction System (ASAPS) based on the Korea Meteorological Administration's Korea Local Analysis and Prediction System (KLAPS) included "Hot Start" as very-short-range forecast system. The GPS total water vapor was used as constraint for integrated water vapor in a variational humidity analysis in KLAPS. Two simulations of heavy rainfall events show that the precipitation forecast have improved in terms of ETS score compared to the simulation without GPS-PWV data. In the first case, the ETS for 0.5 mm of rainfall accumulated during 3 hrs over the Seoul-Gyeonggi area shows an improvement of 0.059 for initial forecast time. In other cases, the ETS improved 0.082 for late forecast time. According to a qualitative analysis, the assimilation of GPS-PWV improved on the intensity of precipitation in the strong rain band, and reduced overestimated small amounts of precipitation on the out of rain band. In the case of heavy rainfall during the rainy season in Gyeonggi province, 8 mm accompanied by the typhoon in the case was shown to increase to 15 mm of precipitation in the southern metropolitan area. The GPS-PWV assimilation was extremely beneficial to improving the initial moisture analysis and heavy rainfall forecast within 3 hrs. The GPS-PWV data on variational data assimilation have provided more useful information to improve the predictability of precipitation for very short range forecasts.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.773-786
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• 2017

This study was to analyze data of climate change impacts on social infrastructure using text-mining methodology, and to visualize the spatial information by integrating those with regional data layers. First of all, the study identified that the following social infrastructure; power, oil and resource management, transport and urban, environment, and water supply infrastructures, were affected by five kinds of climate factors (heat wave, cold wave, heavy rain, heavy snow, strong wind). Climate change impacts on social infrastructure were then analyzed and visualized by regions. The analysis resulted that transport and urban infrastructures among all kinds of infrastructure were highly impacted by climate change, and the most severe factors of the climate impacts on social infrastructure were heavy rain and heavy snow. In addition, it found out that social infrastructure located in Seoul and Gangwon-do region were relatively largely affected by climate change. This study has significance that atypical data in media was used to analyze climate change impacts on social infrastructure and the results were translated into spatial information data to analyze and visualize the climate change impacts by regions.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.2
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• pp.75-82
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• 2008

Heavy rains and typhoons are the most critical meteorological disaster occurred in the Korean peninsular. Due to the global warming, the magnitude of heavy rains and typhoons is becoming heavier resulting in more damage annually. Therefore, it is required to establish a mitigation plan to reduce the damage from meteorological disasters. To do so, in general, it is better to establish a mitigation plan for each district considering the characteristics of a district than a single mitigation plan for the entire districts without considering the characteristics of an individual district. In this study, we provide fundamental data for establishing a mitigation plan from analysis considering the frequency and damage in monetary value by heavy rain and typhoon with the geological and social characteristics of districts. The annual damage reports published by the National Emergency Management Agency, dated from 1994 to 2003, are used for the analysis. The districts are classified into six categories by the geological and social characteristics. Also, the frequency and damage in monetary value are assessed for each district. Based on them, the damage degree by heavy rain and typhoon from 1st to 4th is assigned to each district. The assigned damage degree is, then, analyzed with geological and social characteristics of each district to show the status of damage by meteorological disasters on the district.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.526-533
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• 2014

In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.

• The Korean Journal of Ecology
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• v.22 no.5
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• pp.295-298
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• 1999

This study was carried out to investigate the changes in concentration of heavy metals in throughfall, stemflow and rainfall at the survey area. The Al concentration of Pinus thunbergii forest was 1.3 times higher than those of Quercus acutissima forest at industrial area, and 2.1 times higher at urban area. The Al concentration of stemflow was 2.3 times and 113 times, 4.8 times and 55 times, respectively, higher than those of throughfall, and rainfall at both industrial and urban area. The Al concentration of rainfall was lower at industrial and urban area. The Mn concentration of Pinus thunbergii forest was 2.4 times higher than those of Quercus acutissima forest at urban area. Heavy metal concentrations in rain water were the higher in stemflow, and in the order of throughfall and rainfall. Seasonal changes of heavy metal concentration were the highest on December at industrial area, and were higher in the order of March>June>August. Seasonal changes were not remarkable at urban area. Heavy metal concentrations were higher in the order of Al>Mn>Ni at industrial area, and Mn>Al>Ni at urban area.

• Atmosphere
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• v.22 no.4
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• pp.387-400
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• 2012

This study aims at examining the sensitivity of numerical simulations to the resolution of initial and boundary data, and to an application of WRF (Weather Research and Forecasting) 3DVAR (Three Dimension Variational data Assimilation). To do this, we ran the WRF model by using GDAS (Global Data Assimilation System) FNL (Final analyses) and the KLAPS (Korea Local Analysis and Prediction System) analyses as the WRF's initial and boundary data, and by using an initial field made by assimilating the radar data to the KLAPS analyses. For the sensitivity experiment, we selected a heavy rainfall case of 21 September 2010, where there was localized torrential rain, which was recorded as 259.5 mm precipitation in a day at Seoul. The result of the simulation using the FNL as initial and boundary data (FNL exp) showed that the localized heavy rainfall area was not accurately simulated and that the simulated amount of precipitation was about 4% of the observed accumulated precipitation. That of the simulation using KLAPS analyses as initial and boundary data (KLAPC exp) showed that the localized heavy rainfall area was simulated on the northern area of Seoul-Gyeonggi area, which renders rather difference in location, and that the simulated amount was underestimated as about 6.4% of the precipitation. Finally, that of the simulation using an initial field made by assimilating the radar data to the KLAPS using 3DVAR system (KLAP3D exp) showed that the localized heavy rainfall area was located properly on Seoul-Gyeonggi area, but still the amount itself was underestimated as about 29% of the precipitation. Even though KLAP3D exp still showed an underestimation in the precipitation, it showed the best result among them. Even if it is difficult to generalize the effect of data assimilation by one case, this study showed that the radar data assimilation can somewhat improve the accuracy of the simulated precipitation.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.1
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• pp.64-71
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• 2015

Soil contamination with arsenic and heavy metals is a worldwide problem. Main objective of this research was to evaluated effects of reducing heavy metal leaching under reduced soil condition amended with industrial by-products. The contaminated soil was amended with 3% (w/w) of limestone (Ls), steel slag (SS) and acid mine drainage sludge (AMDS). Synthetic acid rain ($H_2SO_4:HNO_3=6:4$, pH 5.5 fixed) was used for feeding solution with flow rate of $0.78{\sim}0.88mL\;min^{-1}$. Results showed that similar pH and EC of leachate was observed in all treatments regardless of applied industrial by-products. However, arsenic concentration of leachate increased when industrial by-products were mixed. Meanwhile, concentration of heavy metal in the leachate decreased from 11.3 to 4.59 mg for Cd, from 92.3 to 7.93 mg for Pb, and from 11,716 to 1,788 mg for Zn via immobilization in soil with AMDS amended, respectively. Overall, application of industrial by-products can be an environmentally-friendly way to remediate soil and(or) leachate contaminated with metal(loid)s in metal mine site.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.103-106
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• 1999

The Tropical Rainfall Measuring Mission(TRMM) is a United States-Japan project for rain measurement from space. The first spaceborne Precipitation Radar(PR) has been installed aboard the TRMM satellite. The ground based validation of the TRMM satellite observations was conducted by TRMM science team through a Global Validation Program(GVP) consisted of 10 or more ground validation sites throughout the tropics. However, TRMM radar should always be validated and assessed against reference data to be used in Korean Peninsula because the rainrates measured with satellite varies by time and space. We have analyzed errors in the comparison of rainrates measured with the TRMM/PR and the ground-based instrument i.e. Automatic Weather System(AWS) by means of statistical methods. Preliminary results show that the near surface rainrate of TRMM/PR are highly correlated with ground measurements especially for the very deep convective rain clouds, though the correlation is changed according to the type and amount of precipitating clouds. Results also show that TRMM/PR instrument is inclined to underestimate the rainrate on the whole over Korea than the AWS measurement for the cases of heavy rainfall.

• Journal of Korean Society on Water Environment
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• v.22 no.4
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• pp.666-671
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• 2006

Effects of a rainfall event (July 28, 2005) on the hydrochemical characteristics of the Jungrang river, the biggest tributary of the Han river, was investigated. Significant spatial variations in the hydrochemical characteristics were observed. At JR2 location, concentrations of T-N and T-P were relatively low indicating occurrence of active oxidation in the stepped drop structure. At JR3 location, concentrations of Na, K, Cl, $NH_4-N$ and EC were elevated suggesting increased discharge from the nearby waste-water treatment plant and tributaries. The rain event diluted major dissolved ion concentrations in the river by 12~52%. The $NO_3-N$ levels were preserved during the rain then increased about twofold after rainfall, suggesting increased discharge of nitrate-contaminated groundwater. Heavy metals including Cd, Co, Cr, Cu and Pb were not detected in all water samples and the leachates from surface sediment samples. Concentrations of Fe, Mn, Al and Zn were below the Korean Drinking Water Guideline. Results of this study suggested that establishment of water-quality monitoring protocols describing temporal and spatial variations in parameters sensitive to rainfall events, relatively steady factors, and contaminant sources is required.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.26 no.1
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• pp.31-41
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• 1998

The climatic characteristics of summer in 1998 are analyzed with the weather observational data and the upper air observational data. The temperature of that period is lower than that of normal years and the precipitation is larger. Due to the heavy rainfall which started at July 31, rain pured down compared to normal years and the maximum precipitation recorded at the many observational stations, particularly in Seoul, Kyunggi-Do region and mountanious districts like Taegwallyong, Mt. Sokri and Mt. Chiri. The patterns of general circulations in 1982/98 and 1997/98 are compared each other and are analyzed. The anomaly patterns of stream functions on winter in two El Nio years are simialr. The counterclockwise circulation occurred near the date line and the clockwise circulation was appeared near the Hwanam region and Alaska. These patterns are opposite to those of La Nia year, 1988/89. And the anomaly patterns of 500hPa geopotential height in summer are similar, too. The low temperature and much rain were dominated in summer of 1997/98. These phenomena is similar to the existing results of research, that temperature is low and precipitation is large in summer of El Nio years.