• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.297-305
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• 2008

Recently, kernel methods have attracted great interests in the areas of pattern classification, function approximation, and anomaly detection. The role of the kernel is particularly important in the methods such as SVM(support vector machine) and KPCA(kernel principal component analysis), for it can generalize the conventional linear machines to be capable of efficiently handling nonlinearities. This paper considers the problem of combining radar and rain gauge observations utilizing the regression approach based on the kernel-based gaussian process and support vector learning. The data-assimilation results of the considered methods are reported for the radar and rain gauge observations collected over the region covering parts of Gangwon, Kyungbuk, and Chungbuk provinces of Korea, along with performance comparison.

• Atmosphere
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• v.26 no.1
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• pp.47-58
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• 2016

On 10 July 2014, tornado outbreak occurred over Goyang province in Korea. This was the first supercell tornado ever reported or documented in Korea. The characteristics of the supercell tornado were investigated using an X-band polarimetric radar, surface meteorological observation, wind profiler, and operational numerical weather prediction (Regional Data Assimilation and Prediction System, RDAPS). The supercell tornado developed along a preexisting dryline that was contributed to surface wind shear. The radar analyses examined here show that the supercell tornado indicated a hook echo with mesocyclone. The decending reflectivity core as well was detected before tornadogenesis and prior to intensification of supercell. The supercell tornado exhibited characteristics similar to typical supercell tornado over the Great Plains of the United States, such as hook echo, bounded weak echo region, and slower movement speed relative to the mean wind. Compared to the typical supercell tornado over U.S., this tornado showed horizontal scale of the mesocyclone was relatively smaller and left-mover.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.33-33
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• 2011

현재 우리나라 기상청에서는 단기, 중기 및 장기 예보자료를 생산하고 있으나, 이들 자료는 단순히 일기 예보에 치중되어 생산되고 있어 강우-유출해석에 직접 적용하기에는 시 공간 해상도가 크고 정량적 강수예측의 정확도가 미흡하다. 이에 기상 및 수자원분야에서는 정확도 개선을 위해서 관측강우와 예측강우의 비교 분석을 통해 편차를 산정하여 예측강수를 보정하는 기법을 적용하고 있다. 다만, 기존의 편차보정방법은 보정인자로 강수량만을 고려하기 때문에 정확도 개선에는 한계가 존재한다. 따라서 본 연구에서는 수자원분야의 수치예보자료의 정확도를 향상시키기 위해 규모, 발생영역에 대한 강수의 특성을 고려한 강수예측자료의 편차보정 방법을 제안하고 이를 강우-유출모델에 적용하여 개선정도를 평가하고자 한다. 이에 적용유역을 춘천댐상류유역으로 선정하고 국내 기상청의 RDAPS(Regional Data Assimilation and Prediction System)수치예보자료, 지점강우자료, radar자료의 수문기상자료와 지형자료를 수집하였다. 화천, 평화의 댐 일부 미계측유역의 관측자료로 radar자료를 이용하였다. 이상의 자료를 토대로 강우강도 및 규모, 영향범위를 고려한 예측강우의 편차를 산정하여 RDAPS 수치예보자료의 정확도를 개선하고 평가하였다. 이는 해당 유역뿐만 아니라 주변 유역의 정보를 이용하여 예측강우의 발생위치에 대한 오차를 고려한 방법으로, 각 영역별로 예측강우의 편차보정계수를 산정하여 적용하였다. 또한, 이전시간대의 강우 편차에 대한 오차를 줄이기 위해 정규분포방법을 이용한 Ensemble 편차보정계수를 산정하고 최근 생산된 수치예보자료에 적용하여 확률예측강우를 산정하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.155-155
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• 2018

Uncertainty in flood forecasting using a coupled meteorological and hydrological model is arisen from various sources, especially the uncertainty comes from the inaccuracy of Quantitative Precipitation Forecasts (QPFs). In order to improve the capability of flood forecast, the uncertainty estimation and mitigation are required to perform. This study is conducted to investigate and reduce such uncertainty. First, ensemble QPFs are generated by using Monte - Carlo simulation, then each ensemble member is forced as input for a hydrological model to obtain ensemble streamflow prediction. Likelihood measures are evaluated to identify feasible member. These members are retained to define upper and lower limits of the uncertainty interval and assess the uncertainty. To mitigate the uncertainty for very short lead time, a blending method, which merges the ensemble QPFs with radar-based rainfall prediction considering both qualitative and quantitative skills, is proposed. Finally, blending bias ratios, which are estimated from previous time step, are used to update the members over total lead time. The proposed method is verified for the two flood events in 2013 and 2016 in the Yeonguol and Soyang watersheds that are located in the Han River basin, South Korea. The uncertainty in flood forecasting using a coupled Local Data Assimilation and Prediction System (LDAPS) and Sejong University Rainfall - Runoff (SURR) model is investigated and then mitigated by blending the generated ensemble LDAPS members with radar-based rainfall prediction that uses McGill algorithm for precipitation nowcasting by Lagrangian extrapolation (MAPLE). The results show that the uncertainty of flood forecasting using the coupled model increases when the lead time is longer. The mitigation method indicates its effectiveness for mitigating the uncertainty with the increases of the percentage of feasible member (POFM) and the ratio of the number of observations that fall into the uncertainty interval (p-factor).

• Proceedings of the KSRS Conference
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• v.1
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• pp.142-145
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• 2006

The synergism of active and passive microwave techniques for hurricane ocean wind remote sensing is explored. We performed the analysis of Windsat data for Atlantic hurricanes in 2003-2005. The polarimetric third Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the NOAA HWind wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1589-1597
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• 2021

Submarine groundwater discharge (SGD) in coastal areas is gaining importance as a major transport route that bring nutrients and trace metals into the ocean. This paper describes the analysis of the seasonal changes and spatiotemporal characteristicsthrough the modeling monthly SGD for 35 years from 1986 to 2020 for the Nakdong river basin. In this study, we extracted 210 watersheds and SGD estimation points using the SRTM (Shuttle Radar Topography Mission) DEM (Digital Elevation Model). The average annual SGD of the Nakdong River basin was estimated to be 466.7 m²/yr from the FLDAS (Famine Early Warning Systems Network Land Data Assimilation System) recharge data of 10 km which is the highest resolution global model applicable to Korea. There was no significant time-series variation of SGD in the Nakdong river basin, but the concentrated period of SGD was expanded from summer to autumn. In addition, it was confirmed that there is a large amount of SGD regardless of the season in coastal area nearby large rivers, and the trend has slightly increased since the 1980s. The characteristics are considered to be related to the change in the major precipitation period in the study area, and spatially it is due to the high baseflow-groundwater in the vicinity of large rivers. This study is a precedentstudy that presents a modeling technique to explore the characteristics of SGD in Korea, and is expected to be useful as foundational information for coastal management and evaluating the impact of SGD to the ocean.

• Journal of the Korean earth science society
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• v.22 no.3
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• pp.186-194
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• 2001

The operational meso-scale short range NWP system was developed for Cheju Regional Meteorological Office located at Cheju island, Korea. The Central Meteorological Service Center, KMA has reported the information on numerical weather prediction every 12 hours. But this information is not enough to determine the detail forecast for the regional meteorological office because the terrain of the Korean peninsula is very complex and the resolution of the numerical model provided by KMA headquarter is too coarse to resolve the local severe weather system such as heavy rainfall. LAPS and MM5 models were chosen for three-dimentional data assimilation and numerical weather prediction tools respectively. LAPS was designed to provide the initial data to all regional numerical prediction models including MM5. Synoptic observational data from GTS, satellite brightness temperature data from GMS-5 and the composite reflectivity data from 5 radar sites were used in the LAPS data assimilation for producing the initial data. MM5 was performed on PC-cluster based on 16 pentium CPUs which was one of the cheapest distributed parallel computer in these days. We named this system as Halla Short Range Prediction System (HSRPS). HSRPS was verified by heavy rainfall case in July 9, 1999, it showed that HSRPS well resolved local severe weather which was not simulated by 30 km MM5/KMA. Especially, the structure of rainfall amount was very close to the corresponding observation. HSRPS will be operating every 6 hours in the Cheju Regional Meteorological Office from April 2000.

• Journal of the Korean earth science society
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• v.39 no.4
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• pp.305-316
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• 2018

Satellite-derived sea surface winds (SSWs) and atmospheric motion vectors (AMVs) over the global ocean, particularly including the areas in and around tropical cyclones (TCs), have been provided in a real-time and continuous manner. More and better information is now derived from technologically improved multiple satellite missions and wind retrieving techniques. The status and prospects of key SSW products retrieved from scatterometers, passive microwave radiometers, synthetic aperture radar, and altimeters as well as AMVs derived by tracking features from multiple geostationary satellites are reviewed here. The quality and error characteristics, limitations, and challenges of satellite wind observations described in the literature, which need to be carefully considered to apply the observations for both operational and scientific uses, i.e., assimilation in numerical weather forecasting, are also described. Additionally, on-going efforts toward merging them, particularly for monitoring three-dimensional TC wind fields in a real-time and continuous manner and for providing global profiles of high-quality wind observations with the new mission are introduced. Future research is recommended to develop plans for providing more and better SSW and AMV products in a real-time and continuous manner from existing and new missions.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1515-1519
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• 2006

본 연구에서는 초단시간 강수예보(VSRF, Very Short-Range Forecast of precipitation) 시스템 구축 현황을 소개하고자 한다. VSRF 모델은 레이더 반사도 자료와 지상 AWS 자료를 이용하여 레이더-AWS 강우강도를 산출하는 강수분석과정과 분석된 강수량 자료와 중규모 수치예보장을 사용하여 외삽법에 의한 초단시간 강수예보를 수행하는 예보과정, 실시간으로 산출된 강수예보 자료를 검증하고 홈페이지에 제공하는 자료지원과정으로 구성된다. 본 연구에서는 모델의 예보능력을 향상시키기 위해 크게 두 가지 측면에서 모델을 개선하였다. 첫째는 모델의 입력자료인 레이더-AWS 강우강도 자료를 기상연구소 원격탐사연구실에서 운영하던 WPMM (Window Probability Matching Method)과 기상청 기상레이더과에서 운영하던 RQPE(Radar Quantitative Precipitation Estimation)의 알고리즘을 통합하여 정확한 강우강도 자료인 레이더-AWS 강우강도(RAR, Radar-AWS Rain rate) 시스템을 구축하여 개선하였으며, 둘째는 외삽과정을 통한 예보가 3시간이 지나면 예측능력이 감소하는 문제점을 보완하기 위해 현업 중규모 모델(RDAPS, Regional Data Assimilation and Prediction System)의 예측강수와 병합하여 모델을 개선하였다. 또한 이를 시계열 검증 및 공간 검증하는 실시간 검증 시스템을 구축하여 실시간으로 모델의 정확성을 평가하고 있다. 그 결과 입력자료 개선을 통한 모델의 정확도는 크게 향상된 결과는 볼 수 없었지만 미약하게 향상된 것을 확인할 수 있었으며, 모델의 병합을 통한 모델의 개선은 예측 3시간 이후부터는 50% 정도 향상되었다.의 대안을 제시하고자 한다.X>${\mu}_{max,A}$는 최대암모니아 섭취률을 이용하여 구한 결과 $0.65d^{-1}$로 나타났다.EX>$60%{\sim}87%$가 수심 10m 이내에 분포하였고, 녹조강과 남조강이 우점하는 하절기에는 5m 이내에 주로 분포하였다. 취수탑 지점의 수심이 연중 $25{\sim}35m$를 유지하는 H호의 경우 간헐식 폭기장치를 가동하는 기간은 물론 그 외 기간에도 취수구의 심도를 표층 10m 이하로 유지 할 경우 전체 조류 유입량을 60% 이상 저감할 수 있을 것으로 조사되었다.심볼 및 색채 디자인 등의 작업이 수반되어야 하며, 이들을 고려한 인터넷용 GIS기본도를 신규 제작한다. 상습침수지구와 관련된 각종 GIS데이타와 각 기관이 보유하고 있는 공공정보 가운데 공간정보와 연계되어야 하는 자료를 인터넷 GIS를 이용하여 효율적으로 관리하기 위해서는 단계별 구축전략이 필요하다. 따라서 본 논문에서는 인터넷 GIS를 이용하여 상습침수구역관련 정보를 검색, 처리 및 분석할 수 있는 상습침수 구역 종합정보화 시스템을 구축토록 하였다.N, 항목에서 보 상류가 높게 나타났으나, 철거되지 않은 검전보나 안양대교보에 비해 그 차이가 크지 않은 것으로 나타났다.의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에