• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.5
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• pp.223-233
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• 2018

The predictability of winter storm waves using KMA's operational wind forecasts has been studied to predict wind waves and swells in the East coast of Korea using SWAN. The nested model were employed along the East coast of Korea to simulate the wave transformation in the coastal area and wave dissipation term of whitecapping is optimized to improve swell prediction accuracy. In this study, KMA's operational meteorological models (RDAPS and LDAPS) are used as input wind fields. In order to evaluate model accuracy, we also simulate wind waves and swells using ECMWF reanalysis and KIOST WRF wind and they are compared with the KMA's operational wave model and the wave measurement data on the offshore and onshore stations. As a result, it has the lowest RMSE and the highest correlation coefficient in the onshore when the input wind fields are KMA's operational meteorological forecasts. In the offshore, all of the simulate results shows good agreements with similar error statistics. It means that it is very feasible to use SWAN model with the modified whitecapping factor and KMA's operational meteorological forecasts for predicting the wind waves and swells in the East coast of Korea.

• 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.

• Atmosphere
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• v.28 no.4
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• pp.369-382
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• 2018

Planetary boundary layer height (PBLH), produced by the Local Data Assimilation and Prediction System (LDAPS), was verified using RawinSonde (RS) data obtained from observation at Daegwallyeong (DGW) and Sokcho (SCW) during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games (ICE-POP 2018). The PBLH was calculated using RS data by applying the bulk Richardson number and the parcel method. This calculated PBLH was then compared to the values produced by LDAPS. The PBLH simulations for DGW and SCW were generally underestimation. However, the PBLH was an overestimation from surface to 200 m and 450 m at DGW and SCW, respectively; this result of model's failure to correctly simulate the Surface Boundary Layer (SBL) and the Mixing Layer (ML) as the PBLH. When the accuracy of the PBLH simulation is low, large errors are seen in the mid- and low-level humidity. The highest frequencies of Planetary boundary layer (PBL) types, calculated by the LDAPS at DGW and SCW, were presented as types Ι and II, respectively. Analysis of meteorological factors according to the PBL types indicate that the PBLH of the existing stratocumulus were overestimated when the mid- and low-level humidity errors were large. If the instabilities of the surface and vertical mixing into clouds are considered important factors affecting the estimation of PBLH into model, then mid- and low-level humidity should also be considered important factors influencing PBLH simulation performance.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.188-197
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• 2022

We develop a coastal wave forecasting system by using the unstructured grid based on sea wind data of Global Data Assimilation and Prediction System. The verification is performed to examine the performance and accuracy of the wave model. Since the conventional grid has limited wave forecasting on complex coastlines and bathymetry, the unstructured grid system is applied for precise numerical simulation, and applicability for operational support is evaluated. Both grid systems show similar prediction trends in offshore and coastal areas, and the difference in prediction errors according to the grid system is not large. In addition, the applicability of the operational wave forecasting system is confirmed by dramatically reducing the model execution time of the unstructured grid under the same conditions.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.6
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• pp.158-169
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• 2004

A method for predicting the short-term dynamic line ratings in overhead transmission lines using real-time weather forecast data is proposed in this paper. Through some inspections for the 3-hour interval forecasting factors such as ambient temperature, wind speed grade and weather code given by KMA(Korea Meteorological Administration), correlation properties between forecast weather data and actual measured data are analyzed. To use these variable in determining the dynamic line ratings, they are changed into suitable numerical values. Furthermore adaptive neuro-fuzzy systems to improve reliabilities for wind speed and solar heat radiation ate designed It was verified that the forecast weather data can be used to predict the line rating with reliable. As a result it can be possible that the proposed predicting system can be effectively utilized by their anticipation a short-time in advance.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.57-59
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• 2018

오늘날 우리나라의 강수량은 대부분 하절기에 집중되고 있으며 국지성 집중호우에 의한 돌발홍수 발생으로 인명피해가 크게 발생하고 있는 실정이다. 이를 대비하기 위해서는 빠른 시간 안에 좁은 지역에 대한 기상정보 분석이 필요하다. 본 논문에서는 보다 효과적인 기상예보를 위하여 홍수예보모델을 기반으로 모의테스트를 진행 후 결과 분석을 바탕으로 고성능 컴퓨팅 (HPC) 기반 홍수예보시스템을 설계하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.147-149
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• 2015

ECDIS(전자해도표시장치) 기반에 선박의 연료 효율성 모니터링 시스템인 SEEMS(Ship Energy Efficiency Monitoring System)를 연계하여 표시하고, 해상 기상 예보 정보를 도식화 하는 방법에 관하여 연구하였다.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2018.06a
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• pp.117-118
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• 2018

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.19.1-19.1
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• 2011

국가기상위성센터는 2013년 태양활동 극대기를 대비하고 천리안 위성의 안정적인 운영을 위하여 우주기상업무를 추진하고 있다. 2009년에 수행된 우주기상업무 기본계획 수립을 위한 기획연구를 시작으로, 2010년에는 국내 GNSS 자료를 준실시간으로 수집하여 총전자밀도(TEC)를 산출하는 시스템을 개발하였으며, 외국 우주기상 자료를 수집하여 태양 영상을 비롯한 우주환경인자를 실시간으로 제공하기 위한 우주기상 테스트베드를 시험운영하고 있다. 또한 대국민 우주기상 서비스를 위한 우주기상 예측모델 개발을 5개년에 걸쳐 단계적으로 진행하고 있다. 미국의 NOAA-SWPC, NASA-GSFC와 같은 우주기상 선진기관들과의 2013년 태양활동 극대기에 대비한 우주기상 감시, 예측모델 및 예보서비스에 대한 활발한 교류 협력을 통해 기상청의 우주기상예보 역량을 늘려나갈 계획이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.317-317
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• 2019

기상청에서는 시스템 이용자의 편의와 자료의 활용 증진을 위해 분리되어 있던 수문기상과 가뭄정보를 하나로 통합하여 '수문기상 가뭄정보 시스템(https://hydro.kma.go.kr)을 2017년 8월 1일부터 운영하고 있다. 본 시스템은 일반국민과 물관리 유관기관(회원)을 대상으로 관측, 수문기상 감시 예측, 기상 가뭄분석 전망으로 나눠 정보를 생산하여 서비스가 제공하고 있다. 수문기상 서비스는 관측 강수량(기상청, 유관기관), 기상청 위성 토양수분량 및 증발산량 자료와 레이더 관측 자료(Radar AWS Rainrate, RAR)를 GIS 기반 유역단위별(4대강권, 대권역, 중권역, 표준유역단위)로 관측 정보를 제공하며, UM(3km), 멀티모델앙상블, 레이더(MAPLE), 유역강수지수자료들로 예측 서비스를 제공하고 있다. 또한, 메타정보를 통해 유역별, 관측소별 상세조회가 가능하여 원하는 유역 또는 관측소를 선택 시 GIS지도에 위치가 표시되며 선택 지점의 정보를 손쉽게 확인할 수 있다. 가뭄 정보는 기상 가뭄 예보 정보와 가뭄 감시 정보를 제공하고 있다. 기상 가뭄 예보 정보는 매주 금요일에 발표되고 있는 기상 가뭄 예보 1개월 전망과 매월 10일경 관계부처(행정안전부, 기상청, 환경부, 농림축산식품부) 합동으로 발표하고 있는 가뭄 예 경보 3개월 전망자료를 제공하고 있으며, GIS 기반 행정구역 및 유역별로 나눠 여러 가지 가뭄지수(표준강수지수, 표준강수증발산지수, 강수평년비, 유효가뭄지수)를 활용하여 기상 가뭄 감시 정보를 제공하고 있다. 또한, 가뭄 감시 현황 정보는 다양한 형태(시계열, 가뭄지수 조회 및 다운로드, 분포도 비교)로도 확인할 수 있으며, 강수량분석 통계(누적 강수량, 강수량 순위, 무강수일수) 정보를 제공한다. 그 밖에 관측 자료(강수량 분포도, 토양수분량, 증발산량 등), 월별 언론모니터링 자료 등을 제공하고 있다. 향후 수문기상과 가뭄 재해에 선제적으로 대응하여 안정적인 물관리를 지원하고 자료의 신뢰도를 지속적으로 제고하여 우리나라에 맞는 수문기상 가뭄정보 시스템으로 거듭나도록 노력해 나갈 것이다.