• Title/Summary/Keyword: Korea automatic weather system

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A Study on Segmentation and Priority of Tactical Considerations (METT+TC) (전술적 고려요소 (METT+TC)의 세분화 및 우선순위 결정에 관한 연구)

  • Han, Seung-Jo;Park, Joon-Hyoung
    • Journal of Digital Convergence
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    • v.14 no.10
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    • pp.173-181
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    • 2016
  • The objective of this study is to subdivide the tactical considerations (METT+TC; Mission, Enemy, Terrain & Weather, Troops available, Time available, Civil considerations) through Delphi method and prioritize those via AHP (Analytic Hierarchy Process). Though it has been taken for granted that the tactical considerations were inevitable for decision making relating to military operations, their segmentation and priority have not been studied sufficiently in military. The data for Delphi method and AHP were based on interview with military experts and questionnaires answered by those. Six tactical considerations were segmented into 34 sub-considerations by Delphi, and Six tactical considerations and 34 sub-ones were prioritized through AHP in attack and defense aspects. If the research results will be embedded into database of automatic command and control system (e.g. ACTIS; Army Tactical Command Information System), effective decision-making process will get easier and faster.

Design of Very Short-term Precipitation Forecasting Classifier Based on Polynomial Radial Basis Function Neural Networks for the Effective Extraction of Predictive Factors (예보인자의 효과적 추출을 위한 다항식 방사형 기저 함수 신경회로망 기반 초단기 강수예측 분류기의 설계)

  • Kim, Hyun-Myung;Oh, Sung-Kwun;Kim, Hyun-Ki
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.1
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    • pp.128-135
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    • 2015
  • In this study, we develop the very short-term precipitation forecasting model as well as classifier based on polynomial radial basis function neural networks by using AWS(Automatic Weather Station) and KLAPS(Korea Local Analysis and Prediction System) meteorological data. The polynomial-based radial basis function neural networks is designed to realize precipitation forecasting model as well as classifier. The structure of the proposed RBFNNs consists of three modules such as condition, conclusion, and inference phase. The input space of the condition phase is divided by using Fuzzy C-means(FCM) and the local area of the conclusion phase is represented as four types of polynomial functions. The coefficients of connection weights are estimated by weighted least square estimation(WLSE) for modeling as well as least square estimation(LSE) method for classifier. The final output of the inference phase is obtained through fuzzy inference method. The essential parameters of the proposed model and classifier such ad input variable, polynomial order type, the number of rules, and fuzzification coefficient are optimized by means of Particle Swarm Optimization(PSO) and Differential Evolution(DE). The performance of the proposed precipitation forecasting system is evaluated by using KLAPS meteorological data.

Analysis of Correlation between Particulate Matter in the Atmosphere and Rainwater Quality During Spring and Summer of 2020 (봄·여름철 대기 중 미세먼지와 빗물 수질 상관성 분석)

  • Park, Hyemin;Kim, Taeyong;Heo, Junyong;Yang, Minjune
    • Korean Journal of Remote Sensing
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    • v.37 no.6_2
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    • pp.1859-1867
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    • 2021
  • This study investigated seasonal characteristics of the particulate matter (PM) in the atmosphere and rainwater quality in Busan, South Korea, and evaluated the seasonal effect of PM10 concentration in the atmosphere on the rainwater quality using multivariate statistical analysis. The concentration of PM in the atmosphere and meteorological observations(daily precipitation amount and rainfall intensity) are obtained from automatic weather systems (AWS) by the Korea Meteorological Administration (KMA) from March 2020 to August 2020. Rainwater samples (n = 216, 13 rain events) were continuously collected from the beginning of the precipitation using the rainwater collecting device at Pukyong National University. The samples were analyzed for pH, EC (electrical conductivity), water-soluble cations(Na+, Mg2+, K+, Ca2+, and NH4+), and anions(Cl-, NO3-, and SO42-). The concentration of PM10 in the atmosphere was steadily measured before and after the precipitation with a custom-built PM sensor node. The measured data were analyzed using principal component analysis (PCA) and Pearson correlation analysis to identify relationships between the concentration of PM10 in the atmosphere and rainwater quality. In spring, the daily average concentration of PM10 (34.11 ㎍/m3) and PM2.5 (19.23 ㎍/m3) in the atmosphere were relatively high, while the value of daily precipitation amount and rainfall intensity were relatively low. In addition, the concentration of PM10 in the atmosphere showed a significant positive correlation with the concentration of water-soluble ions (r = 0.99) and EC (r = 0.95) and a negative correlation with the pH (r = -0.84) of rainwater samples. In summer, the daily average concentration of PM10 (27.79 ㎍/m3) and PM2.5 (17.41 ㎍/m3) in the atmosphere were relatively low, and the maximum rainfall intensity was 81.6 mm/h, recording a large amount of rain for a long time. The results indicated that there was no statistically significant correlation between the concentration of PM10 in the atmosphere and rainwater quality in summer.

A Feasibility Study on the RPM and Engine Power Estimation Based on the Combination of AIS and ECMWF Database to Replace the Full-scale Measurement (실선계측 데이터 대체를 위한 AIS 및 ECMWF 데이터베이스 조합을 이용한 LNGC의 분당 회전수 및 동력 추정에 관한 타당성 연구)

  • You, Youngjun;Kim, Jaehan;Seo, Min-Guk
    • Journal of the Society of Naval Architects of Korea
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    • v.54 no.6
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    • pp.501-514
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    • 2017
  • In the previous research, a study was carried out to estimate the actual performance such as the propeller Revolution Per Minute (RPM) and engine power of a Liquefied Natural Gas Carrier (LNGC) using the full-scale measurement data. After the predicted RPM and engine power were verified by comparing those with the measured values, the suggested method was regarded to be acceptable. However, there was a limitation to apply the method on the prediction of the RPM and engine power of a ship. Since the information of route, speed, and environmental conditions required for estimating the RPM and engine power is generally regarded as the intellectual property of a shipping company, it is difficult to secure the information on a shipyard. In this paper, the RPM and engine power of the 151K LNGC was estimated using the combination of Automatic Identification System (AIS) and European Centre for Medium-Range Weather Forecasts (ECMWF) database in order to replace the full-scale measurement. The simulation approach, which was suggested in the previous research, was identically applied to the prediction of RPM and engine power. After the results based on the AIS and ECMWF database were compared with those obtained from the full-scale measurement data, the feasibility was briefly reviewed.

A High-Resolution Agro-Climatic Dataset for Assessment of Climate Change over South Korea (남한지역 기후변화량 평가를 위한 고해상도 농업기후 자료)

  • Hur, Jina;Park, Joo Hyeon;Shim, Kyo Moon;Kim, Yong Seok;Jo, Sera
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.22 no.3
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    • pp.128-134
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    • 2020
  • The daily gridded meteorological information and climatology with high resolution (30m and 270m) was produced from 94 Automated Surface Observing System (ASOS) of Korea Meteorological Administration (KMA) for the past 50 years (1971-current) by different downscaling methods. In addition, the difference between daily meteorological data and the mean state of past 30 years (1981-2010) was calculated for the analysis of climate change. These datasets with GeoTiff format are available from the web interface (https://agecoclim. agmet.kr). The performance of the data is evaluated using 172 Automatic Weather S tation (AWS ) of Rural Development of Administration (RDA). The data have biases lower than 2.0, and root mean square errors (RMSE) lower than 3.8. This data may help to better understand the regional climatic change and its impact on agroecosystem in S outh Korea.

Development of Radar-Satellite Blended QPF Technique to Rainfall Forecasting : Extreme heavy rainfall case in Busan, South Korea (레이더-위성 결합 초단기 강우예측 기법 개발: 부산 호우사례 적용 (2014년 8월 25일))

  • Jang, Sang Min;Yoon, Sun Kwon;Park, Kyung Won;Yhang, Yoo Bin
    • Proceedings of the Korea Water Resources Association Conference
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    • 2016.05a
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    • pp.226-226
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    • 2016
  • 최근 이상기상현상과 기후변화로 인하여 국지적인 집중호우의 빈도 및 규모가 증가하고 있으며, 이로 인한 돌발 홍수피해가 증가하고 있다. 이러한 홍수 피해를 줄이기 위해서는 정확도가 우수한 초단시간(1~2시간 이내) 예측 강우량 정보가 필요하다. 본 연구에서는 집중호우에 대한 초단시간예보 및 실황 예측을 위해 시공간적으로 고해상도 자료를 제공할 수 있는 기상레이더 강우자료와 위성영상 자료를 결합하여 초단기 강수 예측기법 개발 연구를 수행하였다. 또한 기상레이더 강우량은 지상강우관측에 비해 정확성이 낮고, 많은 불확실성을 포함하고 있으므로, 위성영상에서 산출되는 강우자료와 결합하여 강우추정의 정확도를 개선하고자 하였다. 레이더 볼륨자료에서 반사도 자료를 추출하여, 1.5km CAPPI(Constant Altitude Plan Position Indicator) 자료를 생성하고, 반사도 CAPPI 자료의 패턴 상관분석을 통하여 강우시스템의 최적 이동벡터를 산출하였다. 또한 이동벡터를 고려하여 시공간적으로 외삽하여 강우이동 예측 모델을 개발하고, 초기자료로 레이더와 천리안 위성(Communication, Ocean and Meteorological Satellite, COMS) 영상자료에서 생성되는 강우자료를 결합한 강수장 자료를 이용하여 강수 예측장을 생성하였다. 레이더-위성 결합 초단기 강우예측 모델의 정확성 검증을 위하여 2014년 8월 25일 부산 및 영남 지역에 발생한 집중호우 사례에 대하여 지상기상자동관측시스템(Automatic Weather System, AWS) 강우 측정 결과를 비교 분석 하였으며, 그 적용 가능성을 검증하였다. 초단기 강우예측 분석 결과 지상강우자료와의 오차가 발생하나, 추후 여러 통계적 후처리 과정을 통하여 그 성능이 개선될 것으로 보이며, 보다 정확한 강우량 예측을 위해서는 지속적인 알고리즘 개선 및 모형의 검 보정이 필요할 것으로 사료된다.

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Negative association between high temperature-humidity index and milk performance and quality in Korean dairy system: big data analysis

  • Dongseok Lee;Daekyum Yoo;Hyeran Kim;Jakyeom Seo
    • Journal of Animal Science and Technology
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    • v.65 no.3
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    • pp.588-595
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    • 2023
  • The aim of this study was to investigate the effects of heat stress on milk traits in South Korea using comprehensive data (dairy production and climate). The dataset for this study comprised 1,498,232 test-day records for milk yield, fat- and protein-corrected milk, fat yield, protein yield, milk urea nitrogen (MUN), and somatic cell score (SCS) from 215,276 Holstein cows (primiparous: n = 122,087; multiparous: n = 93,189) in 2,419 South Korean dairy herds. Data were collected from July 2017 to April 2020 through the Dairy Cattle Improvement Program, and merged with meteorological data from 600 automatic weather stations through the Korea Meteorological Administration. The segmented regression model was used to estimate the effects of the temperature-humidity index (THI) on milk traits and elucidate the break point (BP) of the THI. To acquire the least-squares mean of milk traits, the generalized linear model was applied using fixed effects (region, calving year, calving month, parity, days in milk, and THI). For all parameters, the BP of THI was observed; in particular, milk production parameters dramatically decreased after a specific BP of THI (p < 0.05). In contrast, MUN and SCS drastically increased when THI exceeded BP in all cows (p < 0.05) and primiparous cows (p < 0.05), respectively. Dairy cows in South Korea exhibited negative effects on milk traits (decrease in milk performance, increase in MUN, and SCS) when the THI exceeded 70; therefore, detailed feeding management is required to prevent heat stress in dairy cows.

Validation of Extreme Rainfall Estimation in an Urban Area derived from Satellite Data : A Case Study on the Heavy Rainfall Event in July, 2011 (위성 자료를 이용한 도시지역 극치강우 모니터링: 2011년 7월 집중호우를 중심으로)

  • Yoon, Sun-Kwon;Park, Kyung-Won;Kim, Jong Pil;Jung, Il-Won
    • Journal of Korea Water Resources Association
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    • v.47 no.4
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    • pp.371-384
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    • 2014
  • This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

Development and Wind Speed Evaluation of Ultra High Resolution KMAPP Using Urban Building Information Data (도시건물정보를 반영한 초고해상도 규모상세화 수치자료 산출체계(KMAPP) 구축 및 풍속 평가)

  • Kim, Do-Hyoung;Lee, Seung-Wook;Jeong, Hyeong-Se;Park, Sung-Hwa;Kim, Yeon-Hee
    • Atmosphere
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    • v.32 no.3
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    • pp.179-189
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    • 2022
  • The purpose of this study is to build and evaluate a high-resolution (50 m) KMAPP (Korea Meteorological Administration Post Processing) reflecting building data. KMAPP uses LDAPS (Local Data Assimilation and Prediction System) data to detail ground wind speed through surface roughness and elevation corrections. During the detailing process, we improved the vegetation roughness data to reflect the impact of city buildings. AWS (Automatic Weather Station) data from a total of 48 locations in the metropolitan area including Seoul in 2019 were used as the observation data used for verification. Sensitivity analysis was conducted by dividing the experiment according to the method of improving the vegetation roughness length. KMAPP has been shown to improve the tendency of LDAPS to over simulate surface wind speeds. Compared to LDAPS, Root Mean Square Error (RMSE) is improved by approximately 23% and Mean Bias Error (MBE) by about 47%. However, there is an error in the roughness length around the Han River or the coastline. Accordingly, the surface roughness length was improved in KMAPP and the building information was reflected. In the sensitivity experiment of improved KMAPP, RMSE was further improved to 6% and MBE to 3%. This study shows that high-resolution KMAPP reflecting building information can improve wind speed accuracy in urban areas.

An Observation Study of the Relationship of between the Urban and Architectural Form and Microclimate (도시·건축형태와 미기후의 관계에 대한 관찰 연구)

  • Lee, Gunwon;Jeong, Yunnam
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.11
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    • pp.109-119
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    • 2018
  • This study investigates the effect of urban and architectural forms on the microclimate in urban areas. It applies urban and architectural elements such as urban form and tissue and building form and characteristics as the main influences on the microclimate within urban area. Among the 23 Automated Weather Stations (AWS) installed within Seoul city by the Korea Meteorological Administration, 6 sites were selected for the analysis, based on their different urban and architectural characteristics, and actual measurements were conducted in August 2017 using individual AWS equipment. Also, the measurements of microclimate and urban and architectural elements within a 500m radius of the AWS measurement points were collected and analyzed. The result of the analysis shows that the microclimate elements, such as wind speed, solar radiation, and temperature, were affected by the direction of the streets, the width, depth, and height of the buildings, the topographic elevation and direction and the traffic volume. This study is expected to contribute to mitigating urban heat island effect and setting the foundation for sustainable cities through development of urban management methods and techniques including the relationship between built environment elements and microclimate.