Correlation Between the “seeing FWHM” of Satellite Optical Observations and Meteorological Data at the OWL-Net Station, Mongolia

배영호,조중현,임홍서,박영식,박선엽,문홍규,최영준,장현정,노동구,최진,박마루,조성기,김명진,최은정,박장현 한국우주과학회 2016 Journal of Astronomy and Space Sciences Vol.33 No.2

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.

데이터 로딩 자동화를 위한 RESTful 웹서비스 개발 - 일별 기상자료 처리를 중심으로 -

김태곤,이정재,남원호,서교,Kim, Taegon,Lee, JeongJae,Nam, Won-Ho,Suh, Kyo 한국농공학회 2014 한국농공학회논문집 Vol.56 No.6

Generally data loading is a laborous job to develop models. Meteorological data is basic input data for hydrological models, it is provided through websites of Korea Meteorological Administration (KMA). The website of KMA provides daily meteorological observation data with tabular format classified by years, items, stations. It is cumbersome to manipulate tabular format for model inputs such as time series and multi-item or multi-station data. The provider oriented services which broadcast restricted formed information have caused inconvenient processes. Tim O'Reilly introduces "Web 2.0" which focuses on providing a service based on data. The top ranked IT companies such as google, yahoo, daum, and naver provide customer oriented services with Open API (Application Programming Interface). A RESTful web service, typical implementation for Open API, consists URI request and HTTP response which are simple and light weight protocol than SOAP (Simple Object Access Protocol). The aim of this study is to develop a web-based service that helps loading data for human use instead of machine use. In this study, the developed RESTful web service provides Open API for manipulating meteorological data. The proposed Open API can easily access from spreadsheet programs, web browsers, and various programming environments.

관측자료별 자료동화 성능이 한반도 동부 지역 기상 예보에 미치는 영향 분석 연구

김지선 ( Ji-seon Kim ),이순환 ( Soon-hwan Lee ),손건태 ( Keon-tae Sohn ) 한국환경과학회 2018 한국환경과학회지 Vol.27 No.11

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

Development of Solar-Meteorological Resources Map using One-layer Solar Radiation Model Based on Satellites Data on Korean Peninsula

지준범(Jee, Joonbum),최영진(Choi, Youngjean),이규태(Lee, Kyutae),조일성(Zo, Ilsung) 한국신재생에너지학회 2011 한국신재생에너지학회 학술대회논문집 Vol.2011 No.11

The solar and meteorological resources map is calculated using by one-layer solar radiation model (GWNU model), satellites data and numerical model output on the Korean peninsula. The Meteorological input data to perform the GWNU model are retrieved aerosol optical thickness from MODIS (TERA/AQUA), total ozone amount from OMI (AURA), cloud fraction from geostationary satellites (MTSAT-1R) and temperature, pressure and total precipitable water from output of RDAPS (Regional Data Assimilation and Prediction System) and KLAPS (Korea Local Analysis and Prediction System) model operated by KMA (Korea Meteorological Administration). The model is carried out every hour using by the meteorological data (total ozone amount, aerosol optical thickness, temperature, pressure and cloud amount) and the basic data (surface albedo and DEM). And the result is analyzed the distribution in time and space and validated with 22 meteorological solar observations. The solar resources map is used to the solar energy-related industries and assessment of the potential resources for solar plant. The National Institute of Meteorological Research in KMA released 4km{times}4km solar map in 2008 and updated solar map with 1km{times}1km resolution and topological effect in 2010. The meteorological resources map homepage (http://www.greenmap.go.kr) is provided the various information and result for the meteorological-solar resources map.

신재생에너지 국가참조표준 시스템 구축 및 개발 - 모델 기반 표준기상년

김보영(Boyoung Kim),김창기(Chang Ki Kim),윤창열(Chang-yeol Yun),김현구(Hyun-goo Kim),강용혁(Yong-heack Kang) 한국신재생에너지학회 2024 신재생에너지 Vol.20 No.1

Since 1990, the Renewable Big Data Research Lab at the Korea Institute of Energy Technology has been observing solar radiation at 16 sites across South Korea. Serving as the National Reference Standard Data Center for Renewable Energy since 2012, it produces essential data for the sector. By 2020, it standardized meteorological year data from 22 sites. Despite user demand for data from approximately 260 sites, equivalent to South Koreas municipalities, this need exceeds the capability of measurement-based data. In response, our team developed a method to derive solar radiation data from satellite images, covering South Korea in 400,000 grids of 500 m × 500 m each. Utilizing satellite-derived data and ERA5-Land reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), we produced standard meteorological year data for 1,000 sites. Our research also focused on data measurement traceability and uncertainty estimation, ensuring the reliability of our model data and the traceability of existing measurement-based data.

A neural network-based local rainfall prediction system using meteorological data on the Internet: A case study using data from the Japan Meteorological Agency

Kashiwao, Tomoaki,Nakayama, Koichi,Ando, Shin,Ikeda, Kenji,Lee, Moonyong,Bahadori, Alireza Elsevier 2017 Applied soft computing Vol.56 No.-

<P>In this study, we develop and test a local rainfall (precipitation) prediction system based on artificial neural networks (ANNs). Our system can automatically obtain meteorological data used for rainfall prediction from the Internet. Meteorological data from equipment installed at a local point is also shared among users in our system. The final goal of the study was the practical use of 'big data' on the Internet as well as the sharing of data among users for accurate rainfall prediction. We predicted local rainfall in regions of Japan using data from the Japan Meteorological Agency (JMA). As neural network (NN) models for the system, we used a multi-layer perceptron (MLP) with a hybrid algorithm composed of back-propagation (BP) and random optimization (RO) methods, and radial basis function network (RBFN) with a least squares method (LSM), and compared the prediction performance of the two models. Precipitation (total amount of rainfall above 0.5 mm between 12: 00 and 24: 00 JST (Japan standard time)) at Matsuyama, Sapporo, and Naha in 2012 was predicted by NNs using meteorological data for each city from 2011. The volume of precipitation was also predicted (total amount above 1.0 mm between 17: 00 and 24: 00 JST) at 16 points in Japan and compared with predictions by the JMA in order to verify the universality of the proposed system. The experimental results showed that precipitation in Japan can be predicted by the proposed method, and that the prediction performance of the MLP model was superior to that of the RBFN model for the rainfall prediction problem. However, the results were not better than those generated by the JMA. Finally, heavy rainfall (above 10 mm/h) in summer (Jun.-Sep.) afternoons (12: 00-24: 00 JST) in Tokyo in 2011 and 2012 was predicted using data for Tokyo between 2000 and 2010. The results showed that the volume of precipitation could be accurately predicted and the caching rate of heavy rainfall was high. This suggests that the proposed system can predict unexpected local heavy rainfalls as 'guerrilla rainstorms.' (C) 2017 Elsevier B.V. All rights reserved.</P>

신재생에너지 예측을 위한 송전선로의 계량 데이터 계산 방법

백자현,김현진,최순호,박상호,Ja-hyun, Baek,Hyeonjin, Kim,Soonho, Choi,Sangho, Park 한국전력공사 2022 KEPCO Journal on electric power and energy Vol.8 No.2

This paper introduce Renewable Energy forecasting technology, which is a part of renewable management system. Then, calculation method of dedicated transmission line's meteorological data to forecast renewable energy is suggested. As the case of dedicated transmission line, there is only power output data combined the number of renewable plants' output that acquired from circuit breakers. So it is need to calculate meteorological data for dedicated transmission line that matched combined power output data. this paper suggests two calculation method. First method is select the plant has the largest capacity, and use it's meteorological data as line meteorological data. Second method is average with weight that given according to plants' capacity. In case study, suggested methods are applied to real data. Then use calculated data to Renewable forecasting and analyze the forecasting results.

기상관측데이터를 활용한 일사예측모델 개발

정민희 한국생태환경건축학회 2017 한국생태환경건축학회 논문집 Vol.17 No.6

Purpose: The prediction of solar radiation is essential for the prediction of solar PV generation. In this study, we present a prediction model of solar radiation from data observed at Meteorological Administration and present basic data for the development of solar radiation prediction model through meteorological parameters provided in future weather forecasts. Method: The regression model is presented for one - year observation weather data in Seoul area. At first, the weather variables that will affect the insolation was selected by literature reviews. Secondly, correlation analysis is performed on the selected meteorological variables. Thirdly, a multiple regression analysis is performed using the solar radiation, and a prediction model of solar radiation is presented. Finally, the reliability of the prediction model is verified by comparing the predicted model with the weather observation data. Result: A regression equation model is presented for observational weather data. Variables with the greatest influence on the solar irradiation were sunshine duration> continued sunshine duration> average wind speed> cloud cover> precipitation duration> minimum relative humidity> precipitation> maximum temperature. The reliability of the proposed regression equation was 0.907 and CVRMSE was 15%.

기상정보를 중심으로 한 공공부문 빅데이터 활성화 검토

신지웅(Jiwoong Shin),이두영(Dooyoung Lee) 전북대학교 법학전문대학원 학술지 편집위원회 2013 JEONBUK LAW JOURNAL Vol.3 No.1

본 논문은 공공부문에서 빅데이터 활성화를 지원정책을 분석하고 체계적인 활용 및 개인정보보호 등 역기능을 대비한 법제적 검토를 수행하였다. 특히 기상정보는 전 세계에서 생산되는 관측 빅데이터를 분석 처리하는 공공정보로써 향후 공공정보의 빅데이터 관리 및 법제적 방향을 설정하기 위해 중요한 분야이다. 정부는 빅데이터 공유활용 인프라 구축, 기술연구 개발, 전문인력 양성, 법제도 정비 등 다양한 과제를 부처간 협력을 통해 추진 중에 있다. 특히, 법제도적 지원은 체계적 빅데이터 개방과 관리 및 개인정보보호 등 역기능 대비를 위한 필수적인 요소이다. 이에, 빅데이터 활용 확산과 발생가능한 문제점을 대응하기 위한 법제도적 검토를 통해 스마트 정부 발전 방안을 제시하고자 한다. This study focuses on the legal review for an adverse effect such as private information exposure as well as the analysis of activation policies on Big Data. Especially, as a meterological information is public big data provided by analyzing and dealing with observation value, it will be an important public information in order to set up a management and legal direction of big data. Korea Government is carrying out various task such as an establishment of infrastructure for data sharing platform, R&D, professional manpower training and law system maintenance through the collaboration of related departments, in particular, support of legal system is an essential factor for systemic sharing and management of big data and personal information protection. Accordingly, this paper intends to propose a development plan for smart government through a legal review on potential problems and diffusion of big data's application.

표준기상데이터 형식 분석 및 TRY 가중치 적용

유호천(Yoo Ho-Chun),이관호(Lee Gwan-Ho),박소희(Park So-Hee),김경률(Kim Kyoung-Ryul) 한국태양에너지학회 2007 한국태양에너지학회 논문집 Vol.27 No.4

Typical meteorological data is fundamental to computer simulation introduced for environment-friendly architecture designs. Therefore, in order to improve accuracy of computer simulation, typical meteorological data should be established. By examining how to choose typical meteorological data, this study selected the optimized weight factor for TRY where weighting factor was not clearly set. As a result, the same weighting factor was applied to each climatic element and TRY data where the weight factor was applied could have the distribution very similar to measurement data. The weighting factor is considered to reflect geographical characteristics of Seoul and applied climatic elements.