• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.564-566
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• 2005

The relation between HPA (High Power Amplifier) and COMS (Communication Ocean Meteorological Satellite) multi-carrier is analyzed in this paper. MODAC (Meteorological and Ocean Data Application Center) has a primary mission to transmit processed data, HRIT (High Rate Information Transmission) and LRIT (Low Rate Information Transmission), which is normalized and calibrated by pre-processing. It is also replaced with the SOC (Satellite Operation Center) in emergency case and can transmit the command and ranging tones for operation of COMS. From the result of simulation with modelled HPA, it is found that the multi-carrier in one HPA can give rise to an inter-modulation which makes harmonic and spurious elements increase in-band. Under the environment of these increased parasitic elements, the degradation of multi-carrier's quality is estimated from the ratio of the amount of noise to total output power of HPA.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.1
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• pp.11-18
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• 2010

GNSS(Global Navigation Satellite System) Ground Station performs GNSS signal acquisition and processing. This system generates error correction information and distributes them to GNSS users. GNSS Ground Station consists of sensor station which contains receiver and meteorological sensor, monitoring and control subsystem which monitors and controls sensor station, control center which generates error correction information, and uplink station which transmits correction information to navigation satellites. Monitoring and control subsystem acquires and processes navigation data from sensor station. The processed data is transmitted to GNSS control center. Monitoring and control subsystem consists of data acquisition module, data formatting and archiving module, data error correction module, navigation determination module, independent quality monitoring module, and system maintenance and management module. The independent quality monitoring module inspects navigation signal, data, and measurement. This paper introduces independent quality monitoring and performs the analysis using measurement data.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.367-370
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• 2009

한국해양연구원에서는 2009년 발사 예정인 통신해양기상위성(COMS: Communication, Ocean and Meteorological Satellite)의 해색센서인 정지궤도 해양위성(GOCI: Geostationary Ocean Color Imager) 데이터의 수신, 처리, 배포를 위한 해양위성센터(KOSC: Korea Ocean Satellite Center)를 구축하고 있다. 2005년 "해양위성센터 구축사업"의 시작으로, 전파 수신 환경 등의 조건을 고려하여, 안산에 위치한 한국해양연구원 본원으로 해양위성센터의 위치를 최종 확정하여 구축을 진행하고 있다. 2009년 3월 현재 수신시스템(GDAS: GOCI Data Aquisition System), 자료전처리시스템(IMPS: Image Pre-processing System), 자료처리시스템(GDPS: GOCI Data Processing System), 자료관리 시스템(DMS: Data Management System), 통합감시제어시스템(TMC: Total Management & Controlling System), 기관간 자료교환시스템(EDES: External Data Exchange System) 등이 구축 완료되었고, 위성자료 배포시스템(DDS: Data Distribution System)을 구축하고 있다. 고용량 데이터의 원활한 전송을 위한 데이터센터를 비롯하여 사용자관점에서의 시스템 구축을 추진하고 있으며, 위성 발사 후 사용자 등록을 시작할 계획이다.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.159-161
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• 2007

Geostationary Ocean Color Imager (GOCI), the world-first ocean remote sensing instrument on geostationary Communication, Ocean, Meteorological Satellite (COMS), will be able to take a picture of a large region several times a day (almost with every one hour interval). We, KORDI, are in charge for developing the GOCI data processing system (GDPS) which is the basic software for processing the data from GOCI. The GDPS will be based on windows operating system to produce the GOCI level 2 data products (useful for oceanographic environmental analysis) automatically in real-time mode. Also, the GDPS will be a user-interactive program by well-organized graphical user interfaces for data processing and visualization. Its products will be the chlorophyll concentration, amount of total suspended sediments (TSS), colored dissolved organic matters (CDOM) and red tide from water leaving radiance or remote sensing reflectance. In addition, the GDPS will be able to produce daily products such as water current vector, primary productivity, water quality categorization, vegetation index, using individual observation data composed from several subscenes provided by GOCI for each slit within the target area. The resulting GOCI level 2 data will be disseminated through LRIT using satellite dissemination system and through online request and download systems. This software is carefully designed and implemented, and will be tested by sub-contractual company until the end of this year. It will need to be updated in effect with respect to new/improved algorithms and the calibration/validation activities.

• Atmosphere
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• v.28 no.3
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• pp.263-272
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• 2018

The high-resolution ocean surface wind vector produced by scatterometer was assimilated within the Local Ensemble Transform Kalman Filter (LETKF) in Korea Institute of Atmospheric Prediction Systems (KIAPS). The Advanced Scatterometer (ASCAT) on Metop-A/B wind data was processed in the KIAPS Package for Observation Processing (KPOP), and a module capable of processing surface wind observation was implemented in the LETKF system. The LETKF data assimilation cycle for evaluating the performance improvement due to ASCAT observation was carried out for approximately 20 days from June through July 2017 when Typhoon Nepartak was present. As a result, we have found that the performance of ASCAT wind vector has a clear and beneficial effect on the data assimilation cycle. It has reduced analysis errors of wind, temperature, and humidity, as well as analysis errors of lower troposphere wind. Furthermore, by the assimilation of the ASCAT wind observation, the initial condition of the model described the typhoon structure more accurately and improved the typhoon track prediction skill. Therefore, we can expect the analysis field of LETKF will be improved if the Scatterometer wind observation is added.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.305-308
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• 2005

The COMS, Korea's first geostationary multipurpose satellite program will accommodate 3 kind of payloads; Ka-Band communication transponder, GOCI (Geostationary Ocean Color Imager), and MI (Meteorological Imager). MI raw data will be transferred to ground station via L-band link. The ground station will perform image data processing for raw data, generate them into the LRIT/HRIT format, the user dissemination data recommended by the CGMS. The LRIT/HRIT are disseminated via satellite to user stations. This paper shows the COMS LRIT data generation procedure based on COMS LRIT specification and its verification results using the LRIT user station.

• Journal of Korea Technology Innovation Society
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• v.20 no.1
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• pp.34-61
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• 2017

The objective of this study is to assess the capability of meteorological technology in Korea, the United States, Japan, and the United Kingdom as of 2015 and compare them with the previous values for Korea, the United States, and Japan. For the comparison, the indicators and weights for the assessment similar to those used in previous studies are used and Gordon's rating model is applied here to evaluate the indicators and conduct a survey of weather experts. The survey was administered to 200 of experts in meteorology using the Delphi method. More specifically, we investigate four categories of observation, data processing, forecast, and climate. The overall results show that the United Kingdom has the highest capability of meteorological technology among the four countries. With the result of indicator evaluation on this study the United Kingdom has the highest capability of meteorological technologies compared with Korea, the United States, and Japan. The capability of meteorological technology in Korea is 88.5% of the United Kingdom, 89.9% of Japan, and 90.6% of the United States. The countries in order of score on survey evaluation are the United States, the United Kingdom, Japan, and Korea. Through the result of survey evaluation, the level of meteorological technology in Korea was 88.9% of the United States, 91.6% of the United Kingdom, and 92.2% of Japan.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.589-591
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• 2023

현재 수치예보 시스템은 항공기, 위성 등 다양한 센서에서 얻은 다종 관측 데이터를 동화하여 대기 상태를 추정하고 있지만, 관측변수 또는 물리량이 서로 다른 관측들을 처리하기 위한 계산 복잡도가 매우 높다. 본 연구에서 기존 시스템의 계산 효율성을 개선하여 관측을 평가하거나 전처리하는 데에 효율적으로 활용하기 위해, 각 관측의 특성을 고려한 자기 지도학습 방법을 통해 멀티모달 기상관측으로부터 실제 대기 상태를 추정하는 방법론을 제안하고자 한다. 비균질적으로 수집되는 멀티모달 기상관측 데이터를 융합하기 위해, (i) 기상관측의 heterogeneous network를 구축하여 개별 관측의 위상정보를 표현하고, (ii) pretext task 기반의 self-supervised learning을 바탕으로 개별 관측의 특성을 표현한다. (iii) Graph neural network 기반의 예측 모델을 통해 실제에 가까운 대기 상태를 추정한다. 제안하는 모델은 대규모 수치 시뮬레이션 시스템으로 수행되는 기존 기술의 한계점을 개선함으로써, 이상 관측 탐지, 관측의 편차 보정, 관측영향 평가 등 관측 전처리 기술로 활용할 수 있다.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.6
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• pp.277-283
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• 2020

In order to improve the ground-motion prediction equation, which is an important factor in seismic hazard assessment, it is essential to obtain good quality seismic data for a region. The Korean Peninsula has an environment in which it is difficult to obtain strong ground motion data. However, because digital seismic observation networks have become denser since the mid-2000s and moderate earthquake events such as the Odaesan earthquake (Jan. 20, 2007, M_L 4.8), the 9.12 Gyeongju earthquake (Sep. 12, 2016, M_L 5.8), and the Pohang earthquake (Nov. 15, 2017, M_L 5.4) have occurred, some good empirical data on ground motion could have been accumulated. In this study, we tried to build a ground motion database that can be used for the development of the ground motion attenuation equation by collecting seismic data accumulated since the 2000s. The database was constructed in the form of a flat file with RotD50 peak ground acceleration, 5% damped pseudo-spectral acceleration, and meta information related to hypocenter, path, site, and data processing. The seismic data used were the velocity and accelerogram data for events over M_L 3.0 observed between 2003 and 2019 by the Korean National Seismic Network administered by the Korea Meteorological Administration. The final flat file contains 10,795 ground motion data items for 141 events. Although this study focuses mainly on organizing earthquake ground-motion waveforms and their data processing, it is thought that the study will contribute to reducing uncertainty in evaluating seismic hazard in the Korean Peninsula if detailed information about epicenters and stations is supplemented in the future.

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.626-632
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• 2013

In this study the GPS Precipitable Water Vapor (PWV) was derived and evaluated by a radiosode measure during the winter intensive observation in Gangneung site from January 5 till February 29 in 2012. Bernise 5.0 software was used to derive the GPS data. GPS-derived PWV from Zero difference (GANG) and Single difference (GANG and DAEJ) was high variance in time and about 5 times the PWV of radiosonde. GPS post-processing has been performed from two additional IGS site (Xian Dao, Ibaraki-ken) in order to correct the absolute troposphere errors. As a result, the mean bias error (MBE) and root mean square error (RMSE) and correlation compared with radiosonde measure were 0.67 mm, 6.40 mm, and 0.93, respectively. In order to correct the relative troposphere errors from the altitudinal difference between the two GPS receivers, we calculated the GPS-derived PWV by adding the data of GPS that was installed in Gangneung-Wonju University near the Gangwon Regional Meteorological Administration. In the end, the improved result showed that MBE, RMSE and correlation in comparison with radiosonde measures were 0.61 mm, 5.79 mm, and 0.93, respectively.