• Journal of the Korean earth science society
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• v.39 no.2
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• pp.119-130
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• 2018

Aerosol Optical Properties (AOPs) are retrieved using the geostationary satellite instruments such as Geostationary Ocean Color Imager (GOCI), Meteorological Imager (MI), and Advanced Himawari Imager (AHI) through Yonsei AErosol Retrieval algorithm (YAER). In this study, the retrieved aerosol optical depths (AOD)s from each instrument were intercompared and validated with the ground-based sunphotometer AErosol Robotic NETwork (AERONET) data. As a result, the four AOD products derived from different instruments showed consistent results over land and ocean. However, AODs from MI and GOCI tend to be overestimated due to cloud contamination. According to the comparison results with AERONET, the percentage within expected errors (EE) are 36.3, 48.4, 56.6, and 68.2% for MI, GOCI, AHI-minimum reflectivity method (MRM), and AHI-estimated surface reflectance from shortwave Infrared (ESR) product, respectively. Since MI AOD is retrieved from a single visible channel, and adopts only one aerosol type by season, EE is relatively lower than other products. On the other hand, the AHI ESR is more accurate than the minimum reflectance method as used by GOCI, MI, and AHI MRM method in May and June when the vegetation is relatively abundant. These results are explained by the RMSE and the EE for each AERONET site. The ESR method result show to be better than the other satellite product in terms of EE for 15 out of 22 sites used for validation, and they are better than the other product for 13 sites in terms of RMSE. In addition, the error in observation time in each product is found by using characteristics of geostationary satellites. The absolute median biases at 00 to 06 Universal Time Coordinated (UTC) are 0.05, 0.09, 0.18, 0.18, 0.14, 0.09, and 0.10. The absolute median bias by observation time has appeared in MI and the only 00 UTC appeared in GOCI.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1037-1051
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• 2020

The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.300-304
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• 2003

기상위성은 그 특성상 다양한 Imager, Sounder, 그리고 여러 환경 테스트용 장비를 지니게 되며 일정한 시간동안 지구에 그 정보를 전송한다. 본 논문에서 제안된 수신 시스템은 현재 운영중인 아리랑위성 1호의 임무계획에 필요한 기상정보를 직접 획득하여 운영의 효율성을 높일 필요성에 의해서 GMS-5의 S-VISSR data 뿐만 아니라 2003년 4월 이후에 서비스를 할 것으로 예정된 GOES-9위성의 GVAR data도 역시 수신 및 처리를 할 수 있도록 설계되었다. Link budget 설계를 수행하여 최악의 경우에도 영상을 복원할 수 있는 통신링크가 제공되도록 설계하였고, 시스템 구성 모듈을 가능한 한 상용제품으로 사용하였다. 설치된 후에는 태양을 이용한 G/T의 값을 측정하여 설계치 보다 약1.608 향상된 시스템임을 검증하였고, 수신된 GMS-5의 S-VISSR 데이터를 성공적으로 처리함으로써 자체적으로 개발한 처리 소프트웨어를 검증하였다.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.187-190
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• 2007

The Geostationary Ocean Color Imager (GOCI) is under development to provide a monitoring of ocean-color around the Korean Peninsula from geostationary platforms. It is planned to be loaded on Communication, Ocean, and Meteorological Satellite (COMS) of Korea. The GOCI has been designed to provide multi-spectral data to detect, monitor, quantify, and predict short term changes of coastal ocean environment for marine science research and application purpose. The target area of GOCI observation covers sea area around the Korean Peninsula. Based on the nonlinear radiometric model, the GOCI calibration method has been derived. The nonlinear radiometric model for GOCI will be validated through ground test. The GOCI radiometric calibration is based on on-board calibration devices; solar diffuser, DAMD (Diffuser Aging Monitoring Device). In this paper, the GOCI radiometric error propagation is analyzed. The radiometric model error due to the dark current nonlinearity is analyzed as a systematic error. Also the offset correction error due to gain/offset instability is considered. The radiometric accuracy depends mainly on the ground characterization accuracies of solar diffuser and DAMD.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.146-148
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• 2007

CMDPS (COMS Meteorological Data Processing System) is the operational meteorological products extraction system for data observed from COMS (Communication, Ocean and Meteorological Satellite) meteorological imager. CMDPS baseline products consist of 16 parameters including cloud information, water vapor products, surface information, environmental products and atmospheric motion vector. Additionally, CMDPS includes the function of calibration monitoring, and validation mechanism of the baseline products. The main objective of CMDPS validation module development is near-real time monitoring for the accuracy and reliability of the whole CMDPS products. Also, its long time validation statistics are used for upgrade of CMDPS such as algorithm parameter tuning and retrieval algorithm modification. This paper introduces the preliminary design on CMDPS validation module.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.212.1-212.1
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• 2012

2010년 6월 성공적으로 발사된 천리안위성(COMS; Communication, Ocean, and Meteorological Satellite)의 기상영상기(MI; Meteorological Imager)를 통해 관측된 원시 기상영상은 지상국인 국가기상위성센터에서 지표기준과 위성궤도 및 자세 정보를 이용하여 영상위치보정 과정이 수행된다. 본 연구에서는 정규운영 초기 1년 동안의 운영 자료를 분석하여 계절 및 일변화를 나타내는 천리안위성 기상영상의 영상위치보정 성능 및 특성을 기술하였다. 이를 통하여 천리안위성 기상영상 가시 및 적외 채널의 영상위치결정 정확도 및 영상 위치유지 정확도는 기준값인 $56{\mu}rad$(약 2km) 이내로 유지되는 것을 확인하였다. 이는 천리안위성 기상영상이 우수한 품질의 위치정확도를 가지며 기상현상 분석 및 응용 연구에 높은 효용성을 가지는 것을 보여준다. 또한 본 연구의 결과는 후속 기상위성 영상위치보정 시스템 설계에도 유용하게 활용될 것이다.

• Journal of Environmental Impact Assessment
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• v.22 no.4
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• pp.389-395
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• 2013

Geostationary Ocean Color Imager(GOCI), the World's first spaceborne ocean color observation satellite operated in geostationary orbit, was successfully launched on May 2010. The main missions of GOCI is the coastal environment monitoring of GOCI in order to meet the necessity of long-term climate change monitoring and research. The GOCI have higher spatial resolution than MODIS, $500m{\times}500m$, and 8 spectral ocean color channels. GOCI have a capability for observation on the coastal environment change, GOCI perform the observation with 8 times a day. In this paper, we presented the more improved results for observation on the coastal environment change than MODIS ocean color sensor and detected the spatial difference of CDOM for monitoring coastal environment change.

• Journal of Astronomy and Space Sciences
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• v.33 no.4
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• pp.313-318
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• 2016

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.317-322
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• 2002

Dramatic changes in the patterns of satellite-derived pigment concentrations, sea-level height anomaly, sea surface temperature anomaly, and zonal wind anomaly are observed during the 1997-1998 El Nino. By some measures, the 1997-1998 El Nino was the strongest of the 20$^{th}$ century. A very strong El Nino developed during 1997 and matured late in the year. A dramatic recovery occurred in mid-1998 and led to a La Nina conditions. The largest spatial extent of the phytoplankton bloom was followed recovery from El Nino over the equatorial Pacific. The evolution towards a warm episode (El Nino) continued in the equatorial Pacific from March 2002 and further development toward mature El Nino conditions may be possible in late 2002. The OSMI (Ocean Scanning Multispectral Imager) data can be used for detection of dramatic changes in the patterns of pigment concentration during next El Nino.

• Aerospace Engineering and Technology
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• v.12 no.2
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• pp.147-155
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• 2013

The nominal radiometric calibration equation and additional five algorithms are applied in the infrared channel radiometric calibration for the COMS (Communication, Ocean, Meteorological Satellite) MI (Meteorological Imager). The processing end time of the radiometric calibration is directly related with the start time of geometric calibration processing since the geometric calibration processing is followed by that of the radiometric calibration. This paper describes comparison and analysis results for geometric calibration processing using two types of the radiometric calibration results, outputs from only the nominal radiometric calibration equation and outputs from the complete one (the nominal radiometric calibration equation with additional five algorithms), to propose a method with the earlier start time of the geometric calibration processing. Experimental results show that both of radiometric calibration results, from the nominal radiometric calibration equation with a fast processing speed and from the complete one with accurate radiometric values, can be used in the geometric calibration as the appropriate inputs because those processing results satisfied the requirements of geometric calibration processing accuracy. Thus the radiometric calibration results from the nominal radiometric calibration equation can be used to improve geometric calibration processing time.