• Proceedings of the KSRS Conference
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• v.1
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• pp.220-223
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• 2006

The COMS(Communication, Ocean and Meteorological Satellite) EPS(Electrical Power Subsystem) is derived from an enhanced Eurostar 3000 EPS which is fully autonomous operation in normal conditions or in the event of a failure and provides a high level of reconfiguration capability and flexibility. This paper introduces the COMS EPS preliminary design result. The COMS EPS consists of a battery, a solar array wing, a PSR(Power Supply Regulator), a PRU(Pyrotechnic Unit), a SADM(Solar Array Drive Mechanism) and relay and fuse brackets. This can offer a bus power capability of 3 kW. The solar array is made of a deployable wing with two panels. One type of solar cells is selected as GaAs/Ge triple junction cells. Li-ion battery is base lined with ten series cell module of five cells in parallel. PSR associated with battery and solar array generates a power bus fully regulated 50 V. Power bus is centralised protection and distribution by relay and fuse brackets. PRU provides power for firing actuators devices. The solar array wing is routed by the SADM under control of the AOCS(Attitude Orbit Control Subsystem). The control and monitoring of the EPS especially of the battery, is performed by the PSR in combination with on-board software.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.11-20
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• 2017

This study is to estimate the spatial soil moisture using multiple linear regression model (MLRM) and 15 minutes interval Land Surface Temperature (LST) data of Communication, Ocean and Meteorological Satellite (COMS). For the modeling, the input data of COMS LST, Terra MODIS Normalized Difference Vegetation Index (NDVI), daily rainfall and sunshine hour were considered and prepared. Using the observed soil moisture data at 9 stations of Automated Agriculture Observing System (AAOS) from January 2013 to May 2015, the MLRMs were developed by twelve scenarios of input components combination. The model results showed that the correlation between observed and modelled soil moisture increased when using antecedent rainfalls before the soil moisture simulation day. In addition, the correlation increased more when the model coefficients were evaluated by seasonal base. This was from the reverse correlation between MODIS NDVI and soil moisture in spring and autumn season.

• Aerospace Engineering and Technology
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• v.9 no.2
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• pp.44-50
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• 2010

COMS accommodates multiple payloads; Meteorological Image(MI), Ocean Color Imager(GOCI) and Ka-band communication payloads. In order to improve the quality of MI visible channel, the moon image has been taken into account as backup reference in addition to Albedo monitoring. However, obtaining the moon image by adding special mission schedule is not recommended after IOT, because we may miss chances to obtain meteorological images during the time slots for special imaging. As an alternative solution, an approach extracting moon image from MI FD(Full Disk) image has been proposed when the moon is positioned near to the earth. However, prediction of acquisition time of moon image is somewhat difficult as the moon moves while the MI is scanning type sensor. And the moon can not be seen when it is behind the earth or outside of FD field of view. This paper discusses how effectively the moon can be detected by the MI FD imaging. For that purpose, this paper describes an approach taken to predict the time when the moon image is achievable and then introduces the results obtained from computer simulation.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.167-173
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• 2010

This paper introduces Geostationary Ocean Color Imager, IMage Pre-processing Subsystem (GOCI IMPS) of Communication, Ocean, and Meteorological Satellite (COMS), and describes its functions, development states, and operational concepts. The primary and backup systems of GOCI IMPS have been installed in Korea Ocean Satellite Center (KOSC) and Satellite Operation Center (SOC) and the system are the prelaunch test phase after completing all required tests. It is expected that the GOCI data observed continuously over the Korea Peninsular in the geostationary orbit will be usefully utilized in marine environment research fields such as sea surface temperature changes or marine ecosystems.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.239-252
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• 2022

Quality control methods for the first G-band vapor radiometer (GVR) mounted on a weather aircraft in Korea were developed using the GVR Precipitable Water Vapor (PWV). The aircraft attitude information (degree of pitch and roll) was applied to quality control to select the shortest vertical path of the GVR beam. In addition, quality control was applied to remove a GVR PWV ≥20 mm. It was found that the difference between the warm load average power and sky load average power converged to near 0 when the GVR PWV increased to 20 mm or higher. This could be due to the high brightness temperature of the substratus and mesoclouds, which was confirmed by the Communication, Ocean and Meteorological Satellite (COMS) data (cloud type, cloud top height, and cloud amount), cloud combination probe (CCP), and precipitation imaging probe (PIP). The GVR PWV before and after the application of quality control on a cloudy day was quantitatively compared with that of a local data assimilation and prediction system (LDAPS). The Root Mean Square Difference (RMSD) decreased from 2.9 to 1.8 mm and the RMSD with Korea Local Analysis and Precipitation System (KLAPS) decreased from 5.4 to 4.3 mm, showing improved accuracy. In addition, the quality control effectiveness of GVR PWV suggested in this study was verified through comparison with the COMS PWV by using the GVR PWV applied with quality control and the dropsonde PWV.

• Journal of Satellite, Information and Communications
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• v.1 no.2
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• pp.63-70
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• 2006

This paper presents the results of Ka band qualification model multiplexers for COMS Payload to be launched in 2008. These are the input and output multiplexers of the satellite transponder to use available frequency resources effectively and the diplexer of the satellite antenna to use the same reflector for both transmitting and receiving frequency bands, respectively. The input multiplexer with four frequency channels has four(4) independent channel filters which consist of an 8-pole elliptic band-pass filter for high frequency selectivity and a 2-pole equalizer for group delay equalization. For low insertion loss, mass and volume reduction, manifold type os employed for output multiplexer. E-plane T-junction is used for either splitting or combining a frequency band into two sub-bands. Asymmetric inductive irises are used to tune the receiving filter easily. The electrical performance and environmental test such as vibration test, mechanical shock test, thermal vacuum test and EMC test are performed and the results of all qualification model multiplexers are compliant to the requirement of each multiplexer. Followed by this qualification, the flight model equipment will be developed.

• 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.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.435-452
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• 2016

Land Surface Temperature (LST) has been operationally retrieved from the Communication, Ocean, and Meteorological Satellite (COMS) data by the spilt-window method (CSW_v2.0) developed by Cho et al. (2015). Although the CSW_v2.0 retrieved the LST with a reasonable quality compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data, it showed a relatively poor performance for the strong inversion and lapse rate conditions. To solve this problem, the LST retrieval algorithm (CSW_v2.0) was updated using the simulation results of radiative transfer model (MODTRAN 4.0) by considering the diurnal variations of air temperature. In general, the upgraded version, CSW_v3.0 showed a similar correlation coefficient between the prescribed LSTs and retrieved LSTs (0.99), the relatively smaller bias (from -0.03 K to-0.012 K) and the Root Mean Square Error (RMSE) (from 1.39 K to 1.138 K). Particularly, CSW_v3.0 improved the systematic problems of CSW_v2.0 that were encountered when temperature differences between LST and air temperature are very large and/or small (inversion layers and superadiabatic lapse rates), and when the brightness temperature differences and surface emissivity differences were large. The bias and RMSE of CSW_v2.0 were reduced by 10-30% in CSW_v3.0. The indirect validation results using the MODIS LST data showed that CSW_3.0 improved the retrieval accuracy of LST in terms of bias (from -0.629 K to -0.049 K) and RMSE (from 2.537 K to 2.502 K) compared to the CSW_v2.0.

• 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.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.57-81
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• 2019

Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.