• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.95-97
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• 2005

Communication, Ocean, and Meteorological Satellite (COMS) to be launched in year 2008 will be the first Korean multi-purpose geostationary satellite aiming at three major missions, i.e.: communication, ocean, and meteorological applications. The development of systems for the meteorological mission sponsored by the Korea Meteorological Administration (KMA) consists of payloads, ground system, and data processing system. The program called COMS Meteorological Data Processing System (CMDPS) has been initiated for the development of data processing system. The primary objective ofCMDPS is to derive the level-2 environmental products from geo-Iocated and calibrated level 1.5 COMS data. Preliminary design for the level-2 data processing system consists of 16 baseline products and will be refined by end of 3rd project year. Also considered for the development are the necessary initial information such as land use and digital elevation map, algorithms for the vicarious calibration and procedures for the calibration monitoring, and radiative transfer model. Here, we briefly introduce the overall development strategy, flow chart for the intended baseline products, a few preliminary algorithm results and future plans.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.65-69
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• 2014

The Communication, Ocean and Meteorological Satellite(COMS) data processing system(CMDPS) has developed to support the meteorological observation and weather prediction by NMSC(National Meteorological Satellite Center) and it is generating the 16 kind of meteorological data(Level 2 product). Unfortunately, currently CMDPS has some problems in terms of the system maintenance and the integrated software efficiency, and the extension to support the next generation meteorological satellite data processing. To solve this problems, in this paper, we suggest the extensible component-based system architecture for COMS meteorological data processing with consideration of identified issues. Proposed system is adapted the component-based frameworks with extensible architecture. We expects that this system will be provide easy ways to develop new satellite data processing algorithms and to maintain the system.

• Journal of Korean Society of Forest Science
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• v.99 no.2
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• pp.197-203
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• 2010

The data of average temperature, average relative humidity, precipitation and average wind speed were collected from 674 meteorological stations in China. A specific procedure that processes original data into a new data format needed in forest fire danger rating forecast system of China was introduced systematically, and the feasibility of this method was validated in this paper. In addition, a set of meteorological data processing software was constructed by the secondary development of GIS in order to realize automation of processing data for the system. Results showed that the approach preformed well in handling temperature, average relative humidity and average wind speed, and the processing effect of precipitation was acceptable. Moreover, the automated procedure could be achieved by GIS and the working efficiency was about 3 times as much as that of manual handling. The informationization level of processing meteorological data was greatly enhanced.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.101-116
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• 2012

In this paper, we have surveyed the existing architectures of the image processing systems for several meteorological satellites and identified issues which are taken into consideration to construct the advanced meteorological satellite image processing system that is being developed by NMSC(National Meteorological Satellite Center). Most of the existing systems provide the functionalities of the image acquisition, the image processing, the data management, and the data dissemination. Those systems have some common problems with respect to system integration and system maintenance. To solve these problems, NOAA, NWS and ESA suggest new system architectures to improve the existing systems. This paper introduces domestic and foreign approaches to build the satellite image processing systems and studies some issues and strategies for developing those systems.

• Proceedings of the KSRS Conference
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• v.1
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• pp.200-203
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• 2006

Cloud detection algorithm is being developed as major one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-1R and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithm and preliminary test result of both algorithms.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1295-1297
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• 2003

Owing to the higher temporal resolution, meteorological satellite data is widely used to monitor the disasters happened on the earth's surface. However, the precision of identifying disaster information is limited by the poor spatial resolution. As known, GIS technology is good at processing and analyzing the geographic information. The result shows, integrating with GIS technology, the ability of monitoring forest fire using meteorological satellite data has been greatly improved.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.367-372
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• 2006

Cloud detection algorithm is being developed as primary one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-IR and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithms and preliminary test results of both algorithms.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.95-101
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• 2015

The backup site operation of the Image Data Acquisition and Control System (IDACS) for Communication Ocean Meteorological Satellite (COMS) is discussed in terms of the ground station configuration, image data processing, and the characteristics of backup activities for both the meteorological image data and the ocean image data. The well-performed backup operation of the COMS IDACS is also confirmed with the first three years normal operation results from April, 2011 to March, 2014. The operation results are analyzed through statistical approach to provide the achieved operational performance of the image data reception, preprocessing, and broadcast.

• Atmosphere
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• v.30 no.3
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• pp.277-291
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• 2020

Low-level wind shear (LLWS) events on glide path at Jeju International Airport (CJU) are evaluated using the Aircraft Meteorological Data Relay (AMDAR) and Korea Meteorological Administration Post-Processing (KMAPP) with 100 m spatial resolution. LLWS that occurs in the complex terrains such as Mt. Halla on the Jeju Island affects directly aircraft approaching to and/or departing from the CJU. For this reason, accurate prediction of LLWS events is important in the CJU. Therefore, the use of high-resolution Numerical Weather Prediction (NWP)-based forecasts is necessary to cover and resolve these small-scale LLWS events. The LLWS forecasts based on the KMAPP along the glide paths heading to the CJU is developed and evaluated using the AMDAR observation data. The KMAPP-LLWS developed in this paper successfully detected the moderate-or-greater wind shear (strong than 5 knots per 100 feet) occurred on the glide paths at CJU. In particular, this wind shear prediction system showed better performance than conventional 1-D column-based wind shear forecast.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.1
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• pp.47-54
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• 2015

Recently, rapid urbanization and industrialization had increased the air pollution in major cities by increasing the fuel consumption. Air pollution models have been widely used for air quality management in many countries. Also, a lot of related studies have been conducted using air dispersion models. In this study, The meteorological preprocessing program was developed to convert the korea meteorological data to the U.S. meteorological data and to expand the usability of air dispersion models of U.S. EPA. In addition, the usability evaluation was carried out through a case study. In the results of the evaluation of the program, this program was accurately convert the Korea meteorological data to the U.S. meteorological data, and the prediction was carried out without a error in air quality modeling. Therefore, the program showed a high utilization as meteorological data pre-processing tool.