• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.525-529
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• 2009

On the limited urban area meteorological data are hard to be collected because of the cost problem. The facilities collecting the data require high installment cost. Recently, the sensor network technique comes to the fore as a solution. Furthermore a mobile phone also becomes to be recognized as a sensor. This paper studies an application to service the meteorological map using mobile phone sensor. A design results for system implementation are introduced in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.203-206
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• 2009

Because the meteorological observation towers are scattered over large area, the collected meteorological data are very sparse. Therefore, the need for data collection on the limited urban areas like a specific building or subway area brings about vest cost which is required to install the corresponding sensors on the areas. Recently, to overcome this problem, the sensor network technique comes to the fore. This paper studies an application to service the meteorological map using mobile phone sensors.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.199-202
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• 2007

COMS (Communication, Ocean and Meteorological Satellite) is a geostationary satellite and has been developing by KARI for communication, ocean observation and meteorological observation. Conventional thermal control design, using MLI (Multi Layer Insulation), OSR (Optical Solar Reflector), heater and heat pipe, is utilized. Ka-band components are installed on South wall, while other equipment for sensors are installed on the opposite side, North wall. High dissipating communication units are located on external (surface) heat pipe and are covered by internal insulation blankets to decouple them from the rest of the satellite. External satellite walls are covered by MLI or OSR for insulation from space and for rejection internal heat to space. The ocean and meteorological sensors are installed on optical benches on the top floor to decouple thermally from the satellite. Single solar array wing is adopted in order to secure clear field of view of radiant cooler of IR meteorological sensor. This paper presents principles of thermal control design for the COMS.

• Atmosphere
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• v.19 no.2
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• pp.213-226
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• 2009

In order to investigate the characteristics of Changma over the Korean peninsula, KEOP-2007 IOP (Intensive Observing Period) was conducted from 15 June 2007 to 15 July 2007. KEOP-2007 IOP is high spatial and temporal radiosonde observations (RAOB) which consisted of three special stations (Munsan, Haenam, and Ieodo) from National Institute of Meteorological Research, five operational stations (Sokcho, Baengnyeongdo, Pohang, Heuksando, and Gosan) from Korea Meteorological Administration (KMA), and two operational stations (Osan and Gwangju) from Korean Air Force (KAF) using four different types of radiosonde sensors. The error statistics of the sensor of radiosonde were investigated using quality control check. The minimum and maximum error frequency appears at the sensor of RS92-SGP and RS1524L respectively. The error frequency of DFM-06 tends to increase below 200 hPa but RS80-15L and RS1524L show vice versa. Especially, the error frequency of RS1524L tends to increase rapidly over 200 hPa. Systematic biases of radiosonde show warm biases in case of temperature and dry biases in case of relative humidity compared with ECMWF (European Center for Medium-Range Weather Forecast) analysis data and precipitable water vapor from GPS. The maximum and minimum values of systematic bias appear at the sensor of DFM-06 and RS92-SGP in case of temperature and RS80-15L and DFM-06 in case of relative humidity. The systematic warm and dry biases at all sensors tend to increase during daytime than nighttime because air temperature around sensor increases from the solar heating during daytime. Systematic biases of radiosonde are affected by the sensor type and the height of the sun but random errors are more correlated with the moisture conditions at each observation station.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1077-1080
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• 2009

Dense meteorological data are hard to be collected on the limited urban areas because of vest cost which is required to install the corresponding sensors on the areas. Recently, to overcome this problem, the sensor network technique comes to the fore. This paper studies an application to service the meteorological map using mobile phone sensors. A design results for system implementation are introduced in this paper.

• Atmosphere
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• v.24 no.3
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• pp.445-456
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• 2014

A real-time quality control system for meteorological data (air temperature, air pressure, relative humidity, wind speed, wind direction, and precipitation) measured by an integrated meteorological sensor has been developed based on comparison of quality control procedures for meteorological data that were developed by the World Meteorological Organization and the Korea Meteorological Administration (KMA), using time series and statistical analysis of a 12-year meteorological data set observed from 2000 to 2011 at the Incheon site in Korea. The quality control system includes missing value, physical limit, step, internal consistency, persistence, and climate range tests. Flags indicating good, doubtful, erroneous, not checked, or missing values were added to the raw data after the quality control procedure. The climate range test was applied to the monthly data for air temperature and pressure, and its threshold values were modified from ${\pm}2{\sigma}$ and ${\pm}3{\sigma}$ to ${\pm}3{\sigma}$ and ${\pm}6{\sigma}$, respectively, in order to consider extreme phenomena such as heat waves and typhoons. In addition, the threshold values of the step test for air temperature, air pressure, relative humidity, and wind speed were modified to $0.7^{\circ}C$, 0.4 hPa, 5.9%, and $4.6m\;s^{-1}$, respectively, through standard deviation analysis of step difference according to their averaging period. The modified quality control system was applied to the meteorological data observed by the Weather Information Service Engine in March 2014 and exhibited improved performance compared to the KMA procedures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1327-1332
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• 2011

In the mobile meteorological information services, an existing sensor system should be expanded to serve precise information. This is because of large cost problem to add the existing sensors. This thesis proposes a system architecture to construct scalable mobile meteorological information services and suggests mobile phone, sensor network, and public traffic vehicle as expended sensors. The proposed scalable sensors are compared each other and analysed the results to evaluated their strength and weakness. In this system, based on the characteristics of the sense data collected at server, a data processing methods are proposed to support efficient query processing. The proposing data processing methods have several benefits. They compress some data volume sensed by various sources on some area at some time to a logical unit. Still it could preserve same services quality.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.1155-1167
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• 2018

We developed a small sensor observation system (SSOS) at a relatively low cost to observe the atmospheric boundary layer. The accuracy of the SSOS sensor was compared with that of the automatic weather system (AWS) and meteorological tower at the Korea Meteorological Administration (KMA). Comparisons between SSOS sensors and KMA sensors were carried out by dividing into ground and lower atmosphere. As a result of comparing the raw data of the SSOS sensor with the raw data of AWS and the observation tower by applying the root-mean-square-error to the error, the corresponding values were within the error tolerance range (KMA meteorological reference point: humidity ${\pm}5%$, atmospheric pressure ${\pm}0.5hPa$, temperature ${\pm}0.5^{\circ}C$. In the case of humidity, even if the altitude changed, it tends to be underestimated. In the case of temperature, when the altitude rose to 40 m above the ground, the value changed from underestimation to overestimation. However, it can be confirmed that the errors are within the KMA's permissible range after correction.

• Journal of Satellite, Information and Communications
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• v.8 no.3
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• pp.32-40
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• 2013

The Boltwood Cloud Sensor is meteorological sensor that is used to estimate an amount of clouds in the sky. This sensor will be installed for OWL(Optical Wide-field patroL) telescope and observatory system of Korea Astronomy and Space Science. Before applying this sensor to an observatory system, we performed test observations at Chungbuk University Observatory at Jincheon, Chungbuk. During the test run, a significant correlation between air temperature difference and the number of visible stars recorded in the CCD frames has not been found. This preliminary result can be attributed to test environment of the observation and our lack of knowledge on calculation algorithm as well as the hardware system of the Boltwood Cloud Sensor.In this paper, we present the procedure and the result of the performance test employing the cloud sensor.

• Atmosphere
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• v.24 no.3
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.