• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2005.09a
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• pp.219-221
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• 2005

• ETRI Journal
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• v.38 no.6
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• pp.1172-1178
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• 2016

The atmospheric meteorology parameters of the earth, such as temperature, pressure, and humidity, strongly influence the propagation of signals in Global Navigation Satellite Systems (GNSSs). The propagation delays associated with GNSS signals can be modeled and explained based on the atmospheric temperature, pressure, and humidity, as well as the locations of the satellites and receivers. In this paper, we propose an optimized and simplified low cost GNSS base weather station that can be used to provide a global estimate of the integrated water vapor value. Our algorithm can be used to measure the zenith tropospheric delay based on the measured propagation delays in the received signals. We also present the results of the data measurements performed at our station located in the Tlemcen region of Algeria.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2005.09a
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• pp.202-205
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• 2005

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.60-66
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• 2013

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.113-118
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• 2014

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.104-119
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• 2019

• Atmosphere
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• v.29 no.4
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• pp.429-438
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• 2019

Organic carbon (OC) and elemental carbon (EC) in PM_2.5 were measured with Sunset Laboratory Model-5 Semi-Continuous OC/EC Field Analyzer by NIOSH/TOT method at Anmyeondo Global Atmosphere Watch (GAW) Regional Station (37°32'N, 127°19'E) in July and August, 2017. The mean values of OC and EC were 3.7 ㎍ m^-3 and 0.7 ㎍ m^-3, respectively. During the study period, the concentrations of reactive gases and aerosol compositions were evidently lower than those of other seasons. It is mostly due to meteorological setting of the northeast Asia, where the influence of continental outflow is at its minimum during this season under southwesterly wind. While the diurnal variation of OC and EC were not clear, the concentrations of O₃, CO, NOx, EC, and OC were evidently enhanced under easterly wind at night from 20:00 to 8:00. However, the high concentration of EC was observed concurrently with CO and NOx under northerly wind during 20:00~24:00. It indicates the influence of thermal power plant and industrial facilities, which was recognized as a major emission source during KORUS-AQ campaign. The diurnal variations of pollutants clearly showed the influence of land-sea breeze, in which OC showed good correlation between EC and O₃ in seabreeze. It is estimated to be the recirculation of pollutants in land-sea breeze cycle. This study suggests that in general, Anmyeondo station serves well as a background monitoring station. However, the variation in meteorological condition is so dynamic that it is primary factor to determine the concentrations of secondary species as well as primary pollutants at Anmyeondo station.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2005.09a
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• pp.71-73
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• 2005

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.117-126
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• 2018

The purpose of this study is to analyze the spatial distribution characteristics and spatial changes of Automatic Weather Stations (AWS) in mountainous areas with altitude more than 200 meters in South Korea. In order to analyze the spatial distribution patterns, spatial analysis was performed on 203 Automatic Mountain Meteorology Observation Station (AMOS) points from 2012 to 2016 by Euclidean distance analysis, nearest neighbor index analysis, and Kernel density analysis methods. As a result, change of the average distance between 2012 and 2016 decreased up to 16.4km. The nearest neighbor index was 0.666632 to 0.811237, and the result of Z-score test was -4.372239 to -5.145115(P<0.01). The spatial distributions of AMOSs through Kernel density analysis were analyzed to cover 129,719ha/a station in 2012 and 50,914ha/a station in 2016. The result of a comparison between 2012 and 2016 on the spatial distribution has decreased about 169,399ha per a station for the past 5 years. Therefore it needs to be considered the mountainous regions with low density when selecting the site of AMOS.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.121-125
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• 2001

농업기상정보서비스는 농촌진흥청 정보화 기술개발 사업의 일환으로 개발되었다. 이 사업은 전국의 농업기상자동관측장비(Automatic Weather Station; AWS)를 전산망에 통합하여 전국 농업기상관측망을 구축하고, 농업기상정보의 수집, 저장을 체계화하는 한편, 이를 이용하여 농업인, 정책결정자, 연구원 등에게 필요한 형태로 농업기상정보를 제공하기 위한 목적으로 수행되었다.(중략)