• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.117-127
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• 2020

The Early Warning System for agrometeorological hazard of the Rural Development Administration (Korea) forecasts detailed weather for each farm based on the meteorological information provided by the Korea Meteorological Administration, and estimates the growth of crops and predicts a meteorological hazard that can occur during the growing period by using the estimated detailed meteorological information. For verification of early warning system, automated weather observation network was constructed in the study area. Moreover, a real-time web display system was built to deliver near real-time weather data collected from the observation network. The meteorological observation system collected diverse meteorological variables including temperature, humidity, solar radiation, rainfall, soil moisture, sunshine duration, wind velocity, and wind direction. These elements were collected every minute and transmitted to the server every ten minutes. The data display system is composed of three phases: the first phase builds a database of meteorological data collected from the meteorological observation system every minute; the second phase statistically analyzes the collected meteorological data at ten-minutes, one-hour, or one-day time step; and the third phase displays the collected and analyzed meteorological data on the web. The meteorological data collected in the database can be inquired through the webpage for all data points or one data point in the unit of one minute, ten minutes, one hour, or one day. Moreover, the data can be downloaded in CSV format.

• Atmosphere
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• v.28 no.2
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• pp.187-200
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• 2018

The heavy snowfall phenomenon with thunder and lightning occurred in Yeongdong coastal region on 20 January 2017. Amount of snow on that day was a maximum of 47 cm and was concentrated in a short time (2 hours) at the Yeongdong coastal area. The mechanism of thundersnow was investigated to describe in detail using observational data and numerical simulation (Weather Research and Forecast, WRF) applied lightning option. The results show that a convective cloud occurred at the Yeongdong coastal area. The east wind flow was generated and the pressure gradient force was maximized by the rapidly developed cyclone. The cold and dry air in the upper atmosphere has descended (so called tropopause folding) atmospheric lower layer at precipitation peak time (1200 LST). In addition, latent heat in the lower atmosphere layer and warm sea surface temperature caused thermal instability. The convective cloud caused by the strong thermal instability was developed up to 6 km at that time. And the backdoor cold front was determined by the change characteristics of meteorological elements and shear line in the east sea. Instability indexes such as Total totals Index (TT) and Lightning Potential Index (LPI) are also confirmed as one of good predictability indicates for the explosive precipitation of convective rainfall.

• Plant Resources
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• v.5 no.3
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• pp.196-201
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• 2002

This study was conducted to investigate the relationships between yearly variations of climatic elements and yearly variations of productivity in sesame. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 10 years from 1992 to 2001. The meteorological data gathered at the Yeosu Weather Station for the same period were used to find out the relationships between climatic elements and productivity. Yearly variation of the amount of precipitation in July and September were large with coefficients of variation(c.v.) of 64.59, 92.47%, respectively, but the variation of the average temperature in June and August were relative small. Yield and plant height greatly with c. v. of 26.24, 23.41 %, respectively, 1, 000 grain weights show more or less c.v. of 3.83% and length capsule setting show still less variation. Correlation coefficients between maximun temperature in period of cultivation(from June to September) and yield are positively significant at the level of 5.1 %, respectively. Correlation coefficients amount the plant height, length capsule setting, number of capsules per plant, weight of 1, 000 grains and seed yield were positively significant at the level of 1 %, respectively. Simple linear regression equations by the least square method are estimated for number of capsules per plant(Y$_1$) and the maximun temperature in August(X) as $Y_1$=10.1255+0.1725X, and for yield(Y$_2$) and the maximun temperature in August(X) as $Y_2$=21.6151 + 1.3724X.

• Plant Resources
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• v.6 no.3
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• pp.159-164
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• 2003

This study was conducted to investigate the relationship between yearly variations of climatic elements and yearly variations of productivity in malting barley. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 10 years from 1991 to 2000. The meteorological data gathered at the Yeosu Weather Station for the same period were used to find out the relationships between climatic elements and productivity. Yearly varation of the amount of precipitation in December and January were large with coefficients of variation(c. v.) of 97.9, 51.3%, respectively, but the variation of the maximum temperature and minimum temperature in April were relative small. Yield, weight of 1,000 grains and culm length were greatly with c. v. of 37.3, 49.3 and 41.3%, respectively. spike length and number of spikes show more or less c. v. of 3.8, 24.7% respectively and number of grains per spike show still less variation with c. v. of 9.4%. Correlation coefficients between temperature of mean, maximum and minimum in February and seed yield and yield components were positively significant at level of 5.1%, respectively. Correlation coefficients between precipitation of April and seed yield were positively significant correlation at the level of 5.1 %, respectively, but the duration of sunshine in April and seed yield were negatively significant at the level of 5.1%, respectively. Correlation coefficients of those, yield components and yield, culm length, spike length, number of grains per spike, number of spikes per $m^2$, weight of 1,000 grains and seed yield were positively significant at the level of 5.1 % respectively.

• Proceedings of the Korean Society of Crop Science Conference
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• 1988.07a
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• pp.50-51
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• 1988

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2004.05a
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• pp.222-223
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• 2004

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2010.04a
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• pp.553-554
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• 2010

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2015.08a
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• pp.156-160
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• 2015

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.564-566
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• 2005

The relation between HPA (High Power Amplifier) and COMS (Communication Ocean Meteorological Satellite) multi-carrier is analyzed in this paper. MODAC (Meteorological and Ocean Data Application Center) has a primary mission to transmit processed data, HRIT (High Rate Information Transmission) and LRIT (Low Rate Information Transmission), which is normalized and calibrated by pre-processing. It is also replaced with the SOC (Satellite Operation Center) in emergency case and can transmit the command and ranging tones for operation of COMS. From the result of simulation with modelled HPA, it is found that the multi-carrier in one HPA can give rise to an inter-modulation which makes harmonic and spurious elements increase in-band. Under the environment of these increased parasitic elements, the degradation of multi-carrier's quality is estimated from the ratio of the amount of noise to total output power of HPA.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.2
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• pp.53-62
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• 2012

Demand for high resolution weather data grows in the agriculture and forestry fields. Local Analysis and Prediction System (LAPS) can be used to analyze the local weather at high spatial and temporal resolution, utilizing the data from various sources including numerical weather prediction models, wind or temperature profilers, Automated Weather Station (AWS) networks, radars, and satellites. LAPS has been set to analyze weather elements such as air temperature, relative humidity, wind speed, and wind direction every hour at the spatial resolution of $100m{\times}100m$ for Gyeonggi-do on near real-time basis. The AWS data were revised by adding the agricultural field AWS data (33 stations) in addition to the KMA data. The analysis periods were from 1 to 31 August 2009 and from 15 to 21 February 2010. The comparison of the LAPS output showed the smaller errors when using the agricultural AWS observation data together with the KMA data as its input data than using only either the agricultural or KMA AWS data. The accuracy of the current system needs improvement by further optimization of analyzing options of the system. However, the system is highly applicable to various fields in agriculture and forestry because it can provide site specific data with reasonable time intervals.