• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.5
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• pp.31-40
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• 2017

The aim of this study is to estimate net irrigation requirements for red pepper during growing period using soil moisture model. The soil moisture model based on water balance approach simulates soil moisture contents of 4 soil layers in crop root zone considering soil moisture extraction pattern. The LAMP (Land-Atmosphere Modeling Package) high resolution meteorological data provided from National Center for AgroMeteorology (NCAM) was used to simulate soil moisture as the input weather data. Study area for the LAMP data and soil moisture simulation covers $36.92^{\circ}{\sim}37.40^{\circ}$ in latitude and $127.36^{\circ}{\sim}127.94^{\circ}$ in longitude. Soil moisture was monitored using FDR (Frequency Domain Reflectometry) sensors and the data were used to validate the simulation model from May 24 to October 20 in 2016. The results showed spatially detailed soil moisture pattern under different weather conditions and soil texture. Net irrigation requirements were also different by location reflecting the spatially distributed weather condition. The average of the requirements was 470.7 mm and averages about soil texture were 466.8 mm, 482.4 mm, 456.0 mm, 481.7 mm, and 465.6 mm for clay loam, sandy loam, silty clay loam, clay, and sand respectively. This study showed spatial differences of soil moisture and the irrigation requirements of red pepper about spatially uneven weather condition and soil texture. From the results, it was demonstrated that high resolution meteorological data could provide an opportunity of spatially different crop water requirement estimation during the irrigation management.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.29-40
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• 2023

Anxiety is known to upset the balance of the attentional system and prioritize the stimulus-driven system over the goal-directed system; however, self-instruction induces goal-directed behavior with the self-regulation effect. This study verified the effects of meteorological and self-instruction conditions on pilot anxiety and flight task performance for in-service pilots in a virtual reality environment. The meteorological conditions were divided into visual meteorological and very low visibility conditions, and the flight tasks were conducted by varying whether or not self-instruction was performed. The experiment results reveal that anxiety and heart rate were higher, and the performance of the flight task was lower in the very low visibility condition. However, anxiety and heart rate were lower, and the performance of the flight task was higher in the self-instruction condition. This result suggests that accidents due to difficulty in flight may increase because of anxiety, but such accidents may decrease because of flight performance improvement by self-instruction.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.10a
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• pp.404-405
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• 2008

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2010.04a
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• pp.162-164
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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.171-176
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• 2015

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.873-875
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• 2003

It was studied the relationship between the red tide occurrence and the meteorological factors, and the satellite monitoring for red tide. From 1990 through 2001, the red tide continuously appeared and the number of red tide occurrence increased every year. A common condition for the red tide occurrence was heavy precipitation 2${\sim}$4 days earlier, and the favorable conditions for the red tide formation were high air temperature, proper sunshine and light winds for the day in red tide occurrence. From satellite images, it was possible to monitor the spatial distributions and concentrations of red tide.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.271-278
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• 2021

In this paper, a tropospheric delay error was calculated by using meteorological data collect from weather station and Saastamoinen model, and an empirical variogram of the tropospheric delay in the Korean peninsula was estimated. In order to estimate the empirical variogram of the tropospheric delay according to weather condition, sunny day, rainy day, and typhoon day were selected as analysis days. Analysis results show that a maximum correlation range of the empirical variogram on sunny day was about 560 km because there is overall trend of the tropospheric delay. On the other hand, the maximum correlation range of the empirical variogram on rainy was about 150 km because the regional variation was large. Although there is regional variation when the typhoon exists, there is a trend of the tropospheric delay due to a movement of the typhoon. Therefore, the maximum correlation range of the empirical variogram on typhoon day was about 280 km which is between sunny and rainy day.

• Clean Technology
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• v.19 no.2
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• pp.95-104
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• 2013

Onsan Industrial Complex located in a nearby the Ulsan Petrochemical Complex and in the east of the coast. For this reason, air pollution substances emitted by Onsan Industrial Complex especially tend to have an effect on meteorological factors such as sea breeze. In this study, we assessed the frequency of sea breeze and mist using the meteorological data, and analyzed potential temperature and upper wind condition for assessment of atmospheric pollution concentration influenced by meteorological phenomena in a nearby the Onsan industrial complex. From an analysis results, when mist and sea breeze happened, each higher concentration phenomenon of $PM_{10}$ and $SO_2$ appeared each 57.2%, 71.8% and 46.6%, 57.7% respectively. Hence, we confirmed that meteorological phenomena such as mist and sea breeze had an effect on high concentration of air pollution substances in the research area. Analytical result of meteorological data in upper layer using potential temperature and wind condition, we confirmed that advection of air pollution substances emitted in Ulsan Petrochemical Complex by sea breeze have an effect on high concentration in Onsan Industrial Complex and nearby the residential area. In particular;concentration in Onsan Industrial Complex were higher than the average concentration by a factor of more than over 1.5 times when sea breeze by stable condition in atmospheric layer appeared.

• The Journal of Information Systems
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• v.31 no.3
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.60-60
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• 2017

It is important to measure the gas exchange activity of the crops in canopy scale to understand the process of biomass production and yield formation. Thermal imaging of the canopy surface temperature is a powerful tool to detect the gas exchange activity of the crop canopy. The simultaneous measurement of the canopy temperature and the meteorological data enables us to calculate the canopy diffusive conductance ($g_c$) based on the heat flux model (Monteith et al. 1973, Horie et al. 2006). It is, however, difficult to realize the long-term and continuous monitoring of $g_c$ due to the occurrence of the calculation error caused by the fluctuation of the environmental condition. This is partly because the model assumption is too simple to describe the meteorological and aerodynamic conditions of the crop canopy in the field condition. Here we report the novel method of the direct measurement of the aerodynamic resistance ($r_a$) of the crop canopy, which enables us the stable and continuous measurement of the gas exchange capacity of the crop plants. The modified heat balance model shows the improved performance to quantify $g_c$ under the fluctuating meteorological condition in the field. The relationship between $g_c$ and biomass production of rice and soybean varieties is also discussed in the presentation.