• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 춘계학술대회 논문집
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• pp.67-71
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• 2009

본 논문에서는 우리나라에서 동일한 환경에 설치되어 있는 247.5kW bulk형 모듈과 a-Si형 모듈의 6월 발전량을 조사 분석하여 기상조건(일조량, 평균기온, 강수량, 운량, 풍속 등)과의 관계를 분석하고 최근 지구온난화 등으로 인한 기후변화에 따라 보다 고효율적인 모듈 산정방안을 제시하였다.

• 한국농공학회논문집
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• 제59권5호
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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.

• 감성과학
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• 제26권4호
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• pp.29-40
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• 2023

불안은 주의 시스템의 균형을 깨트려 목표 지향 시스템보다 자극 주도 시스템을 우선하게 만드는 것으로 알려져 있으나, 자기 교시는 자기 조절의 효과로 목표 지향적 행동을 유도하게 한다. 본 연구는 가상현실 환경에서 현직 조종사를 대상으로 기상 및 자기 교시 조건이 조종사에게 발생하는 불안과 비행 과제의 수행에 미치는 영향을 검증하였다. 기상 조건은 시계비행 기상 상황과 악기상 상황으로 구분하였고 자기 교시의 수행 여부를 달리하여 비행 과제를 수행하게 하였다. 실험 결과 악기상 상황에서 불안과 심박수가 더 높고 비행 과제의 수행도가 더 낮은 것으로 나타났으나, 자기 교시를 수행하는 조건에서는 불안과 심박수가 더 낮고 비행 과제의 수행도가 더 높은 것으로 나타났다. 이 결과는 불안의 영향으로 비행에 어려움을 겪어 사고로 연결될 가능성이 증가할 수 있으나, 자기 교시에 의한 비행 수행의 향상으로 사고로 연결될 가능성이 감소할 수 있음을 시사한다.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2008년도 추계학술대회 논문집
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• pp.404-405
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• 2008

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2010년도 춘계학술대회 논문집
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• pp.162-164
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• 2010

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2015년도 하계 학술발표논문집
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• pp.171-176
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• 2015

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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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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• 제10권4호
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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.

• 청정기술
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• 제19권2호
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• pp.95-104
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• 2013

온산공업단지는 인근에 울산석유화학단지가 위치해 있고 동쪽에는 바다가 위치하고 있는 공업지역이다. 이러한 이유로 온산공업단지에서 배출되는 대기오염물질은 특히, 해풍과 같은 기상인자에 영향을 받기 쉽다. 본 연구에서는 기상자료를 분석하여 해풍과 박무발생 빈도를 평가하였으며, 온산공업단지 인근의 기상현상에 의해 영향을 받는 대기오염물질의 농도를 평가하기 위해 상층바람조건과 온위를 분석하였다. 분석결과, 박무와 해풍이 발생될 때, 미세먼지($PM_{10}$)는 각각 57.2%, 71.8%, 이산화황($SO_2$)은 46.6%, 57.7%로 고농도 현상이 나타났다. 이런 결과를 통해 박무와 해풍과 같은 기상현상이 대기오염물질의 고농도에 영향을 주는 것을 확인하였다. 온위와 상층바람조건을 활용한 상층기상을 분석한 결과, 해풍에 의한 울산석유 화학단지에서 배출된 대기오염물질의 이류가 온산공업단지 인근의 고농도 현상에 영향을 주는 것을 확인하였다. 특히, 안정한 대기조건에서 해풍이 발생했을 때, 온산공업단지의 평균농도에 비해 1.5배 이상 고농도 현상이 나타났다.

• 한국정보시스템학회지:정보시스템연구
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• 제31권3호
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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.