• Journal of Wetlands Research
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• v.5 no.1
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• pp.29-40
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• 2003

This study was performed to research the relation between airmass thunderstorm and stability index with 12 years meteorological data(1990~2001) at Busan. Also We used the analysed stability indices from University of Wyoming to consider airmass thunderstorm. The frequency of thunderstorm occurrence during 12 years was 156 days(annual mean 13days). The airmass thunderstorm frequency was 14 days, most of those occurrence were summertime(59%). And occurrence hour of airmass thunderstorm was distributed from 1300LST to 2100LST broadly. The highest forecast index for airmass thunderstorm at Busan was K index, the lowest forecast index was SWEAT index. The forecasting of thunderstorms is based primary on the concepts of conditional instability, convective instability, and forced lifting of air near the surface. Instability is a critical factor in severe weather development. Severe weather stability indices can be a useful tool when applied correctly to a given convective weather situation.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.187-189
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• 2004

This paper investigates the effect of weather factors(such as winds, rain, snows, temperature, clouds and humidity) on transmission line outages. The result shows that weather variables have significant effects on the transmission line historical outages and the relationship between them is nonlinear. Multiple regression analysis using Logit model is proved to be appropriate in forecasting line failure rate in KEPCO systems. It could also provide system operators with useful informations about system operation and planing.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.27 no.4
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• pp.296-313
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• 1982

At a time when world population and food supply are in a delicate balance, it is essential that we look at factors to improve this balance. We can alter the environment to better fit the plant's needs, or we can alter the plant to better fit the environment. Improved technology has allowed us to increase the yield level. For moderately detrimental weather events technology has generally decreased the yield variation, yet for major weather disasters the variation has increased. We have raised the upper level, but zero is still the bottom level. As we concentrate the production of particular crops into limited areas where the environment is closest to optimum, we may be increasing the risk of a major weather related disaster. We need to evaluate the degree of variability of different crops, and how weather and technology can interact to affect it. The natural limits of crop production are imposed by important ecological factors. Production is a function of the climate, the soil, and the crop and all activities related to them. In looking at the environment of a crop we must recognize these are individuals, populations and ecosystems. Under intensive agriculture we try to limit the competition to one desired species. The environment is made up of a complex of factors; radiation, moisture, temperature and wind, among others. Plant response to the environment is due to the interaction of all of these factors, yet in attempting to understand them we often examine each factor individually. Variation in crop yields is primarily a function of limiting environmental parameters. Various weather parameters will be discussed, with emphasis placed on how they impact on crop production. Although solar radiation is a driving force in crop production, it often shows little relationship to yield variation. Water may enter into crop production as both a limiting and excessive factor. The effects of moisture deficiency have received much more attention than moisture excess. In many areas of the world, a very significant portion of yield variation is due to variation in the moisture factor. Temperature imposes limits on where crops can be grown, and the type of crop that can be grown in an area. High temperature effects are often combined with deficient moisture effects. Cool temperatures determine the limits in which crops can be grown. Growing degree units, or heat accumulations, have often been used as a means of explaining many temperature effects. Methods for explaining chilling effects are more limited.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.319-327
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• 2016

This research attempts an analysis that fuses the big data concerning weather variation and health care from January 1, 2011 to December 31, 2014; it gives the weather factor as to what kind of influence there is for the incidence of food poisoning, and also endeavors to be helpful regarding national health prevention. By using R, the Logistic and Lasso Logistic Regression were analyzed. The main factor germ generating the food poisoning was classified and the incidence was confirmed for the germ of bacteria and virus. According to the result of the analysis of Logistic Regression, we found that the incidence of bacterial food poisoning was affected by the following influences: the average temperature, amount of sunshine deviation, and deviation of temperature. Furthermore, the weather factors, having an effect on the incidence of viral food poisoning, were: the minimum vapor pressure, amount of sunshine deviation and deviation of temperature. This study confirmed the correlation of meteorological factors and incidence of food poisoning. It was also found out that even if the incidence from two causes were influenced by the same weather factor, the incidence might be oppositely affected by the characteristic of the germs.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.3
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• pp.171-186
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• 2017

This paper introduces a study on ship performance in waves to consider the effects of added resistance in the early stage of hull-form design. A ship experiences a loss of speed in actual seaways, hence this study proposes the overall procedure of a new design concept that takes into account the hydrodynamic performance of ship in waves. In the procedure, the added resistance is predicted using numerical methods: slender-body theory and Maruo's far-field formulation, since these methods are efficient in initial design stage, and an empirical formula is adopted for short waves. As computational models, KVLCC2 hull and Supramax bulk carrier are considered, and the results of added resistance and weather factor for test models are discussed. The computational results of vertical motion response and added resistance of KVLCC2 hull are compared with the experimental data. In addition, the sensitivity analysis of added resistance and weather factor for KVLCC2 hull to the variations of ship dimensions are conducted, and the change of the added resistance and propulsion factors after hull form variations are discussed.

• KIEAE Journal
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• v.12 no.6
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• pp.113-121
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• 2012

A hospital is the most important infra-facility of the places which take care of people's body in social environment. There exist several environmental factors in the ways to heal the human body in hospital ward, but this study tried to look into the improvable pleasant sickroom environment with focus on light environment among the factors. In other words, this study aims at the research on proper daylight inflow into sickroom space as basic data for understanding the link between healing environment and natural lighting. In the simulation analysis through this research, this study completed the initial simulation using Autodesk Revit 2011 with focus on two types of individual multi-bed room units of the two general hospitals located in Gwangju City. This study made a simulation analysis of The two multi-bed rooms looking to the west using the weather data on Gwangju district, which is the strong point of ECOTECT2011. Conclusively, looking into the analysis of the simulation model in time of attaching the length of in & outside light shelf, the angle controlling of light shelf, the daylight factor and DA were found to show the tendency to decrease in the numerical value due to the decrease in sunlight inflow as the simulation model moved more toward the room from the window in comparison with the existing analysis of multi-bed rooms. Particularly, this study was able to read that the daylight factor and DA were more decreasing to improve at the light shelf than the existing bedrooms; conclusively, this study judges that the natural lighting simulation analysis could be helpful in improving the healing environment as basic data.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.26-31
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• 2009

This study was analysed influence of urban higher temperature in Busan about time series analysis of AWS data. The results are as follows. (1) The temperature of Busan show min $13.2^{\circ}C$ ~max $15.8^{\circ}C$ by 50 years, it is on the rise. (2) The seasonal adjustment series, summer appeared min $17.5^{\circ}C$ ~max $28.9^{\circ}C$ with primitive series similarly. The winter was min $-11.4^{\circ}C$ ~max $17.9^{\circ}C$, the minimum temperature was more lowly than primitive series and maximum temperature was more higher than primitive series. The results, seasonal adjustment series is guessed with influence difference urban structural element beside seasonal factor. (3) Regional analytical result, January appeared with range of min 28% ~max 196% of the seasonal factor and August appeared min 90% ~ max 106%. One of the case which is of 100% or more of the seasonal factor January 12nd~17th, August appears at the 15~17th.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.3
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• pp.304-310
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• 2014

Based on atmosphere weather data by balloon in Osan and Gwangju area, if icing condition occurs in weather environment of altitude range where helicopter is operated was analyzed in quantitative way. Yearly icing occurrence frequency for daytime during recent three years was average 102 days in Osan, average 91 days in Gwangju. Icing weather environment to highly affect operation of helicopter varies a little according to analysis methods but icing intensity at MDT level was calculated in all the methods, and 14.5~38 times was suggested in Osan; 2.5~30 times in Gwangju. Icing at MDT level was calculated in common in all the analysis methods through wide periods such as Jan., Feb., Mar., and Nov. in Osan. In Gwangju, icing at MDT level was suggested focusing on Jan. only. Therefore, military helicopter developed in Korea is required to strive obtaining certificate of airworthiness about icing condition at MDT level for implementation of perfect operational mission and safe operation.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.661-668
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• 2015

Them traffic accidents have been increased every year due to increasing of vehicles numbers as well as the gravitation of the population. The carelessness of drivers, many road weather factors have a great influence on the traffic accidents. Especially, the number of traffic accident is governed by precipitation, visibility, humidity, cloud amounts and temperature. The purpose of this paper is to analyse the effect of road weather factors on traffic accident. We use the data of traffic accident, AWS weather factors (precipitation, existence of rainfall, temperature, wind speed), time zone and day of the week in 2013. We did statistical analysis using logistic regression analysis and decision tree analysis. These prediction models may be used to predict the traffic accident according to the weather condition.

• Journal of Digital Convergence
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• v.18 no.4
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• pp.243-250
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• 2020

Systematic farming can be planned and managed if long-term agricultural weather information of the plantation is available. Because the greatest risk factor for crop cultivation is the weather. In this study, a method for long-term predicting of agricultural weather using the GloSea5 and machine learning is presented for the cultivation of Chinese cabbage. The GloSea5 is a long-term weather forecast that is available up to 240 days. The deep neural networks and the spatial randomforest were considered as the method of machine learning. The longterm prediction performance of the deep neural networks was slightly better than the spatial randomforest in the sense of root mean squared error and mean absolute error. However, the spatial randomforest has the advantage of predicting temperatures with a global model, which reduces the computation time.