• Journal of Korean Elementary Science Education
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• v.17 no.2
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• pp.123-136
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• 1998

In this study, it was purposed to investigate that the student's understading and usage of weather information for the students of elementary, middle and high school The questionaire of 20 questions of 5 categories which included how to get weather information, the understanding of reason for variation of weather elements, the abilities of reading weather map, understanding of weather forecast and the necessity and usefulness of weather map and clouds pictures of weather satellite were prepared and 2 classes of elementary school 5th grade each one class of 2nd and 3rd grade of middle school and 2 classes of high school were tested. followings were revealed in this study; 1) Students of all school are fond of TV watching to get weather information as they used to. 2) They think air temperatures is the most important weather elements and then rainfall. 5ut they seems to unknown the reason why weather elements are vary. 3) They seems to have poor ability of reading weather symbols in weather map and the distribution of air pressure systems. 4) They can read and understand about the reports of words on weather forecast, but most of them can't make weather forecast by the reading of weather map. 5) More than half of students think that the weather map is helpful and especially the cloud pictures from weather satellite is useful for usage of weather information.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.14 no.2
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• pp.125-137
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• 1985

Standard weather data for Seoul has been developed for use in computer calculations for energy requirements, and the 8760 sequential hourly values for seven weather elements have been placed in magnetic tape and cards. Applying the method determining average month, developed by Japanese Society of Heating, Air-Conditioning and Sanitary Engineers, the standard year data have been selected from the monthly average values for three weather elements during the 10year period of 1971 through 1980. The followings are obtained. 1. The Test Reference Year, consisting of 12 months chosen from different calendar years, has been determined, and TRY tape which contains seven weather elements has been prepared. 2. The Typical Weather Year, which means a year close to the average value, is the year of 1978 during the above 10 year period. 3. During the period, Winter Season needs the maximum heating load is from Dec. 1976 to Mar. 1977 and Summer Season needs the maximum cool ins load is from Jun. to Sep, 1978.

• Plant Resources
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• v.7 no.1
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• pp.54-59
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• 2004

This study was conducted to investigate the relationships between yearly variations of weather elements and productivity in rice. In addition, coefficients of correlation among yield and yield components were used to find out the relationships between weather elements and productivity. Coefficients of variance (C.V.) of air temperature mean was considerable with 25％, but the variation by duration of sunshine was small in May. Culm length and number of spikes were great with c.v. of 21.5, 16.4％, respectively. Coefficients of correlation between temperatures of cultivation in May and yield were positive correlations. Coefficients of correlation between precipitation and sunshine of cultivation period from Oct. to May and yield were negative correlations. Coefficients of correlation amount the culm length, number of spikes, 1,000 grains wt. of seed, and yield were positively significant at the level of 1 ％, respectively.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1124-1128
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• 2005

The duration of a construction project is not only a key element for taking a new order, but also a strict yardstick to determine certain project successful or not. However, since construction project is basically outdoor job and most of the activities are proceeded out-air, no matter how the schedule plan has been established accurately, actual project proceeds due to the weather condition, beyond anyone's control. In this paper, the functional relationship between work productivity rate and weather elements is suggested by regression analysis. Difference of the relationship and influence of weather due to the seasonal group are also revealed. With these results, by simulating actual weather data and generating weather forecast through historical data, more accurate schedule would be obtained.

• Korean Journal of Construction Engineering and Management
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• v.5 no.6 s.22
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• pp.80-89
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• 2004

Among the various factors influencing construction productivity, weather conditions or elements become very important factors in planning and executing construction project. It is especially true in Korea where the weather changes dramatically through few seasons. In this study, relationship between construction productivity of the reinforced concrete structure we for the high-rise apartment buildings and 5 weather elements including temperature, humidity, day time, rainfall, and wind velocity have been analyzed The results trough regression analysis showed that weather elements explain $58.8\%$ of productivity in total and temperature and day time were more important factors among them.

• Journal of Environmental Science International
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• v.31 no.4
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• pp.329-339
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• 2022

Better understanding the mechanism of black ice occurrence on the road in winter is necessary to reduce the socio-economic damage it causes. In this study, intensive observations of road weather elements and surface information under the influence of synoptic high-pressure patterns (22^nd December, 2020 and 29^th January, and 25^th February, 2021) were carried out using a mobile observation vehicle. We found that temperature and road surface temperature change is significantly influenced by observation time, altitude and structure of the road, surrounding terrain, and traffic volume, especially in tunnels and bridges. In addition, even if the spatial distribution of temperature and road surface temperature for the entire observation route is similar, there is a difference between air and road surface temperatures due to the influence of current weather conditions. The observed road temperature, air temperature and air pressure in Nongong Bridge were significantly different to other fixed road weather observation points.

• Journal of the Korean Solar Energy Society
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• v.34 no.1
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• pp.8-18
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• 2014

Building simulation is used in a variety of sectors. In its early years, building simulation was mainly used in the design phase of a building for basic functions. Recently, however, it has become increasingly important during the operating phase, for commissioning and facility management. Most building simulation tools are used to estimate the thermal environment and energy consumption performance, and hence, they require the inputting of hourly weather data. A building simulation used for prediction should take into account the use of standard weather data. Weather data, which is used as input for a building simulation, plays a crucial role in the prediction performance, and hence, the selection of appropriate weather data is considered highly important. The present study proposed a technique for generating real-time weather data files, as opposed to the standard weather data files, which are required for running the building simulation. The forecasted weather elements provided by the Korea Meteorological Administration (KMA), the elements produced by the calculations, those utilizing the built-in functions of Energy Plus, and those that use standard values are combined for hourly input. The real-time weather data files generated using the technique proposed in the present study have been validated to compare with measured data and simulated data via EnergyPlus. The results of the present study are expected to increase the prediction accuracy of building control simulation results in the future.

• Journal of Integrative Natural Science
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• v.2 no.2
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• pp.131-167
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• 2009

Global warming is regarded as one of the most critical issues that should be taken care of by the entire global community as it threatens the survival of mankind. South Korea, in particular, undergoes faster warming than the average rate of global warming. South Korea has revealed various warming rates and trends being surrounded by sea on three sides and having complex terrains dominated by mountains. The rates vary according to regions and their urbanization and industrialization. Differences also derive from seasons and weather elements. Changes to the highest, mean, and lowest temperature are also different according to the characteristics of regions and observatories, which is more apparent where the force of artificial weather applies. In an urban area, temperature gaps tend to decrease as the lowest temperature rises more than the highest temperature. Meanwhile, temperature gaps grow further in a coastal or country region where the force of artificial weather is small and the force of natural weather prevails. In this study, the investigator analyzed the changes to the weather elements of 11 observation spots that had gone through no changes in terms of observation environment since 1961, were consecutively observed, and had the quality of their observation data monitored on an ongoing basis. Using the results, I tried to identify natural and artificial causes affecting certain spots. Located on the east coast of the Asian Continent, South Korea sees weather changing very dynamically. Having huge influences on our weather, China has achieved very rapid industrialization for the last 30 years and produced more and more greenhouse gases and air pollution due to large-size development projects. All those phenomena affect our weather system in significant ways. Global warming continues due to various reasons with regional change differences. Thus the analysis results of the study will hopefully serve as basic data of weather statistics with which to set up countermeasures against climate changes.

• The Journal of Internal Korean Medicine
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• v.30 no.1
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• pp.200-211
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• 2009

There are many reports about correlations between meteorological elements and stroke. In Oriental medicine, it is recognized that the weather affects the human body and diseases, but there are few studies about the correlation between meteorological elements and pattern identification of stroke. 105 stroke patients classified into fire-heat pattern or dampress-phlegm pattern were registered during the study period. We took the measurement of each meteorological element (atmospheric pressure, temperature, humidity, wind speed) according to pattern identification and analyzed pattern identification into two groups according to mean of each meteorological element during the study period. Mean temperature was higher with the heat-fire pattern than with the dampness-phlegm pattern. Heat-fire pattern also had higher frequency when temperature was higher than mean temperature. There was no correlation between atmospheric pressure, relative humidity, or wind speed and pattern identification.

• Journal of Environmental Science International
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• v.29 no.10
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• pp.1003-1010
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• 2020

In this study, the necessity for a village unit Automatic Weather System (AWS) was suggested to obtain correct agricultural weather information by comparing the data of AWS of the weather station with the data of AWS installed in agricultural villages 7 km away. The comparison sites are Hyogyo-ri and Hongseong weather station. The seasonal and monthly averaged and cumulative values of data were calculated and compared. The annual time series and correlation was analyzed to determine the tendency of variation in AWS data. The average values of temperature, relative humidity and wind speed were not much different in comparison with each season. The difference in precipitation was ranged from 13.2 to 91.1 mm. The difference in monthly precipitation ranged from 1.2 to 75.4 mm. The correlation coefficient between temperature, humidity and wind speed was ranged from 0.81 to 0.99 and it of temperature was the highest. The correlation coefficient of precipitation was 0.63 and the lowest among the observed elements. Through this study, precipitation at the weather station and village unit area showed the low correlation and the difference for a quantitative comparison, while the elements excluding precipitation showed the high correlation and the similar annual variation pattern.