• Journal of The Korea Institute of Healthcare Architecture
• /
• v.17 no.1
• /
• pp.33-40
• /
• 2011

Daylight is highly beneficial for improving the indoor environmental quality and reducing building energy consumption, daylighting applications are scarcely considered, especially during the care facility design process, because of lack of previous studies on elderly- light environment and complex simulation process. Therefore, daylighting process were performed using ECOTECT, which has various advantage such as easy user interface and simple simulation processes. Moreover, dynamic daylight simulation were performed using whether data. Static simulation are performed to compute static metrics such as daylight factor, whereas dynamic simulation are performed for dynamic metrics such as daylight autonomy and useful daylight illuminance using annual weather data On the basis of daylight autonomy and useful daylight illuminance analysis result, variations in annual daylight performances. A parametric and regression analysis of the window-to-wall ratio and visible transmittance showed that daylight factor, daylight autonomy increased with window-to-wall ratio and visible transmittance. It can be concluded that this new daylight criteria. useful daylight illuminance, will enable architect to obtain better fenestration design.

• Journal of Forest and Environmental Science
• /
• v.34 no.3
• /
• pp.249-252
• /
• 2018

Climate is one of most important environmental factors on the forest ecosystem. This study was conducted to analyze the characteristics of meteorological factors in the forest area and weather stations from July 2015 to June 2016 in Cheuncheon and Hongcheon of Kangwon Province in Korea. The HOBO data logger was installed for meteorological analysis in forests area (site 1 and site 2). The meteorological data from the HOBO data logger compared with meteorological data of the weather station. The meteorological data used for the analysis was monthly mean temperature ($^{\circ}C$), monthly mean minimum temperature ($^{\circ}C$), monthly mean maximum average temperature ($^{\circ}C$), and monthly mean relative humidity (%). As a result of this study, the mean temperature ($^{\circ}C$) of forest area was relatively lower than weather station which is the outside the forest area, and the mean maximum temperature ($^{\circ}C$) of weather station was relatively higher than that of forest area. The mean relative humidity (%) was higher in forest area than weather station.

• Journal of the Korean Solar Energy Society
• /
• v.38 no.1
• /
• pp.1-11
• /
• 2018

In this work, we propose weather prediction models to estimate hourly outdoor temperatures and solar irradiance in the next day using forecasting information. Hourly weather data predicted by the proposed models are useful for setting system operating strategies for the next day. The outside temperature prediction model considers 3-hourly temperatures forecasted by Korea Meteorological Administration. Hourly data are obtained by a simple interpolation scheme. The solar irradiance prediction is achieved by constructing a dataset with the observed cloudiness and correspondent solar irradiance during the last two weeks and then by matching the forecasted cloud factor for the next day with the solar irradiance values in the dataset. To verify the usefulness of the weather prediction models in predicting a short-term building load, the predicted data are inputted to a TRNSYS building model, and results are compared with a reference case. Results show that the test case can meet the acceptance error level defined by the ASHRAE guideline showing 8.8% in CVRMSE in spite of some inaccurate predictions for hourly weather data.

• Journal of Environmental Science International
• /
• v.27 no.7
• /
• pp.509-518
• /
• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.6
• /
• pp.116-126
• /
• 2013

Weather factor to affect driver's driving environment are due to changes in weather conditions is caused rainfall, snowfall, fog etc and the reducing of road capacity and because deteriorating weather could be affect the headway and vehicle speed and the decrease in lane caused by an accident occurs that was analyzed that bad weather occur congestion greater than on the clear day. Bad weather to reduce of the driver's visibility was analysed the sensitive to changes in travel speed and traffic accident to appears high characteristics according to weather conditions on the expressway(higher speed) than general road. As a result, visibility have been determined to be important factor in changes of the highway traffic flow characteristics. Therefore, in this study, we selected traffic volume and travle speed that have a major impact on high-speed expressway basic segments as importance effect factor and we selected to subject of analysis among the Metropolitan Expressway that it could be obtained certain level of traffic volume data and we studied the changing of expressway traffic flow due to change visibility after the collecting of meteorological and traffic data. In order to perform this study, data collection and analysis methods were established through the existing literature and we had selected level of visibility of the expressway and we had performed the statistical verification. Finally, we had calculated the rate of change of expressway traffic flow characteristics due to visibility and we had come up with a way to apply at capacity and service level analysis.

• Atmosphere
• /
• v.14 no.3
• /
• pp.19-28
• /
• 2004

In this study, two years Automatic Weather Station (AWS) data observed near the coast and islands are used to evaluate gust factors only when time averaged wind speed is higher than 5 ms. The gust factors are quite different in spatial and temporal domain according to analysis method. As the averaged time is increased, the gust factors are also increased. But the gust factors are decreased when wind speed is increased. It is because each wind speed is averaged one and a maximum wind is the greatest one for each time interval. The result from t-test is shown that all data are included within the 99% significance level. A sample standard deviation of ten minutes and one minute are 0.137~0.197, 0.067~0.142, respectively. Recently, the gust factor provided at the Korea Meteorological Administration (KMA) Homepage is calculated with one-hour averaged method. All though this method is hard to use directly for forecasting the strong wind over sea and coast, the result will be a great help to express Ocean Storm Flash in the Regional Meteorological Offices and the Meteorological Stations.

• Plant Journal
• /
• v.7 no.1
• /
• pp.40-48
• /
• 2011

This study shows the comparison between expected and actual capacity factors of a wind farm through wind resource analyzation. The expected capacity factor comes from an 'automatic weather system' run by the Korean national weather service and a 'meteorological mast' run by a project owner. Based on this comparison and analysis, the importance of meteorological mast micro-siting and selection of wind turbine class and type, will be studied along with presenting important implications for wind farm expansion and development.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2004.11a
• /
• pp.394-397
• /
• 2004

Working-day calculation with weather factors of construction-site has estimated wethout proper data. They usually estimate it with their own experience and intuition. It causes not only economic loss to time-adjustment but also conflict with each participants. Moreover, weather estimation becomes worse than before, due to tendency of recently weather change. So, in this paper we present optimal estimation method as assessment by period of the arithmetical mean methods. For that, we analyse characteristic of the regions and weather change of temperature and rainfall which affects time.

• Atmosphere
• /
• v.30 no.4
• /
• pp.347-360
• /
• 2020

The automatic algorithm optimized for the Korean Peninsula was developed to detect and track the center of typhoon based on a geometrical method using high-resolution retrieved WISSDOM (WInd Syntheses System using DOppler Measurements) wind and reflectivity data. This algorithm analyzes the center of typhoon by detecting the geometric circular structure of the typhoon's eye in radar reflectivity and vorticity 2D field data. For optimizing the algorithm, the main factors of the algorithm were selected and the optimal thresholds were determined through sensitivity experiments for each factor. The center of typhoon was detected for 5 typhoon cases that approached or landed on Korean Peninsula. The performance was verified by comparing and analyzing from the best track of Korea Meteorological Administration (KMA). The detection rate for vorticity use was 15% higher on average than that for reflectivity use. The detection rate for vorticity use was up to 90% for DIANMU case in 2010. The difference between the detected locations and best tracks of KMA was 0.2° on average when using reflectivity and vorticity. After the optimization, the detection rate was improved overall, especially the detection rate more increased when using reflectivity than using vorticity. And the difference of location was reduced to 0.18° on average, increasing the accuracy.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
• /
• v.3 no.3
• /
• pp.199-208
• /
• 1974

The effectiveness with which evaporative cooling can be used in Korea was analysed by making use of weather data of 15cities in a past decade. In ASHRAE comfort chart for a still air atmospheric condition was divided into two dimensional array, 14 zones by effective temperature and 10 zones by relative humidity, and all hours of weather condition in those zones were. computed from every 4 hours weather data in a past decade. From this computation obtained were for 15 cities : 1. average annual total hours above $23^{\circ}C$ ET 2. effective temperatures with $5\%$ excess factor, and 3. ratios of all hours in wet (above $25.6^{\circ}C$ WBT), intermediate $(22^{\circ}C\;to\;25.6^{\circ}C\;WBT)$, and dry $(below\;22^{\circ}C\;WBT)$ area to total hours in whole area on comfort chart beyond $23^{\circ}C$ ET to effective temperature of $5\%$ excess factor. It was shown from this computational result that in Korea evaporative cooling was not effective for building and residential comfort air conditioning but could be useful for comfort air conditioning in industry and industrial air conditioning, depending upon the air stream velocity and the type of application.