• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 1998.10a
• /
• pp.287-288
• /
• 1998

• Journal of Environmental Science International
• /
• v.5 no.5
• /
• pp.619-633
• /
• 1996

Intraseasonal variability of the tropical convection over the Indian/western Pacific is studied using the Geostationary Meteorological Satellite high cloud amount. This study is directed to find the tropical-extratropical interaction in the frequency range of intraseasonal and interannual variabilities of the summer monsoon occured over the domain of 90E-171W and 495-50N. Especially, in order to investigate the intraseasonal interaction of last Asia summer monsoon associated with the tropical convections in the high cloud amounts, the spatial and time structure of the intraseasonal oscillation for the movement-and the evolution of the large-scale connections are studied. To describe the spatial and the time evolution, the extended empirical orthogonal function analysis is applied. The first mode may be considered to a normal structure, indicating that the strong convection band over 90E-120E is extended to sastward but this mode was detected as the intraseasonal variability during summer monsoon. It is found that the dominant intraseasonal mode of the tropical convection consists of the spatial changes over a broad period range centered around 40~50days.

• Proceedings of the Korean Institute of Landscape Architecture Conference
• /
• 2006.10a
• /
• pp.76-78
• /
• 2006

• Journal of the Korean Solar Energy Society
• /
• v.32 no.2
• /
• pp.28-34
• /
• 2012

It is necessary to estimate the regression coefficients in order to predict the daily global radiation on a horizontal surface. Therefore many different equations have proposed to evaluate them for certain areas. In this work a new correlation has been made to predict the solar radiation for 16 different areas over Korea by estimating the regression coefficients taking into account cloud hours of bright sunshine. Particularly, the multiple linear regression model proposed shows reliable results for estimating the global radiation on a horizontal surface with monthly average deviation of-0.26 to +0.53% and each station annual average deviation of -1.61 to +1.7% from measured values.

• KIEAE Journal
• /
• v.11 no.1
• /
• pp.15-20
• /
• 2011

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design. For the six locations (Seoul, Incheon, Daejeon, Deagu, Gwangju and Busan) in South Korea where the global hourly solar irradiation (GHSI) is currently measured, GHSI was calculated using a comparatively simple cloud cover radiation model (CRM) and sunshine fraction radiation model (SFRM). The result was that the measured and calculated values of GHSI were similar for the six regions. Results of cloud cover and sunshine fraction models have been compared with the measured data using the coefficient of determination (R2), root-mean-square error (RMSE) and mean bias error (MBE). The strength of correlation R2 varied within similar ranges: 0.886-0.914 for CRM and 0.908-0.934 for SFRM. Average MBE for the CRM and SFRM were 6.67 and 14.02 W/m2, respectively, and average RMSE 104.36 and 92.15 W/m2. This showed that SFRM was slightly accurate and used many regions as compared to CRM for prediction of GHSI.

• 한국태양에너지학회:학술대회논문집
• /
• 2011.11a
• /
• pp.232-235
• /
• 2011

Radiation data are the best source of information for estimating average incident radiation. Lacking this or data from nearby locations of similar climate, it is possible to use empirical relationships to estimate radiation from days of cloudiness. It is necessary to estimate the regression coefficients in order to predict the daily global radiation on a horizontal surface. There fore many different equations have proposed to evaluate them for certain areas. In this work a new correlation has been made to predict the solar radiation for 16 different areas over Korea by estimating the regression coefficients taking into account cloud cover. Particularly, the straight line regression model proposed shows reliable results for estimating the global radiation on a horizontal surface with monthly average deviation of-0.26 to +0.53% and each station annual average deviation of -1.61 to +1.7% from measured values.

• Journal of the Korean Solar Energy Society
• /
• v.40 no.2
• /
• pp.37-48
• /
• 2020

This study compares cloud radiation model (CRM) and sunshine fraction radiation model (SFRM) according to the solar altitude using hourly sunshine duration (SD) and cloud cover (CC) data. Solar irradiance measurements are not easy for the expensive measuring equipment and precise measuring technology. The two models with the site fitting and South Korea coefficients have been analyzed for fourteen cities of South Korea during the period (1986-2015) and evaluated using the root mean square error (RMSE) and the mean bias error (MBE). From the comparison of the results, it is found that the SFRM with the site fitting coefficients could be the best method for fourteen locations. It may be concluded that the SFRM models of South Korea coefficients generated in this study may be used reasonably well for calculating the hourly horizontal global irradiance (HGI) at any other location of South Korea.

• Journal of the Korean Solar Energy Society
• /
• v.37 no.4
• /
• pp.13-22
• /
• 2017

In this study, long and short-wave radiations were observed in urban and suburban areas during the summer season, and frequency analysis was performed for each radiation intensity by a new analysis method. The following results were obtained. (1) Long-wave radiation values were found to be larger in the afternoon than in the morning, in both urban and suburban areas, unlike short-wave radiation values. (2) Short-wave radiation showed a right-skewed frequency distribution. In the high energy area greater than $900W/m^2$, the frequency was significantly higher in the suburbs than in the urban areas. (3) Long-wave radiation was in the range of $290{\sim}479W/m^2$, its frequency distribution resembled a normal distribution, and the frequency of 410, $420W/m^2$ was the highest.

• Journal of the Korean earth science society
• /
• v.39 no.3
• /
• pp.228-240
• /
• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.11
• /
• pp.445-452
• /
• 2017

Electric pole is a supporting beam used for power transmission/distribution which accelerometer are used for measuring a external force. The meteorological condition has various effects on the external forces of electric pole. One of them is the elasticity change of the aerial wire. It is very important to perform modelling. The acceleration sensor is converted into a pitch and a roll angle. The meteorological condition has a high correlation between variables, and selecting significant explanatory variables for modeling may result in the problem of over-fitting. We constructed high deviance explained model considering multicollinearity using the Generalized Additive Model which is one of the machine learning methods. As a result of the Variation Inflation Factor Test, we selected and fitted the significant variable as temperature, precipitation, wind speed, wind direction, air pressure, dewpoint, hours of daylight and cloud cover. It was noted that the Hours of daylight, cloud cover and air pressure has high explained value in explonatory variable. The average coefficient of determination (R-Squared) of the Generalized Additive Model was 0.69. The constructed model can help to predict the influence on the external forces of electric pole, and contribute to the purpose of securing safety on utility pole.