• Journal of the Korean Solar Energy Society
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• v.28 no.2
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• pp.10-18
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• 2008

This study aims to figure out typical meteorological data according to Korean time in order to evaluate building energy performance. Various methods of calculating typical meteorological data were compared and examined to improve accuracy and reliability of this study. This study analyzed and examined such methodologies as typical meteorological data for HASP/ACLD-8001, UK CIBSE TRY developed by CIBSE and prEN ISO 15927-4, (=ISO TRY) an international standard to evaluate annual energy demand of cooling and heating devices. In addition, actual data of KMA corresponding to Seoul in $1985{\sim}2005$ were statistically analyzed according to calculation methodology. The calculated typical meteorological data were compared te actual data using MBE, RMSE and t-Statistic. As a result, According to the comparison between average annual for HASP/ACLD-8001 and ISO TRY standard year, the average annual for HASP/ACLD-8001 is closer to actual measurement, showing that the use of typical meteorological data for HASP/ACLD-8001 is preferred. However, since the input format requested by current simulation is the same international standard as TRY. Therefore, it is necessary to improve accuracy of TRY calculation methodology and accordingly figure out Korean typical meteorological data based on average year.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.330-335
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• 2009

kDomestic studies on meteorologicaldata have been carried out, however they were mostly not constant but limited to fragment compilation. The studies on solar energy, among others, have been relatively active but the measurement of solar irradiance is also limited to some extent. This study, in an effort to identify the difference in data between solar radiance and cloud cover, was intended to compare and analyze the typical meteorological data developed by Korean Solar Energy Society with the solar irradiance calculated using the typical meteorological data and cloud cover data provided by current simulation program. Monthly average solar irradiance from the meteorological data (ISO TRY) of Korea's typical meteorological data which was actuallymeasured appeared to be far below the monthly solar irradiance from the American Department of Energy. The solar irradiance calculated based on cloud cover indicates very limited difference between the two data, so the solar irradiance measured by Korean typical metrologicaldata (ISO TRY) indicated the similar value, which demonstrates the solar irradiance data from Korean Meteorological Administration is more accurate than those US National Weather Center.

• Journal of the Korean Solar Energy Society
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• v.27 no.4
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• pp.157-165
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• 2007

Typical meteorological data is fundamental to computer simulation introduced for environment-friendly architecture designs. Therefore, in order to improve accuracy of computer simulation, typical meteorological data should be established. By examining how to choose typical meteorological data, this study selected the optimized weight factor for TRY where weighting factor was not clearly set. As a result, the same weighting factor was applied to each climatic element and TRY data where the weight factor was applied could have the distribution very similar to measurement data. The weighting factor is considered to reflect geographical characteristics of Seoul and applied climatic elements.

• KIEAE Journal
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• v.17 no.2
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• pp.13-20
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• 2017

Meteorological data is one of the important factors in the calculation of building energy demand. The purposes of this study are to review the limitations of the typical meteorological data of ECO2 program and to create the new typical meteorological data and then analyze the building energy demands for additional regions which are not included in the existing 13 region in the ECO2 program. The extended typical meteorological data to a total of 33 regions were based on IWEC(International Weather for Energy Calculations) data files and were created in the form applicable to the building energy efficiency rating certification system. As a result of comparing the heating energy demands of a representative region with the surrounding regions in each of five regions in Korea, the variance of Cv(RMSE) ranged from 36% to 344% and MBE ranged from -32% to 190% for the whole regions. This suggests that the difference of heating energy demand may vary greatly depending on the region where the meteorological data is used and the meteorological data of more detailed regions is needed for reliable calculation of building energy demand.

• 한국태양에너지학회:학술대회논문집
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• 2009.04a
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• pp.13-18
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• 2009

Building is a major energy consumer, and now many efforts are made to save energy in the design and using equipments. The most noticeable achievement in those efforts is a building energy performance assessment program. But most programs are not satisfying enough to provide exact meteorological data, and data source and calculation, and data collection period are not clearly defined. That is common in most of domestic programs. This study collects typical meteorological data in 16 items and analyzes them with Visual DOE 4.0 to compare with existing data. The comparison found that revised data shows a 11% increase on average during cooling period from June to September, and a 13% decrease on average during heating period from December to February, in terms of building heating and cooling load in a monthly basis.

• New & Renewable Energy
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• v.8 no.2
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• pp.14-23
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• 2012

The TMY (Typical Meteorological Year) for the solar energy study is generated using observation data with 22 solar sites from KMA (Korea Meteorological Administration) during 11 years (2000-2010). The meteorological data for calculation the TMY are used solar radiation, temperature, dew point temperature, wind speed and humidity data. And the TMY is calculated to apply the FS (Finkelstein and Schafer) statistics and RMSE (Root Mean Squared Error) methods. FS statistics performed with each point and each variable and then selected top five candidate TMM months with statistical analysis and normalization. Finally TMY is generated to select the highest TMM score with evaluation the average errors for the 22 whole points. The TMY data is represented average state and long time variations with 22 sites and meteorological data. When TMY validated with the 11-year daily solar radiation data, the correlation coefficient was about 0.40 and the highest value is 0.57 in April and the lowest value is 0.23 in May. Mean monthly solar radiation of TMY is 411.72 MJ which is 4 MJ higher than original data. Average correlation coefficient is 0.71, the lowest correlation is 0.43 in May and the highest correlation is 0.90 in January. Accumulated annual solar radiation by TMY have higher value in south coast and southwestern region and have relatively low in middle regions. And also, differences between TMY and 11-year mean of is distributed lower 100 MJ in Kyeongbuk, higher 200 MJ in Jeju and higher 125 MJ in Jeonbuk and Jeonnam, respectively.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.943-960
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• 2009

This study suggests an algorithm for generating TMY(typical meteorological year) for the Korean peninsula, and generates the TMY based on the algorithm using 11 years(1998~2008) wind data observed at 77 sites of Regional Meteorological Offices(RMO). The algorithm consists of computing TMM scores based on the various statistics defined by the Fikenstein-Shafer statistical model and, in turn, generating TMY based on the TMM scores. Also the algorithm has two stages designed to yield the best representation of the regional wind characteristics appeared during the 11 years(1998~2008). The first stage is designed for the representation of each of 77 regions of RMO and the second is for the Korean peninsula. Various comparison studies are provided to demonstrate the properties of the TMY like its utility and typicality.

• New & Renewable Energy
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• v.20 no.1
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• pp.102-109
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• 2024

The Typical Meteorological Year (TMY) dataset compiles 12 months of data that best represent long-term climate patterns, focusing on global horizontal irradiance and other weather-related variables. However, the irradiance measured on the plane of the array (POA) shows certain distinct distribution characteristics compared with the irradiance in the TMY dataset, and this may introduce some biases. Our research recalculated POA irradiance using both the Isotropic and DIRINT models, generating an updated dataset that was tailored to POA characteristics. Our analysis showed a 28% change in the selection of typical meteorological months, an 8% increase in average irradiance, and a 40% reduction in the range of irradiance values, thus indicating a significant shift in irradiance distribution patterns. This research aims to inform stakeholders about accurate use of TMY datasets in potential decision-making. These findings underscore the necessity of creating a typical dataset by using the time series of POA irradiance, which represents the orientation in which PV panels will be deployed.

• Journal of the Korean Solar Energy Society
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• v.29 no.6
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• pp.102-109
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• 2009

The research on meteorological data in Korea has been carried out but without much consistency and has been limited to some areas only. Of relatively more importance has been the area in the utilization of the solar energy, however, the measurement of the global solar horizontal irradiation has been quite limited. In the current study, the actually measured value of the global solar horizontal irradiation from the meteorological data and the theoretically calculated value of the global solar horizontal irradiation from the cloud amount will be analyzed comparatively. The method of analysis will employ the standard meteorological data drafted by the Korean Solar Energy Society, the standard meteorological data from the presently used simulation program and the corresponding results have been compared with the calculated value of the global solar horizontal irradiation from the cloud amount. The results of comparing the values obtained from MBE(Mean Bias Error), RMSE(Root Mean Squares for Error), t-Statistic methods and those from each of the standard meteorological data show that the actually measured value of the meteorological data which have been converted into standard meteorological data with the help of the ISO TRY method give the monthly average value of the global solar horizontal irradiation. These values compared with the monthly average value from the IWEC from the Department of Energy of the USA show that the value of the global solar horizontal irradiation in the USA is quite similar. In the case of the values obtained from calculation from the cloud amount, the weather data provided by TRNSYS, except only slight difference, which means that the actually measured values of the global solar horizontal irradiation are significant. This goes to show that in the case of Korea, the value of the global solar horizontal irradiation provided by the Korea Meteorological Administration is will be deemed correct.

• Atmosphere
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• v.26 no.1
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• pp.47-58
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• 2016

On 10 July 2014, tornado outbreak occurred over Goyang province in Korea. This was the first supercell tornado ever reported or documented in Korea. The characteristics of the supercell tornado were investigated using an X-band polarimetric radar, surface meteorological observation, wind profiler, and operational numerical weather prediction (Regional Data Assimilation and Prediction System, RDAPS). The supercell tornado developed along a preexisting dryline that was contributed to surface wind shear. The radar analyses examined here show that the supercell tornado indicated a hook echo with mesocyclone. The decending reflectivity core as well was detected before tornadogenesis and prior to intensification of supercell. The supercell tornado exhibited characteristics similar to typical supercell tornado over the Great Plains of the United States, such as hook echo, bounded weak echo region, and slower movement speed relative to the mean wind. Compared to the typical supercell tornado over U.S., this tornado showed horizontal scale of the mesocyclone was relatively smaller and left-mover.