• Atmosphere
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• v.25 no.2
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• pp.309-322
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• 2015

The objective of this study is to evaluate the impact of the high resolution topographies and landuses data on simulated meteorological variables (wind speed at 10 m, temperature at 2 m and relative humidity at 2 m) in WRF. We compare the results with WRF simulation using each resolution of the topographies and landuses, and with 37 AWS observation data on the Seoul metropolitan regions. According to results of using high-resolution topography, WRF model gives better topographical expression over domain. And we can separate more detail (Low intensity residential, high intensity residential, industrial or commercial) using high resolution landuses data. The result shows that simulated temperature and wind speed are generally higher than AWS observation data. However, simulation trend with temperature, wind speed, and relative humidity are similar to observation data. The reason for that is that the high precipitation event occurred in CASE 1 and 2. Temperature have correlation of 0.43~0.47 and standard deviation of $2.12{\sim}2.28^{\circ}C$ in CASE 1, while correlation of more than 0.8 and standard deviation of $3.05{\sim}3.18m\;s^{-1}$ in CASE 2. In case of wind speed, correlation have lower than 0.5 and Standard Deviation of $1.88{\sim}2.34m\;s^{-1}$ in CASE 1 and 2. In statistical analysis shows that using highest resolution (U01) results are more close to the AWS observation data. It can be concluded that the topographies and landuses are important factor that affect model simulation. However, the tendency to always use high resolution topographies and landuses data appears to be unjustified, and optimal solution depends on the combination of scale effect and mechanisms of dynamic models.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.363-369
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• 2002

Orifice meter is the most widely used flowmeter in custody transfer between KOGAS and city gas companies. Absolute pressure value is needed to calculate the gas flow of orifice metering system, but the gauge pressure transmitters are mainly used in the field. In case that the gauge pressure transmitters are used, the fixed value as standard atmospheric pressure(101.325kPa) is applied for the absolute pressure value. The real, local atmospheric pressures of each metering station are different from the standard condition as the altitude and weather conditions. In this study the flow calculation errors were quantitatively analyzed through examining the atmospheric pressures of 50 stations of KOGAS. The data for analysis are such like the time data of supplied gas amount, the altitude of each metering station, the time data of atmospheric pressures and altitudes of each weather observatory. The results showed that the local atmospheric pressures were different from the standard value and the gas flow calculation errors were distributed between $-0.024\%{\~}0.025\%$ based on the supplied gas amount in the year 1999 and 2000.

• Journal of the Korean Institute of Landscape Architecture
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• v.21 no.4
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• pp.69-82
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• 1994

The purpose of this study is to estimate the probable period of the planting work in consideration of weather factors. The impact degree of weather factors on the control of planting schedule was measured by the possible working days on the basis of weather condition. To establish the weather standard, the researcher analyzed the questionnaires on the manager of planting work and also the meteorological data for 10 years(1983-1992) in Seoul. The results are as follows; $\circled1$ The possible period of the planting work is from March 17 to May 18 Spring and from September 26 to December 15 in Autumn during a year. $\circled2$ The problem working days of the planting work(106-130) days per year) are less than the building construction days(174 days per year), because of handling the living material of plants, specially in summer and winter.

• Atmosphere
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• v.26 no.3
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• pp.461-471
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• 2016

A quality check algorithm for the Weather Information Service Engine pulsed Doppler wind lidar is developed from a view point of spatial and temporal consistencies of observed wind speed. Threshold values for quality check are determined by statistical analysis on the standard deviation of 3-component of wind speed obtained by a wind lidar, and the vertical gradient of horizontal wind speed obtained by a radiosonde system. The algorithm includes carrier-to-noise ratio (CNR) check, data availability check, and vertical gradient of horizontal wind speed check. That is, data sets whose CNR is less than -29 dB, data availability is less than 90%, or vertical gradient of horizontal wind speed is less than $-0.028s^{-1}$ or larger than $0.032s^{-1}$ are classified as 'doubtful', and flagged. The developed quality check algorithm is applied to data obtained at Bucheon station for the period from 1 to 30 September 2015. It is found that the number of 'doubtful' data shows maxima around 2000 m high, but the ratio of 'doubtful' to height-total data increases with increasing height due to atmospheric boundary height, cloud, or rainfall, etc. It is also found that the quality check by data availability is more effective than those by carrier to noise ratio or vertical gradient of horizontal wind speed to remove an erroneous noise data.

• Journal of Navigation and Port Research
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• v.35 no.3
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• pp.265-270
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• 2011

The purpose of this study is to compare and analyze the differences of a building's heating and cooling loads depending on the weather variation. Followings are the results. The temperature, humidity and wind speeds of standard year are bigger than those of 2006~2009. The 2006~2009's total horizontal solar irradiance is greater than that of standard year, and the direct solar irradiance of standard year is bigger in winter and vice versa in summer. As results of simulation on heating and cooling loads, it is difficult to find out the bilateral influences between maximum thermal loads and annual's. The equivalent-time operating ratio(EOR) is defined on this study to estimate the differences between year and year, and the EOR of standard year shows low value comparing to 2006~2009 years'.

• New & Renewable Energy
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• v.20 no.1
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• pp.95-101
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• 2024

Since 1990, the Renewable Big Data Research Lab at the Korea Institute of Energy Technology has been observing solar radiation at 16 sites across South Korea. Serving as the National Reference Standard Data Center for Renewable Energy since 2012, it produces essential data for the sector. By 2020, it standardized meteorological year data from 22 sites. Despite user demand for data from approximately 260 sites, equivalent to South Korea's municipalities, this need exceeds the capability of measurement-based data. In response, our team developed a method to derive solar radiation data from satellite images, covering South Korea in 400,000 grids of 500 m × 500 m each. Utilizing satellite-derived data and ERA5-Land reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), we produced standard meteorological year data for 1,000 sites. Our research also focused on data measurement traceability and uncertainty estimation, ensuring the reliability of our model data and the traceability of existing measurement-based data.

• Water Engineering Research
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• v.3 no.2
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• pp.113-122
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict flash floods. In this study, a Quantitative Flood Forecasting (QFF) model was developed by incorporating the evolving structure and frequency of intense weather systems and by using neural network approach. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as lifetime, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. All these processes stretched leadtime up to 18 hours. The QFF model will be applied to the mid-Atlantic region of United States in a forthcoming paper.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.9-20
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• 1999

The use of climatic information is essential in the industial society. More specialized weather servies are required to perform better industrial acivities including agriculture. Especially, crop models require daily weather data of crop growing area or cropping zones, where routine weather observations are rare. Estimates of the spatial distribution of daily climates might complement the low density of standard weather observation stations. This study was conducted to estimate the spatial distribution of daily minimum and maximum temperatures in Korean Peninsula. A topoclimatological technique was first applied to produce reasonable estimates of monthly climatic normals based on 1km $\times$ 1km grid cell over study area. Harmonic analysis method was then adopted to convert the monthly climatic normals into daily climatic normals. The daily temperatures for each grid cell were derived from a spatial interpolation procedure based on inverse-distance weighting of the observed deviation from the climatic normals at the nearest 4 standard weather stations. Data collected from more than 300 automatic weather systems were then used to validate the final estimates on several dates in 1997. Final step to confirm accuracy of the estimated temperature fields was comparing the distribution pattern with the brightness temperature fields derived from NOAA/AVHRR. Results show that differences between the estimated and the observed temperatures at 20 randomly selected automatic weather systems(AWS) range from -3.$0^{\circ}C$ to + 2.5$^{\circ}C$ in daily maximum, and from -1.8$^{\circ}C$ to + 2.2$^{\circ}C$ in daily minimum temperature. The estimation errors, RMSE, calculated from the data collected at about 300 AWS range from $1.5^{\circ}C$ to 2.5$^{\circ}C$ for daily maximum/minimum temperatures.

• Journal of Environmental Impact Assessment
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• v.18 no.6
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• pp.321-330
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• 2009

Spatiotemporal changes in the thermal environment in a large city, Seoul, Korea were analyzed using a thermal index, perceived temperature (PT), to standardize the weather conditions. PT is a standard index for the thermal balance of human beings in thermophysiological environment. For the analysis of PT, the data from long-term monitoring and intensive observations in and around the inner-city stream called 'Cheonggye' in Seoul, were compared with a reference data from the Seoul weather station. Long-term data were monitored by installing two automatic weather stations at 66m (S1) and 173m (S2) away from the center of the stream. Through the analysis of the data during the summer of 2006 and intensive observation periods, it was revealed that the stream's effects on the PT extended up to the distance of the S1 site. In winter, the increase of the PT between pre- and post-restoration was stronger at S1, which was nearer than S2 from the stream. These results suggest that PT can be used as an effective model in analyzing the changes of the thermal environment in relation with the changes of water surface areas.

• Advances in environmental research
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• v.3 no.3
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• pp.253-281
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• 2014

The quest for enhanced thermal comfort for dwellings encompasses the holistic utilization of improved building fabric, impact of weather variation and amongst passive cooling design consideration the provision of appropriate ventilation and shading strategy. Whilst thermal comfort is prime to dwellings considerations, limited research has been done in this area with the attention focused mostly on non-dwellings. This paper examines the current and future thermal comfort implications of four different standard construction specifications which show a progressive increase in thermal mass and airtightness and is underpinned by the newly developed CIBSE adaptive thermal comfort method for assessing the risk of overheating in naturally ventilated dwellings. Interactive investigation on the impact of building fabric variation, natural ventilation scenarios, external shading and varying occupants' characteristics to analyse dwellings thermal comfort based on non-heating season of current and future weather patterns of London and Birmingham is conducted. The overheating analysis focus on the whole building and individual zones. The findings from the thermal analysis simulation are illustrated graphically coupled with statistical analysis of data collected from the simulation. The results indicate that, judicious integrated approach of improved design options could substantially reduce the operating temperatures in dwellings and enhance thermal comfort.