• Nuclear Engineering and Technology
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• 제33권6호
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• pp.557-565
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• 2001

Variations in the number of early health effects resulting from the severe accidents of the YGN 3&4 nuclear power plants were examined for different combinations of release parameters and meteorological data . The release parameters and meteorological data were selected in combination to define a limited number of basic spectra characterized by release height, heat content, release time, warning time, wind speed, rainfall rate, and atmospheric stability class. Variant seasonal spectra were also defined in order to estimate the potential significance of seasonal variations as a factor determining the incidence or number of early health effects. The results show that there are large differences in consequences from spectrum to spectrum, although an equal amount and mix of radioactive material is released to the atmosphere in each case. Also, there are large differences in the estimated number of health effects from season to season due to distinct seasonal variations in meteorological combinations in Korea. Therefore, it is necessary to consider seasonal characteristics in developing optimum emergency response strategies.

• 대기
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• 제25권3호
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• pp.483-499
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• 2015

This study examined the impact of change of land-use and meteorological condition due to urbanization on heat environment in Seoul metropolitan area over a decade (2000 and 2009) using Weather Research and Forecasting (WRF)-Urban Canopy Model (UCM). The numerical simulations consist of three sets: meteorological conditions of (1) October 2000 with land-use data in 2000 (base simulation), (2) October 2009 with land-use data in 2000 (meteorological condition change effect) and (3) October 2009 with land-use data in 2009 (both the effects of land-use and meteorological condition change). According to the experiment results, the change of land-use and meteorological condition by urbanization over a decade showed different contribution to the change of heat environment in Seoul metropolitan area. There was about $1^{\circ}C$ increase in near-surface (2 m) temperature over all of the analyzed stations due to meteorological condition change. In stations where the land-use type changed into urban, large temperature increase at nighttime was observed by combined effects of meteorological condition and land-use changes (maximum $4.23^{\circ}C$). Urban heat island (UHI) over $3^{\circ}C$ (temperature difference between Seoul and Okcheon) increased 5.24% due to the meteorological condition change and 26.61% due to the land-use change. That is, land-use change turned out to be contributing to the strengthening of UHI more than the meteorological condition change. Moreover, the land-use change plays a major role in the increase of sensible heat flux and decrease of latent heat flux.

• 대기
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• 제17권4호
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• pp.435-453
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• 2007

KEOP (Korea Enhanced Observing Period)-2004 intensive summer observation was carried out from 20 June to 5 July 2004 over the Southwestern part of the Korean peninsula. In this study, the effects of KEOP-2004 intensive observation data on the simulation of precipitation system are investigated using KLAPS (Korea Local Analysis and Prediction System) and PSU/NCAR MM5. Three precipitation cases during the intensive observation are selected for detailed analysis. In addition to the control experiments using the traditional data for its initial and boundary conditions, two sensitivity experiments using KEOP data with and without Jindo radar are performed. Although it is hard to find a clear and consistent improvement in the verification score (threat score), it is found that the KEOP data play a role in improving the position and intensity of the simulated precipitation system. The experiments started at 00 and 12 UTC show more positive effect than those of 06 and 18 UTC. The effect of Jindo radar is dependent on the case. It plays a significant role in the heavy rain cases related to a mesoscale low over Changma front and the landing of a Typhoon. KEOP data produce more strong difference in the 06/18 UTC experiments than in 00/12 UTC, but give more positive effects in 00/12 UTC experiments. One of the possible explanations for this is that : KEOP data could properly correct the atmosphere around them when there are certain amounts of data, while gives excessive effect to the atmospheric field when there are few data. CRA analysis supports this reasoning. According to the CRA (Contiguous Rain Area) analysis, KEOP data in 00/12 UTC experiments improve only the surrounding area, resulting in essentially same precipitation system so the effects remain only in each convective cell rather than the system itself. On the other hand, KEOP data modify the precipitation system itself in 06/18 UTC experiments. Therefore the effects become amplified with time integration.

• 대한원격탐사학회지
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• 제34권1호
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• pp.25-43
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• 2018

The effects of hydro-meteorological and surface variables on the frequency of Asian dust events (FAE) were investigated using ground station and satellite-based data. Present weather codes 7, 8, and 9 derived from surface synoptic observations (SYNOP)were used for counting FAE. Surface wind speed (SWS), air temperature (Ta), relative humidity (RH), and precipitation were analyzed as hydro-meteorological variables for FAE. The Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), and snow cover fraction (SCF) were used to consider the effects of surface variables on FAE. The relationships between FAE and hydro-meteorological variables were analyzed using Z-score and empirical orthogonal function (EOF) analysis. Although all variables expressed the change of FAE, the degrees of expression were different. SWS, LST, and Ta (indices applicable when Z-score was < 0) explained about 63.01, 58.00, and 56.17% of the FAE,respectively. For NDVI, precipitation, and RH, Asian dust events occurred with a frequency of about 55.38, 67.37, and 62.87% when the Z-scores were > 0. EOF analysis for the FAE showed the seasonal cycle, change pattern, and surface influences related to dryness condition for the FAE. The intensity of SWS was the main cause for change of FAE, but surface variables such as LST, SCF, and NDVI also were expressed because wet surface conditions suppress FAE. These results demonstrate that not only SWS and precipitation, but also surface variables, are important and useful precursors for monitoring Asian dust events.

• 복식문화연구
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• 제25권2호
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• pp.117-129
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• 2017

The purpose of this study was to investigate meteorological factors' effects on clothing sales based on empirical data from a leading apparel company. The daily sales data were aggregated from "A" company's store records for the Fall/Winter season from 2012 to 2015. Daily weather data corresponding to sales volume data were collected from the Korea Meteorological Administration. The weekend effect and meteorological factors including temperature, wind, humidity, rainfall, fine dust, sea level pressure, and sunshine hours were selected as independent variables to calculate their effects on A company's apparel sales volume. The analysis used a SAS program including correlation analysis, t-test, and multiple-regression analysis. The study results were: First, the weekend effect was the most influential factor affecting sales volume, followed by fine dust and temperature. Second, there were significant differences in the independent variables'effects on sales volume according to the garments' classification. Third, temperature significantly affected outer garments'sales volume, while top garments' sales volume was not influenced significantly. Fourth, humidity, sea level pressure and sunshine affected sales volume partly according to the garments' item. This study can provide proof of significant relationships between meteorological factors and the sales volume of garments, which will serve well to establish better inventory strategies.

• 대기
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• 제29권4호
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• pp.343-353
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• 2019

The seasonal climatology of atmospheric rivers (ARs) and their effects on the seasonal precipitation and temperature in Korea are examined using the AR chronology obtained by a methodology based on the vertically integrated water vapor transport (IVT) in conjunction with a fine-scale gridded analysis of station precipitation and temperature. ARs are found to affect Korea most heavily in the warm season with minimal impacts in winter. This contrasts the AR effects in the western North America and the Western Europe that are affected most in winters. Significant portions of precipitation in Korea are associated with AR landfalls for all seasons; over 35% (25%) of the summer (winter) rainfall in the southern part of the Korean peninsula. The percentage of AR precipitation over Korea decreases rapidly towards the north. AR landfalls are also associated with heavier-than-normal precipitation events for all seasons. AR landfalls are associated with above-normal temperatures in Korea; the warm anomalies increase towards the north. The warm anomalies during AR landfalls are primarily related to the reduction in cold episodes as the AR landfalls in Korea are accompanied by anomalous southerlies/southwesterlies.

• Smart Structures and Systems
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• 제32권2호
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• pp.83-99
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• 2023

The temperature prediction approaches of three important locations in an operational longitudinal slab track-bridge structure by using three typical neural network methods based on the field measuring platform of four meteorological factors and internal temperature. The measurement experiment of four meteorological factors (e.g., ambient temperature, solar radiation, wind speed, and humidity) temperature in the three locations of the longitudinal slab and base plate of three important locations (e.g., mid-span, beam end, and Wide-Narrow Joint) were conducted, and then their characteristics were analyzed, respectively. Furthermore, temperature prediction effects of three locations under five various meteorological conditions are tested by using three neural network methods, respectively, including the Artificial Neural Network (ANN), the Long Short-Term Memory (LSTM), and the Convolutional Neural Network (CNN). More importantly, the predicted effects of solar radiation in four meteorological factors could be identified with three indicators (e.g., Root Means Square Error, Mean Absolute Error, Correlation Coefficient of R2). In addition, the LSTM method shows the best performance, while the CNN method has the best prediction effect by only considering a single meteorological factor.

• 복식
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• 제52권2호
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• pp.139-150
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• 2002

The purpose of this study was to explore the effects of meteorological factors on sales of apparel products. Basic fiat came out daily meteorological data and sales data of apparel products in department store from 1998 to 2000. Four factors(the average temperature, rainfall, wind velocity, sunshine duration) from the nine meteorological factors were selected and were collected with Korea Meteorological Administration. Sales data were collected with business strategy department of H (department store in Seoul. The sales data were divided into six classifications, which are woman's wear, men's wear, children's wear, golf wear, sports wear, and inner wear. The results of this study were as follows: 1) Sales of apparel products were significantly correlated with the average temperature, rainfall, wind velocity, sunshine duration. Among the meteorological factors, temperature turned out to be the most influential in apparel sales and then the amount of rainfall, sunshine duration affected sales according to apparel classifications differently. 2) There were some differences among the apparel classifications in the effect of meteorological factors on the sales of apparel. In the spring. the higher the temperature was, the higher the sales of women's wear and golf wear were, but the lower the sales of children's wear, sports wear and inner wear were. In the summer, The higher the amount of rainfall was, the lower the sales of all the apparel classification were. The higher the temperature was, the higher the sales of sports wear were. In the fall, the lower the temperature was, the higher the sales of all the apparel classification except snorts wear were. In the winter, the meteorological factors had little effect on the sales of women's wear, men's wear and children's wear. The higher the temperature was, the higher the sales of golf wear were. The lower the temperature was, the higher the sales of sports wear were.

• Current Optics and Photonics
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• 제4권3호
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• pp.174-185
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• 2020

Multiscattering occurs when a laser transmits into dense atmosphere targets (e.g. fogs, smoke or clouds), which can cause depolarization effects even though the scattering particles are spherical. In addition, multiscattering effects have additional information about microphysical properties of scatterers. Thus, multiscattering can be utilized to study the microphysical properties of the liquid water cloud. In this paper, a Monte Carlo method was used to simulate multi-scattering transmission properties of Lidar signals in the cloud. The results showed the slope of the degree of linear polarization (SLDLP) can be used to invert the extinction coefficient, and then the cloud effective size (CES) and the liquid water content (LWC) may be easily obtained by using the extinction coefficient and saturation of the degree of linear polarization (SADLP). Based on calculation results, a microphysical properties inversion method for a liquid cloud was presented. An innovative multiscattering polarization Lidar (MSPL) system was constructed to measure the LWC and CES of the liquid cloud, and a new method based on the polarization splitting ratio of the Polarization Beam Splitter (PBS) was developed to calibrate the polarization channels of MSPL. By analyzing the typical observation data of MSPL observation in the northern suburbs of Nanjing, China, the LWC and CES of the liquid water cloud were obtained. Comparisons between the results from the MSPL, MODIS and the Microwave radar data showed that, the microphysical properties of liquid cloud could be retrieved by combining our MSPL and the inversion method.

• 한국환경과학회지
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• 제22권9호
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• pp.1171-1180
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• 2013

Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements and using the Lagrange multipliers method, the fixed-effects model for the production of five types of food crop and the seven meteorological elements were analyzed. Results showed that the key factors effecting increases in production of rice grains were average temperature, average relative humidity and average ground surface temperature, while wheat and barley were found to have positive correlations with average temperature and average humidity. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the production of food crops. Second, when compared to existing studies, the study was not limited to one food crop but encompassed all five types, and went beyond other studies that were limited to temperature and rainfall to include various meterological elements.