• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.279-284
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• 2004

Red tide(harmful algae) in the Korean Coastal Waters has a given a great damage to the fishery every year. However, the aim of our study understands the influence of meteorological factors (air and water tempaerature, precipitation, sunshine, solar radiation, winds) relating to the mechanism of red tide occurrence and monitors red tide by satellite remote sensing, and analyzes the potential area for red tide occurrence by GIS. The meteorological factors have directly influenced on red tide formation. Thus, We want to predict and apply to red tide formation from statistical analyses on the relationships between red tide formation and meteorological factors. In future, it should be realized the near real time monitoring for red tide by the development of remote sensing technique and the construction of integrated model by the red tide information management system (the data base of red tide - meteorological informations).

• Atmosphere
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• v.27 no.2
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• pp.163-175
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• 2017

The global terrestrial ecosystems have shown a large spatial variability in recent decades and represented a carbon sink pattern at mid-to-high latitude in Northern Hemisphere. However, there are many uncertainties in magnitude and spatial distribution of terrestrial carbon fluxes due to the effect of climate factors. So, it needs to accurately understand the spatio-temporal variations on carbon exchange flux with climate. This study focused on the effects of climate factors, .i.e. temperature, precipitation, and solar radiation, to terrestrial biosphere carbon flux. We used the terrestrial carbon flux that is simulated by a CarbonTracker, which performs data assimilation of global atmospheric $CO_2$ mole fraction measurements. We demonstrated significant interactions between Net Ecosystem Production (NEP) and climate factors by using the partial correlation analysis. NEP showed positive correlation with temperature at mid-to-high latitude in Northern Hemisphere but showed negative correlation pattern at $0-30^{\circ}N$. Also, NEP represented mostly negative correlation with precipitation at $60^{\circ}S-30^{\circ}N$. Solar radiation affected NEP positively at all latitudes and percentage of positive correlation at tropical regions was relatively lower than other latitudes. Spring and summer warming had potentially positive effect on NEP in Northern Hemisphere. On the other hand as increasing the temperature in autumn, NEP was largely reduced in most northern terrestrial ecosystems. The NEP variability that depends on climate factors also differently represented with the type of vegetation. Especially in crop regions, land carbon sinks had positive correlation with temperature but showed negative correlation with precipitation.

• Atmosphere
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• v.31 no.1
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• pp.29-43
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• 2021

In this study, two-step statistical approach including Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) was employed, and main meteorological factors explaining the high-PM2.5 episodes were identified in two regions: Seoul and Busan. We first performed PCA to isolate the Principal Component (PC) that is linear combination of the meteorological variables observed at two levels: surface and 850 hPa level. The employed variables at surface are: temperature (T2m), wind speed, sea level pressure, south-north and west-east wind component and those at 850 hPa upper level variables are: south-north (v850) and west-east (u850) wind component and vertical stability. Secondly we carried out MLR analysis and verified the relationships between PM2.5 daily mean concentration and meteorological PCs. Our two-step statistical approach revealed that in Seoul, dominant factors for influencing the high PM2.5 days are mainly composed of upper wind characteristics in winter including positive u850 and negative v850, indicating that continental (or Siberian) anticyclone had a strong influence. In Busan, however, the dominant factors in explanaining in high PM2.5 concentrations were associated with high T2m and negative u850 in summer. This is suggesting that marine anticyclone had a considerable effect on Busan's high PM2.5 with high temperature which is relevant to the vigorous photochemical secondary generation. Our results of both differences and similarities between two regions derived from only statistical approaches imply the high-PM2.5 episodes in Korea show their own unique characteristics and seasonality which are mostly explainable by two layer (surface and upper) mesoscale meteorological variables.

• Proceedings of the KIEE Conference
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• 2004.07c
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• pp.1802-1804
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• 2004

In seashore, outdoor insulators are polluted due to salty wind and the pollution causes the flashover and failure of electric equipments. As well known, the pollution has a close relation with meteorological factors such as wind velocity, precipitation, wind direction, relative humidity, dew point, etc. In this paper we statistically analyzed the correlation between the pollution and the meteorological factors including snowfall and freezing. The multiple regression analysis was used for the statistical analysis; daily measured equivalent salt deposit density(dependent variable) and the meteorological data(independent variable) were used. From the results of this investigation, we verified the influence of snowfall and freezing on the ESDD, which has been overlooked in the preceding investigation.

• Journal of Environmental Science International
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• v.9 no.6
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• pp.469-474
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• 2000

The traffic accidents in large cities such as Pusan metropolitan city have been increased every year due to increasing of vehicles numbers as well as the gravitation of the population. In addition to the carelessness of drivers, many meteorological factors have a great influence on the traffic accidents. Especially, the number of traffic accidents is governed by precipitation, visibility, cloud amounts temperature, etc. In this study, we have analyzed various data of meteorological factors from 1992 to 1997 and determined the standardized values for contributing to each traffic accident. Using the relationship between meteorological factors(visibility, precipitation, relative humidity and cloud amounts) and the total automobile mishaps, and experimental prediction formula for their traffic accident rates was seasonally obtained at Pusan city in 1997. Therefore, these prediction formulas at each meteorological factor may by used to predict the seasonal traffic accident numbers and contributed to estimate the variation of its value according to the weather condition it Pusan city.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.233-239
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• 2018

Since solar power generation is intermittent depending on weather conditions, it is necessary to predict the accurate generation amount of solar power to improve the efficiency and economical efficiency of solar power generation. This study proposes a short - term deep learning prediction model of solar power generation using meteorological data from Mokpo meteorological agency and generation data of Yeongam solar power plant. The meteorological agency forecasts weather factors such as temperature, precipitation, wind direction, wind speed, humidity, and cloudiness for three days. However, sunshine and solar radiation, the most important meteorological factors for forecasting solar power generation, are not predicted. The proposed model predicts solar radiation and solar radiation using forecast meteorological factors. The power generation was also forecasted by adding the forecasted solar and solar factors to the meteorological factors. The forecasted power generation of the proposed model is that the average RMSE and MAE of DNN are 0.177 and 0.095, and RNN is 0.116 and 0.067. Also, LSTM is the best result of 0.100 and 0.054. It is expected that this study will lead to better prediction results by combining various input.

• Journal of Environmental Health Sciences
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• v.42 no.1
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• pp.41-52
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• 2016

Objectives: Scrub typhus is one of the most prevalent vector-borne diseases. It is caused by Orientia tsutsugamushi, which is transmitted when people are bitten by infected chigger mites. This study aims at quantifying the association between the incidence of scrub typhus and meteorological factors in Jeollabuk-do Province over the period 2001-2015. Methods: Reported cases of scrub typhus were collected from the website of the Disease Web Statistical System supported by the Korea Centers for Disease Control and Prevention (KCDC). Simultaneous meteorological data, including temperature, rainfall, relative humidity, and sunshine duration were collected from the website of the National Climate Data Service System by the Korea Meteorological Administration. Correlation and regression analyses were applied to identify the association between the incidence of scrub typhus and meteorological factors. Results: The general epidemiological characteristics of scrub typhus in Jeollabuk-do Province were similar to those nationwide for sex, age, and geographical distribution. However, the annual incidence rate (i.e., cases per 100,000) of scrub typhus in Jeollabuk-do Province was approximately four times higher than all Korea's 0.9. The number of total cases was the highest proportion at 13.3% in Jeonbuk compared to other regions in Korea. The results of correlation analysis showed that there were significant correlations between annual cases of scrub typhus and monthly data for meteorological factors such as temperature and relative humidity in late spring and summer, especially in the case of temperature in May and June. The results of regression analysis showed that determining factors in the regression equation explaining the incidence of scrub typhus reached 46.2% and 43.5% in May and June. Using the regression equation, each 1oC rise in the monthly mean temperature in May or June may lead to an increase of 38 patients with scrub typhus compared to the annual mean of incidence cases in Jeollabuk-do Province. Conclusion: The result of our novel attempts provided rational evidence that meteorological factors are associated with the occurrence of scrub typhus in Jeollabuk-do. It should therefore be necessary to observe the trends and predict patterns of scrub typhus transmission in relation to global-scale climate change. Also, action is urgently needed in all areas, especially critical regions, toward taking steps to come up with preventive measures against scrub typhus transmission.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.59-66
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• 2013

Among many factors, especially meteorological conditions can impact agricultural productivities. This study was conducted to analyze the relationships between crop yield and meteorological factors. We collected meteorological data (i.e., temperature and precipitation) from the Automated Weather System (AWS) of Korea Meteorological Administration (KMA) and the yield data of Chinese cabbage and Radish from local Nonghyup (NCAF:National Agricultural Cooperative Federation) and Farmers' Corporate Association. The agricultural data were classified into two groups. These groups are comprised of the farmers who produced a crop under 30 kg per $3.3m^2$ and over 30k g per $3.3m^2$ respectively. The daily meteorological data were calculated from the average value for ten days. Based on the regression analysis, we concluded that the yield of Chinese cabbage (Haenam) was related to average temperature, minimum temperature, precipitation, and number of days with precipitation, whereas that of Radish (Jeju) was related to average temperature, maximum temperature, and minimum temperature. The result suggests that these meteorological data can be used more effectively for the prediction of crop yield.

• The Research Journal of the Costume Culture
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• v.25 no.2
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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.

• Journal of Digital Convergence
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• v.14 no.6
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• pp.457-466
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• 2016

To achieve eco-friendly hospitals it is necessary to empirically verify the effect of meteorological factors on the power consumption of the hospital. Using daily meteorological big data from 2009 to 2013, we studied the weather conditions impact to power consumption and analyzed the patterns of power consumption of two hospitals. R analysis revealed that temperature among the meteorological factors had the greatest impact on the hospital power consumption, and was a significant factor regardless of hospital size. The pattern of hospital power consumption differed considerably depending on the hospital size. The larger hospital had a linear pattern of power consumption and the smaller hospital had a quadratic nonlinear pattern. A typical pattern of increasing power consumption during a hot summer and a cold winter was evident for both hospitals. The results of this study suggest that a hospital's functional specificity and meteorological factors should be considered to improve energy savings and eco-friendly building.