• Journal of the Korean earth science society
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• v.41 no.6
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• pp.557-574
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• 2020

The purpose of this study is to analyze the cause of high PM2.5 mass concentrations in Cheongju for the period of non-Asian dust days using the weather chart, the stream lines at 850 hPa, the backward trajectory, and the weather and air quality model. As a result of analyzing the time series of PM2.5 concentrations and weather charts for the episodic days in Cheongju, the weather patterns were shown in related to long-range transport of PM2.5 from China or surrounding areas. In fact, in the PM2.5 time series, 60-80 ㎍ m-3, which is more than 2-3 times higher than the concentration attributed to Cheongju activities, was observed as a background concentration related to long-range transport. The distribution of high PM2.5 concentration was typically dependent on the locations of the high and low pressures above the ground while the upper jet stream passed through the Korean Peninsula. Consequently, the high PM2.5 concentration in Cheongju is due to massive air pollutants in the form of smog originated from industrial, household and energy combustion sources of Beijing and other nearby regions of China. These air pollutants move along a fast zonal wind caused by the atmospheric pressure arrangement. high concentration of PM2.5 in Cheongju City is because the mass of air pollutants in the form of smog generated from industrial, household and energy combustion origins in Beijing or other nearby regions of China move along a fast wind speed zone according to the atmospheric pressure arrangement of long-distance transportation. Air pollutants including PM2.5 show an M-shaped pattern that passes through the topography of the Cheongju basin from north to south as a belt or band-shaped pollutant. The ground high pressure according to the above-ground high pressure expansion area and cut-off low or low pressure arrangement, or the bands in the form of river stems appear in a gradual incremental pattern that changes into a U-shape under the influence of the wind.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.478-484
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• 2018

This study predicts solar radiation, solar radiation, and solar power generation using hourly weather data such as temperature, precipitation, wind direction, wind speed, humidity, cloudiness, sunshine and solar radiation. I/O pattern in supervised learning is the most important factor in prediction, but it must be determined by repeated experiments because humans have to decide. This study proposed four input and output patterns for solar and sunrise prediction. In addition, we predicted solar power generation using the predicted solar and solar radiation data and power generation data of Youngam solar power plant in Jeollanamdo. As a experiment result, the model 4 showed the best prediction results in the sunshine and solar radiation prediction, and the RMSE of sunshine was 1.5 times and the sunshine RMSE was 3 times less than that of model 1. As a experiment result of solar power generation prediction, the best prediction result was obtained for model 4 as well as sunshine and solar radiation, and the RMSE was reduced by 2.7 times less than that of model 1.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.16-29
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• 2013

The purpose of this study is to evaluate air ventilation using wind patterns of MetPhoMod program at nighttime focused on Changwon-si, Gyeongsangnam-do. Evaluation indices of air ventilation are wind resistant and retention used by results of each wind speed and diversity. The results are as follows. Vulnerable areas of air ventilation are Bonglim-dong, Bansong-dong, Yongji-dong and so on. In high-rise apartment, commercial area and single residential area of Yongji-dong, Sangnam-dong and Sapa-dong, wind is stagnated by high buildings. Therefore, these areas should construct urban spaces to circulate the wind. And to inflow persistingly the fresh wind generated in a rural area, we think that the construction of wind corridor is suggested by development plan and policy wind corridor.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.65-73
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• 2001

Until recently, we use only weekly and monthly adjustment factors in order to estimate the AADT. By the way. we can suppose that the traffic is time series data related to flow of time. So we tried to analyse traffic patterns using time series analysis and apply them to estimate the AADT. We could divide traffic patterns into trend, cyclic variation, seasonal variation and irregular variation like as time series data. Also, in order to reduce random error components, we have looked for the weather conditions as an influential factor. There are many weather conditions such as rainfalls, but, temperatures, and sunshine hours among others but we selected rainfalls and lowest temperatures. And then, we have estimated the AADT using time series factors. To compare the results of, we have applied both irregular variation joined to weather factors and that not joined to. RMSE and U-test were opted at methods to appreciate results of AADT estimation.

• Journal of the Korean earth science society
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• v.41 no.5
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• pp.447-458
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• 2020

This study presents the K-means clustering analysis-based classification of the meteorological patterns affecting the occurrence of high PM₁₀ concentration in the southeastern region of the Korean peninsula for the last five years (2014-2018). Regional differences in Busan, Ulsan, and Gyeongnam related to high PM₁₀ episodes, were clarified through the statistical comparison study using synoptic scale meteorological elements using NCEP (National Centers for Environmental Prediction/FNL (Final Operational Global Analysis) re-analysis meteorological data. Meteorological patterns were classified into a total of five categories (C1-C5). The incidence of each cluster was 24.8% (C1), 21.3% (C2), 20.4% (C3), 17.3% (C4), and 16.2% (C5), respectively. The high PM₁₀ concentration in the southeastern region resulted from long and short range transports (C1, C3, C5) from outside of the region, and the emissions (C2, C4) inside the region. In the high PM₁₀ episodes in Busan, Ulsan, and Gyeongnam regions, meteorological characteristics such as different geopotential height and wind speed at 500 hPa in each cluster and the change in the location of high pressure over Korean Peninsula is strongly associated with the dispersion of PM₁₀ around inventories in the region and the tendency of long-range transportation of PM₁₀ emitted from outside of region.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.269-296
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• 2006

With the concern of the potential problems which can be observed in terms of the power supply of renewable energies, we need to analyze the impact of additional power generation capacities of renewable energy sources on peak load. Each renewable energy sources are dependent upon wind speed, solar radiation, head differences caused by lunar calendar. Considering that these exogenous renewable energy sources follow their own stochastic distributions, we analyze the probability distribution of the impact of each renewable energy power supply on peak load. As a conclusion, we note that traditional tools used for the analysis of power supply such as capacity factors are no longer appropriate for the analysis of renewable energy sources in that perspective.

• Journal of the Society of Naval Architects of Korea
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• v.36 no.3
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• pp.15-21
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• 1999

The flow characteristics around KRISO 300K VLCC double-body model have been experimentally investigated in a closed-type subsonic wind tunnel. The local mean velocity and turbulence statistics including turbulent intensity. Reynolds shear stress and turbulent kinetic energy were measured using a x-type hot-wire probe. The measurements were carried out at several transverse stations of the stern and near wake regions. The surface flow was visualized using on oil-film technique to see the flow pattern qualitatively. The flow in the stern and near wake region revealed complicated three-dimensional flow characteristics. The VLCC model shows a hook-shaped wake structure behind the propeller boss in the main longitudinal vortex region. The thin boundary layer at midship was increased gradually in thickness over the stern and evolved into a full three-dimensional turbulent wake.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.366-366
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• 2022

유역의 하천유량과 같은 수문 시계열을 모의 또는 예측하기 위한 수문 모델링에서 최근 기계 학습 방법을 활용한 연구가 활발하게 적용되고 있는 추세이다. 이러한 데이터 기반 모델링 접근법은 입출력 자료에서 관찰된 패턴을 학습하며, 특히, 장단기기억(Long Short-Term Memory, LSTM) 네트워크는 많은 연구에서 수문 시계열 예측에 대한 적용성이 검증되었으나, 장기간의 고품질 관측자료를 활용할 때 더 나은 예측성능을 보인다. 그러나 우리나라의 경우 장기간 관측된 고품질의 하천유량 자료를 확보하기 어려운 실정이다. 따라서 본 연구에서는 LSTM 네트워크의 학습 시 가용한 모든 유역의 자료를 통합하여 학습시켰을 때 하천유량 예측성능을 개선할 수 있는지 판단해보고자 하였다. 이를 위해, 우리나라 13개 댐 유역을 대상으로 대상 유역의 자료만을 학습한 모델의 예측성능과 모든 유역의 자료를 학습한 모델의 예측성능을 비교해 보았다. 학습은 2001년부터 2010년까지 기상자료(강우, 최저·최고·평균기온, 상대습도, 이슬점, 풍속, 잠재증발산)를 이용하였으며, 2011년부터 2020년에 대해 테스트 되었다. 다지점 통합학습을 통해 테스트 기간에 대해 예측된 각 유역의 일 하천유량의 KGE 중앙값이 0.74로 단일지점 학습을 통해 예측된 KGE(0.72)보다 다소 개선된 결과를 보여주었다. 다지점 통합학습이 하천유량 예측에 큰 개선을 달성하지는 못하였으며, 추가적인 가용 자료 확보와 LSTM 구성의 개선을 통해 추가적인 연구가 필요할 것으로 판단된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.3
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• pp.148-156
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• 2011

The purpose of this study is to analyze the patterns of forest fire possibly related with Asian dust event and carry out a correlation analysis between forest fire occurrence and existence or not of the Asian dust event during dry seasons i.e. February to May in 2000 to 2008. To study the correlation of forest fire and Asian dust, we surveyed information of Asian dust observations, forest fire statistics, fire danger rating index, weather data such as temperature, relative humidity and wind speed of the day occurring the forest fire. As a consequence of analysis, the regional frequency of Asian dust was the highest in Gyeonggi and Chungbuk divisions. Frequencies of forest fire occurrence by the Asian dust events were the highest in the day before three days of the Asian dust event. The highest frequent regions of forest fire occurrence were district of boundary line between Gyeonggi and Western of Gangwon, Chungbuk and Gyeonbuk inland. The correlation between forest fire and fire danger rating index showed the high correlation with the day before three days and after three days of the Asian dust event. These correlation coefficients were 0.50038 and 0.53978 to 1% significance level. The result of analysis between the frequency of forest fire occurrence and wind speed had a highly negative relationship at all the Asian dust days, the day before and after three days. The correlation coefficients had been -0.58623 to -0.61245 to 1% significance level. Relative humidity showed a little of negative relationship with forest fire occurrence in -0.2568(p ${\leq}$ 0.01) for the Asian dust day and -0.35309(p ${\leq}$ 0.01) for next three days. Moreover, at the day before three days of Asian dust events, it was -0.23701 to 1% significance level. However, the mean temperature did not correlate with frequency of forest fire occurrence by Asian dust events at all.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.199-207
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• 2016

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for practical forecasting of forest fire danger rate by reflecting the climate change for the time period of 2000yrs. Forest fire in South Korea is highly influenced by humidity, wind speed, temperature, and precipitation. To effectively forecast forest fire occurrence, we developed a forest fire danger rating model using weather factors associated with forest fire in 2000yrs. Forest fire occurrence patterns were investigated statistically to develop a forest fire danger rating index using times series weather data sets collected from 76 meteorological observation centers. The data sets were used for 11 years from 2000 to 2010. Development of the national forest fire occurrence probability model used a logistic regression analysis with forest fire occurrence data and meteorological variables. Nine probability models for individual nine provinces including Jeju Island have been developed. The results of the statistical analysis show that the logistic models (p<0.05) strongly depends on the effective and relative humidity, temperature, wind speed, and rainfall. The results of verification showed that the probability of randomly selected fires ranges from 0.687 to 0.981, which represent a relatively high accuracy of the developed model. These findings may be beneficial to the policy makers in South Korea for the prevention of forest fires.