• Atmosphere
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• v.24 no.4
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• pp.541-554
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• 2014

Historical, RCP4.5 and RCP8.5 scenarios from HadGEM2-AO are dynamically downscaled over the northeast East Asia with WRFV3.4. The horizontal resolution of the produced data is 12.5 km and the periods of integration are 1979~2010 for historical and 2019~2100 for both RCP4.5 and RCP8.5. We analyze the time series, climatology, EOF and extreme climate in terms of 2 m-temperature and precipitation during 30-year for the Historical (1981~2010) and RCP4.5 and RCP8.5 (2071~2100) scenarios. According to the result, the temperature of the northeast Asia centered at the Korean Peninsula increase 2.9 and $4.6^{\circ}C$ in the RCP4.5 and RCP8.5 scenarios, respectively, by the end of the 21st century. The temperature increases with latitude and the increase is larger in winter rather than in summer. The annual mean precipitation is expected to increase by about $0.3mm\;day^{-1}$ in RCP4.5 scenario and $0.5mm\;day^{-1}$ in RCP8.5 scenario. The EOF analysis is also performed for both temperature and precipitation. For temperature, the EOF $1^{st}$ modes of all scenarios in summer and winter show that temperature increase with latitude. The $2^{nd}$ mode of EOF of each scenario shows the natural variability, exclusive of the global warming. The summer precipitation over the Korean Peninsula projected increases in EOF $1^{st}$ modes of all scenarios. For extreme climate, the increment of the number of days with daily maximum temperature above $30^{\circ}C$ per year ($DAY_{TX30}$) is 25.3 and 49.7 days in RCP4.5 and RCP8.5 respectively over the Korean Peninsula. The number of days with daily precipitation above $20mm\;day^{-1}$ per year ($DAY_{PR20}$) also increases 3.1 and 3.5 days in RCP4.5 and RCP8.5 respectively.

• Environmental and Resource Economics Review
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• v.24 no.3
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• pp.463-488
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• 2015

A more detailed design of offset system is needed according to the emission trading system started in 2015. This study aims to estimate the supply of potential offset that can be secured by expanding high-efficiency household electric appliances. The target commodities for analysis are three different householding electric appliances: TV, washing machine, electric fan, refrigerator and air conditioner. By using the ARDL model, we estimated the coefficients of diffusion of these high-efficiency appliances from 2016 to 2022. Then, the potential supply of offset was drawn by calculating the amount of electricity saving by efficiency improvement and by applying the rates of carbon exchange. Supposing that the electricity savings rates of high-efficiency appliances are each 10% and 20%, the accumulated carbon decrement in 2022 was respectively $361,899CO_2t$ and $723,797CO_2t$. The appliance that showed the biggest carbon decrement was air conditioner, and the second biggest was refrigerator and the next was TV, followed by washing machine, electric fan.

• Journal of the Korean Society for Marine Environment & Energy
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• v.9 no.1
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• pp.55-62
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• 2006

Correlations between air-temperature variation and SST variation around Jeju Island have been studied with data JRMO($1924{\sim}2004$) and NFRDI($l971{\sim}2000$). Air-temperature has increased about $0.02^{circ}C/year$ for the period of $1924{\sim}2004$ but relatively high 0.035/year for the last 30 years. SST has increased about $0.024^{circ}C/year$ for the period of $1971{\sim}2000$ and relatively high $0.047^{circ}C/year$ in December. According to the analysis of time series of the two kind of variation, the SST and air-temperature are positively correlated. They are generally in phase, and SST anomaly is similar to air-temperature anomaly as well. Consequently, SST variation has high correlation with air-temperature variation around Jeju Island.

• Journal of Korea Port Economic Association
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• v.32 no.3
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• pp.67-81
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• 2016

This paper examines the influence of Brexit on container volume of Korea, especially of macroeconomic variables such as exchange rate and industrial production of EU and United Kingdom. To do this, we use monthly time series data during 2000-2016, and introduce the analysis method of cointegration test and VECM, and analyze the influence of industrial production and exchange rate of EU and U.K. on container volume of Korea. The results are as follows. First, the container volume of Korea is influenced by the exchange rate and industrial production of EU in the long run. But the exchange and industrial production of U.K. influenced on only export container volume of Korea, and the influence of U.K. macroeconomic variables on container volume of Korea was not large in the long lun. Second, In the shot run, the influence of exchange rate on container volume of Korea, especially on export container volume was significant in EU and U.K. To sum up, the influence of EU macroeconomic variables on container volume of Korea is larger than that of U.K., and the influence of exchange rate variable is more significant than that of industrial production variable.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.458-468
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• 2019

This research attempted to estimate monthly sales of food and beverage at the passenger terminal of Incheon int'l airport from June of 2015 to December 2020. This paper used ARIMA-Intervention model which can estimate the change of the sales amount suggesting the predicted monthly food and beverage sales revenue. The intervention variable was travel-ban policy against south Korea from P.R. China since July 2016 to December 2017 due to THAAD in south Korea. According to ARIMA, it was found normal predicted sales amount showed the slow growth increase rate until 2020 due to the effect of intervened variable. However, the monthly food sales in July and August 2019 was 20.3 and 21.2 billion KRW respectively. Each amount would increase even more in 2020 and the amount would increase to 21.4 and 22.1 billion KRW. The sales amount in 2019 would be 7.7 and 8.1 billion KRW and climb up 7.9 and 8.2 billion KRW in 2020. It was expected LCC passengers tend to spend more money for F&B at airport due to no meal or drink service of LCC or the paid-in meal and beverage service of LCC. The growth of sales of food and beverate will be accompanied with the growth of LCC according to estimated data.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1519-1529
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• 2018

The volcanic ash can spread out over hundreds of kilometers in case of large volcanic eruption. The deposition of volcanic ash may induce damages in urban area and transportation facilities. In order to respond volcanic hazard, it is necessary to estimate efficiently the diffusion area of volcanic ash. The purpose of this study is to compare in-situ volcanic deposition and satellite images of the volcanic eruption case. In this study, we used Near-Infrared (NIR) channels 7 and 8 of Geostationary Ocean Color Imager (GOCI) images for Mt. Aso eruption in 16:40 (UTC) on October 7, 2016. To estimate deposit area clearly, we applied Principal Component Analysis (PCA) and a series of morphology filtering (Eroded, Opening, Dilation, and Closing), respectively. In addition, we compared the field data from the Japan Meteorological Agency (JMA) report about Aso volcano eruption in 2016. From the results, we could extract volcanic ash deposition area of about $380km^2$. In the traditional method, ash deposition area was estimated by human activity such as direct measurement and hearsay evidence, which are inefficient and time consuming effort. Our results inferred that satellite imagery is one of the powerful tools for surface change mapping in case of large volcanic eruption.

• Science of Emotion and Sensibility
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• v.22 no.1
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• pp.35-44
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• 2019

Individuals with problematic hypersexual behavior (PHB) evince the inability to control sexual impulses and arousal. Previous studies have identified that these characteristics are related to structural and functional changes in the brain region responsible for inhibitory functions. However, very little research has been conducted on the functional connectivity of these brain areas during the resting state in individuals with PHB. Therefore, this study used functional magnetic resonance imaging devices with the intention of identifying the deficit of the functional connectivity in the executive control network in individuals with PHB during the resting state. Magnetic resonance imaging data were obtained for 16 individuals with PHB and 19 normal controls with similar demographic characteristics. The areas related to the executive control network (LECN, RECN) were selected as the region of interest, and the correlation coefficient with time series signals between these areas was measured to identify the functional connectivity. Between groups analysis was also used. The results revealed a significant difference in the strength of the functional connectivity of the executive control network between the two groups. In other words, decreased functional connectivity was found between the superior/middle frontal gyrus and the caudate, and between the superior/middle frontal gyrus and the superior parietal gyrus/angular gyrus in individuals with PHB. In addition, these functional Connectivities related to the severity of hypersexual behavior. The findings of this study suggest that the inability to control sexual impulses and arousal in individuals with PHB might be related to the reduced functional connectivity of executive control circuits.

• Journal of Korean Society of Forest Science
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• v.108 no.1
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• pp.10-20
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• 2019

The purpose of this study is to identify the long-term area changes in the subalpine coniferous forests in Korea in order to understand the changes in the subalpine forest ecosystems vulnerable to climate change. We analyzed 20 years of time-series Landsat satellite images (mid 1990s, mid 2010s) for change detection of coniferous forests and compared with the long term changes of climate information to identify their relationship in the study area. As a result, the area of coniferous forests in the study region decreased by 25% over 20 years. The regions with largest changes are Seoraksan, Baegunsan-Hambaeksan-Jangsan, Jirisan, and Hallasan. The region with the largest decrease in area was Baegunsan (reduced area: 542 ha), and the region with large decrease in area and the largest rate of decrease was Hallasan (rate of decrease: 33.3%). As the Jeju region has the most rapid temperature rise, it is projected that Hallasan is the most vulnerable forest ecosystem affected by climate change. The result of this study shows that from a long-term perspective the overall coniferous forests in the subalpine region are declining, but the trend varies in each region. This national and long-term information on the change of coniferous forests in the subalpine region can be utilized as baseline data for the detailed survey of endangered subalpine coniferous trees in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.83-94
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• 2022

In order to actively prepare to frost damage that occurs in the process of growing crops, the spatial and temporal distribution of frost occurrence in South Korea was derived using frost observation data from 20 regions over the past 21 years (2000~2020). The main products are the number of frost days, first frost day, and last frost day by region. And the climatic trends of these results were identified by performing the Mann-Kendall trend test and Sen's slope estimator. In South Korea, a lot of frost occurs in the inland area to the west of the Taebaek and Sobaek Mountains. Relatively closer to the coastal area, the number of frost days is small, the first frost day is slow, and the last frost day is early. The east coast region has fewer frost days, the first frost day is later, and the last frost day is earlier than the west coast region. The southern sea, the southeastern sea region, and the island region rarely experience frost. As a result of the annual time series trend analysis, although South Korea is a country where climate warming is progressing, there was no trend in reducing the number of frost days and slowing the first frost day, and it was found that the last frost day is delayed by 0.5 days per year.