• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.267-275
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• 2023

This study predicted rice harvest date in South Korea using 11-year (2012-2022) hindcasts based on dynamically downscaled 2m air temperature at subseasonal (1-month lead) timescale. To obtain high (5 km) resolution meteorological information over South Korea, global prediction obtained from the NOAA Climate Forecast System (CFSv2) is dynamically downscaled using the Weather Research and Forecasting (WRF) double-nested modeling system. To estimate rice harvest date, the growing degree days (GDD) is used, which accumulated the daily temperature from the seeding date (1 Jan.) to the reference temperature (1400℃ + 55 days) for harvest. In terms of the maximum (minimum) temperatures, the hindcasts tends to have a cold bias of about 1. 2℃ (0. 1℃) for the rice growth period (May to October) compared to the observation. The harvest date derived from hindcasts (DOY 289) well simulates one from observation (DOY 280), despite a margin of 9 days. The study shows the possibility of obtaining the detailed predictive information for rice harvest date over South Korea based on the dynamical downscaling method.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.2
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• pp.49-57
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• 2016

Even if an external forcing that will drive a climate change is given uniformly over the globe, the corresponding climate change and the feedbacks by the climate system differ by region. Thus the detection of global warming signal has been made on a regional scale as well as on a global average against the internal variabilities and other noises involved in the climate change. The purpose of this study is to estimate a timing of unprecedented climate due to global warming and to analyze the regional differences in the estimated results. For this purpose, unlike previous studies that used climate simulation data, we used an observational dataset to estimate a magnitude of internal variability and a future temperature change. We calculated a linear trend in surface temperature using a historical temperature record from 1880 to 2014 and a magnitude of internal variability as the largest temperature displacement from the linear trend. A timing of unprecedented climate was defined as the first year when a predicted minimum temperature exceeds the maximum temperature record in a historical data and remains as such since then. Presumed that the linear trend and the maximum displacement will be maintained in the future, an unprecedented climate over the land would come within 200 years from now in the western area of Africa, the low latitudes including India and the southern part of Arabian Peninsula in Eurasia, the high latitudes including Greenland and the mid-western part of Canada in North America, the low latitudes including Amazon in South America, the areas surrounding the Ross Sea in Antarctica, and parts of East Asia including Korean Peninsula. On the other hand, an unprecedented climate would come later after 400 years in the high latitudes of Eurasia including the northern Europe, the middle and southern parts of North America including the U.S.A. and Mexico. For the ocean, an unprecedented climate would come within 200 years over the Indian Ocean, the middle latitudes of the North Atlantic and the South Atlantic, parts of the Southern Ocean, the Antarctic Ross Sea, and parts of the Arctic Sea. In the meantime, an unprecedented climate would come even after thousands of years over some other regions of ocean including the eastern tropical Pacific and the North Pacific middle latitudes where an internal variability is large. In summary, spatial pattern in timing of unprecedented climate are different for each continent. For the ocean, it is highly affected by large internal variability except for the high-latitude regions with a significant warming trend. As such, a timing of an unprecedented climate would not be uniform over the globe but considerably different by region. Our results suggest that it is necessary to consider an internal variability as well as a regional warming rate when planning a climate change mitigation and adaption policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.179-185
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• 2016

This study verifies whether speculative trading in commodity markets acted as the primary cause of the increase in commodity prices after the global financial crisis using the Structural Vector Autoregressive (SVAR) model. The effects of speculative trading on commodity prices increased by a factor of 3 to 6 after the crisis compared to those before the crisis. Although the demand related variables, such as industrial production, affected commodity prices significantly before the crisis, their effects decreased after the crisis. Consequently, the rebound of commodity prices after the crisis was mainly caused by the increase in speculative money, fortified by the expansion of the global liquidity supply. The global liquidity may well increase in the future, because the U.S. Federal Reserve Board is likely to continue to increase its interest rate. This study claims that when global liquidity shrinks as a result of a change in the Fed's monetary policy stance, speculative trading will slow down, leading to a decline in commodity prices.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.451-451
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• 2015

최근 1900년부터 1990년 사이 해수면은 매년 평균 1.2mm 상승했지만 1990년부터는 매년 평균 3mm씩 높아지고 있으며, 이에 1990년부터 현재까지 해수면 수위의 상승속도가 이전 90년 동안 측정된 수치보다 2.5배 빠르다는 연구결과가 발표되었다. 해수면 상승으로 인한 피해는 범람과 침식을 야기할 수 있으며 해일 및 폭풍으로 인한 피해를 증가시킴으로 물질적 피해와 인명 피해를 유발할 수 있다. 이러한 이유로 해수면 상승에 따른 과학적인 분석과 신뢰성 있는 전망을 통하여 해수면 상승에 따른 대응과 대비가 필요하다. 이에 본 연구에서는 비정상성 빈도해석 방법을 통하여 미래의 해수면 상승을 고려할 수 있는 비정상성 빈도해석 기법을 개발하였다. 본 연구에서는 극치사상을 추출하기 위해 국립해양조사원 (Korea Hydrographic and Oceanographic Administration, KHOA)에서 관리한 45개 조위관측소의 시 조위 자료를 이용하였다. 45개 조위관측소의 한 시간 단위 자료로부터 연최대 및 연평균 조위계열 (annual average and annual maximum sea level series)을 추출하였다. 본 연구에서는 한반도 해안을 동해안, 서해안, 남해안, 제주 권역으로 구분하고 빈도 해석의 신뢰성을 만족하기 위해 자료 구축기간이 20년 이상이며, 각 해안을 나타낼 수 있는 지점을 선정하였다. 비정상성 빈도해석은 Gumbel 극치분포를 적용하였으며, 계층적 Bayesian 기법을 결합하여 매개변수들에 대한 사후분포를 추정하였다. 본 연구에서는 대부분의 지점에서 비정상성 빈도해석 결과와 정상성 빈도해석 결과와 상당한 차이를 보여주고 있으며, 이는 주로 정상성 가정에 기인하는 문제점으로 판단된다. 향후 기후변화에 따른 연안지역의 홍수 및 사회기반시설의 위험도를 평가하기 위해서는 비정상성을 고려한 빈도해석 절차의 수립과 적용이 필요할 것으로 판단된다.

• Environmental and Resource Economics Review
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• v.20 no.4
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• pp.859-882
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• 2011

Since two oil crises in the 1970s, Korea has actively engaged in overseas E&P projects to increase energy diversity as well as its self-development rate of energy resources. Korea's energy self-development rate, an index that indicates the ratio of resources acquired through overseas development compared to direct imports. Currently, Korea is conducting a total of 180 promising overseas oil development projects in 36 countries as of the end of 2010. By now, it has secured a reserve of around 1.63 billion barrels and production of around 176 thousand barrels of oil per day. The self-development rate for oil rose from 2.8% in 2006 to 7.4% in 2010. Not content with these remarkable successes, the korean government is planning to raise its self-development rate in oil to 25% by 2019, by promoting the active participation of Korean companies in overseas oil development projects. This paper is concerned with estimation of the required amount of government subsidies that includes loans and financial support through state-controlled banking institutions in order to reach the target 25% rate by 2019. The estimation results shows that government subsidies of at least 268 million dollars are needed for the current rate of 7.4% in oil. However, the amount sharply increases up to 1.25 billion dollars in 2019 when domestic oil demand rises to 1.02 billion barrels.

• Journal of Climate Change Research
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• v.1 no.2
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• pp.121-131
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• 2010

This study was carried out to evaluate spatial variations in rice production areas by simulating rice growth and yield with CERES-Rice growth model under GCM $2{\times}CO_2$ climate change scenarios. A modified window version(v4.0) of CERES-Rice was used to simulate the growth and development of three varieties, representing early, medium, and late maturity classes. Simulated growth and yield data of the three cultivars under the climate for 1971 to 2000 was set as a reference. Compared with the current normal(1971 to 2000), heading period from transplanting to heading date decreased by 7~8 days for the climate in $2^{\circ}C$ increase over normal, and 16~18 days for the climate in UKMO with all maturity classes, while change of ripening period from heading to harvesting date was different with maturity classes. That is, physical maturity was shortened by 1~3 days for early maturity class and 14~18 days for late maturity class under different climate change scenarios. Rice yield was in general reduced by 4.5%, 8.2%, 9.9%, and 14.9% under the climate in $2^{\circ}C$, $3^{\circ}C$, $4^{\circ}C$, and about $5^{\circ}C$ increase, respectively. The yield reduction was due to increased high temperature-induced spikelet sterility and decreased growth period. The results show that predicted climate changes are expected to bring negative effects in rice production in Korea. So, it is required for introduction of new agricultural technologies to adapt to climate change, which are, for example, developing new cultivars, alternations of planting dates and management practices, and introducing irrigation systems, etc.

• Journal of Science and Technology Studies
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• v.16 no.1
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• pp.29-61
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• 2016

This paper explains the one of the most problematic factor in the society that leads to social inequality - increase in non-regular work. Theoretically, this expansion of non-regular work can be explained by technologies that are designed to save the labor force, especially since corporations in Korea have strategies to replace the regular workers with temporary workers, to save money. OECD also noted that Korea's income inequality is pretty high in ranking when compared with the rest of the OECD members, and says that globalization and technological innovation are the factors of this problem. To refine the argument, this study also looks at relationship between development made in sciences - which can be stated as a proxy variable to look at the advances made in technology - and expansion of temporary work force by using VAR methodology. Based on the results of this analysis in the future temporary/regular workers ratio started with decline, then turn to rise. These temporary/regular workers ratio sustained growth prediction shows that the expansion of the temporary expansion contributes to instability and social inequality in the labor market and technological change are interrelated.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.3
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• pp.351-365
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• 2019

This study aims to predict the changes in population distribution in Korea by considering spatio-temporal characteristics of major migration reasons. For the purpose, we analyze the spatio-temporal characteristics of each major migration reason(such as job, family, housing, and education) and estimate the transition probability, respectively. By appling Markov chain model processes with the ChapmanKolmogorov equation based on the transition probability, we predict the changes in the population distribution for the next six years. As the results, we found that there were differences of population changes by regions, while there were geographic movements into metropolitan areas and cities in general. The methodologies and the results presented in this study can be utilized for the provision of customized planning policies. In the long run, it can be used as a basis for planning and enforcing regionally tailored policies that strengthen inflow factors and improve outflow factors based on the trends of population inflow and outflow by region by movement factors as well as identify the patterns of population inflow and outflow in each region and predict future population volatility.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.385-391
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• 2018

Abalone aquacultural industry has been growing rapidly in a short period of time, however, there has been just a few researches related to the forecast of the supply, demand and price. Even the models developed by these researches have problems of low compatibility and reliability. To resolve these problem, a biological supply model needs to be developed that maintains time difference and linkage among the quantity of juvenile abalone into the plots, quantity of cultivation, quantity of shipment, and at the same time juvenile abalone is transplanted into the plot, matured and shipped by the expected market price. This study focus on the development of the model for determining quantity of the abalone cultivation, which is the core part of the entire abalone demand and supply model. Key factors that affect cultivation quantity were identified and verified the causal relationship among these variables and cultivation quantity. It turned out that the quantity of juvenile abalone transplanted and the relative price(the abalone price of the place of produce divided by the brown seaweed price) have a great influence on the cultivation quantity. Also, the similarity of the variation for the cultivation quantity of the observed value and the forecasted value implies that the model developed in this study has a high compatibility.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.121-135
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• 2022

The purpose of this study is to explore the convergence sector of the spatial information industry based on the business transaction data of spatial information companies and to predict the market size of the industry using the Seemingly Unrelated Regression(SUR) model. The convergence part of spatial information industry, which cannot be identified in the Spatial Data Industry Survey, was analyzed by exploring keywords related to spatial information using the business DB of Korea Enterprise Data (2010-2019). The convergence of spatial information businesses mainly appeared in the business relationship between the value chain between Seoul and Gyeonggi Province. The convergence business has the largest sales in the value chain 2 (utilization, service) & 3 (convergence), and also the convergence in the value chain 1 (production, construction) & 2, 2 & 3 stages has doubled in 2019 compared to 2010. In 2019, the total sales of the spatial information industry based on the Statistical Korea were announced at about 8 trillion won, but in this study, the total sales of the spatial information industry were estimated at 28 trillion won considering convergence activities. Finally, when scenario 1 (0.38% population growth, 2020-2024) and 0.07% (2026-2030) were applied using the SUR model to predict the expected market size of the industry, sales decreased by -0.37% to 0.069% in 2025 and 2030 by respectively. When scenario 2 (average wage growth 1.2%) was applied during the same period, sales in the industry increased by 2.326% to 12.185%. In other words, the sales in the spatial information industry depends on Labor, Total Factor Productivity, and Capital Productivity so it is necessary to additional research on policy development and alternatives of enhancing each productivity.