• Journal of Climate Change Research
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• v.9 no.2
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• pp.171-179
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• 2018

The causal relationship between El Nino-Southern Oscillation (ENSO) and winter climate variability in Korea is tested by analyzing Korea Meteorological Administration Automatic Synoptic Observing System datasets for the past 59 years. Consistent with previous studies, positive phase of ENSO (El Nino) tends to cause warmer temperature and heavier precipitation in Korea in early winter with three-week lead time. This causality is quantified by performing Granger causality test. It turns out that ENSO explains an additional 9.25% of the variance of early-winter temperature anomalies in Korea, beyond that already provided by temperature itself. Likewise, 22.18% additional information is gained to explain early-winter precipitation variance by considering ENSO. This result, which differs from simple lead-lag correlation analysis, suggests that ENSO needs to be considered in predicting early-winter surface climate variability in Korea.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.209-210
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• 2017

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.60-66
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• 2013

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.361-372
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• 2016

Reliable long-term dam inflow prediction is necessary for efficient multi-purpose dam operation in changing climate. Since 2000s the teleconnection between global climate indices (e.g., ENSO) and local hydroclimate regimes have been widely recognized throughout the world. To date many hydrologists focus on predicting future hydrologic conditions using lag teleconnection between streamflow and climate indices. This study investigated the utility of teleconneciton for predicting dam inflow with 1-month lead time at Andong dam basin. To this end 40 global climate indices from NOAA were employed to identify potential predictors of dam inflow, areal averaged precipitation, temperature of Andong dam basin. This study compared three different approaches; 1) dam inflow prediction using SWAT model based on teleconneciton-based precipitation and temperature forecast (SWAT-Forecasted), 2) dam inflow prediction using teleconneciton between dam inflow and climate indices (CIR-Forecasted), and 3) dam inflow prediction based on the rank of current observation in the historical dam inflow (Rank-Observed). Our results demonstrated that CIR-Forecasted showed better predictability than the other approaches, except in December. This is because uncertainties attributed to temporal downscaling from monthly to daily for precipitation and temperature forecasts and hydrologic modeling using SWAT can be ignored from dam inflow forecast through CIR-Forecasted approach. This study indicates that 1-month lead dam inflow forecast based on teleconneciton could provide useful information on Andong dam operation.

• Environmental and Resource Economics Review
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• v.17 no.2
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• pp.287-311
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• 2008

This paper is designed to examine how the global timber market impacted by climate change would affect global warming through the carbon flux of forests. For this purpose, we integrated the modified TSM 2000 and the extended TCM in order to simulate the projection of net carbon release of forests from 1995 to 2085. On the basis of the simulation results under normal demand growth scenario, we identified that the global timber market impacted by climate change ameliorates the atmospheric carbon about 3.60% of carbon dioxide concentration in 1990 over 90 years. This implies that the global timber market impacted by climate change has a negative feedback effect on global warming over 90 years. For sensitivity analysis, we performed these simulation procedure under high demand growth scenario and very high demand growth scenario.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.9
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• pp.809-817
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• 2010

Reducing emissions across all sectors requires a well-designed policies tailored to fit specific national circumstances. And every climate policymaker would like to have an accurate method of assessing the quantitative impacts of future policies to address GHG-related problems. Estimates of future changes in a nation's GHG emissions, the expected environmental impacts of future energy sector developments, and the potential costs and benefits of different climate technology and mitigation policy options are desirable inputs to policy making. Various mitigation analysis and modeling approaches helped to fill the needs for these kinds of information, and as such has been an important part of national mitigation policy making in many countries for most of two decades. This paper provides a overview of GHG mitigation policies and mitigation analysis, and sectoral mitigation circumstances and potentials.

• Journal of Navigation and Port Research
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• v.34 no.1
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• pp.65-70
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• 2010

Recently, the number of design for open-spaces at waterfront, such as open-air restaurant and cafeteria, has been increasing to provide openness and natural environment of waterfront. However, when planning open-air restaurant and cafeteria, it is essential to investigate the climate characteristic of waterfront, especially wind environment, since the waterfront has a special quality of climate like low-temperature and strong wind which differs from downtown or inland. In this study, wind environments of Haeundae, Suyoungman, and Gwanganli, the famous waterfronts in Busan, were investigated for design of open-air restaurants and open cafeterias. The main results were as follows. 1) the waterfront area of Haeundae, Suyoungman, and Gwanganli is suitable for open-air restaurant and open cafeterias; and 2) the appropriate period for open space in this area is from the end of March to November.

• Journal of Climate Change Research
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• v.3 no.2
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• pp.89-100
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• 2012

This study analyzes spatio-temporal variability of discomfort index for summer the during the past ten years(2001~2010) in the Korean Peninsula, and considers the application possibility of discomfort index as a preliminary data for various phenomenon of society based on the analysis. Discomfort index defined as daily representative value was estimated using hourly temperature and humidity data which are observed 60 weather stations managed by Korea Meteorological Administration. The result indicates that the discomfort index in summer keeps the level at which one feels unpleasant, and the level increased steadily as temperature is rising. And discomfort index in 3 pm and on August are the highest during the day and year. Gangwon-do have shown the lowest discomfort index among the provinces. Variability analysis of discomfort index due to climate changes can be used for making policies in various fields such as industry and public health field.

• Korean Journal of Construction Engineering and Management
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• v.1 no.4 s.4
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• pp.74-81
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• 2000

The duration of construction in the construction works contains non-working days as well as working days. The duration is so relevant to climate that it should be calculated after fully considered about the regional climate in which construction processes. In most construction fields, however, there has been a frequent adjustment of duration because the field supervisor's experiences have decided non-working days indiscriminately without any accurate information about weather. Not only has that done great economic damages, but also caused many problems in interests among construction subject. So, in this study, we will analyse the elements of climate which has influences on the duration and implement the hypothetical weather simulation. By connecting the results of simulation with the duration of construction, we will propose the decision-making support model for the efficient calculation of duration when the field supervisor makes the projects schedule.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.224-224
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• 2019

국제기상기구의 Global Framework for Climate Services (GFCS)의 관점에서 살펴보면 국내의 기상 기후 정보는 기상청을 중심으로 관측 자료와 중장기 예측 및 기후변화 시나리오 정보 등의 다양한 시간규모로 생산되고 있다. 하지만 사용자가 직접적으로 다양한 기후정보를 상세화하여 활용하기 위해서는 기후정보의 구축 및 전처리를 수행해야하는 어려움이 있다. 따라서 APEC Climate Center (APCC)에서 다학제 융합 기반 기후정보 서비스를 중심으로 사용자 인터페이스 플랫폼 (User Interface Platform: UIP)의 기술적 플랫폼으로 APCC Integrated Modeling Solution (AIMS)를 개발하였다. AIMS는 사용자의 관점으로 상세화를 수행할 수 있고, 다양한 응용 분야에 적용하기 쉽게 데이터를 생성하여 연구에 도움을 주고 있다. 본 연구는 AIMS에서 제공하고 있는 기존의 국가별로 제공하는 제 5차 결합 기후모델 비교사업 (The $5^{th}$ phase of the coupled model intercomparision project, CMIP5)에서 해석한 전구기후모델 (General Circulation Model, GCM)의 통계적 상세화 방법인 Simple Quantile Mapping (SQM)과 Spatial Disaggregation Quantile Delta Mapping (SDQDM)를 포함하여 AIMS에 새롭게 추가 된 통계적 상세화 방법인 Bias Correction and Stochastic Analog (BCSA) 방법을 소개하고자 한다. 또한 60개의 종관기상관측 (Automated Surface Observing System, ASOS)자료를 중심으로 생성한 세 가지 통계적 상세화방법의 과거재현성과 RCP4.5, RCP8.5 시나리오를 활용한 미래 불확실성 평가 결과를 이용하여 연구자들의 맞춤형 자료를 생산하고 평가하는데 도움을 줌으로써 다양한 기후자료의 효과적인 활용이 가능할 것으로 기대된다.