• Journal of Korean Society on Water Environment
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• v.40 no.2
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• pp.89-100
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• 2024

Climate change has a broad impact on the entire water environment, and this impact is growing. Climate adaptation in water supply systems often involves quantity and quality control, but there has been a lack of research examining the impacts of climatic factors on water supply productivity and operation conditions. Therefore, the present study focused on, first, building a database of climatic factors and water purification operating conditions, and then identifying the correlations between factors to reveal their impacts. News big data was analyzed with keywords of climatic factors and water supply systems in either nationwide or region-wide analyses. Metropolitan area exhibited more issues with cold waves whereas there were more issues with drought in the Southern Chungcheong area. A survey was conducted to seek experts' opinions on the climatic impacts leading to these effects. Pre-chlorination due to drought, high-turbidity of intake water due to rainfall, an increase of toxins in intake water due to heat waves, and low water temperature due to cold waves were expected. Pearson correlation analysis was conducted based on meteorological data and the operating data of a water purification plant. Heavy rain resulted in 13 days of high turbidity, and the subsequent low turbidity conditions required 3 days of high coagulant dosage. This insight is expected to help inform the design of operation manuals for waterworks in response to climate change.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.2
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• pp.79-88
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• 2015

Preparations need to be made for Korean pine(Pinus koraiensis) in anticipation of climate change because Korean pine is an endemic species of South Korea and the source of timber and pine nut. Therefore, climate change adaptation policy has been established to conduct an impact assessment on the distribution of Korean pine. Our objective was to predict the distribution of Korean pine while taking into account uncertainty and afforestation conditions. We used the 5th forest types map, a forest site map and BIOCLIM variables. The climate scenarios are RCP 4.5 and RCP 8.5 for uncertainty and the climate models are 5 regional climate models (HadGEM3RA, RegCM4, SNURCM, GRIMs, WRF). The base period for this study is 1971 to 2000. The target periods are the mid-21st century (2021-2050) and the end of the 21st century (2071-2100). This study used the MaxEnt model, and 50% of the presences were randomly set as training data. The remaining 50% were used as test data, and 10 cross-validated replicates were run. The selected variables were the annual mean temperature (Bio1), the precipitation of the wettest month (Bio13) and the precipitation of the driest month (Bio14). The test data's ROC curve of Korean pine was 0.689. The distribution of Korean pine in the mid-21st century decreased from 11.9% to 37.8% on RCP 4.5 and RCP 8.5. The area of Korean pine at an artificial plantation occupied from 32.1% to 45.4% on both RCPs. The areas at the end of the 21st century declined by 53.9% on RCP 4.5 and by 86.0% on RCP 8.5. The area of Korean pine at an artificial plantation occupied 23.8% on RCP 4.5 and 7.2% on RCP 8.5. Private forests showed more of a decrease than national forests for all subsequent periods. Our results may contribute to the establishment of climate change adaptation policies for considering various adaptation options.

• Journal of Ecology and Environment
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• v.44 no.3
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• pp.115-125
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• 2020

Background: The phenomenon of tree dieback in forest ecosystems around the world, which is known to be associated with high temperatures that occur simultaneously with drought, has received much attention. Korea is experiencing a rapid rise in temperature relative to other regions. Particularly in the growth of evergreen conifers, temperature increases in winter and spring can have great influence. In recent years, there have been reports of group dieback of Pinus densiflora trees in Korea, and many studies are being conducted to identify the causes. However, research on techniques to diagnose and monitor drought stress in forest ecosystems on local and regional scales has been lacking. Results: In this study, we developed and evaluated an index to identify drought and high-temperature vulnerability in Pinus densiflora forests. We found the Drought Stress Index (DSI) that we developed to be effective in generally assessing the drought-reactive physiology of trees. During 2001-2016, in Korea, we refined the index and produced DSI data from a 1 × 1-km unit grid spanning the entire country. We found that the DSI data correlated with the event data of Pinus densiflora mass dieback compiled in this study. The average DSI value at times of occurrence of Pinus densiflora group dieback was 0.6, which was notably higher than during times of nonoccurrence. Conclusions: Our combination of the Standard Precipitation Index and growing degree days evolved and short- and long-term effects into a new index by which we found meaningful results using dieback event data. Topographical and biological factors and climate data should be considered to improve the DSI. This study serves as the first step in developing an even more robust index to monitor the vulnerability of forest ecosystems in Korea.

• KIEAE Journal
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• v.16 no.6
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• pp.69-75
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• 2016

Climate change has resulted in the urban heat island (UHI) effect throughout the globe, contributing to heat-related illness and fatalities. In order to reduce such damage, it is necessary to improve the climate observation network for precise observation of the urban thermal environment and quick UHI forecasting system. Purpose: This study analyzed the effective range of the climate observation network and the distribution of the existing Automatic Weather Stations (AWS) in Seoul to propose optimal locations for additional installment of AWS. Method: First, we performed quality analysis to pinpoint missing values and outliers within the high-density temperature data measured. With the result from the analysis, a spatial autocorrelation structure in the temperature data was tested to draw the effective range and correlation distance for each major time period. Result: As a result, it turned out that the optimal effective range for the climate observation network in Seoul in July was a radius of 2.8 kilometers. Based on this result, population density, and temperature data, we selected the locations for additional installment of AWS. This study is expected to be used to generate urban temperature maps, select and move measurement locations since it is able to suggest valid, specific spatial ranges when the data measured in point is converted into surface data.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.705-716
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• 2008

The objectives of this study are the detection and forecast of climate change signal in the annual mean of surface temperature data, which are generated by MRI/JMA CGCM over the Korean Peninsula. MRI/JMA CGCM outputs consist of control run data(experiment with no change of $CO_2$ concentration) and scenario run data($CO_2$ 1%/year increase experiment to quadrupling) during 142 years for surface temperature and precipitation. And ECMWF reanalysis data during 43 years are used as observations. All data have the same spatial structure which consists of 42 grid points. Two statistical models, the Bayesian fingerprint method and the regression model with autoregressive error(AUTOREG model), are separately applied to detect the climate change signal. The forecasts up to 2100 are generated by the estimated AUTOREG model only for detected grid points.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• Ocean and Polar Research
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• v.44 no.4
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• pp.287-296
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• 2022

High-frequency (HF) radar measures sea surface currents from the radio waves transmitted and received by antenna on land. Since the data quality of HF radar measurements sensitively depend on the radio wave environment around antenna, Antenna Pattern Measurements (APM) plays an important role in evaluating the accuracy of measured surface currents. In this study, APM was performed by selecting the times when the background noise level around antenna was high and low, and radial data were generated by applying the ideal pattern and measured pattern. The measured antenna pattern for each case was verified with the current velocity data collected by drifters. The radial velocity to which the ideal pattern was applied was not affected by the background noise level around antenna. However, the radial velocity obtained with APM in the period of high background noise was significantly lower in quality than the radial velocity in a low noise environment. It is recomended that APM be carried out in consideration of the radio wave environment around antenna, and that the applied result be compared and verified with the current velocity measurements by drifters. If it is difficult to re-measure APM, we suggest using radial velocity in generating total vector with the ideal pattern through comparative verification, rather than poorly measured patterns, for better data quality.

• 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.

• Korean Journal of Construction Engineering and Management
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• v.18 no.2
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• pp.81-90
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• 2017

In Imjin River basin, three floods occurred between 1996 and 1999, causing many casualties and economic losses of 900 billion won. In Korea, flood damage is expected to increase in the future due to climate change. This study used the climate scenarios to estimate future flood damage costs and suggested a real options-based economic assessment method. Using proposed method, the flood control infrastructures in Imjin River basin were selected as a case study site to analyze the economic feasibility of the investment. Using RCP (Representative Concentration Pathway) climate scenarios, the future flood damage costs were estimated through simulated rainfall data. This study analyzed the flood reduction benefits through investment in the flood control infrastructures. The volatility of flood damage reduction benefits were estimated assuming that the RCP8.5 and RCP4.5 climate scenarios would be realized in the future. In 2071, the project option value would be determined by applying an extension option to invest in an upgrading that would allow the project to adapt to the flood of the 200-year return period. The results of the option values show that the two investment scenarios are economically feasible and the project under RCP8.5 climate scenario has more flood damage reduction benefits than RCP4.5. This study will help government decision makers to consider the uncertainty of climate change in the economic assessment of flood control infrastructures using real options analysis. We also proposed a method to quantify climate risk factors into economic values by using rainfall data provided by climate scenarios.

• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.161-161
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• 2003

During the last century, most scientific questions related to climate change were focused on the evidence of anthropogenic global warming (IPCC, 2001). There are robust evidences of warming and also human-induced climate change. We now understand the global, mean change a little bit better; however, the uncertainties for regional climate change still remains large. The purpose of this study is to understand the past climate change over Korea based on the observational data and to project future regional climate change over East Asia using ECHAM4/HOPE model and MM5 for downscaling. There are significant evidences on regional climate change in Korea, from several variables. The mean annual temperature over Korea has increased about 1.5∼$1.7^{\circ}C$ during the 20th century, including urbanization effect in large cities which can account for 20-30% of warming in the second half of the 20th century. Cold extreme temperature events occurred less frequently especially in the late 20th century, while hot extreme temperature events were more common than earlier in the century. The seasonal and annual precipitation was analyzed to examine long-term trend on precipitation intensity and extreme events. The number of rainy days shows a significant negative trend, which is more evident in summer and fall. Annual precipitation amount tends to increase slightly during the same period. This suggests an increase of precipitation intensity in this area. These changes may influence on growing seasons, floods and droughts, diseases and insects, marketing of seasonal products, energy consumption, and socio-economic sectors. The Korean Peninsular is located at the eastern coast of the largest continent on the earth withmeso-scale mountainous complex topography and itspopulation density is very high. And most people want to hear what will happen in their back yards. It is necessary to produce climate change scenario to fit forhigh-resolution (in meteorological sense, but low-resolution in socio-economic sense) impact assessment. We produced one hundred-year, high-resolution (∼27 km), regional climate change scenario with MM5 and recognized some obstacles to be used in application. The boundary conditions were provided from the 240-year simulation using the ECHAM4/HOPE-G model with SRES A2 scenario. Both observation and simulation data will compose past and future regional climate change scenario over Korea.