• Journal of Climate Change Research
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• v.9 no.1
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• pp.1-12
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• 2018

There is an emphasis on the importance of adaptation against to climate change and related natural disasters. As a result, various climate information with different time-scale can be used for science-based climate change adaptation policy. From the aspects of Global Framework for Climate Services (GFCS), various time-scaled climate information in Korea is mainly produced by Korea Meteorological Administration (KMA) However, application of weather and climate information in different application sectors has been done individually in the fields of agriculture and water resources mostly based-on weather information. Furthermore, utilization of climate information including seasonal forecast and climate change projections are insufficient. Therefore, establishment of the Cooperation Center for Application of Weather and Climate Information is necessary as an institutional platform for the UIP (User Interface Platform) focusing on multi-model ensemble (MME) based climate service, seamless climate service, and climate service based on multidisciplinary approach. In addition, APCC Integrated Modeling Solution (AIMS) was developed as a technical platform for UIP focusing on user-centered downscaling of various time-scaled climate information, application of downscaled data into impact assessment modeling in various sectors, and finally producing information can be used in decision making procedures. AIMS is expected to be helpful for the increase of adaptation capacity against climate change in developing countries and Korea through the voluntary participation of producer and user groups within in the institutional and technical platform suggested.

• Ocean and Polar Research
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• v.34 no.2
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• pp.239-251
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• 2012

The food web dynamics in a coastal ecosystem of Korea were predicted with Ecosim, a trophic flow model, under various scenarios of primary productivity due to ocean warming and ocean acidification. Changes in primary productivity were obtained from an earth system model 2.1 under A1B scenario of IPCC $CO_2$ emission and replaced for forcing functions on the phytoplankton group during the period between 2020 and 2100. Impacts of ocean acidification on species were represented in the model for gastropoda, bivalvia, echinodermata, crustacean and cephalopoda groups with effect sizes of conservative, medium and large. The model results show that the total biomass of invertebrate and fish groups decreases 5%, 11~28% and 14~27%, respectively, depending on primary productivity, ocean acidification and combined effects. In particular, the blenny group shows zero biomass at 2080. The zooplankton group shows a sudden increase at the same time, and finally reaches twice the baseline at 2100. On the other hand, the ecosystem attributes of the mean trophic level of the ecosystem, Shannon's H and Kempton's Q indexes show a similar reduction pattern to biomass change, indicating that total biomass, biodiversity and evenness shrink dynamically by impacts of climate change. It is expected from the model results that, after obtaining more information on climate change impacts on the species level, this study will be helpful for further investigation of the food web dynamics in the open seas around Korea.

• Ocean and Polar Research
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• v.31 no.4
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• pp.369-377
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• 2009

Performance of the Korea Ocean Research and Development Institute (KORDI) operational storm surge prediction system for the Korean coast is presented here. Results for storm surge hindcasts and forecasts calculations were analyzed. The KORDI storm surge system consists of two important components. The first component is atmospheric models, based on US Army Corps of Engineers (CE) wind model and the Weather Research and Forecasting (WRF) model, and the second components is the KORDI-storm surge model (KORDI-S). The atmospheric inputs are calculated by the CE wind model for typhoon period and by the WRF model for non-typhoon period. The KORDI-S calculates the storm surges using the atmospheric inputs and has 3-step nesting grids with the smallest horizontal resolution of ${\sim}$300 m. The system runs twice daily for a 72-hour storm surge prediction. It successfully reproduced storm surge signals around the Korean Peninsula for a selection of four major typhoons, which recorded the maximum storm surge heights ranging from 104 to 212 cm. The operational capability of this system was tested for forecasts of Typhoon Nari in 2007 and a low-pressure event on August 27, 2009. This system responded correctly to the given typhoon information for Typhoon Nari. In particular, for the low-pressure event the system warned of storm surge occurrence approximately 68 hours ahead.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.75-86
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• 2019

Recently, natural disasters due to abnormal climates are frequently outbreaking, and there is rapid increase of damage to aged agricultural infrastructure. As agricultural infrastructure facilities are in contact with water throughout the year and the number of them is significant, it is important to build a maintenance management system. Especially, the current maintenance management system of pumping and drainage stations among the agricultural facilities has the limit of lack of objectivity and management personnel. The purpose of this study is to develop a performance evaluation model using the factors related to performance degradation of pumping and drainage facilities and to predict the performance of the facilities in response to climate change. In this study, we focused on the pumping and drainage stations belonging to each climatic zone separated by the Korea geographical climatic classification system. The performance evaluation model was developed using three different statistical models of POLS, RE, and LASSO. As the result of analysis of statistical models, LASSO was selected for the performance evaluation model as it solved the multicollinearity problem between variables, and showed the smallest MSE. To predict the performance degradation due to climate change, the climate change response variables were classified into three categories: climate exposure, sensitivity, and adaptive capacity. The performance degradation prediction was performed at each facility using the developed performance evaluation model and the climate change response variables.

• Journal of Korea Water Resources Association
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• v.44 no.8
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• pp.653-666
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• 2011

The purposes of this study are to suggest flood vulnerability assessment method on climate change with evaluation of this method over the 5 river basins and to present the uncertainty range of assessment using multi-model ensemble scenarios. In this study, the data related to past historical flood events were collected and flood vulnerability index was calculated. The vulnerability assessment were also performed under current climate system. For future climate change scenario, the 39 climate scenarios are obtained from 3 different emission scenarios and 13 GCMs provided by IPCC DDC and 312 hydrology scenarios from 3 hydrological models and 2~3 potential evapotranspiration computation methods for the climate scenarios. Finally, the spatial and temporal changes of flood vulnerability and the range of uncertainty were performed for future S1 (2010~2039), S2 (2040~2069), S3 (2070~2099) period compared to reference S0 (1971~2000) period. The results of this study shows that vulnerable region's were Han and Sumjin, Youngsan river basins under current climate system. Considering the climate scenarios, variability in Nakdong, Gum and Han river basins are large, but Sumjin river basin had little variability due to low basic-stream ability to adaptation.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.5
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• pp.32-40
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• 2006

This study's objects are to suggest effective forest community-level management measures by identifying the vulnerable forest vegetation communities types to climate change through a comparative analysis with present forest communities identified and delineated in the Actual Vegetation Map. The methods of this study are to classify the climatic life zones based on the correlative climate-vegetation relationship for each forest vegetation community, the Holdridge Bio-Climate Model was employed. This study confirms relationship between forest vegetation and environmental factors using Pearson's correlation coefficient analysis. Then, the future distribution of forest vegetation are predicted derived factors and present distribution of vegetation by utilizing the multinomial logit model. The vulnerability of forest to climate change was evaluated by identifying the forest community shifts slower than the average velocity of forest moving (VFM) for woody plants, which is assumed to be 0.25 kilometers per year. The major findings in this study are as follows : First, the result of correlative analysis shows that summer precipitation, mean temperature of the coldest month, elevation, soil organic matter contents, and soil acidity (pH) are highly influencing factors to the distribution of forest vegetation. Secondly, the result of the vulnerability assessment employing the assumed velocity of forest moving for woody plants (0.25kmjyear) shows that 54.82% of the forest turned out to be vulnerable to climate change. The sub-alpine vegetations in regions around Mount Jiri and Mount Seorak are predicted to shift the dominance toward Quercus mongolica and Pinus densiflora communities. In the identified vulnerable areas centering the southern and eastern coastal regions, about 8.27% of the Pinus densiflora communities is likely to shift to sub-tropical forest communities, and 3.38% of the Quercus mongolica communities is likely to shift toward Quercus acutissima communities. In the vulnerable areas scattered throughout the country, about 8.84% of the Quercus mongolica communities is likely to shift toward Pinus densiflora communities due to the effects of climate change. The study findings concluded that challenges associated with predicting the future climate using RCM and the assessment of the future vulnerabilities of forest vegetations to climate change are significant.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.525-533
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• 2008

Global circulation models (GCMs) have been used to study impact of climate change on water resources for hydrologic models as inputs. Recently, regional circulation models (RCMs) have been used widely for climate change study, but the RCMs have been rarely used in the climate change impacts on water resources in Korea. Therefore, this study is intended to use a set of climate scenarios derived by RegCM3 RCM ($27km{\times}27km$), which is operated by Korea Meteorological Administration. To begin with, the RCM precipitation data surrounding major rainfall stations are extracted to assess validation of the scenarios in terms of reproducing low frequency behavior. A comprehensive comparison between observation and precipitation scenario is performed through statistical analysis, wavelet transform analysis and EOF analysis. Overall analysis confirmed that the precipitation data driven by RegCM3 shows capabilities in simulating hydrological low frequency behavior and reproducing spatio-temporal patterns. However, it is found that spatio-temporal patterns are slightly biased and amplitudes (variances) from the RCMs precipitation tend to be lower than the observations. Therefore, a bias correction scheme to correct the systematic bias needs to be considered in case the RCMs are applied to water resources assessment under climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.75-88
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• 2024

It would be advantageous to predict acreage and yield of crops in major grain-exporting countries, which would improve decisions on policy making and grain trade in Korea. A climate suitability model can be used to assess crop acreage and yield in a region where the availability of observation data is limited for the use of process-based crop models. The objective of this study was to determine the climate suitability index of wheat by province in Ukraine, which would allow for the spatial assessment of acreage and yield for the given crop. In the present study, the official data of wheat acreage and yield were collected from the State Statistics Service of Ukraine. The EarthStat data, which is a data product derived from satellite data and official crop reports, were also gathered for the comparison with the map of climate suitability index. The Fuzzy Union model was used to create the climate suitability maps under the historical climate conditions for the period from 1970 to 2000. These maps were compared against actual acreage and yield by province. It was found that the EarthStat data for acreage and yield of wheat differed from the corresponding official data in several provinces. On the other hand, the climate suitability index obtained using the Fuzzy Union model explained the variation in acreage and yield at a reasonable degree. For example, the correlation coefficient between the climate suitability index and yield was 0.647. Our results suggested that the climate suitability index could be used to indicate the spatial distribution of acreage and yield within a region of interest.

• Asian Journal of Atmospheric Environment
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• v.11 no.4
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• pp.330-343
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• 2017

Climate change is an important issue, with many researches examining not only future climatic conditions, but also the interaction of climate and air quality. In this study, a new version of the emissions processing software tool - Python-based PRocessing Operator for Climate and Emission Scenarios (PROCES) - was developed to support climate and atmospheric chemistry modeling studies. PROCES was designed to cover global and regional scale modeling domains, which correspond to GEOS-Chem and CMAQ/CAMx models, respectively. This tool comprises of one main system and two units of external software. One of the external software units for this processing system was developed using the GIS commercial program, which was used to create spatial allocation profiles as an auxiliary database. The SMOKE-Asia emissions modeling system was linked to the main system as an external software, to create model-ready emissions for regional scale air quality modeling. The main system was coded in Python version 2.7, which includes several functions allowing general emissions processing steps, such as emissions interpolation, spatial allocation and chemical speciation, to create model-ready emissions and auxiliary inputs of SMOKE-Asia, as well as user-friendly functions related to emissions analysis, such as verification and visualization. Due to its flexible software architecture, PROCES can be applied to any pregridded emission data, as well as regional inventories. The application results of our new tool for global and regional (East Asia) scale modeling domain under RCP scenario for the years 1995-2006, 2015-2025, and 2040-2055 was quantitatively in good agreement with the reference data of RCPs.

• Atmosphere
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• v.22 no.2
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• pp.221-231
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• 2012

Representative Concentration Pathways (RCP) are the latest emission scenarios recommended to use for the fifth assessment report of Intergovernmental Panel on Climate Change. This study investigates the projection of extreme precipitation in South Korea during the forthcoming 21st Century using the generalized extreme value (GEV) analysis based on two different RCP conditions i.e., RCP 4.5 and 8.5. Maximum daily precipitation required for GEV analysis for RCP 4.5 and 8.5 are obtained from a high-resolution regional climate model forced by the corresponding global climate projections, which are produced within the CMIP5 framework. We found overall increase in frequency of extreme precipitation over South Korea in association with climate change. Particularly, daily extreme precipitation that has been occurred every 20 years in current climate (1980~2005) is likely to happen about every 4.3 and 3.4 years by the end of 21st Century (2070~2099) under the RCP 4.5 and 8.5 conditions, respectively.