• 한국전산유체공학회:학술대회논문집
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• 2007.04a
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• pp.2-2
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• 2007

• Journal of Korean Society of Water and Wastewater
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• v.38 no.2
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• pp.61-68
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• 2024

In the context of the Ministry of Environment's 2022 Climate Change Adaptation Plan for Public Institutions, public sewage treatment plants are one of the important targets for climate change response aimed at sustainable water management. In this study, it is applied a modified methodology to four water regeneration centers (public sewage treatment facilities) in charge of sewage treatment in Seoul to analyze the impacts and risks of climate change and discuss priorities for adaptation measures. The results of the study showed that heavy rains, heat waves, and droughts will be the key impacts of climate change, and highlighted the need for measures to mitigate these risks, especially for facility managers.

• Atmosphere
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• v.23 no.2
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• pp.237-243
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• 2013

A set of scripts for GrADS (Grid Analysis and Display System) and R was implemented to produce agricultural climate information using the future climate scenarios based on the Representative Concentration Pathways. The GrADS script was used to calculate agricultural climate indices including growing degree days and cooling degree days. The script generated agricultural climate maps of these indices, which are compatible with common Geographic Information System (GIS) applications. To perform a statistical analysis using the agricultural climate maps, a script for R, which is open source statistical software, was used. Because a large number of spatial climate data were produced, parallel processing packages such as SNOW, doSNOW, and foreach were used to perform a simple statistical analysis in the R script. The parallel script of R had speedup on workstations with multi-CPU cores.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1143-1152
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• 2009

A canonical correlation analysis(CCA)-based method is proposed for prediction of future climate change which combines information from ensembles of atmosphere-ocean general circulation models(AOGCMs) and observed climate values. This paper focuses on predictions of future climate on a regional scale which are of potential economic values. The proposed method is obtained by coupling the classical CCA with empirical orthogonal functions(EOF) for dimension reduction. Furthermore, we generate a distribution of climate responses, so that extreme events as well as a general feature such as long tails and unimodality can be revealed through the distribution. Results from real data examples demonstrate the promising empirical properties of the proposed approaches.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.6
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• pp.111-117
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• 2011

This study attempts to facilitate climate change adaptation in conservation area by spatial planning of climate adaptation zone for endangered species. Spatial area is South Korea and select leopard cat (Prionailurus bengalensis) as a target species of this study. In order to specify the climate adaptation zone, firstly, Maximum entropy method (Maxent) was used to identify suitable habitat, and then core habitat was selected for leopard cat. Secondly, land use resistance index was evaluated and least cost distance was analyzed for target species. In this step we choose dispersal capacity of leopard cat to reflect species ecological characteristic. Finally, climate adaptation zone is described and adaptation measures are suggested. The presented approach could be generalized for application into conservation planning and restoration process. Furthermore, spatial planning of climate adaptation zone could increase heterogeneity of habitat and improve adaptive capacity of species and habitat itself.

• Magazine of the Korean Society of Hazard Mitigation
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• v.2 no.4 s.7
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• pp.40-47
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• 2002

Since it is important to understand the bio-climatic change in Seoul for ecological city planning in the future, this paper gives an overview on bio-climate analysis of urban environments at Seoul. We analyzed its characteristics in recent years using the observations of 24 of Automatic Weather Station (AWS) by Korea Meteorological Administration (KMA). In urbanization, Seoul metropolitan area is densely populated and is concentrated with high buildings. This urban activity changes land covering, which modifies the local circulation of radiation, heat and moisture, precipitation and creating a specific climate. Urban climate is evidently manifested in the phenomena of the increase of the air temperature, called urban heat Island and in addition urban sqall line of heavy rain. Since a city has its different land cover and street structure, these form their own climate character such as climate comfort zone. The thermal fold in urban area such as the heat island is produced by the change of land use and the air pollution that provide the bio-climate change of urban eco-system. The urban wind flow is the most important climate element on dispersion of air pollution, thermal effects and heavy shower. Numerical modeling indicates that the bio-climatic transition of wind wake in urban area and the dispersion of the air pollution by the simulations of the wind variation depend on the urban land cover change. The winds are separately simulated on small and micro-scale at Seoul with two kinds of kinetic model, Witrak and MUKLIMO.

• Journal of Environmental Health Sciences
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• v.39 no.1
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• pp.19-31
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• 2013

Objectives: Elevated temperatures during summer months have been reported since the early 20th century to be associated with increased daily mortality. However, future death impacts of high temperatures resulting from climate change could be variously estimated in consideration of the future changes in historical temperature-mortality relationships, mortality, and population. This study examined the future death burden of high temperatures resulting from climate change in Seoul over the period of 2001-2040. Methods: We calculated yearly death burden attributable to high temperatures stemming from climate change in Seoul from 2001-2040. These future death burdens from high temperature were computed by multiplying relative risk, temperature, mortality, and population at any future point. To incorporate adaptation, we assumed future changes in temperature-mortality relationships (i.e. threshold temperatures and slopes), which were estimated as short-term temperature effects using a Poisson regression model. Results: The results show that climate change will lead to a substantial increase in summer high temperature-related death burden in the future, even considering adaptation by the population group. The yearly death burden attributable to elevated temperatures ranged from approximately 0.7 deaths per 100,000 people in 2001-2010 to about 1.5 deaths per 100,000 people in Seoul in 2036-2040. Conclusions: This study suggests that adaptation strategies and communication regarding future health risks stemming from climate change are necessary for the public and for the political leadership of South Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.1
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• pp.49-66
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• 2024

Extreme rainfall will become intense due to climate change, increasing inundation risk to agricultural land. Hydrological and hydraulic simulations for the entire watershed were conducted to analyze the impact of climate change. Rainfall data was collected based on past weather observation and SSP (Shared Socio-economic Pathway)5-8.5 climate change scenarios. Simulation for flood volume, reservoir operation, river level, and inundation of agricultural land was conducted through K-HAS (KRC Hydraulics & Hydrology Analysis System) and HEC-RAS (Hydrologic Engineering Center - River Analysis System). Various scenarios were selected, encompassing different periods of rainfall data, including the observed period (1973-2022), near-term future (2021-2050), mid-term future (2051-2080), and long-term future (2081-2100), in addition to probabilistic precipitation events with return periods of 20 years and 100 years. The inundation area of the Aho-Buin district was visualized through GIS (Geographic Information System) based on the results of the flooding analysis. The probabilistic precipitation of climate change scenarios was calculated higher than that of past observations, which affected the increase in reservoir inflow, river level, inundation time, and inundation area. The inundation area and inundation time were higher in the 100-year frequency. Inundation risk was high in the order of long-term future, near-term future, mid-term future, and observed period. It was also shown that the Aho and Buin districts were vulnerable to inundation. These results are expected to be used as fundamental data for assessing the risk of flooding for agricultural land and downstream watersheds under climate change, guiding drainage improvement projects, and making flood risk maps.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.109-128
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• 2020

A climate-impact projection usually consists of several stages, and the uncertainty of the projection is known to be quite large. It is necessary to assess how much each stage contributed to the uncertainty. We call an uncertainty quantification method in which relative contribution of each stage can be evaluated as uncertainty decomposition. We propose a new Bayesian model for uncertainty decomposition in climate change impact assessments. The proposed Bayesian model can incorporate uncertainty of natural variability and utilize data in control period. We provide a simple and efficient Gibbs sampling algorithm using the auxiliary variable technique. We compare the proposed method with other existing uncertainty decomposition methods by analyzing streamflow data for Yongdam Dam basin located at Geum River in South Korea.

• Journal of Climate Change Research
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• v.7 no.1
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• pp.69-75
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• 2016

Recently, many countries all over the world have been suffered from disaster caused by climate change. Especially in case of developed countries, the disaster is concentrated in the industry sector. In this research, we analyzed industrial vulnerable homogeneous hotspot for the climate change using spatial autocorrelation analysis on the south Korea. Homogeneous hot spot areas through autocorrelation analysis indicate the spatial pattern of areas interacted each other. Industry sector have responsibility of green house gas emissions, and should adapt to the climate change caused by greenhouse gas already released. So, we integrated the areas sensitive to mitigation option with the areas hardly adapt to climate change because of vulnerable infrastructure. We expected that the result of this research could contribute to the decision-making system of climate change polices.