• Atmosphere
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• v.22 no.2
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• pp.149-161
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• 2012

Going by the research results of the past, of all the uncertainties resulting from the research on climate change, the uncertainty caused by the climate change scenario has the highest degree of uncertainty. Therefore, depending upon what kind of climate change scenario one adopts, the projection of the water resources in the future will differ significantly. As a matter of principle, it is highly recommended to utilize all the GCM scenarios offered by the IPCC. However, this could be considered to be an impractical alternative if a decision has to be made at an action officer's level. Hence, as an alternative, it is deemed necessary to select several scenarios so as to express the possible number of cases to the maximum extent possible. The objective standards in selecting the climate change scenarios have not been properly established and the scenarios have been selected, either at random or subject to the researcher's discretion. In this research, a new scenario selection process, in which it is possible to have the effect of having utilized all the possible scenarios, with using only a few principal scenarios and maintaining some of the uncertainties, has been suggested. In this research, the use of cluster analysis and the selection of a representative scenario in each cluster have efficiently reduced the number of climate change scenarios. In the cluster analysis method, the K-means clustering method, which takes advantage of the statistical features of scenarios has been employed; in the selection of a representative scenario in each cluster, the selection method was analyzed and reviewed and the PDF method was used to select the best scenarios with the closest simulation accuracy and the principal scenarios that is suggested by this research. In the selection of the best scenarios, it has been shown that the GCM scenario which demonstrated high level of simulation accuracy in the past need not necessarily demonstrate the similarly high level of simulation accuracy in the future and various GCM scenarios were selected for the principal scenarios. Secondly, the "Maximum entropy" which can quantify the uncertainties of the climate change scenario has been used to both quantify and compare the uncertainties associated with all the scenarios, best scenarios and the principal scenarios. Comparison has shown that the principal scenarios do maintain and are able to better explain the uncertainties of all the scenarios than the best scenarios. Therefore, through the scenario selection process, it has been proven that the principal scenarios have the effect of having utilized all the scenarios and retaining the uncertainties associated with the climate change to the maximum extent possible, while reducing the number of scenarios at the same time. Lastly, the climate change scenario most suitable for the climate on the Korean peninsula has been suggested. Through the scenario selection process, of all the scenarios found in the 4th IPCC report, principal climate change scenarios, which are suitable for the Korean peninsula and maintain most of the uncertainties, have been suggested. Therefore, it is assessed that the use of the scenario most suitable for the future projection of water resources on the Korean peninsula will be able to provide the projection of the water resources management that maintains more than 70~80% level of uncertainties of all the scenarios.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.103-115
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• 2018

The uncertainty of climate scenarios, as initial information, is one of the significant factors among uncertainties of climate change impacts and vulnerability assessments. In this sense, the quantification of the uncertainty of climate scenarios is essential to understanding these assessments of impacts and vulnerability for adaptation to climate change. Here we quantified the precision of surface temperature of ensemble scenarios (high resolution (1km) RCP4.5 and 8.5) provided by Korea Meteorological Administration, with spatiotemporal variation of the standard deviation of them. From 2021 to 2050, the annual increase rate of RCP8.5 was higher than that of RCP4.5 while the annual variation of RCP8.5 was lower than that of RCP4.5. The standard deviations of ensemble scenarios are higher in summer and winter, particularly in July and January, when the extreme weather events could occur. In general, the uncertainty of ensemble scenarios in summer were lower than those in winter. In spatial distribution, the standard deviation of ensemble scenarios in Seoul Metropolitan Area is relatively higher than other provinces, while that of Yeongnam area is lower than other provinces. In winter, the standard deviations of ensemble scenarios of RCP4.5 and 8.5 in January are higher than those of December. Especially, the standard deviation of ensemble scenarios is higher in the central regions including Gyeonggi, and Gangwon, where the mean surface temperature is lower than southern regions along with Chungbuk. Such differences in precisions of climate ensemble scenarios imply that those uncertainty information should be taken into account for the implementation of national climate change policy.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.2
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• pp.1-13
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• 2015

The Coupled Model Intercomparison Project Phase 5 (CMIP5), coordinated by the World Climate Research Programme in support of the Intergovernmental Panel on Climate Change (IPCC) AR5, is the most recent, provides projections of future climate change using various global climate models under four major greenhouse gas emission scenarios. There is a wide selection of climate models available to provide projections of future climate change. These provide for a wide range of possible outcomes when trying to inform managers about possible climate changes. Hence, future agrometeorological indicators estimation will be much impacted by which global climate model and climate change scenarios are used. Decision makers are increasingly expected to use climate information, but the uncertainties associated with global climate models pose substantial hurdles for agricultural resources planning. Although it is the most reasonable that quantifying of the future uncertainty using climate change scenarios, preliminary analysis using reasonable factors for selecting a subset for decision making are needed. In order to narrow the projections to a handful of models that could be used in a climate change impact study, we could provide effective information for selecting climate model and scenarios for climate change impact assessment using maximum/minimum temperature, precipitation, reference evapotranspiration, and moisture index of nine Representative Concentration Pathways (RCP) scenarios.

• Journal of Climate Change Research
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• v.9 no.2
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• pp.133-142
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• 2018

Climate change will affect not only the crop productivity but also the pattern of rice disease epidemics in Korea. Impact assessments for the climate change are conducted using various climate change scenarios from many global climate models (GCM), such as a scenario from a best GCM or scenarios from multiple GCMs, or a combination of both. Here, we evaluated the feasibility of using a climate change scenario from the best GCM for the impact assessment on the potential epidemics of a rice leaf blast disease in Korea, in comparison to a multi?model ensemble (MME) scenario from multiple GCMs. For this, this study involves analyses of disease simulation using an epidemiological model, EPIRICE?LB, which was validated for Korean rice paddy fields. We then assessed likely changes in disease epidemics using the best GCM selected for individual agro?climatic zones and MME scenarios constructed by running 11 GCMs. As a result, the simulated incidence of leaf blast epidemics gradually decreased over the future periods both from the best GCM and MME. The results from this study emphasized that the best GCM selection approach resulted in comparable performance to the MME approach for the climate change impact assessment on rice leaf blast epidemic in Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.31-41
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• 2011

This study was conducted to predict future land-cover changes under climate change scenarios and to cluster analysis of regional land-cover characteristics. To simulate the future land-cover according to climate change scenarios - A1B, A2, and B1 of the Special Report on Emissions Scenarios (SRES), Dyna-CLUE (Conversion of Land Use Change and its Effects) was applied for modeling of competition among land-use types in relation with socioeconomic and biophysical driving factors. Gyeonggi-do were selected as study areas. The simulation results from 2010 to 2040 suggested future land-cover changes under the scenario conditions. All scenarios resulted in a gradual decrease in paddy area, while upland area continuously increased. A1B scenario showed the highest increase in built-up area, but all scenarios showed only slight changes in forest area. As a result of cluster analysis with the land-cover component scores, 31 si/gun in Gyeonggi-do were classified into three clusters. This approach is expected to be useful for evaluating and simulating land-use changes in relation to development constraints and scenarios. The results could be used as fundamental basis for providing policy direction by considering regional land-cover characteristics.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.269-281
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• 2011

In this review, numerical model results from global and regional climate models are introduced to regional detailed climate changes over East Asia and Korea. In particular, regional climate change scenarios in this region, which are created by several research groups in Korea based on Special Report on Emissions Scenarios (SRES) of IPCC 4th assessment report are introduced and characteristics of the scenarios are investigated. Despite slight differences in intensity, all scenarios reveal prominent warming over the Korean peninsula in future climate. Changes in precipitation amount vary with given scenarios and periods, but the frequency and intensity of heavy precipitation generally tend to increase in all scenarios. South Korea except for mountainous regions is expected to change into subtropical climate in future, which accompanies distinct changes in ecosystems and seasons.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.556-570
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• 2012

The Low Carbon Path Calculator is an excel-based model to project greenhouse gas emissions from 2009 to 2050, which is based on the 2050 Pathways Calculator developed by the UK Department of Energy and Climate Change (DECC). Scenarios are developed to reduce GHG emissions in Korea at 50% based on 2005 levels by 2050 using a Low Carbon Path Calculator. They were classified in four different cases, which are high renewable, high nuclear, high CCS and mixed option scenarios. The objectives of this study are to compare scenarios in terms of GHG emissions, final energy, primary energy and electricity generation and examine the usefulness of that model in terms of identifying pathways towards a low carbon emission society. This model will enhance the understanding of the pathways toward a low carbon society and the level of the climate change policy for policy makers, stakeholders, and the public. This study can be considered as a reference for developing strategies in reducing GHG emissions in the long term.

• The Journal of Fisheries Business Administration
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• v.47 no.4
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• pp.31-44
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• 2016

The purpose of this study is to analyze the climate change exposure of fisheries and fish species in the southern sea of Korea under the RCP climate change scenarios. The extent of exposure was calculated through weighted sum of the sea temperature forecasted by National Institute of Fisheries Science, and the weight were obtained from the time-space distribution of each fisheries or species, based on the micro-data for the fishing information reported by each fisherman. Results show that all the exposed sea temperature of RCP8.5 is higher than that of RCP4.5 in year 2100 as well as in near 2030, therefore it is thought to be very important to reduce the GHG emission even in the short term. The extent of exposure was analyzed to be comparatively high especially in the fisheries such as anchovy drag nets and species like cod, anchovy and squid. Meanwhile the method of this study is considered to be excellent to obtain the accurate extent of exposure under RCP scenarios, and therefore it is applicable on assessing the vulnerability of climate change in fisheries.

• Journal of the Korean Solar Energy Society
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• v.33 no.2
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• pp.64-69
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• 2013

According to the Fourth Assessment Report of Intergovernmental Panel on Climate Change(IPCC) Working Group III, climate change is already in progress around the world, and it is necessary to execute mitigation in order to minimize adverse impacts. This paper suggests future climate change needs, employing IPCC Special Report on Emissions Scenarios(SRES) to predict temperature rises over the next 100 years. This information can be used to develop sustainable architecture applications for energy efficient buildings and renewable energy. Such climate changes could also affected the present supplies of renewable energy sources. This paper discusses one recent Fourth Assessment Report of IPCC (Mitigation of Climate Change) and the Hadley Centre climate simulation of relevant data series for South Korea. Result of this research may improve consistency and reliability of simulation weather data or climate change in order to take advantage of SRES and PRECIS QUMP. It is expected that these calculated test reference years will be useful to the designers of solar energy systems, as well as those who need daily solar radiation data for South Korea. Also, those results may contribute zero carbon and design of sustainable architecture establishing future typical weather data that should be gone ahead to energy efficient building design using renewable energy systems.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.1
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• pp.22-38
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• 2012

Adaptation of climate change is necessary to avoid unexpected impacts of climate change caused by human activities. Vulnerability refers to the degree to which system cannot cope with impacts of climate change, encompassing physical, social and economic aspects. Therefore the quantification of climate change impacts and its vulnerability is needed to identify vulnerable regions and to setup the proper strategies for adaptation. In this study, climate change vulnerability is defined as a function of climate exposure, sensitivity, and adaptive capacity. Also, we identified regions vulnerable to ozone due to climate change in Korea using developed proxy variables of vulnerability of regional level. 18 proxy variables are selected through delphi survey to assess vulnerability over human health sector for ozone concentration change due to climate change. Also, we estimate the weighting score of proxy variables from delphi survey. The results showed that the local regions with higher vulnerability index in the sector of human health are Seoul and Daegu, whereas regions with lower one are Jeollanam-do, Gyeonggi-do, Gwangju, Busan, Daejeon, and Gangwon-do. The regions of high level vulnerability are mainly caused by their high ozone exposure. We also assessed future vulnerability according to the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2, A1FI, A1T, A1B, B2, and B1 scenarios in 2020s, 2050s and 2100s. The results showed that vulnerability increased in all scenarios due to increased ozone concentrations. Especially vulnerability index is increased by approximately 2 times in A1FI scenarios in the 2020s. This study could support regionally adjusted adaptation polices and the quantitative background of policy priority as providing the information on the regional vulnerability of ozone due to climate change in Korea.