• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.196-201
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• 2023

The future is complex and unpredictable. In particular, it is unlikely to occur, but once it occurs, no one knows how it will affect our society if X-event, which has a tremendous impact, is created. This study was conducted only in the climate field to offset the ripple effect of this X-event, and was conducted through in-depth interviews with experts from the Korea Army Research Center for Future & Innovation and the Army College. As a result, it was possible to explore what factors would trigger X-event from their discourse and what X-event would be newly created by spreading them to other fields. Starting with this study, if we accumulate the discourse of experts in various fields such as population, science and technology, as well as climate, and other fields other than the Army, we can predict X-event and offset the threats that may arise.

• Journal of Soil and Groundwater Environment
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• v.19 no.6
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• pp.30-36
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• 2014

The objective of this study is to estimate soil loss in the buffer zone of Guem river with future climate change simulation. Revised Universal Soil Loss Equation (RUSLE) model was used for the estimation of soil loss at the buffer zone of Guem river. As results of simulations, the area of the maximum soil loss potential was estimated as the Cheongsung-myeon Okchun-gun Chungcheongbuk-do. The soil losses were estimated to be 106.67 and 103.00 ton/ha/yr for the 2020 segi (2015-2025) and 2040 segi (2035-2045) in the Cheongsung-myeon area, respectively. Also, the estimated average values of soil losses in the Cheongsung-myeon with future climate change was 110.78 ton/ha/yr.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.45-55
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• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• Atmosphere
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• v.18 no.4
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• pp.507-524
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• 2008

In this paper, future climate changes over East Asia($20^{\circ}{\sim}50^{\circ}N$, $100^{\circ}{\sim}150^{\circ}E$) are projected by anthropogenic forcing of greenhouse gases and aerosols using coupled atmosphere-ocean general circulation model (AOGCM) simulations based on Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) B1, A1B and A2 scenarios. Before projection future climate, model performance is assessed by the $20^{th}$ Century (20C3M) experiment with bias, root Mean Square Error (RMSE), ratio of standard deviation, Taylor diagram analysis. The result of examination of the seasonal uncertainty of T2m and PCP shows that cold bias, lowered than that of observation, of T2m and wet bias, larger than that of observation, of PCP are found over East Asia. The largest wet bias is found in winter and the largest cold bias is found in summer. The RMSE of temperature in the annual mean increases and this trend happens in winter, too. That is, higher resolution model shows generally better performances in simulation T2m and PCP. Based on IPCC SRES scenarios, East Asia will experience warmer and wetter climate in the coming $21^{st}$ century. It is predict the T2m increase in East Asia is larger than global mean temperature. As the latitude goes high, the warming over the continents of East Asia showed much more increase than that over the ocean. An enhanced land-sea contrast is proposed as a possible mechanism of the intensified Asian summer monsoon. But, the inter-model variability in PCP changes is large.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.325-334
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• 2016

We projected the distribution of Hedera rhombea, an evergreen broad-leaved climbing plant, under current climate conditions and predicted its future distributions under global warming. Inaddition, weexplained model uncertainty by employing 9 single Species Distribution model (SDM)s to model the distribution of Hedera rhombea. 9 single SDMs were constructed with 736 presence/absence data and 3 temperature and 3 precipitation data. Uncertainty of each SDM was assessed with TSS (Ture Skill Statistics) and AUC (the Area under the curve) value of ROC (receiver operating characteristic) analyses. To reduce model uncertainty, we combined 9 single SDMs weighted by TSS and resulted in an ensemble forecast, a TSS weighted ensemble. We predicted future distributions of Hedera rhombea under future climate conditions for the period of 2050 (2040~2060), which were estimated with HadGEM2-AO. RF (Random Forest), GBM (Generalized Boosted Model) and TSS weighted ensemble model showed higher prediction accuracies (AUC > 0.95, TSS > 0.80) than other SDMs. Based on the projections of TSS weighted ensemble, potential habitats under current climate conditions showed a discrepancy with actual habitats, especially in the northern distribution limit. The observed northern boundary of Hedera rhombea is Ulsan in the eastern Korean Peninsula, but the projected limit was eastern coast of Gangwon province. Geomorphological conditions and the dispersal limitations mediated by birds, the lack of bird habitats at eastern coast of Gangwon Province, account for such discrepancy. In general, potential habitats of Hedera rhombea expanded under future climate conditions, but the extent of expansions depend on RCP scenarios. Potential Habitat of Hedera rhombea expanded into Jeolla-inland area under RCP 4.5, and into Chungnam and Wonsan under RCP 8.5. Our results would be fundamental information for understanding the potential effects of climate change on the distribution of Hedera rhombea.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.203-203
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• 2016

The linkage between climate change and water security, i.e., the response of water resource to the future climate change, have been of great concern to both scientific community and policy makers. In this study, the impact of future climate on water resources in Yellow River Basin in North of China has been investigated using the Coupled Land surface and Hydrology Model System (CLHMS) and IPCC AR5 projected future climate change in the basin. Firstly, the performances of 14 IPCC AR5 models in reproducing the observed precipitation and temperature in China, especially in North of China, have been evaluated, and it's suggested most climate models do show systematic bias compared with the observation, however, CNRM-CM5、HadCM5 and IPSL-CM5 model are generally the best models among those 14 models. Taking the daily projection results from the CNRM-CM5, along with the bias-correction technique, the response of water resources in Yellow river basin to the future climate change in different emission scenarios have been investigated. All the simulation results indicate a reduction in water resources. The current situation of water shortage since 1980s will keep continue, the water resources reduction varies between 28 and 23% for RCP 2.6 and 4.5 scenarios. RCP 8.5 scenario simulation shows a decrease of water resources in the early and mid 21th century, but after 2080, with the increase of rainfall, the extreme flood events tends to increase.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.965-972
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• 2017

Assessment of vulnerability of water use to climate change include a variety of climate change scenarios. However, in most future vulnerability studies, only the climate change scenarios are used and not the future scenarios of social and economic indicators. Therefore, in this study, we applied the Representative Concentration Pathway (RCP) climate change scenario and Shared Socioeconomic reference Pathway (SSP) developed by IPCC to reflect the future. We selected indicators for estimating the vulnerability of water use, and indices were integrated with a multi-criteria decision making approach - Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The indicator data utilized national statistics and reports, social and economic scenarios, and simulated results from the Soil and Water Assessment Tool (SWAT) model which reflects climate change scenario. Finally, we derived the rankings of water use vulnerability for the short-term future (2020) and mid-term future (2050) within the Han River watershed. Generally, considering climate change alone and considering climate change plus social and economic changes showed a similar spatial distribution. In the future scenarios, the watershed rankings were similar, but showed differences with SSP scenario in some watersheds. Therefore, considering social and economic changes is expected to contribute to more effective responses to climate change.

• Korean Journal of Environmental Biology
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• v.40 no.4
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• pp.567-578
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• 2022

Various social and environmental problems have recently emerged due to global climate change. In South Korea, coniferous forests in the highlands are decreasing due to climate change whereas the distribution of subtropical species is gradually increasing. This study aims to respond to changes in the distribution of forest species in South Korea due to climate change. This study predicts changes in future suitable areas for Pinus koraiensis, Cryptomeria japonica, and Chamaecyparis obtusa cultivated as timber species based on climate, topography, and environment. Appearance coordinates were collected only for natural forests in consideration of climate suitability in the National Forest Inventory. Future climate data used the SSP scenario by KMA. Species distribution models were ensembled to predict future suitable habitat areas for the base year(2000-2019), near future(2041-2060), and distant future(2081-2100). In the baseline period, the highly suitable habitat for Pinus koraiensis accounted for approximately 13.87% of the country. However, in the distant future(2081-2100), it decreased to approximately 0.11% under SSP5-8.5. For Cryptomeria japonica, the habitat for the base year was approximately 7.08%. It increased to approximately 18.21% under SSP5-8.5 in the distant future. In the case of Chamaecyparis obtusa, the habitat for the base year was approximately 19.32%. It increased to approximately 90.93% under SSP5-8.5 in the distant future. Pinus koraiensis, which had been planted nationwide, gradually moved north due to climate change with suitable habitats in South Korea decreased significantly. After the near future, Pinus koraiensis was not suitable for the afforestation as timber species in South Korea. Chamaecyparis obtusa can be replaced in most areas. In the case of Cryptomeria japonica, it was assessed that it could replace part of the south and central region.

• Journal of Climate Change Research
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• v.7 no.4
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• pp.451-463
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• 2016

We explore the impact of Chinese future air pollutant emissions on ozone air quality in Northeast Asia (NEA) and health in South-Korea using an assessment framework including ICAMS (The Integrated Climate and Air Quality Modeling System) and BenMAP (The Environmental Benefits Mapping and Analysis Program). The emissions data sets from the climate change scenarios, the Representative Concentration Pathways (RCPs) (emission scenarios, EMSO), are used to simulate ozone air quality in NEA in the current (1996~2005, 2000s), the near future (2016~2025, 2020s) and the distant future (2046~2055, 2050s). Furthermore, the simulated ozone changes in the 2050s are used to analyze ozone-related premature mortality and economic cost in South-Korea. While different EMSOs are applied to the China region, fixed EMSO are used for other country regions to isolate the impacts of the Chinese emissions. Predicted ozone changes in NEA are distinctively affected by large changes in NOx emission over most of China region. Comparing the 2020s with the 2000s situation, the largest increase in mean ozone concentrations in NEA is simulated under RCP 8.5 and similarly small increases are under other RCPs. In the 2050s in NEA, the largest increase in mean ozone concentrations is simulated under RCP 6.0 and leads to the occurrence of the highest premature mortalities and economic costs in South-Korea. Whereas, the largest decrease is simulated under RCP 4.5 leads to the highest avoided premature mortality numbers and economic costs. Our results suggest that continuous reduction of NOx emissions across the China region under an assertive climate change mitigation scenario like RCP 4.5 leads to improved future ozone air quality and health benefits in the NEA countries including South-Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.5
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• pp.25-34
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• 2009

The objective of this study is to evaluate the future potential climate and vegetation canopy change impact on a dam watershed hydrology. A $6,661.5\;km^2$ dam watershed, the part of Han-river basin which has the watershed outlet at Chungju dam was selected. The SWAT model was calibrated and verified using 9 year and another 7 year daily dam inflow data. The Nash-Sutcliffe model efficiency ranged from 0.43 to 0.91. The Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model3 (CGCM3) data based on Intergovernmental Panel on Climate Change (IPCC) SRES (Special Report Emission Scenarios) B1 scenario was adopted for future climate condition and the data were downscaled by artificial neural network method. The future vegetation canopy condition was predicted by using nonlinear regression between monthly LAI (Leaf Area Index) of each land cover from MODIS satellite image and monthly mean temperature was accomplished. The future watershed mean temperatures of 2100 increased by $2.0^{\circ}C$, and the precipitation increased by 20.4 % based on 2001 data. The vegetation canopy prediction results showed that the 2100 year LAI of deciduous, evergreen and mixed on April increased 57.1 %, 15.5 %, and 62.5% respectively. The 2100 evapotranspiration, dam inflow, soil moisture content and groundwater recharge increased 10.2 %, 38.1 %, 16.6 %, and 118.9 % respectively. The consideration of future vegetation canopy affected up to 3.0%, 1.3%, 4.2%, and 3.6% respectively for each component.