• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.108-112
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• 2014

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.124-137
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• 2012

Climate analysis is important in urban planning for human comfort. Synoptic weather conditions can only resolve the 30% of local variance of wind conditions whereas 70% of the variance arise from local terrain, buildings, and other small scale thermal conditions. Climate Analysis Seoul (CAS) was developed to resolve such micro-scale climate. The Local-scale air temperature Deviation (LD) analysis map from CAS showed the co-existence of built-up and suburban areas in the study region (CR, Cold-air analysis Region) despite its small extent. Temperature, humidity, wind speed, and wind direction were monitored in CR. Hourly observed cooling rate agreed well with LD. Cold air production, transportation, and stagnation was visualized by the observed Vertical Temperature Gradient (VTG) along the small stream in CR. VTG observed at the upper-most stream can be divided into two components: radiative cooling and cold air inflow from outside. Radiative cooling exists regardless of the wind speed whereas cold air inflow occurs only with calm wind. From the regression analyses based on the wind speed, the inflow portion was determined as 84% of radiative cooling. Climate analysis in the future will be able to characterize the changes in cold air by urban development plan to support the human comfort.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.146-157
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• 2019

One of the most distinctive features of the South Korean rural environment is that the variation of weather or climate is large even within a small area due to complex terrains. The Geospatial Schemes based on Topo-Climatology (GSTP) was developed to simulate such variations effectively. In the present study, we reviewed the progress of the geospatial schemes for production of farm-scale agricultural weather data. Efforts have been made to improve the GSTP since 2000s. The schemes were used to provide climate information based on the current normal year and future climate scenarios at a landscape scale. The digital climate maps for the normal year include the maps of the monthly minimum temperature, maximum temperature, precipitation, and solar radiation in the past 30 years at 30 m or 270 m spatial resolution. Based on these digital climate maps, future climate change scenario maps were also produced at the high spatial resolution. These maps have been used for climate change impact assessment at the field scale by reprocessing them and transforming them into various forms. In the 2010s, the GSTP model was used to produce information for farm-specific weather conditions and weather forecast data on a landscape scale. The microclimate models of which the GSTP model consists have been improved to provide detailed weather condition data based on daily weather observation data in recent development. Using such daily data, the Early warning service for agrometeorological hazard has been developed to provide weather forecasts in real-time by processing a digital forecast and mid-term weather forecast data (KMA) at 30 m spatial resolution. Currently, daily minimum temperature, maximum temperature, precipitation, solar radiation quantity, and the duration of sunshine are forecasted as detailed weather conditions and forecast information. Moreover, based on farm-specific past-current-future weather information, growth information for various crops and agrometeorological disaster forecasts have been produced.

• Atmosphere
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• v.29 no.2
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• pp.165-181
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• 2019

In this study, the regional climate model, RegCM4.0 (25 km), with the HadGEM2-AO data as boundary conditions, was used to simulate the mean climate changes in the mid and late 21st century for CORDEX Phase 2 East Asian region. 122 years (1979~2100) of simulation were performed, and RCP 4.5 and RCP 8.5 were used for the simulation of future climate. In the mid-21st century, the temperature is expected to increase by about 0.5 to $3.0^{\circ}C$ in all regions of East Asia, regardless of season and scenario. The increase in temperature is greater in summer and winter, especially in the northern part of simulation domain. Interannual variability (IAV) is expected to decrease by 25% in summer for RCP 8.5, while it is expected to increase by more than 30% in autumn for both scenarios. Regardless of the scenario, the precipitation in South Korea is expected to increase in late June but decrease in mid-July, with an increase in precipitation greater than $100mm\;day^{-1}$. In RCP 4.5 of the late 21st century, relatively uniform temperature increase ($1.0{\sim}2.5^{\circ}C$) is expected throughout the continent, while RCP 8.5 shows a very diverse increase ($3.0{\sim}6.0^{\circ}C$) depending on season and geographical location. In addition, the IAV of temperature is expected to decrease by more than 35% in both scenarios in the summer. In most of the Northwest Pacific region, precipitation is expected to decrease in all seasons except for the summer, but in South Korea, it is projected to increase by about 10% in all seasons except autumn.

• Journal of Environmental Impact Assessment
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• v.27 no.5
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• pp.489-508
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• 2018

As climate changes, it is necessary to predict changes in the habitat environment in order to establish more aggressive adaptation strategies. The bioclimatic classification which clusters of areas with similar habitats can provide a useful ecosystem management framework. Therefore, in this study, biological habitat environment of Northeast Asia was identified through the establishment of the bioclimatic zones, and the impac of climate change on the biological habitat was analyzed. An ISODATA clustering was used to classify Northeast Asia (NEA)into 15 bioclimatic zones, and climate change impacts were predicted by projecting the future spatial distribution of bioclimatic zones based upon an ensemble of 17 GCMs across RCP4.5 and 8.5 scenarios for 2050s, and 2070s. Results demonstrated that significant changes in bioclimatic conditions can be expected throughout the NEA by 2050s and 2070s. The overall zones moved upward, and some zones were predicted to be greatly expanded or shrunk where we suggested as regions requiring intensive management. This analysis provides the basis for understanding potential impacts of climate change on biodiversity and ecosystem. Also, this could be used more effectively to support decision making on climate change adaptation.

• Journal of Environmental Science International
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• v.26 no.5
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• pp.601-608
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• 2017

The effects of elevated atmospheric $CO_2$ on growth and photosynthesis of soybean (Glycine max Merr.) were investigated to predict its productivity under elevated $CO_2$ levels in the future. Soybean grown for 6 weeks showed significant increase in vegetative growth, based on plant height, leaf characteristics (area, length, and width), and the SPAD-502 chlorophyll meter value (SPAD value) under elevated $CO_2$ conditions ($800{\mu}mol/mol$) compared to ambient $CO_2$ conditions ($400{\mu}mol/mol$). Under elevated $CO_2$ conditions, the photosynthetic rate (A) increased although photosystem II (PS II) photochemical activity ($F_v/F_m$) decreased. The maximum photosynthetic rate ($A_{max}$) was higher under elevated $CO_2$ conditions than under ambient $CO_2$ conditions, whereas the maximum electron transport rate ($J_{max}$) was lower under elevated $CO_2$ conditions compared to ambient $CO_2$ conditions. The optimal temperature for photosynthesis shifted significantly by approximately $3^{\circ}C$ under the elevated $CO_2$ conditions. With the increase in temperature, the photosynthetic rate increased below the optimal temperature (approximately $30^{\circ}C$) and decreased above the optimal temperature, whereas the dark respiration rate ($R_d$) increased continuously regardless of the optimal temperature. The difference in photosynthetic rate between ambient and elevated $CO_2$ conditions was greatest near the optimal temperature. These results indicate that future increases in $CO_2$ will increase productivity by increasing the photosynthetic rate, although it may cause damage to the PS II reaction center as suggested by decreases in $F_v/F_m$, in soybean.

• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.163-173
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• 2022

Climate change is a key factor that greatly influences changes in the biological seasons and geographical distribution of species. In the ecological field, the BioClimatic predictor (BioClim), which is most related to the physiological characteristics of organisms, is used for vulnerability assessment. However, BioClim values are not provided other than the future period climate average values for each GCM for the Shared Socio-economic Pathways (SSPs) scenario. In this study, BioClim data suitable for domestic conditions was produced using 1 km resolution SSPs scenario detailed data produced by Rural Development Administration, and based on the data, a species distribution model was applied to mainly grow in southern, Gyeongsangbuk-do, Gangwon-do and humid regions. Appropriate habitat distributions were predicted every 30 years for the base years (1981 - 2010) and future years (2011 - 2100) of the Acer pictum subsp. mono. Acer pictum subsp. mono appearance data were collected from a total of 819 points through the national natural environment survey data. In order to improve the performance of the MaxEnt model, the parameters of the model (LQH-1.5) were optimized, and 7 detailed biolicm indices and 5 topographical indices were applied to the MaxEnt model. Drainage, Annual Precipitation (Bio12), and Slope significantly contributed to the distribution of Acer pictum subsp. mono in Korea. As a result of reflecting the growth characteristics that favor moist and fertile soil, the influence of climatic factors was not significant. Accordingly, in the base year, the suitable habitat for a high level of Acer pictum subsp. mono is 3.41% of the area of Korea, and in the near future (2011 - 2040) and far future (2071 - 2100), SSP1-2.6 accounts for 0.01% and 0.02%, gradually decreasing. However, in SSP5-8.5, it was 0.01% and 0.72%, respectively, showing a tendency to decrease in the near future compared to the base year, but to gradually increase toward the far future. This study confirms the future distribution of vegetation that is more easily adapted to climate change, and has significance as a basic study that can be used for future forest restoration of climate change-adapted species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.348-357
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• 2015

The main purpose of this study is to understand the potential geographic distribution of P. koraiensis, which is known to be one of major economic tree species, based on the RCP (Representative Concentration Pathway) 8.5 scenarios and current geographic distribution from National Forest Inventory(NFI) data using ecological niche modeling. P. koraiensis abundance data extracted from NFI were utilized to estimate current geographic distribution. Also, GARP (Genetic Algorithm for Rule-set Production) model, one of the ecological niche models, was applied to estimate potential geographic distribution and to project future changes. Environmental explanatory variables showing Area Under Curve (AUC) value bigger than 0.6 were selected and constructed into the final model by running the model for each of the 27 variables. The results of the model validation which was performed based on confusion matrix statistics, showed quite high suitability. Currently P. koraiensis is distributed widely from 300m to 1,200m in altitude and from south to north as a result of national greening project in 1970s although major populations are found in elevated and northern area. The results of this study were successful in showing the current distribution of P. koraiensis and projecting their future changes. Future model for P. koraiensis suggest large areas predicted under current climate conditions may be contracted by 2090s showing dramatic habitat loss. Considering the increasing status of atmospheric $CO_2$ and air temperature in Korea, P. koraiensis seems to experience the significant decrease of potential distribution range in the future. The final model in this study may be used to identify climate change impacts on distribution of P. koraiensis in Korea, and a deeper understanding of its correlation may be helpful when planning afforestation strategies.

• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.33-50
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• 2009

The impact on hydrologic components considering future potential climate, land use change and vegetation cover information was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated (1999 - 2000) and validated (2001 - 2002) for the upstream watershed ($260.4\;km^2$) of Gyeongancheon water level gauging station with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.77 to 0.60 and 0.79 to 0.60, respectively. Two GCMs (MIROC3.2hires, ECHAM5-OM) future weather data of high (A2), middle (A1B) and low (B1) emission scenarios of the IPCC (Intergovernmental Panel on Climate Change) were adopted and the data was corrected by 20C3M (20th Century Climate Coupled Model) and downscaled by Change Factor (CF) method using 30 years (1977 - 2006, baseline period) weather data. Three periods data of 2010 - 2039 (2020s), 2040 - 2069 (2050s), 2070 - 2099 (2080s) were prepared. To reduce the uncertainty of land surface conditions, future land use and vegetation canopy prediction were tried by CA-Markov technique and NOAA NDVI-Temperature relationship respectively. MIROC3.2 hires and ECHAM5-OM showed increase tendency in annual streamflow up to 21.4 % for 2080 A1B and 8.9 % for 2050 A1B scenario respectively. The portion of future predicted ET about precipitation increased up to 3 % in MIROC3.2 hires and 16 % in ECHAM5-OM respectively. The future soil moisture content slightly increased compared to 2002 soil moisture.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.145-159
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• 2014

This study is to evaluate the future climate change impact on turbidity water and eutrophication for Chungju Lake by using CE-QUAL-W2 reservoir water quality model coupled with SWAT watershed model. The SWAT was calibrated and validated using 11 years (2000~2010) daily streamflow data at three locations and monthly stream water quality data at two locations. The CE-QUAL-W2 was calibrated and validated for 2 years (2008 and 2010) water temperature, suspended solid, total nitrogen, total phosphorus, and Chl-a. For the future assessment, the SWAT results were used as boundary conditions for CE-QUAL-W2 model run. To evaluate the future water quality variation in reservoir, the climate data predicted by MM5 RCM(Regional Climate Model) of Special Report on Emissions Scenarios (SRES) A1B for three periods (2013~2040, 2041~2070 and 2071~2100) were downscaled by Artificial Neural Networks method to consider Typhoon effect. The RCM temperature and precipitation outputs and historical records were used to generate pollutants loading from the watershed. By the future temperature increase, the lake water temperature showed $0.5^{\circ}C$ increase in shallow depth while $-0.9^{\circ}C$ in deep depth. The future annual maximum sediment concentration into the lake from the watershed showed 17% increase in wet years. The future lake residence time above 10 mg/L suspended solids (SS) showed increases of 6 and 17 days in wet and dry years respectively comparing with normal year. The SS occupying rate of the lake also showed increases of 24% and 26% in both wet and dry year respectively. In summary, the future lake turbidity showed longer lasting with high concentration comparing with present behavior. Under the future lake environment by the watershed and within lake, the future maximum Chl-a concentration showed increases of 19 % in wet year and 3% in dry year respectively.