• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.317-331
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• 2011

The CERES-Barley crop simulation model of DSSAT package was used to assess the impacts of climate change on potential yield of winter covered barley in Korea. 56 sites over the southern part of Korean peninsula were selected to compare the climate change impacts in various climatic conditions. The climatological normals (1971~2000) and the three future climatological normals (2011~2040, 2041~2070, and 2071~2100), based on A1B climate change scenarios of Korea, were used in this study, and the three future climatological normals were simulated under three environmental conditions, where only temperature change, only carbon dioxide change, and both of temperature and carbon dioxide change with future A1B climate change scenarios, respectively. Results: The CERES-Barley model was suitable for predicting climate change impacts on the potential yield of winter covered barley, because of the agreement between observed and simulated outcomes (e.g., the coefficient of determination of grain yield equals 0.84). (1) The only increased temperature effect with the climate change scenarios was mostly negative to the potential yield of winter covered barley and its magnitude ranges from -21% to +1% for the three future normals. (2) The effect of the only elevated carbon dioxide on the potential yield of winter covered barley was positive and its magnitude ranged from 12% to 43% for the three future normals. (3) For increased temperature and elevated carbon dioxide change cases, potential yields increased by 13%, 21%, 19% increase for the 2011~2040, 2041~2070, 2071~2100 normals, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.287-298
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• 2020

It is predicted that future climate warming will occur, and the subtropical climate zone currently confined to the south coast of Korea will gradually rise north. The shift of climate zone implies a change in area for cultivating crops. This study aimed to evaluate the current and future status of climate zones based on the high-resolution climate data of South Korea to prepare adaptation measures for cultivating crops under changing agricultural climate conditions. First, the climatic maps of South and North Korea were produced by using the high-resolution monthly maximum and minimum daily temperature and monthly cumulative precipitation produced during the past 30 years (1981-2010) covering South and North Korea. Then the climate zones of the Korean Peninsula were classified based on the Köppen climate classification. Second, the changes in climate zones were predicted by using the corrected monthly climate data of the Korean Peninsula (grid resolution 30-270m) based on the RCP8.5 scenario of the Korea Meteorological Administration. Köppen climate classification was applied based on the RCP8.5 scenario, the temperature and precipitation of the Korean Peninsula would continue to increase and the climate would become simpler. It was predicted that the temperate climate, appearing in the southern region of Korea, would be gradually expanded and the most of the Korean Peninsula, excluding some areas of Hamgkyeong and Pyeongan provinces in North Korea, would be classified as a temperate climate zone between 2071 and 2100. The subarctic climate would retreat to the north and the Korean Peninsula would become warmer and wetter in general.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.4
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• pp.192-203
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• 2011

The CERES-Barley crop simulation model was used to assess the impacts of climate change on the potential yield of winter naked barley in Korea. Fifty six sites over the southern part of the Korean Peninsula were selected to compare the climate change impacts in various climatic conditions. Based on the A1B climate change scenarios of Korea, the present climatological normal (1971-2000) and the three future ones (2011-2040, 2041-2070, and 2071-2100) were considered in this study. The three future normals were divided by three environmental conditions with changes in: (1) temperature only, (2) carbon dioxide concentration only, and (3) both temperature and carbon dioxide concentration. The agreement between the observed and simulated outcomes was reasonable with the coefficient of determination of grain yield to be 0.78. We concluded that the CERES-Barley model was suitable for predicting climate change impacts on the potential yield of winter naked barley. The effect of the increased temperature only with the climate change scenario was negative to the potential yield of winter naked barley, which ranges from -34 to -9% for the three future normals. However, the effect of the elevated carbon dioxide concentration only on the potential yield of winter naked barley was positive, ranging from 6 to 31% for the three future normals. For the elevated conditions of both temperature and carbon dioxide concentration, the potential yields increased by 8, 15, and 13% for the 2011-2040, 2041-2070, and 2071-2100 normals, respectively.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.352-363
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• 2019

Background: Invasive plant species are considered a major threat to biodiversity, ecosystem functioning, and human wellbeing worldwide. Climatically suitable ranges for invasive plant species are expected to expand due to future climate change. The identification of current invasions and potential range expansion of invasive plant species is required to plan for the management of these species. Here, we predicted climatically suitable habitats for 11 invasive plant species and calculated the potential species richness and their range expansions in different provinces of the Republic of Korea (ROK) under current and future climate change scenarios (RCP 4.5 and RCP 8.5) using the maximum entropy (MaxEnt) modeling approach. Results: Based on the model predictions, areas of climatically suitable habitats for 90.9% of the invasive plant species are expected to retain current ecological niches and expand to include additional climatically suitable areas under future climate change scenarios. Species richness is predicted to be relatively high in the provinces of the western and southern regions (e.g., Jeollanam, Jeollabuk, and Chungcheongnam) under current climatic conditions. However, under future climates, richness in the provinces of the northern, eastern, and southeastern regions (e.g., Seoul, Incheon, Gyeonggi, Gyeongsangnam, Degue, Busan, and Ulsan) is estimated to increase up to 292%, 390.75%, and 468.06% by 2030, 2050, and 2080, respectively, compared with the current richness. Conclusions: Our study revealed that the rates of introduction and dispersion of invasive plant species from the western and southern coasts are relatively high and are expanding across the ROK through different modes of dispersion. The negative impacts on biodiversity, ecosystem dynamics, and economy caused by invasive plant species will be high if preventive and eradication measures are not employed immediately. Thus, this study will be helpful to policymakers for the management of invasive plant species and the conservation of biodiversity.

• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.71-82
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• 2014

The objective of this study is to project and analyze drought conditions using future climate and hydrology information over South Korea. This study used three Global Climate Models (GCMs) and three hydrological models considering the uncertainty of future scenario. Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI) and Standardized Soil moisture Index (SSI) classified as meteorological, hydrological and agricultural droughts were estimated from the precipitation, runoff and soil moisture. The Mann-Kendall test showed high increase in future drought trend during spring and winter seasons, and the drought frequency of SRI and SSI is expected higher than that of SPI. These results show the high impact of climate change on hydrological and agriculture drought compared to meteorological drought.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.104-109
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• 2021

In the aftermath of the global pandemic that started in 2019, there have been many changes in the import/export and supply/demand process of agricultural products in each country. Amid these changes, the necessity and importance of each country's food self-sufficiency rate is increasing. There are several conditions that must accompany efficient agricultural activities, but among them, temperature is by far one of the most important conditions. For this reason, the need for high-accuracy climate data for stable agricultural activities is increasing, and various studies on climate prediction are being conducted in Korea, but data that can visually confirm climate prediction data for farmers are insufficient. Therefore, in this paper, we propose an artificial intelligence-based temperature prediction algorithm that can predict future temperature information by collecting and analyzing temperature data of farms in Gyeonggi-do in Korea for the last 10 years. If this algorithm is used, it is expected that it can be used as an auxiliary data for agricultural activities.

• Journal of Environmental Impact Assessment
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• v.15 no.4
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• pp.249-258
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• 2006

Impacts of global warming have been identified in many areas including natural ecosystem. A good number of studies based on climate models forecasting future climate have been conducted in many countries worldwide. Due to its global coverage, GCM, which is a most frequently used climate model, has limits to apply to Korea with such a narrower and complicated terrain. Therefore, it is necessary to perform a study impact assessment of climate changes with a climate model fully reflecting characteristics of Korean climate. In this respect, this study was designed to compare and analyze the GCM and RCM in order to determine a suitable climate model for Korea. In this study, spatial scope was Korea for 10 years from 1981 to 1990. As a research method, current climate was estimated on the basis of the data obtained from observation at the GHCN. Future climate was forecast using 4 GCMs furnished by the IPCC among SRES A2 Scenario as well as the RCM received from the NIES of Japan. Pearson correlation analysis was conducted for the purpose of comparing data obtained from observation with GCM and RCM. As a result of this study, average annual temperature of Korea between 1981 and 1990 was found to be around $12.03^{\circ}C$, with average daily rainfall being 2.72mm. Under the GCM, average annual temperature was between 10.22 and $16.86^{\circ}C$, with average daily rainfall between 2.13 and 3.35mm. Average annual temperature in the RCM was identified $12.56^{\circ}C$, with average daily rainfall of 5.01mm. In the comparison of the data obtained from observation with GCM and RCM, RCMs of both temperature and rainfall were found to well reflect characteristics of Korea's climate. This study is important mainly in that as a preliminary study to examine impact of climate changes such as global warming it chose appropriate climate model for our country. These results of the study showed that future climate produced under similar conditions with actual ones may be applied for various areas in many ways.

• Journal of Korea Water Resources Association
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• v.41 no.4
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• pp.379-394
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• 2008

Recently, extreme precipitation events beyond design capacity of hydraulic system have been occurred and this is the causes of failure of hydraulic structure for flood prevention and of severe flood damage. Therefore it is very important to understand temporal and spatial characteristics of extreme precipitation events as well as expected changes in extreme precipitation events and distributional characteristics during design period under future climate change. In this paper, climate change scenarios were used to assess the impacts of future climate change on extreme precipitation. Furthermore, analysis of future extreme precipitation characteristics and I-D-F analysis were carried out. This study used SRES B2 greenhouse gas scenario and YONU CGCM to simulate climatic conditions from 2031 to 2050 and statistical downscaling method was applied to establish weather data from each of observation sites operated by the Korean Meteorological Administration. Then quantile mapping of bias correction methods was carried out by comparing the simulated data with observations for bias correction. In addition Modified Bartlett Lewis Rectangular Pulse(MBLRP) model (Onof and Wheater, 1993; Onof 2000) and adjust method were applied to transform daily precipitation time series data into hourly time series data. Finally, rainfall intensity, duration, and frequency were calculated to draw I-D-F curve. Although there are 66 observation sites in Korea, we consider here the results from only Seoul, Daegu, Jeonju, and Gwangju sites in this paper. From the results we found that the rainfall intensity will be increased and the bigger intensity will be occurred for longer rainfall duration when we compare the climate conditions of 2030s with present conditions.

• Journal of Forest and Environmental Science
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• v.39 no.2
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• pp.105-117
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• 2023

Climate change and invasive alien plant species (IAPs) are having a significant impact on mountain ecosystems. The combination of climate change and socio-economic development is exacerbating the invasion of IAPs, which are a major threat to biodiversity loss and ecosystem functioning. Species distribution modelling has become an important tool in predicting the invasion or suitability probability under climate change based on occurrence data and environmental variables. MaxEnt modelling was applied to predict the current suitable distribution of most noxious weed A. adenophora (Spreng) R. King and H. Robinson and analysed the changes in distribution with the use of current (year 2000) environmental variables and future (year 2050) climatic scenarios consisting of 3 representative concentration pathways (RCP 2.6, RCP 4.5 and RCP 8.5) in Bhutan. Species occurrence data was collected from the region of interest along the road side using GPS handset. The model performance of both current and future climatic scenario was moderate in performance with mean temperature of wettest quarter being the most important variable that contributed in model fit. The study shows that current climatic condition favours the A. adenophora for its invasion and RCP 2.6 climatic scenario would promote aggression of invasion as compared to RCP 4.5 and RCP 8.5 climatic scenarios. This can lead to characterization of the species as preferring moderate change in climatic conditions to be invasive, while extreme conditions can inhibit its invasiveness. This study can serve as reference point for the conservation and management strategies in control of this species and further research.