• Journal of Climate Change Research
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• v.5 no.1
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• pp.37-46
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• 2014

The purpose of this study is to analyze the determinants affecting Korean farmers' perception to climate change using multinomial logit and ordered logit model. The major findings of this study are summarized as follows. First, the results indicate that 85.7 percent of farmers have perceived climate change and 85.8 percent of farmers have anticipated that the impact of climate change on agriculture within 10 years. Second, the results show that farming experience, successor to farming, use of computer have a significant impact on expectation to climate change. Finally, the findings also indicate that sex, age, and education have a significant impact on expectation of the mean temperature to climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.108-125
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• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.907-917
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• 2008

This study investigates differences in hydrological responses to the climatic scenarios resulting from the use of different three hydrological models, PRMS, SLURP, and SWAT. First, the capability of the three models in simulating the present climate water balance components is evaluated at Andong-dam watershed. And then, the results of the models in simulating the impact using hypothetical climate change scenarios are analyzed and compared. The results show that three models have similar capabilities in simulating observed data. However, greater differences in the model results occur when the models are used to simulate the hydrological impact under hypothetical climate change. According as temperature change grows, the differences between model results is increasing because of differences of the evapotranspiration estimation methods. The results suggest that technique that consider the uncertainty by using different hydrological models will be needed when climate change impact assessment on water resources.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.71-79
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• 2017

Climate change phenomenon is posing a serious threat to sustainable corn production in Ghana. This study investigated the impacts of climate change on the rain-fed corn yield in the Dangme East district, Ghana by using Aquacrop model with a daily weather data set of 22-year from 1992 to 2013. Analysis of the weather data showed that the area is facing a warming trend as the numbers of years hotter and drier than the normal seemed to be increasing. Aquacrop model was assessed using the limited observed data to verify model's sufficiency, and showed credible results of $R^2$ and Nash-Sutcliffe efficiency (NSE). In order to simulate the corn yield response to climate variability four climate change scenarios were designed by varying long-term average temperature in the range of ${\pm}1^{\circ}C{\sim}{\pm}3^{\circ}C$ and average annual rainfall to ${\pm}5%{\sim}{\pm}30%$, respectively. Generally, the corn yield was negatively correlated to temperature rise and rainfall reduction. Rainfall variations showed more prominent impacts on the corn yield than that of temperature variations. The reduction in average rainfall would instantly limit the crop growth rate and the corn yield irrespective of the temperature variations.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.145-145
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• 2018

Small islands rely heavily on groundwater resources in addition to rainwater as the source of freshwater since surface water bodies are often absent. The groundwater resources are vulnerable to sea level rise, coastal flooding, saltwater intrusion, irregular pattern of precipitation resulting in long droughts and flash floods. Increase in population increases the demand for the limited groundwater resources, thus aggravating the problem. In this study, the effects of climate change on Tongatapu Island, Kingdom of Tonga, a small island in Pacific Ocean, are investigated using a sharp interface transient groundwater flow model. Twenty nine downscaled General Circulation Model(GCM) predictions are input to a water balance model to estimate the groundwater recharge. The temporal variation in recharge is predicted over the period of 2010 to 2099. A set of GCM models are selected to represent the ensemble of 29 models based on cumulative recharge at the end of the century. This set of GCM model predictions are then used to simulate a total of six climate scenarios, three each (2010-2039, 2040-2069, and 2070-2099) under RCP 4.5 and RCP 8.5. The impacts of predicted climate change on groundwater resources is evaluated in terms of freshwater volume changes and saltwater ratios in pumping wells compared to present conditions. Though the cumulative recharge at the end of the century indicates a wetter climate compared to the present conditions the large variability in rainfall pattern results in frequent periods of groundwater drought leading to saltwater intrusion in pumping wells. Thus for sustaining the limited groundwater resources in small islands, implementation of timely assessment and management practices are of utmost importance.

• Journal of Korea Water Resources Association
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• v.42 no.12
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• pp.1091-1102
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• 2009

This study developed an integrated approach to climate change and urbanization impact assessment by linking models of SDSM (statistical downscaling model), HSPF (hydrological simulation program?Fortran) and ICM (impervious cover model). A case study of the Anyangcheon watershed illustrated how the proposed framework can be used to analyze the impacts of climate change and urbanization in terms of flood control, water security and water quality. The evaluation criteria were the variations of flow and pollutant concentration duration curves. In this study, nine scenarios including three climate (present condition, A1B and A2) and three urbanization scenarios were analyzed using HSPF model. As a result, climate change is a large influence on the flowrate and the urbanization affects the pollutant concentration. Therefore, the impacts of both climate change and urbanization must be included into the watershed management and water resources planning for sustainable development.

• Journal of Environmental Impact Assessment
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• v.23 no.2
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• pp.101-111
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• 2014

The research was carried out in order to find climate factors which determine the distribution of Neolitsea sericea, and the potential habitats (PHs) under the current climate and three climate change scenario by using species distribution models (SDMs). Four climate factors; the minimum temperature of the coldest month (TMC), the warmth index (WI), summer precipitation (PRS), and winter precipition (PRW) : were used as independent variables for the model. Three general circulation models under A1B emission scenarios were used as future climate scenarios for the 2050s (2040~2069) and 2080s (2070~2099). Highly accurate SDMs were obtained for N. sericea. The model of distribution for N. sericea constructed by SDMs showed that minimum temperature of the coldest month (TMC) is a major climate factor in determining the distribution of N. sericea. The area above the $-4.4^{\circ}C$ of TMC revealed high occurrence probability of the N. sericea. Future PHs for N. sericea were projected to increase respectively by 4 times, 6.4 times of current PHs under 2050s and 2080s. It is expected that the potential of N. sericea habitats is expanded gradually. N. sericea is applicable as indicator species for monitoring in the Korean Peninsula. N. sericea is necessary to be monitored of potential habitats.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.314-314
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• 2023

Extreme climate events can have a large impact on human life by hampering social, environmental, and economic development. Global circulation models (GCMs) are the widely used numerical models to understand the anticipated future climate change. However, different GCMs can project different future climates due to structural differences, varying initial boundary conditions and assumptions about the physical phenomena. The multi-model ensemble (MME) approach can improve the uncertainties associated with the different GCM outcomes. In this study, a comprehensive rating metric was used to select the best-performing GCMs out of 11 CMIP5 and 13 CMIP6 GCMs, according to their skills in terms of four temporal and five spatial performance indices, in replicating the 21 extreme climate indices during the baseline (1975-2017) in South Korea. The MME data were derived by averaging the simulations from all selected GCMs and three top-ranked GCMs. The random forest (RF) algorithm was also used to derive the MME data from the three top-ranked GCMs. The RF-derived MME data of the three top-ranked GCMs showed the highest performance in simulating the baseline extreme climate which was subsequently used to project the future extreme climate indices under both the representative concentration pathway (RCP) and the socioeconomic concentration pathway scenarios (SSP). The extreme cold and warming indices had declining and increasing trends, respectively, and most extreme precipitation indices had increasing trends over the period 2031-2100. Compared to all scenarios, RCP8.5 showed drastic changes in future extreme climate indices. The coasts in the east, south and west had stronger warming than the rest of the country, while mountain areas in the north experienced more extreme cold. While extreme cold climatology gradually declined from north to south, extreme warming climatology continuously grew from coastal to inland and northern mountainous regions. The results showed that the socially, environmentally and agriculturally important regions of South Korea were at increased risk of facing the detrimental impacts of extreme climatology.

• Atmosphere
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• v.34 no.1
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• pp.1-21
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• 2024

Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.435-443
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• 2018

Climate technology applied to address climate change requires a comprehensive review such as environmental and social acceptability in addition to economic feasibility. Not only mitigation and adaptation technologies, but also integration of climate technologies into a business model with other relevant technologies including ICT, finance, and policy instruments could enhance technical, economic, and environmental performances to respond to climate changes. However, many climate projects (and business models) are currently not designed to consider adequately complex climate?related issues. In addition, there is a lack of research on assessment systems that can comprehensively evaluate business feasibility of such models. In this study, we developed a system consisting of nine major indicators in four fields to assess climate technology-based business models. Each indicator was weighed using the analytic hierarchy process (AHP) for systematic assessment of business models. The process can be utilized as a tool to guide improvement of climate technology business models.