• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.161-161
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• 2023

Bias correction of values is a necessary step in downscaling coarse and systematically biased global climate models for use in local climate change impact studies. In addition to univariate bias correction methods, many multivariate methods which correct multiple variables jointly - each with their own mathematical designs - have been developed recently. While some literature have focused on the inter-comparison of these multivariate bias correction methods, none have focused extensively on the effect of diverse configurations (i.e., different combinations of input variables to be corrected) of climate variables, particularly high-dimensional ones, on the ability of the different methods to remove biases in uni- and multivariate statistics. This study evaluates the impact of three configurations (inter-variable, inter-spatial, and full dimensional dependence configurations) on four state-of-the-art multivariate bias correction methods in a national-scale domain over South Korea using a gridded approach. An inter-comparison framework evaluating the performance of the different combinations of configurations and bias correction methods in adjusting various climate variable statistics was created. Precipitation, maximum, and minimum temperatures were corrected across 306 high-resolution (0.2°) grid cells and were evaluated. Results show improvements in most methods in correcting various statistics when implementing high-dimensional configurations. However, some instabilities were observed, likely tied to the mathematical designs of the methods, informing that some multivariate bias correction methods are incompatible with high-dimensional configurations highlighting the potential for further improvements in the field, as well as the importance of proper selection of the correction method specific to the needs of the user.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.143-143
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• 2021

Climate change indicators, mainly frequent drought which has happened since the drought of 1994, 1995, and 2012 causing the devastating effect to the agricultural sector, and could be more disruptive given the context of climate change indicators by increasing the temperature and more variable and extreme precipitation. Changes in frequency, duration, and severity of droughts will have enormous impacts on agriculture production and water management. Since both the possibility of drought manifestation and substantial yield losses, we are propositioning an integrated method for evaluating past and future agriculture drought hazards that depend on models' simulations in the Hung-up watershed. to discuss the question of how climate change might influence the impact of extreme agriculture drought by assessing the potential changes in temporal trends of agriculture drought. we will calculate the temporal trends of future drought through drought indices Standardized Precipitation Evapotranspiration Index, Standardized Precipitation Index, and Palmer drought severity index by using observed data of (1991-2020) from Wonju meteorological station and projected climate change scenarios (2021-2100) of the Representative Concentration Pathways models (RCPs). expected results confirmed the frequency of extreme agricultural drought in the future projected to increase under all studied RCPs. at present 100 years drought is anticipated to happen since the result showing under RCP2.6 will occur every 24 years, RCP4.5 every 17 years, and RCPs8.5 every 7 years, and it would be double in the largest warming scenarios. On another side, the result shows unsupportable water management, could cause devastating consequences in both food production and water supply in extreme events. Because significant increases in the drought magnitude and severity like to be initiate at different time scales for each drought indicator. Based on the expected result that the evaluating the impacts of extreme agricultural droughts and recession could be used for the development of proactive drought risk management, policies for future water balance, prioritize sustainable strengthening and mitigation strategies.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.257-265
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• 2021

This study analyzed the influence of career-education on job satisfaction in the multicultural family service centers focused on the mediating effects of multicultural practice competence and organizational climate. A self-reported questionnaire survey was done on 180 multicultural practitionser in Seoul and Kyunggi Do. A total of 175 copies were used for final analysis with ones insincerely made were excluded. Collected date underwent Multivariate structural equation model analysis using AMOS 21.0 and frequency, descriptive, and corelation analysis were made using SPSS 20.0. Statistical program. The study results revealed that career-education directly affect organizational climate and multicultural practice competence, and organizational climate directly affected job satisfaction. Career education did not affect job satisfaction, but organizational climate had complete mediating effect in the structural equation model. Additionally multicultural practice competence didn't have an effect on job satisfaction and mediating effect in the structural equation model. Based on the results, intervention strategies to increase job satisfaction of multicultural practitioners and future study implications were suggested.

• Knowledge Management Research
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• v.10 no.3
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• pp.133-152
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• 2009

The purpose of this study is to enhance an understanding of employee's OCB(organizational citizenship behavior) in manufacturing innovations like a TPM(total productive maintenance). OCB is examined as a dependent variable in three dimensions; compliance behavior, altruistic behavior, and innovative behavior. The six determinants of OCB are considered based on previous literature : organizational culture, team climate, transactional leadership, transformational leadership, job satisfaction, and organizational commitment. And the moderating effect of TPM on the relationships between OCB and determinants are examined. Data is collected through questionnaires and interviews from 684 employees in the Korean medium-sized manufacturing company that are conducting TPM. The result indicates that the important influencing factors of OCB are team climate, organizational culture, and job satisfaction. And the moderating effect of TPM on the relationships between OCB and job satisfaction is founded.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2016.09a
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• pp.25-28
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• 2016

Recently, because of the weather forecasts through the low-resolution data has been limited, the demand of the high-resolution data is sharply increasing. Therefore, in this study, we restore the ultra-high resolution synthetic precipitation and temperature data for 2000-2014 due to small-scale topographic effect using the QPM (Quantitative Precipitation Model)/QTM (Quantitative Temperature Model). First, we reproduce the detailed precipitation and temperature data with 1km resolution using the distribution of Automatic Weather System (AWS) data and Automatic Synoptic Observation System (ASOS) data, which is about 10km resolution with irregular grid over South Korea. Also, we recover the precipitation and temperature data with 1km resolution using the MERRA reanalysis data over North Korea, because there are insufficient observation data. The precipitation and temperature from restored current climate reflect more detailed topographic effect than irregular AWS/ASOS data and MERRA reanalysis data over the Korean peninsula. Based on this analysis, more detailed prospect of regional climate is investigated.

• Journal of Soil and Groundwater Environment
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• v.21 no.1
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• pp.1-5
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• 2016

Capillary barriers, consisting of relatively fine-over-coarse materials, have been suggested as an alternative to traditional compacted soil covers. So, We were analysed to capillary barrier effect according to five cases of multi-layer cover systems. Water balance simulation was conducted with unsaturated flow model HELP to assess unsaturated hydraulic parameters such as hydraulic conductivity, climate affecting the performance of capillary barriers. Simulation were conducted for 5 Cases in the Ulsan area. Result of simulation indicated that three cases was formed unsaturated condition and capillary barrier effect.

• Spatial Information Research
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• v.19 no.6
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• pp.101-109
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• 2011

Climate change affects all components of the global environment system and, in turn, all components mutually interact and affect climate change through non-linear feedback processes. It is thus necessary to study the interaction between the climate and the environment, in order to comprehensively understand and predict climate and environment change. However, current relevant systems are limited to particular areas and do not sufficiently support the mutual linking of research studies. Therefore, this study develops prototype a GIS based integrated DB management system for supporting the climate and environment data storage, management and distribution. The integrated DB management system was developed using VB.NET languages and ArcObjects component. First, considering the demands of climate environment experts, the study areas are selected and the methods of data management and utilization were defined. In addition, a location-based GIS DB was created in order to aid in understanding climate change through visual representation. Finally, the integrated DB management system provides an efficient data management and distribution data and it creates synergistic effect on climate and environment study. It also contributes significantly to the comprehensive diagnosis and prediction of climate change and environment systems.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.305-312
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• 2018

The crops cultivated and consumed in Korea require specific climate conditions corresponding to their own growth characteristics. This study aims to analyze the relationship between climate change and agricultural productivity. According to growing concern about climate change internationally, many agricultural studies are developing technology to prevent damage from climate change. Before developing technology, we should figure out what kind of crop gets huge damage and how much caused by climate change. In the context of agricultural economics, we can define the reduction of agricultural product yield as a decline in productivity. As a result, this study analyzes the effects of climate change on agricultural productivity using Stochastic Frontier Analysis model. There are several kinds of climate change phenomena that increase the inefficiency of production. In other words, there are several kinds of crops that get negative influence by climate change. The result of this study can be used as basic guideline for producers to prepare for changing weather prior to developing disaster tolerance technology coping actively with special weather report.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.77-85
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• 2013

Objective: The aim of this study sets factors from previous research known to impact transfer effects as the independent variables, and examines their relationship with the dependent variables, near transfer effects and far transfer effects. Background: Transfer of Training refers to the application of what learners acquire knowledge and skills in training programs to their job. The ultimate goal of training is to apply what employees learn in training sessions to their workplace. In this sense, transfer of training has been a vital concern for training effectiveness. For training to be effective, trainees(learners) should be able to use what they learn in training program back on the job. Method: For this research purpose, this study conducted a survey on 170 nuclear operators in nuclear education and training center. Of these, survey result from the 167 recruits were sampled. Theoretical model of this study is based on Holton & Baldwin's(2003) distance model of transfer effects. This study sets transfer effects(near transfer, far transfer) as the main dependent variables. Meanwhile, the independent variables are trainee characteristics, training characteristics, organizational transfer climate. Each independent variable has subordinate variables. Subordinate variables of trainee characteristics are self-efficacy, motivation to learn, motivation to transfer and ability to transfer. Subordinate variables of training characteristics are training contents, ability of trainers, training design, training climate. The last Subordinate variables of organizational transfer climate are support of supervisors, support of peer, support of organization. Conclusion: As a analysis result, trainee characteristics appeared to be in effect only significant influence near far transfer of training, the effect of the far transfer of training, there is no significant. In addition, the training characteristics appeared to be having a significant influence on near and far transfer effects. Organizational transfer climate appeared to be having a significant influence on near and far transfer effects. Finally, near transfer effect appeared to be having a significant influence on far transfer effects. Application: Results of this analysis in the study to training organization and training characteristics of the transition environment effects on nuclear power institutions and operators training organization having a significant impact that says. The transfer of knowledge and technology, as well as that can be applied to a new situation in terms of education and training are important characteristics.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.355-365
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• 2015

As the global climate has dramatically changed over the past decades, there has been active research on evaluating its effects on food security, which has been recognized as one of the most important issues in the field. In this study, we analyzed the impact of the climate change on the Korean agriculture using meta-analysis methods. Especially, our research focus is on estimating the effect of CO2 concentration and two adaptations (planting-date and cultivar adjustments)on rice that accounts for a larger proportion of the Korean domestic agriculture. Unlike traditional general meta-analysis methods that use summary statistics of effects of interest, meta analysis specific to the agriculture literature was conducted by integrating the data on rice yield that were generated under various CO2 emission scenarios and general circulating models of the 6 collected individual studies. As a modeling approach, the rice yield change ratio was set as the dependent variable and the main and interaction effects of CO2 concentration and adaptation were considered as independent variables in a regression model, As a result, CO2 is estimated to have opposite effects on rice yield depending on whether any of the two adaptations is applied or not; decreasing effect without adaptation and increasing effect with adaptation. In addition, it turns out that the cultivar adjustment has a higher increasing effect on rice yield than the planting-date adjustment. The results of the study are expected to be used as basic quantitative data for establishing responsive polices to the future climate changes.