• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.830-840
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• 2011

Climate change has been settled as pending issues to consider water resources and environment all over the world, however, scientific and quantitative assessment methods of climate change have never been standardized. When South Korea headed toward water deficiency nation, the study is not only required analysis of atmospheric or hydrologic factors, but also demanded analysis of correlation with water quality environment factors to gain management policies about climate change. Therefore, this study explored appropriate monthly rainfall elasticity in chosen 41 unit watersheds in Nak-dong river which is the biggest river in Korea and applied monitored discharge data in 2004 to 2009 with monthly rainfall using Thiessen method. Each unit watershed drew elasticity between water temperature and water quality factors such as BOD, COD, SS, T-N, and T-P. Moreover, this study performed non-linear correlation analysis with monitored discharge data. Based on results of analysis, this is first steps of climate change analysis using long-term monitoring to develop basic data by Nak-dong river Environmental Research Center (Ministry of Environment) and to draw quantitative results for reliable forecasting. Secondary, the results considered characteristic of air temperature and rainfall in each unit watershed so that the study has significance its various statistical applications. Finally, this study stands for developing comparable data through "The 4 major river restoration" project by Korea government before and after which cause water quality and water environment changes.

• Journal of Climate Change Research
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• v.5 no.2
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• pp.109-125
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• 2014

Suitable climate condition is essential for stable growth of crops which directly leads to an increase in crop production. Preceding domestic researches mostly used crop models to predict grain or crop yield in relation to climate change. However, the use of various models and input data based on foreign background lowered the reliability for result. Therefore in this study, we evaluated domestic applicability by comparing and analyzing various crop models developed abroad. In addition, we selected models based on the possibility of acquiring input data and suggested domestic applicability.

• Atmosphere
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• v.31 no.5
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• pp.525-537
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• 2021

Black ices on road surfaces in winter tend to cause severe and terrible accidents. It is very difficult to detect black ice events in advance due to their localities as well as sensitivities to surface and upper meteorological variables. This study develops a methodology to detect the road sections vulnerable to black ice with the use of road surface temperature data obtained from a mobile road weather observation vehicle. The 7 experiments were conducted on the route from Nam-Wonju IC to Nam-Andong IC (132.5 km) on the Jungang Expressway during the period from December 2020 to February 2021. Firstly, temporal road surface temperature data were converted to the spatial data with a 50 m resolution. Then, the spatial road surface temperature was normalized with zero mean and one standard deviation using a simple normalization, a linear de-trend and normalization, and a low-pass filter and normalization. The resulting road thermal map was calculated in terms of road surface temperature differences. A road ice index was suggested using the normalized road temperatures and their horizontal differences. Road sections vulnerable to black ice were derived from road ice indices and verified with respect to road geometry and sky view, etc. It was found that black ice could occur not only over bridges, but also roads with a low sky view factor. These results are expected to be applicable to the alarm service for black ice to drivers.

• Korean Journal of Occupational Health Nursing
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• v.32 no.1
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• pp.20-29
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• 2023

Purpose: This study aimed to identify the effects of hospital ethical climate and communication self-efficacy on nursing care left undone. Methods: The participants were 142 nurses working in a general hospital. Data were collected from July 18 to August 30, 2021. Data were analyzed by t-test, ANOVA, Pearson correlation, and multiple regression analysis using the SPSS/WIN 25.0 program. Results: (a) The mean value of hospital ethical climate was 3.54±0.41, communication self-efficacy was 5.03±0.81, and the sum of nursing cares left undone was 3.68±3.14. (b) Nursing cares left undone had a negative correlation with hospital ethical climate(r=-.25, p=.003) but not with communication self-efficacy (r=-.13, p=.116). (c) Factors that affected nursing cares left undone included education (≥master) (β=.23, p=.005), marital status (single) (β=-.19, p=.018), age (26~27) (β=-.18, p=.022), and hospital ethical climate (β=-.18, p=.029); the explanation power was 18.0% (F=8.66, p<.001). Conclusion: Our study shows that hospital ethical climate plays a significant role in nursing cares left undone of nurses. It is important to strengthen hospital ethical climate to lower the incidence of nursing cares left undone. These results may serve as basic data to help develop strategies for reducing the incidence of nursing cares left undone.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.160-160
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• 2023

Generally, Global Climate Models (GCM) cannot be used directly due to their inherent error arising from over or under-estimation of climate variables compared to the observed data. Several bias correction methods have been devised to solve this problem. Most of the traditional bias correction methods are one dimensional as they bias correct the climate variables separately. One such method is the Quantile Mapping method which builds a transfer function based on the statistical differences between the GCM and observed variables. Laux et al. introduced a copula-based method that bias corrects simulated climate data by employing not one but two different climate variables simultaneously and essentially extends the traditional one dimensional method into two dimensions. but it has some limitations. This study uses objective functions to address specifically, the limitations of Laux's methods on the Quantile Mapping method. The objective functions used were the observed rank correlation function, the observed moment function and the observed likelihood function. To illustrate the performance of this method, it is applied to ten GCMs for 20 stations in South Korea. The marginal distributions used were the Weibull, Gamma, Lognormal, Logistic and the Gumbel distributions. The tested copula family include most Archimedean copula families. Five performance metrics are used to evaluate the efficiency of this method, the Mean Square Error, Root Mean Square Error, Kolmogorov-Smirnov test, Percent Bias, Nash-Sutcliffe Efficiency and the Kullback Leibler Divergence. The results showed a significant improvement of Laux's method especially when maximizing the observed rank correlation function and when maximizing a combination of the observed rank correlation and observed moments functions for all GCMs in the validation period.

• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.1
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• pp.49-66
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• 2024

Extreme rainfall will become intense due to climate change, increasing inundation risk to agricultural land. Hydrological and hydraulic simulations for the entire watershed were conducted to analyze the impact of climate change. Rainfall data was collected based on past weather observation and SSP (Shared Socio-economic Pathway)5-8.5 climate change scenarios. Simulation for flood volume, reservoir operation, river level, and inundation of agricultural land was conducted through K-HAS (KRC Hydraulics & Hydrology Analysis System) and HEC-RAS (Hydrologic Engineering Center - River Analysis System). Various scenarios were selected, encompassing different periods of rainfall data, including the observed period (1973-2022), near-term future (2021-2050), mid-term future (2051-2080), and long-term future (2081-2100), in addition to probabilistic precipitation events with return periods of 20 years and 100 years. The inundation area of the Aho-Buin district was visualized through GIS (Geographic Information System) based on the results of the flooding analysis. The probabilistic precipitation of climate change scenarios was calculated higher than that of past observations, which affected the increase in reservoir inflow, river level, inundation time, and inundation area. The inundation area and inundation time were higher in the 100-year frequency. Inundation risk was high in the order of long-term future, near-term future, mid-term future, and observed period. It was also shown that the Aho and Buin districts were vulnerable to inundation. These results are expected to be used as fundamental data for assessing the risk of flooding for agricultural land and downstream watersheds under climate change, guiding drainage improvement projects, and making flood risk maps.

• Journal of Korean Academy of Nursing Administration
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• v.9 no.1
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• pp.63-73
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• 2003

Purpose : The purpose of this study is to analyze the comparison of organizational climate and job satisfaction of nurses between a secondary hospital and a tertiary hospital. Method : The subjects of this study were 50 nurses who were working in a secondary hospital and 50 working in a tertiary hospital. The data was collected by self-reporting questionnaires. The data were analysed using frequency, percentage, mean, standard deviation, t-test, ANOVA, Pearson's correlation coefficient, regression analysis. Result : 1) There was no statistical significance of the difference of organizational climate between a secondary hospital and a tertiary hospital. However, there was a statistical significance of the difference of job satisfaction. 2) In the organizational climate, there was a significant difference by income in a secondary hospital, and by position in a tertiary center. 3) In the job satisfaction, there was significant differences by age, marriage, position, and duration of working in a secondary hospital, otherwise. there was no significant difference in a tertiary hospital. 4) There was significant positive correlation between organizational climate and job satisfaction. Organizational climate significantly affected job satisfaction. Conclusion : It is suggested that the nursing organizational effectiveness program should be developed with reflecting on organizational characteristics that the nurses perceived.

• Architectural research
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• v.14 no.4
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• pp.117-124
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• 2012

High rise office buildings represent one of the most energy-intensive architectural typologies. The growth of urban population necessitates sustainable high rise towers that lessen environmental impacts and energy consumption. Among various sustainable strategies, the integrated design is long known to be an important process that has great impact on building's sustainability. The framework for this paper is based on the case study of integrated towers that are located in different climate zones. The paper specifically addresses to what extent climate conditions influence the design of a high rise building and what kinds of the climate integrated design has been implemented. Qualitative case studies were carried out using published data and architectural drawing set. The technical work presented in the paper is based on computer simulation that examines the insolation analysis using hourly recorded weather data. The analysis results revealed that the site and building envelope integration and the site and building service systems have shown the most frequently employed in the integrated towers through the implementation of renewable resource integration, high performance envelopes and sustainable building service systems. Internal comfort and further energy saving in the integrated towers are offered through an automatic building management system. Due to the dynamic climate conditions, integration of building systems requires a sophisticated approach to building sustainability.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.707-717
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• 2020

Global warming affects climate change and has an overall impact on all aspects of life. On the other hand, community behavior and disaster aspects also have an important role in people's lives. This will also have an impact on regional development. This study aims to find the effect of climate, disaster, and social community on rural development. This study uses data on the potential of rural development from PODES 2014, and 2018 data collection on climate conditions and regional status is sourced from relevant ministries. This research uses Ordinary Least Square (OLS) Regression Analysis method, then continued with CHAID analysis to find the segmentation of the role of climate, disaster, and social factors on rural development. The results of this study found that all research regressor variables significantly influence the Rural Development Index (IPD2018), with an R-squared value of 32.9 percent. Efforts need to be taken in order to implement policies that are targeted, effective, and efficient. The results of this study can be a reference for the government in determining policies by focusing on rural development that have high duration of sunshine, cultivating natural disaster warnings, especially in areas prone to natural disasters, and need to focus on underdeveloped areas.