• 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.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.31-45
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• 2018

This study implemented the prediction of drought properties (number of drought events, intensity, duration) using the user-oriented systematical procedures of downscaling climate change scenarios based the multiple global climate models (GCMs), AIMS (APCC Integrated Modeling Solution) program. The drought properties were defined and estimated with Effective Drought Index (EDI). The optimal 10 models among 29 GCMs were selected, by the estimation of the spatial and temporal reproducibility about the five climate change indices related with precipitation. In addition, Simple Quantile Mapping (SQM) as the downscaling technique is much better in describing the observed precipitation events than Spatial Disaggregation Quantile Delta Mapping (SDQDM). Even though the procedure was systematically applied, there are still limitations in describing the observed spatial precipitation properties well due to the offset of spatial variability in multi-model ensemble (MME) analysis. As a result, the farther into the future, the duration and the number of drought generation will be decreased, while the intensity of drought will be increased. Regionally, the drought at the central regions of the Korean Peninsula is expected to be mitigated, while that at the southern regions are expected to be severe.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.285-291
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• 2020

The Noah 3.3 Land Surface Model (LSM) was used to estimate the global soil moisture in this study and these soil moisture datasets were assessed against satellite-based and reanalysis soil moisture products. The Noah 3.3 LSM simulated soil moistures in four soil layers and root-zone soil moistures defined as a depth-weighted average in the first three soil layers (i.e., up to 1.0 m deep). The Noah LSM soil moisture products were then compared with a satellite-based soil moisture dataset (European Space Agency Climate Change Initiatives (ESA CCI) SM v04.4) and reanalysis soil moisture datasets (ERA-interim). In addition, the five major basins (Yangtze, Mekong, Mississippi, Murray-Darling, Amazon) were selected for the assesment with the Gravity Recovery and Climate Experiment (GRACE)-based Total Water Storage Anomaly (TWSA) and TWS Change (TWSC). The results revealed that high anomaly correlations were found in most of the Asia-Pacific regions including East Asia, South Asia, Australia, and Noth and South America. While the anomaly correlations in the Murray-Darling basin were somewhat low, relatively higher anomaly correlations in the other basins were found. It is concluded that this study can be useful for the development of soil moisture based drought indices and subsequently can be helpful to reduce damages from drought by timely providing an efficacious strategy.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1286-1295
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• 2020

It has been increasingly difficult to predict the amounts of Acer mono sap to be collected due to droughts and cold waves caused by recent climate changes with few studies conducted on the prediction of its collection volume. This study thus set out to propose a Big Data prediction system based on meteorological information for the collection of Acer mono sap. The proposed system would analyze collected data and provide managers with a statistical chart of prediction values regarding climate factors to affect the amounts of Acer mono sap to be collected, thus enabling efficient work. It was designed based on Hadoop for data collection, treatment and analysis. The study also analyzed and proposed an optimal prediction model for climate conditions to influence the volume of Acer mono sap to be collected by applying a multiple regression analysis model based on Hadoop and Mahout.

• Journal of Engineering Education Research
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• v.19 no.5
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• pp.57-64
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• 2016

This study is about interdisciplinary education model of using Davis Guggenheim's documentary film on global warming which is a big concern in climate change issues, An Inconvenient Truth. It based on Al Gore's slide speech. Through a course student analyzed the cause and phenomenon of global warming resulted from increase of $CO_2$ by using fossil fuel and its environmental science effects-heat wave, desertification, tornado, hurricane, sea level rise caused by melting glaciers, destroying ecosystem like habitat degradation of wild animals, for example polar bear, extreme cold wave caused by change of ocean currents- of global warming. After, student discussed of efforts to prevent global warming. This educational model is appropriate for lower grade student of environmental engineering and also available for converged majors or general education class.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.2
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• pp.156-166
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• 2007

Purpose: The purpose of the present study was to examine the causal relationships among hospital nursing organizational characteristics (organizational climate, workload), individual characteristics (experience, education) and outcome variables (job satisfaction, job stress, task performance) by constructing and testing a conceptual framework. Method: Five large general hospitals located in Seoul were selected to participated. The total sample of 245 registered nurses represents a response rate of 94 percent. Data for this study was collected from January to February in 2006 by questionnaire. Path analyses with LISREL program were used to test the fit of the proposed model to the data and to examine the causal relationships among variables. Result: Both the proposed model and the modified model fit the data excellently. The model revealed relatively high explanatory power of work stress (40%), job satisfaction (46%) and task performance (27%) by predicted variables. In predicting work stress, job satisfaction and task performance, the finding of this study clearly demonstrate organizational climate might be the most important variable. Conclusion: Based on the findings of the study, it was suggested that desirable organizational climate was needed to increase the nurses' mental and physical health as well as qualified task performance.

• Wind and Structures
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• v.13 no.6
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• pp.519-528
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• 2010

A meteorological model, RAMS, and a commercial computational fluid dynamics (CFD) model, FLUENT are combined as a one-way off-line nested modeling system, namely, RAMS/FLUENT system. The system is experimentally applied in the wind simulation over a complex terrain, with which numerical simulations of wind field over Foyeding weather station located in the northwest mountainous area of Beijing metropolis are performed. The results show that the method of combining a meteorological model and a CFD model as a modeling system is reasonable. In RAMS/FLUENT system, more realistic boundary conditions are provided for FLUENT rather than idealized vertical wind profiles, and the finite volume method (FVM) of FLUENT ensures the capability of the modeling system on describing complex terrain in the simulation. Thus, RAMS/FLUENT can provide fine-scale realistic wind data over complex terrains.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.69-69
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• 2021

From the unprecedented 2011 spring flood, the residens reside by Lake Champlain and Richelieu River encountered enormous damages. The International Joint Committee (IJC) released the Lake Champlain-Richelieu River (LCRR) Plan of Study (PoS). One of the major tasks for the PoS is to investigate the possible scenarios that might happen in the LCRR basin based on the stochastic simulation of the Net Basin Supplies that calculates the amount of flow into the lake and the river. Therefore, the current study proposed a novel apporach that simulate the annual NBS teleconnecting the climate index. The proposed model employed the bivariate empirical decomposition to contamporaneously model the long-term evolution of nonstationary oscillation embeded in the annual NBS and the climate signal (here, Artic Oscillation: AO). In order to represent the variational behavior of NBS correlation structure along with the temporal revolution of the climate index, a new nonstationary parameterization concept is proposed. The results indicate that the proposed model is superior performance in preserving long and short temporal correlation. It can even preserve the hurst coefficient better than any other tested models.

• Journal of Environmental Science International
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• v.22 no.12
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• pp.1691-1698
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• 2013

The purpose of this article is analyzing the economic impacts of abnormal climate on fall chinese cabbage farmers and consumers in Korea, with employing the equilibrium displacement model. Our results show that there were little difference in gross farm income, even though there were significant yield reductions due to abnormal climate changes. However periodic occurrences of abnormal climates caused serious damage to consumption levels which had declined by 10.6~17.1 percent with higher prices by 15.3~24.6 percent than normal climate years since 1990.