• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.45-52
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• 2010

The relationship between climate changes and transportation could be separated by two approaches. One of methods was to find how climate changes affected transportation, and the other way was how transportation affected climate changes. In this study, we reported from the former standpoint, how climate changes affected transportation fields. When there is a lot of snowfall in Seoul, it starts ripple effect through the travel patterns. They can be explained by travel time and operating cost. The travel costs were calculated in this paper for analysing the effect of disbenefit by climate changes. Snow Melting System was also studied for relieving negative influences under the unpredictable weather condition. As a result, the system was effective for minimizing disbenefit by climate changes.

• Korean Journal of Environmental Biology
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• v.40 no.1
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• pp.1-10
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• 2022

Global warming has a major impact on the Earth's precipitation and temperature fluctuations, and significantly affects the habitats and biodiversity of many species. Although the number of alien plants newly introduced in South Korea has recently increased due to the increasing frequency of international exchanges and climate change, studies on how climate change affects the distribution of these alien plants are lacking. This study predicts changes in the distribution of suitable habitats according to RCPs climate change scenarios using the current distribution of the invasive alien plant Conyza sumatrensis and bioclimatic variables. C. sumatrensis has a limited distribution in the southern part of South Korea. Isothermality (bio03), the max temperature of the warmest month (bio05), and the mean temperature of the driest quarter (bio09) were found to influence the distribution of C. sumatrensis. In the future, the suitable habitat for C. sumatrensis is projected to increase under RCP 4.5 and RCP 8.5 climate change scenarios. Changes in the distribution of alien plants can have a significant impact on the survival of native plants and cause ecosystem disturbance. Therefore, studies on changing distribution of invasive species according to climate change scenarios can provide useful information required to plan conservation strategies and restoration plans for various ecosystems.

• Environmental and Resource Economics Review
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• v.24 no.2
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• pp.343-363
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• 2015

This study is to analyze the effects of climate change on national total factor productivity. Changes in temperature and rainfalls which are the representative climate variables are used as main factors to measure climate change. Not only average values of the variables but those highest values are used as independent variables in the model, in order to consider the characteristic pattern of recent climate change, the high volatilities. The OLS results are corresponding to previous literature that average temperature has a negative relationship with productivities while average rainfalls have a positive relationship. However, the results of panel analysis contradict the argument of the negative relationship between average temperature and productivities since human beings can adapt the climate change. Therefore adaptation capacity is important to forecast the effects of climate changes on economies.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2018.06a
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• pp.119-119
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• 2018

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.151-153
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• 2014

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.309-310
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• 2019

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.243-243
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• 2019

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2012.07a
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• pp.101-103
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• 2012

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.273-273
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• 2019

• Atmosphere
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• v.34 no.1
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• pp.55-67
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• 2024

This paper aims to provide a detailed introduction to the concept of the Ratio of Predictable Component (RPC) and the Signal-to-Noise Paradox. Then, we derive insights from them by exploring the paradoxical features by conducting a seasonal and regional analysis through ensemble expansion in KMA's climate prediction system (GloSea). We also provide an explanation of the ensemble generation method, with a specific focus on stochastic physics. Through this study, we can provide the predictability limits of our forecasting system, and find way to enhance it. On a global scale, RPC reaches a value of 1 when the ensemble is expanded to a maximum of 56 members, underlining the significance of ensemble expansion in the climate prediction system. The feature indicating RPC paradoxically exceeding 1 becomes particularly evident in the winter North Atlantic and the summer North Pacific. In the Siberian Continent, predictability is notably low, persisting even as the ensemble size increases. This region, characterized by a low RPC, is considered challenging for making reliable predictions, highlighting the need for further improvement in the model and initialization processes related to land processes. In contrast, the tropical ocean demonstrates robust predictability while maintaining an RPC of 1. Through this study, we have brought to attention the limitations of potential predictability within the climate prediction system, emphasizing the necessity of leveraging predictable signals with high RPC values. We also underscore the importance of continuous efforts aimed at improving models and initializations to overcome these limitations.