• 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.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.692-693
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• 2013

The effects of Climate change and Installation Price for Photovoltaic System were investigated through power generation analysis and economic analysis though. Photovoltaic System would be the same as governmental regulated 3 KW capacity used for the analysis. Also climate information which are serviced on the KMA (Korea Meteorological Administration) used as well. The experimental results indicate that climate change and installation price change could be influenced more higher on photovoltaic system than last 30-years. Furthermore the economic advantages could be higher on the future.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.97-107
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• 2021

Abnormal climate caused by climate change causes enormous social and economic damage. And such damage and its impact may vary depending on the location and regional characteristics of the region and the social and economic conditions of local residents. Therefore, it is necessary to continuously monitor whether there are indicators that are weaker than other regions among the detailed indicators that constitute the risk, exposure and vulnerability of climate change risk. In this study, the concept of climate change risk was used for heatwave to determine regional inequality of climate change risk. In other words, it was judged that inequality in climate change risk occurred in regions with high risk but high exposure and low vulnerability compared to other regions. As a result of the analysis, it was found that 13 local governments in Korea experienced regional inequality in climate change risk. In order to resolve regional inequality in climate change risks, the current status of regional inequality in climate change should be checked based on the analysis proposed in this study, there is a need for an evaluation and monitoring system that can provide appropriate feedback on areas where inequality has occurred. This continuous evaluation and monitoring-based feedback system is expected to be of great help in resolving regional inequality in climate change risks.

• Atmosphere
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• v.14 no.4
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• pp.19-23
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• 2004

Progresses in numerical prediction of weather and climate have been in parallel with those of computing resources, especially the development of supercomputers. Advanced techniques in numerical modeling, computational schemes, and data assimilation cloud not have been practically achieved without the aid of supercomputers. With such techniques and computing powers, the accuracy of numerical forecasts has been tremendously improved. Supercomputers are also indispensible in constructing and executing the synthetic Earth system models. In this study, a brief overview on numerical weather / climate prediction, Earth system modeling, and the values of supercomputing is provided.

• Atmosphere
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• v.33 no.2
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• pp.297-306
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• 2023

Celebrating its 60th anniversary, this study suggests the future vision of the Korean Meteorological Society (KMS) for the next 60 years. The vision is "to advance atmospheric science and technology that contributes to human society as well as protect people from not only climate change risks but also weather, climate, and environmental disasters". Based on the suggestions from its members, this study proposes the KMS future development plan as follows. The first plan is to strengthen in leading the development and growth of atmospheric sciences in Korea, especially to improve weather, climate, and environment forecasts and to reduce uncertainty in future climate projections. The second is to enhance interaction not only among its members in academy, Korea Meteorological Administration and related organizations, meteorological industry, and science communicators but also with other related fields such as energy, water resources, agriculture, fishery, and forestry. The third is to enhance in nurturing young scientists by supporting domestic and international networks and training the state-of-the-art sciences, and to create opportunities for young scientists to advance into a wider field. The last is to expand its international activities for solving the challenges facing mankind, such as climate change risks and weather, climate, and environment disasters. The KMS should also continue the efforts to establish an integrative platform for leading fundamental and interdisciplinary research in weather, climate, and environment.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.6
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• pp.615-631
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• 2012

This study provides an evaluation for capability of Integrated Climate and Air quality Modeling System (ICAMS) on future regional scale climate projection. Temperature and precipitation are compared between ground-level observation data and results of regional models (MM5) for the past 30 years over the Korean peninsula. The ICAMS successfully simulates the local-scale spatial/seasonal variation of the temperature and precipitation. The probability distribution of simulated daily mean and minimum temperature agree well with the observed patterns and trends, although mean temperature shows a little cold bias about $1^{\circ}C$ compared to observations. It seems that a systematic cold bias is mostly due to an underestimation of maximum temperature. In the case of precipitation, the rainfall in winter and light rainfall are remarkably simulated well, but summer precipitation is underestimated in the heavy rainfall phenomena of exceeding 20 mm/day. The ICAMS shows a tendency to overestimate the number of washout days about 7%. Those results of this study indicate that the performance of ICAMS is reasonable regarding to air quality predication over the Korean peninsula.

• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.5
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• pp.196-206
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• 2000

These days, the fuzzy logic or the fuzzy set theory has received attention from a number of researchers in the area of industrial application. Moreover, the fuzzy logic control has been successfully applied to a large numbers of control problems where the conventional control methods had failed. Using this control theory we designed a climate controller for an automotive climate control system whose mathematical model is difficult. This paper describes an automotive climate control where the fuzzy control has been used to stabilize parameter uncertainties and disturbance effects. To show the validity and effectiveness of the proposed control method, the fuzzy logic controller was implemented with a philips 80C552 microcomputer chip and tested in an actual vehicle. From the experimental results, it could be conduced that the proposed controller is superior to conventional controllers in both control performance and thermal comfort. The climate control system in cars is difficult to model mathematically so we tested a fuzzy logic control system which promised better results.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.563-573
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• 2018

An Expert Seasonal Prediction System for operational Seasonal Outlook (ESPreSSO) is developed based on the APEC Climate Center (APCC) Multi-Model Ensemble (MME) dynamical prediction and expert-guided statistical downscaling techniques. Dynamical models have improved to provide meaningful seasonal prediction, and their prediction skills are further improved by various ensemble and downscaling techniques. However, experienced scientists and forecasters make subjective correction for the operational seasonal outlook due to limited prediction skills and biases of dynamical models. Here, a hybrid seasonal prediction system that grafts experts' knowledge and understanding onto dynamical MME prediction is developed to guide operational seasonal outlook in Korea. The basis dynamical prediction is based on the APCC MME, which are statistically mapped onto the station-based observations by experienced experts. Their subjective selection undergoes objective screening and quality control to generate final seasonal outlook products after physical ensemble averaging. The prediction system is constructed based on 23-year training period of 1983-2005, and its performance and stability are assessed for the independent 11-year prediction period of 2006-2016. The results show that the ESPreSSO has reliable and stable prediction skill suitable for operational use.

• KIEAE Journal
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• v.14 no.4
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• pp.127-131
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• 2014

The ground source heat pump (GSHP) system is a kind of the temperature differential energy system using relatively stable underground temperature as heat source of space heating and cooling. This system can achieve higher performance of system than it of conventional air source heat pump systems. However, its superiority of the system performance is different according to installation location or local climate, because the system performance depends on the underground condition which is decided by annual average air temperature. In this study, in order to estimate the feasibility of the ground source heat pump system according to the local climate, numerical simulation was conducted using the ground heat transfer model and the surface heat balance model. The case study was conducted in the condition of Seoul, Daejeon, and Busan, In the result, the heat exchange rate of Busan was 34.33 W/m as the largest in heating season and it of Seoul was 40.61 W/m as the largest in cooling.