• Journal of the Economic Geographical Society of Korea
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• v.15 no.2
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• pp.304-313
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• 2012

Uncertainty increases as a result of environment change and change of individual decision-making in extreme weather. This study consider individual decision-making which has been not covered until now. The purpose of this study is making Agent-Based Model to predict it more accurate that how much change travel demand in heavy rain and heavy snow. Through this model, it can be utilized to forecast travel demand, changes in travel behavior and traffic patterns. It will be also possible to predict discomfort index and risk of accidents.

• Advances in environmental research
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• v.3 no.3
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• pp.253-281
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• 2014

The quest for enhanced thermal comfort for dwellings encompasses the holistic utilization of improved building fabric, impact of weather variation and amongst passive cooling design consideration the provision of appropriate ventilation and shading strategy. Whilst thermal comfort is prime to dwellings considerations, limited research has been done in this area with the attention focused mostly on non-dwellings. This paper examines the current and future thermal comfort implications of four different standard construction specifications which show a progressive increase in thermal mass and airtightness and is underpinned by the newly developed CIBSE adaptive thermal comfort method for assessing the risk of overheating in naturally ventilated dwellings. Interactive investigation on the impact of building fabric variation, natural ventilation scenarios, external shading and varying occupants' characteristics to analyse dwellings thermal comfort based on non-heating season of current and future weather patterns of London and Birmingham is conducted. The overheating analysis focus on the whole building and individual zones. The findings from the thermal analysis simulation are illustrated graphically coupled with statistical analysis of data collected from the simulation. The results indicate that, judicious integrated approach of improved design options could substantially reduce the operating temperatures in dwellings and enhance thermal comfort.

• Journal of Wind Energy
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• v.14 no.3
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• pp.25-33
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• 2023

In order to secure the safety of increasing offshore activities such as offshore wind farm maintenance and fishing, IMPACT, a mid-term marine weather forecasting system, was established by predicting marine weather up to 7 days in advance. Forecast data from the Korea Hydrographic and Oceanographic Agency (KHOA), which provides the most reliable marine meteorological service in Korea, was used, but wind speed and wave height forecast errors increased as the leading forecast period increased, so improvement of the accuracy of the model results was needed. The Model Output Statistics (MOS) method, a post-correction method using statistical machine learning, was applied to improve the prediction accuracy of wave height, which is an important factor in forecasting the risk of marine activities. Compared with the observed data, the wave height prediction results by the model before correction for 6 to 7 days ahead showed an RMSE of 0.692 m and R of 0.591, and there was a tendency to underestimate high waves. After correction with the MOS technique, RMSE was 0.554 m and R was 0.732, confirming that accuracy was significantly improved.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.195-202
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• 2017

This study aims to suggest the basics for the implementation of the farmstead-specific early warning system (FEWS) for weather risk management nationwide. A survey by questionnaire was conducted to examine farmer's response, and a cost-benefit analysis was made to examine the effect of the FEWS on the economy. The farmers who volunteered to participate in this survey responded that they were generally satisfied with the FEWS, and that they used it well for farming. Willingness to pay (WTP) for the early warning service was estimated to be 8,833 KRW per month by survey respondents. If the early warning service is extended to nationwide and 50% of farmers use it for six months, then the ratio of benefit to cost will be 2.2, indicating that nationwide expansion of the FEWS is very feasible.

• Korean Journal of Construction Engineering and Management
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• v.20 no.1
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• pp.41-51
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• 2019

With the aging of the population and the slowdown of the job market, elderly workers make up a large portion of the construction workforce. Also, due to the nature of the construction industry, where outdoor work is frequent, the weather has a more sensitive impact on elderly workers than on younger ones. The study aims to analyze the degree of weather risks exposed to elderly workers in the construction industry using the measure of work loss days. To that end, construction accidents that affected 28,514 elderly workers in seven cities from 2012 to 2016 (a total of 12,789 days) were analyzed to calculate work loss days per different weather factors. The results show that the elderly workers were seriously affected when the temperature was between $-12^{\circ}C$ and $-10^{\circ}C$, humidity between 55% and 60%, precipitation between 128mm and 181mm, and wind speed between 5.5m/s and 6.5m/s, with the highest work loss days. The combined effects between the weather factors were also analyzed to identify the conditiosn that leaded to high work loss days of elderly workers. This study contributes to effective safety management and pleasant working environment between weather factors and shedding light on the relationship between weather factors and work loss days of elderly workers.

• Journal of Navigation and Port Research
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• v.28 no.7
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• pp.647-651
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• 2004

FPSOs are commonly proposed and used for offshore oil production. Due to the fundamental requirement of FPSOs to remain moored at their location, they are unable to avoid severe weather. FPSOs normally operate head to the weather, and sensitive equipment located near the bow will be susceptible to green water damage. Damage may occur to both equipment and superstructure, with resulting risk to personnel. To initially access green water is allowed by the physical understanding of green water events. In this paper the main focus is put on the physical phenomena of green water accounted for with the tested data in regular waves.

• Special Issue of the Society of Naval Architects of Korea
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• 2007.09a
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• pp.94-98
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• 2007

The latest development of the submarine oil field and the deep-sea explorer, FPSO is commonly proposed and used for offshore oil production. And because the fundamental requirement of FPSOs to remain moored at their position, they are unable to avoid severe weather and environment. FPSO normally operates head to the weather, and sensitive equipment located the exposed area will be influenced by green water damages, the damages may occur to both onboard equipment and topside structures with resulting risk to personnel. In this paper, the main focus considers the physical structures of green water protector in order to preserve topside structures, equipment and personnel from green water.

• East Asian Economic Review
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• v.27 no.4
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• pp.273-301
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• 2023

This study investigates the impacts of long-term climate variability on household consumption in Indonesia, a country highly vulnerable to climate change. The analysis combines household survey data from nearly 5,998 families with satellite-derived weather data from NASA POWER spanning 30 years. We use the long-term variability in temperature and precipitation as a proxy for climate change. This study examines the impact of climate change which proceeds over the long term, unlike previous studies concerning one-off or short-term climate events. In addition, using satellite data enhances the accuracy of households' exposure to climate variability. The analysis finds that households in a village with higher temperature and precipitation variability significantly consume less food. This implies that households more exposed to climate change are at higher risk of malnutrition in developing countries. This study has a limitation that it cannot rule out the potential endogeneity of choosing a climate-vulnerable residential location due to economic poorness.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.115-124
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• 2023

Currently, as the frequency of extreme weather events increases, the scale of damage increases when extreme weather events occur. This has been providing forecast information by investing a lot of time and resources to predict rainfall from the past. However, this information is difficult for non-experts to understand, and it does not include information on how much damage occurs when extreme weather events occur. Therefore, in this study, a risk matrix based on heavy rain damage rating was presented by using the impact forecasting standard through the creation of a risk matrix presented for the first time in the UK. First, through correlation analysis between rainfall data and damage data, variables necessary for risk matrix creation are selected, and PERCENTILE (25%, 75%, 90%, 95%) and JNBC (Jenks Natural Breaks Classification) techniques suggested in previous studies are used. Therefore, a rating standard according to rainfall and damage was calculated, and two rating standards were synthesized to present one standard. As a result of the analysis, in the case of the number of households affected by the disaster, PERCENTILE showed the highest distribution than JNBC in the Yeongsan River and Seomjin River basins where the most damage occurred, and similar results were shown in the Chungcheong-do area. Looking at the results of rainfall grading, JNBC's grade was higher than PERCENTILE's, and the highest grade was shown especially in Jeolla-do and Chungcheong-do. In addition, when comparing with the current status of heavy rain warnings in the affected area, it can be confirmed that JNBC is similar. In the risk matrix results, it was confirmed that JNBC replicated better than PERCENTILE in Sejong, Daejeon, Chungnam, Chungbuk, Gwangju, Jeonnam, and Jeonbuk regions, which suffered the most damage.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.302-310
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• 2023

In this study, the extent of the impact of rainfall on the outbreak of fire blight during the blossom infection risk period was explored. In the Chungnam province, the outbreak of fire blight disease began in 2015, and changes in the outbreak's scale were most pronounced between 2020 and 2022, significantly escalating from 63 orchards in 2020 to 170 orchards in 2021, before decreasing to 46 orchards in 2022. In 2022, the number of incidence has decreased and the number of canker symptom in branches has also decreased. It was evaluated that the significant decrease of fire blight disease in 2022 was due to the dry weather during the flowering season. In other words, this yearly fluctuation in fire blight outbreaks was correlated with the presence or absence of rainfall and accumulated precipitation during the blossom infection risk period. This trend was observed across all surveyed regions where apples and pears were cultivated. Among the weather conditions influencing the blossom infection risk period, rainfall notably affected the activation of pathogens from over-wintering cankers and flower infections. In particular, precipitation during the initial 3 days of the blossom infection risk warning was confirmed as a decisive factor in determining the outbreak's scale.