• Environmental Engineering Research
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• v.16 no.3
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• pp.175-183
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• 2011

The climate of the $21^{st}$ century is likely to be significantly different from that of the 20th century because of human-induced climate change. An extreme weather event is defined as a climate phenomenon that has not been observed for the past 30 years and that may have occurred by climate change and climate variability. The abnormal climate change can induce natural disasters such as floods, droughts, typhoons, heavy snow, etc. How will the frequency and intensity of extreme weather events be affected by the global warming change in the $21^{st}$ century? This could be a quite interesting matter of concern to the hydrologists who will forecast the extreme weather events for preventing future natural disasters. In this study, we establish the extreme indices and analyze the trend of extreme weather events using extreme indices estimated from the observed data of 66 stations controlled by the Korea Meteorological Administration (KMA) in Korea. These analyses showed that spatially coherent and statistically significant changes in the extreme events of temperature and rainfall have occurred. Under the global climate change, Korea, unlike in the past, is now being affected by extreme weather events such as heavy rain and abnormal temperatures in addition to changes in climate phenomena.

• Journal of Construction Engineering and Project Management
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• v.4 no.4
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• pp.33-40
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• 2014

Maximizing the profitability and minimizing the duration of construction projects in extreme weather regions is a challenging objective that is essential for project success. An optimization model is presented herein for the time-profit trade-off analysis of construction projects under extreme weather conditions. The model generates optimal/near optimal schedules that maximize profit and minimize the duration of construction projects in extreme weather regions. The computations in the model are organized into: (1) a scheduling module that develops practical schedules for construction projects, (2) a profit module that computes project costs (direct, indirect, and total) and project profit, and (3) a multi-objective module that determines optimal/near optimal trade-offs between project duration and profit. One example is used to show the impact of extreme weather on construction time and profit. Another example is used to show the model's ability to generate optimal trade-offs between the time and profit of construction projects under extreme weather conditions.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.234-234
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• 2015

The global patterns of annual and extreme precipitation are projected to be altered by climate change. There are various weather systems which bring precipitation (e.g. tropical cyclone, extratropical cyclone, etc.). It is possible in some regions that multiple weather systems affect the changes of precipitation. However, previous studies have assessed only the changes of precipitation associated with individual weather systems. The relative contributions of the weather systems to the changes of precipitation have not been quantified yet. Also, the changes of the relative importance of weather systems have not been assessed. This study present the quantitative estimates of 1) the relative contributions of weather systems (tropical cyclone (TC), extratropical cyclone (ExC), and "others") to the future changes of annual and extreme precipitation and 2) the changes of the proportions of precipitation associated with each weather system in annual and extreme precipitation based on CMIP5 generation GCM outputs. Weather systems are objectively detected from twelve GCM outputs and six models are selected for further analysis considering the reproducibility of weather systems. In general, the weather system which is dominant in terms of producing precipitation in the present climate contributes the most to the changes of annual and extreme precipitation in each region. However, there are exceptions for the tendency. In East Asia, "others", which ranks the second in the proportion of annual precipitation in present climate, has the largest contribution to the increase of annual precipitation. It was found that the increase of the "others" annual precipitation in East Asia is mainly explained by the changes of that in summer season (JJA), most of which can be regarded as the summer monsoon precipitation. In Southeast Asia, "others" precipitation, the second dominant system in the present climate, has the largest contribution to the changes of very heavy precipitation (>99.9 percentile daily precipitation of historical period). Notable changes of the proportions of precipitation associated with each weather system are found mainly in subtropics, which can be regarded as the "hotspot" of the precipitation regime shift.

• Journal of the Korean Professional Engineers Association
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• v.41 no.4
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• pp.43-46
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• 2008

The extreme weather events have increased around the world this century. One of the main reasons of frequent occurrence is the change of atmospheric circulation by El nino. also Korea Peninsular is not exception. The 97 % of death toll and 89 % of property loss of total are related with extreme-weather events for the last 10 years. for example the heavy rainfall (1998-4999) and Typhoon Rusa and Mamie. In spite of the percent of death toll by extreme-weather disaster is increasing and the total population is growing. but the number of death toll from natural disasters is decreasing. It shows that the loss of property and life can be minimize by preparing the proper disaster prevention measures. There are several preparations to reduce the damage by extreme-weather events: Public facilities have overall check up, to recognize the weather alert, the awareness of the escape route and the art of measures

• Journal of Environmental Science International
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• v.17 no.6
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• pp.657-669
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• 2008

Lately extreme weather event is occurring because of the global warming. Especially disaster due to the extreme heat are increasing but the definition and the standard of the extreme heat is obscure until now. So this study established the extreme heat standard by using the number of daily deaths. As a result, considering the climate of the megalopolis using daily maximum heat index and daily maximum temperature was the best for the standard of the extreme heat. And it showed that extreme heat lasted for 2 days affects the death toll the most. The regional incidence of the extreme heat is highest at August and July, September and June is following.

• Journal of Environmental Science International
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• v.19 no.10
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• pp.1237-1246
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• 2010

This paper aims to analyze the perception of university students for the extreme heat watch warning and suggest the usefulness of special weather reports. For this, we have made up a descriptive questionnaires including the perception, mass media, usefulness and satisfaction of special weather report. Using the SPSS 17.0 program, descriptive statistics, t-test, ANOVA and Scheffe test were used to analyze the collected data. The result are as follows; The perception of extreme heat watch warning was some low as 59.1 percentile, we think it needs education and public relations about the extreme heat watch warning. The usefulness of special weather report was 66.6 percentile and of girl students of university that was educated about health care was higher than one of boy students of university, it needs continuous education of these students in order to upgrade satisfaction of special report and mitigate the hazard of extreme heat according to climate change. The main media to get the meteorological information of university undergraduate students were TV and Internet, it needed education and development of new contents. From these findings, suggestions are presented to help improve the extreme heat watch warning.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.164-170
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• 2020

The weather conditions, such as temperature, precipitation, and sunshine duration, play one of the key roles in Agriculture. In particular, extreme weather events have crucial impacts on growth and yields of crops. This study estimates statistics of extreme weather events in 167 Si-gun over South Korea derived from high-resolution(30 and 270m) topo-climatology model for key three meteorological variables(temperature, precipitation and sunshine duration). It is shown that the characteristic of each extreme weather frequency in the topo-climatology model is in good agreement with observation from Korean Meteorological Administration's Automatic Surface Observing System. Moreover, it is possible to analyze the statistics of extreme weather more realistically because this data can cover the weather at not-observed regions. Hence, this data is expected to be used as baseline data for assessing vulnerability to extreme weather and politic decisions for damage reduction in agricultural sector.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.461-470
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• 2018

The frequency of extreme weather events was analyzed using meteorological data (air temperature, precipitation, and duration of sunshine) collected from 61 stations over a 36-year span (1981-2016). The 10-day meteorological data were used as a basic unit for this analysis. On average, the frequency of occurrence of abnormal weather was 9.88 per year and has increased significantly during this 36-year period. According to the type of abnormal weather, the frequencies of occurrence of abnormally high air temperature and short duration of sunshine have increased by 0.50 and 0.41 per 10 years, respectively; however, that for abnormally low air temperature has decreased by 0.31 per 10 years and the trend was statistically significant. The highest frequency of abnormal weather appeared in 2007, with a frequency of 14.31. Abnormal weather was the most frequent at Yeongdeok station with an average frequency of 11.78 per year over this 36-year span.

• Wind and Structures
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• v.39 no.1
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• pp.1-14
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• 2024

Widespread damages from extreme winds have attracted lots of attentions of the resilience assessment of power distribution systems. With many related environmental parameters as well as numerous power infrastructure components, such as poles and wires, the increased challenge of power asset management before, during and after extreme events have to be addressed to prevent possible cascading failures in the power distribution system. Many extreme winds from weather events, such as hurricanes, generate widespread damages in multiple areas such as the economy, social security, and infrastructure management. The livelihoods of residents in the impaired areas are devastated largely due to the paucity of vital utilities, such as electricity. To address the challenge of power grid asset management, power system clustering is needed to partition a complex power system into several stable clusters to prevent the cascading failure from happening. Traditionally, system clustering uses the Binary Decision Diagram (BDD) to derive the clustering result, which is time-consuming and inefficient. Meanwhile, the previous studies considering the weather hazards did not include any detailed weather-related meteorologic parameters which is not appropriate as the heterogeneity of the parameters could largely affect the system performance. Therefore, a fragility-based network hierarchical spectral clustering method is proposed. In the present paper, the fragility curve and surfaces for a power distribution subsystem are obtained first. The fragility of the subsystem under typical failure mechanisms is calculated as a function of wind speed and pole characteristic dimension (diameter or span length). Secondly, the proposed fragility-based hierarchical spectral clustering method (F-HSC) integrates the physics-based fragility analysis into Hierarchical Spectral Clustering (HSC) technique from graph theory to achieve the clustering result for the power distribution system under extreme weather events. From the results of vulnerability analysis, it could be seen that the system performance after clustering is better than before clustering. With the F-HSC method, the impact of the extreme weather events could be considered with topology to cluster different power distribution systems to prevent the system from experiencing power blackouts.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.1-24
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• 2014

This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. Many studies have reported on the significant reduction in maize production in the USA due to the extreme weather event (combined heat wave and drought) that occurred in 2012. However, most of these studies focused on yield and did not assess the potential effect of weather extremes on food prices and security. The overall goal of this study was to use geo-spatial crop modeling and trend analysis to quantify the impact of weather extremes on both yield and, followed food security in the developing world. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively. The weather extremes that occurred in the USA in 2012 resulted in a sharp increase in the world maize price. In addition, it likely played a role in the reduction in world maize consumption and trade in 2012/13, compared to 2011/12. The most vulnerable countries to the weather extremes are poor countries with high maize import dependency ratios including those countries in the Caribbean, northern Africa and western Asia. Other vulnerable countries include low-income countries with low import dependency ratios but which cannot afford highly-priced maize. The study also highlighted the pathways through which a weather extreme would affect food security, were it to occur in 2050 under climate change. Some of the policies which could help vulnerable countries counter the negative effects of weather extremes consist of social protection and safety net programs. Medium- to long-term adaptation strategies include increasing world food reserves to a level where they can be used to cover the production losses brought by weather extremes.