• Wind and Structures
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• 제31권3호
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• pp.197-207
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• 2020

Knowledge on the design value of extreme wind pressure coefficients (EWPC) of a specific zone of buildings is essential for the wind-resistant capacity of claddings. This paper presents a method to estimate the representative EWPC introducing the multivariate extreme value model. The spatial correlations of the extreme wind pressures at different locations can be consider through the multivariate extreme value. The moving average method is also adopted in this method, so that the measured point pressure can be converted to wind pressure of an area. The proposed method is applied to wind tunnel test results of a large flat roof building. Comparison with existing methods shows that it can give a good estimation for all target zones with different sizes.

• Communications for Statistical Applications and Methods
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• 제13권2호
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• pp.389-407
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• 2006

Extreme value theory has been used widely in many areas of science and engineering to deal with the assessment of extreme events which are rare but have catastrophic consequences. The potential of extreme value theory has only been recognized recently in finance area. In this paper, we provide an overview of extreme value theory for estimating and assessing value at risk and expected shortfall which are the methods for modelling and measuring the extreme financial risks. We illustrate that the approach based on extreme value theory is very useful for estimating tail related risk measures through backtesting of an empirical data.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.653-655
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• 2008

In order to examine the influences by the extreme weather changes on the human physical conditions, we need to undertake human biometeorology research such as the assesment on the extreme heat's influences on human health. Most of the preceding studied have been found to be focused on the influences by extreme heat on the human body, they used statistics on the daily mortality. But thismethod estimate an indirectly influences by extreme heat on the human body. So, to be able to predict the possible directly influences by the extreme heat on the physical conditions. We measure thermal stress by extreme heat.

• Wind and Structures
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• 제26권3호
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• pp.129-146
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• 2018

Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.314-314
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• 2023

Extreme climate events can have a large impact on human life by hampering social, environmental, and economic development. Global circulation models (GCMs) are the widely used numerical models to understand the anticipated future climate change. However, different GCMs can project different future climates due to structural differences, varying initial boundary conditions and assumptions about the physical phenomena. The multi-model ensemble (MME) approach can improve the uncertainties associated with the different GCM outcomes. In this study, a comprehensive rating metric was used to select the best-performing GCMs out of 11 CMIP5 and 13 CMIP6 GCMs, according to their skills in terms of four temporal and five spatial performance indices, in replicating the 21 extreme climate indices during the baseline (1975-2017) in South Korea. The MME data were derived by averaging the simulations from all selected GCMs and three top-ranked GCMs. The random forest (RF) algorithm was also used to derive the MME data from the three top-ranked GCMs. The RF-derived MME data of the three top-ranked GCMs showed the highest performance in simulating the baseline extreme climate which was subsequently used to project the future extreme climate indices under both the representative concentration pathway (RCP) and the socioeconomic concentration pathway scenarios (SSP). The extreme cold and warming indices had declining and increasing trends, respectively, and most extreme precipitation indices had increasing trends over the period 2031-2100. Compared to all scenarios, RCP8.5 showed drastic changes in future extreme climate indices. The coasts in the east, south and west had stronger warming than the rest of the country, while mountain areas in the north experienced more extreme cold. While extreme cold climatology gradually declined from north to south, extreme warming climatology continuously grew from coastal to inland and northern mountainous regions. The results showed that the socially, environmentally and agriculturally important regions of South Korea were at increased risk of facing the detrimental impacts of extreme climatology.

• Wind and Structures
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• 제30권2호
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• pp.141-153
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• 2020

Probabilistic information regarding directional extreme wind speeds is important for the precise estimation of the design wind loads on structures. A joint probability distribution model of directional extreme typhoon wind speeds is established using Monte Carlo simulation and empirical copula function to fully consider the correlations of extreme typhoon wind speeds among the different directions. With this model, a procedure for estimating directional extreme wind speeds for given return periods, which ensures that the overall risk is distributed uniformly by direction, is established. Taking 5 typhoon-prone cities in China as examples, the directional extreme typhoon wind speeds for given return periods estimated by the present method are compared with those estimated by the method proposed by Cook and Miller (1999). Two types of directional factors are obtained based on Cook and Miller (1999) and the UK standard's drafting committee (Standard B, 1997), and the directional risks for the given overall risks are discussed. The influences of the extreme wind speed correlations in the different directions and the simulated typhoon wind speed sample sizes on the estimated extreme wind speeds for a given return period are also discussed.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.857-865
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• 2013

집중 호우로 인한 피해가 증가하면서 다양한 기법들을 이용하여 강우량 예측에 대한 관심이 높아졌다. 최근에는 극단분포를 활용하여 강우량을 예측하려는 시도가 늘고 있다. 본 연구에서는 일반화 극단 분포를 활용하여 실제 서울시의 1973년부터 2010년까지 7월달의 사후예측분포를 생성하고, 수치적인 계산을 위해서 MCMC (Markov chain Monte Carlo)알고리즘을 활용하였다. 이 연구를 통해서 사후예측분포의 점추정값들을 비교하였고 2011년 7월달의 자료와 비교해 봤을 때 집중 호우의 확률이 증가한 것을 알 수 있었다.

• 한국해안해양공학회지
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• 제4권4호
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• pp.250-260
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• 1992

본 논문에서는 비교적 장기간의 조위 관측자료가 축적되어 있는 인천, 제주, 여수, 부산, 묵호에 대하여 극치확률법과 결합확률법을 이용하여 극치해면을 산정하였다. 극치확률법의 분포는 Gumbel, Weibull 및 일반화 극치(GEV)분포에 대하여 최소자승법, 모멘트법, 확률가중적률(PWM)법으로 parameter를 추정하여 극치해면을 산출하였다. 그 결과 Gumbel 분포와 최소자승법이 각각 다른 분포와 다른 parameter 추정법에 비해 크게 추정되는 경향이 있다. 그리고 결합확률법이 극치확률법 보다 대략 5-l0cm 정도 크게 나타났다. 이는 극치확률법이 tide와 surge가 동시에 발생한 조위를 사용한 반면 결합확률법은 동시 발생하지 않은 극치 tide와 극치 surge도 포함하여 극치해면을 산출하기 때문에 값이 조금 크게 추정된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.124-124
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• 2020

This study proposes a framework to evaluate extreme drought using the natural drought index and hot spot analysis. The study area was South Korea. Data were used from 59 automatic synoptic observing system stations. The variable infiltration capacity model was used for the period from 1981 to 2016. The natural drought index was constructed from precipitation, runoff and soil moisture data, which reflect the water cycle. The average interval, duration and severity of extreme drought events were determined following Run theory. The most extreme drought period occurred in 2014-2016, with 46 of 59 weather stations exhibition drought conditions and 78% exhibition extreme drought conditions. The Inje and Seosan station exhibited the longest drought duration of 6 months, and the most severe drought was 5 times higher than the extreme drought severity threshold. The hot spot analysis was used to explore the extreme drought conditions and showed an increasing trend in the middle and northeastern parts of South Korea. Overall, this study provides water resource managers with essential information about locations and significant trends of extreme drought.

• 한국환경과학회지
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• 제24권11호
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• pp.1493-1500
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• 2015

Observation data (1981-2014) and climate change scenario data (historical: 1981-2005; RCP 2.6 and 8.5: 2006-2100) were used to analyze occurrence and future outlook of the extreme heat days and tropical nights in Daegu and Jeju. Then we compared the mortality and observations data (1993-2013). During 1981-2014, the average of extreme heat days (tropical nights) was 24.41 days (12.47 days) in Daegu, and 6.5 days (22.14 days) in Jeju. Extreme heat days and tropical nights have been similarly increased in Daegu, but tropical nights increased more than extreme heat days in Jeju. Extreme heat days and tropical nights in both, Daegu and Jeju showed high correlation with daily mortality, specifically Daegu's correlation was higher than that of jeju. The yearly increasing rate of extreme heat of the future (2076-2100) was 1.7-3.6 times and 7.8-37.7 times higher than the past (1981-2005) in Daegu and Jeju, respectively. The yearly increase rate of tropical nights of future was 2.6-5.0 times and 2.9-5.6 times higher in Daegu and Jeju, respectively. During 2006-2100 periods, the trend of extreme heat days was observed both in Daegu and Jeju. On the average, extreme heat days and tropical nights in Jeju increased more than that of Daegu. However, the trend of extreme heat days increase in Daegu was higher than that in Jeju, whereas, the trend of tropical nights in Jeju was higher than that in Daegu.