• Journal of Korean Biological Nursing Science
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• v.16 no.3
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• pp.164-172
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• 2014

Purpose: The purpose of this study was to identify the effects of an extreme heat Adaptation Program on the blood pressure, stress response, self-efficacy, and knowledge of management of hypertension and extreme heat of patients who suffered from hypertension. Methods: A quasi-experimental study with a non-equivalent control group pretest-posttest design was used. The data collection period was between July 2 and August 20, 2012. Thirty-seven patients participated in the study (18 in the experimental group and 19 in the control group). Data were analyzed using $X^2$-test, t-test, and Cronbach's alpha coefficients with SPSS/WIN 19.0. Results: Patients who participated in the program showed statistically significant improvements in systolic blood pressure (SBP), self-efficacy, and knowledge of management of hypertension and extreme heat. Conclusion: The results indicate that this extreme heat adaptation program can be utilized for patients suffering from hypertension in order to reduce their SBP and to increase self-efficacy and knowledge of management of hypertension and extreme heat. Therefore, it is recommended that this program be used for elderly patients suffering from chronic disease.

• Wind and Structures
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• v.31 no.5
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• pp.473-482
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• 2020

The first-order method for estimating the extreme wind pressure on building envelopes with consideration of the directionality of wind speed and wind pressure is improved to enhance its computational efficiency. In this improved method, the result is obtained directly from the empirical distribution of a random selection of annual maximum wind pressure samples generated by a Monte Carlo method, rather than from the previously utilized extreme wind pressure probability distribution. A discussion of the relationship between the first- and full-order methods indicates that when extreme wind pressures in a non-typhoon climate with a high return period are estimated with consideration of directionality, using the relatively simple first-order method instead of the computationally intensive full-order method is reasonable. The validation of this reasonableness is equivalent to validating two assumptions to improve its computational efficiency: 1) The result obtained by the full-order method is conservative when the extreme wind pressure events among different sectors are independent. 2) The result obtained by the first-order method for a high return period is not significantly affected when the extreme wind speeds among the different sectors are assumed to be independent. These two assumptions are validated by examples in different regions and theoretical derivation.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.3
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• pp.57-69
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• 2016

In this study, we analyzed the extreme rainfall distribution scenarios based on probable rainfall calculation and applying various time distribution models over the landslide high risk zones in urban areas. We used observed rainfall data form total 71 ASOS (Automated Synoptic Observing System) station and AWS (Automatic Weather Station) in KMA (Korea Meteorological Administration), and we analyzed the linear trends for 1-hr and 24-hr annual maximum rainfall series using simple linear regression method, which are identified their increasing trends with slopes of 0.035 and 0.660 during 1961-2014, respectively. The Gumbel distribution was applied to obtain the return period and probability precipitation for each duration. The IDF (Intensity-Duration-Frequency) curves for landslide high risk zones were derived by applying integrated probability precipitation intensity equation. Results from IDF analysis indicate that the probability precipitation varies from 31.4~38.3 % for 1 hr duration, and 33.0~47.9 % for 24 hr duration. It also showed different results for each area. The $Huff-4^{th}$ Quartile method as well as Mononobe distribution were selected as the rainfall distribution scenarios of landslide high risk zones. The results of this study can be used to provide boundary conditions for slope collapse analysis, to analyze sediment disaster risk, and to use as input data for risk prediction of debris flow.

• Proceedings of the Korean Society of Crop Science Conference
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• 2000.11a
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• pp.3-11
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• 2000

The Asian summer monsoon has a profound social and economic impact in East Asia and its surrounding countries. The monsoon is basically a response of the atmosphere to the differential heating between the land mass of the Asian continent and the adjacent oceans. The atmospheric response, however, is quite complicated due to the interactions between the atmospheric heat sources, land-sea contrast, and topography, The occurrence of extreme summertime floods in Korea, Japan, and China in 1998 and 1999 has highlighted the range of variability of the East Asian summertime monsoon circulation and spurred interest in investigating the cause of such extreme variability. While ENSO is often considered a prime mechanism responsible for the unusual hydrological disasters in East Asia, understanding of the connection between ENSO and the East Asian monsoon is hampered by their dynamic complexities. Along with a recent phenomenon of weather abnormalities observed in many parts of the globe, Korea has seen its share of increased weather abnormalities such as the record-breaking heavy rainfalls due to a series of flash floods in the summers of 1998 and 1999, following devastating Yangtze river floods in China. A clear regime shift is found in the tropospheric mean temperature in the northern hemisphere middle latitudes and the surface temperature over the Asian continent during the summer with a sudden warming since 1977. Either decadal climate variation or climate regime shift in the Asian continent is evident and may have altered the characteristics of the East Asian summer monsoon. Considering the summertime rainfall amount in Korea is overall increased lately, the 1998/99 heavy rainfalls may not be isolated episodes related only to ENSO, but could be a part of long-term climate variation. The record-breaking heavy summer rainfalls in Korea may not be direct impact of ENSO. Instead, the effects of decadal climate variation and ENSO may be coupled to each other and also to the East Asian summer monsoon system, while their individual impacts are difficult to separate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.645-654
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• 2018

Extreme rainfall events caused severe damage to human life and property due to the inundation in major urban areas. In particular, the increase in the intensity of rainfall due to climate change causes changes in the design flood discharge. As a result, it causes uncertainty in the design criteria of hydraulic structures. However, quantitative analysis results have not been provided due to the limitations of climate scenarios and the uncertainty in climate changes. Therefore, this research chose Bulgwangcheon basin as the target basin to analysis the discharge considering climate change. As the result, it is necessary to strengthen design standards since the amount of discharge increased by 14.2% even in the near future.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.127-136
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• 2024

Flooding presents a significant threat to infrastructure, and climate change is exacerbating these risks. High-speed rail (HSR) infrastructure, designed based on historical data, may struggle to cope with future extreme flood events. Infrastructure stakeholders require forecasting capabilities to predict the intensity and frequency of future floods so they can develop adaptive strategies to mitigate flood risks and impacts. Floods can cause significant damage to HSR infrastructure networks, disrupting their operations. Traditional network theory-based frameworks are insufficient for analyzing the three-dimensional effects of floods on HSR networks. To address this issue, this study proposes a comprehensive approach to assess flood risk and vulnerability under future climate scenarios for HSR networks. The method consists of three components. (i) Generate flood inundation data by utilizing global climate models, Shared Socioeconomic Pathways(SSPs), and the CaMa-Flood model. (ii) Fit extreme flood depths to the Gumbel distribution to generate flood inundation scenarios. (iii) Overlay flood scenarios on the HSR network and quantitatively assess network vulnerability based on topology network. When applied to the HSR system in mainland China, the results indicate that flood severity does not necessarily increase under higher SSPs, but may worsen over time. The minimum flood return period that causes HSR disruptions is decreasing, with Hubei Province showing a significant increase in HSR segment failure probability. Discontinuous phase transitions in HSR network topology metrics suggest potential nationwide collapses under future infrequent floods. These findings can inform preventive measures for the HSR sector and flood-resistant standards for HSR infrastructure. The method used in this study can be extended to analyze the vulnerability of other transportation systems to natural disasters, serving as a quantitative tool for improving resilience in a changing climate.

• Journal of the Korean Society for Marine Environment & Energy
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• v.1 no.2
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• pp.71-81
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• 1998

In this paper the statistical characteristics of the waves at Hong-do and Mara-do are examined. The wane scatter diagrams of H/sub s/ and T/sub z/ and H/sub 1/3/and T/sub 1/3/ at two locations are given and various statistical characteristics of the ocean waves are examined. If the sea is not narrowband, the modified Rayleigh distribution introduced by Longuet-Higgins can be used for the individual wave height distribution. However the modified Rayleigh distribution has not been widely used due to the inconvenience of determining the empirical constant. In this paper a simple method to determine the empirical constant for the modified Rayleigh distribution is proposed. Extreme waves based on the measured wave data are estimated. There is no significant difference depending on the distribution functions. However the estimations of the extreme waves from H/sub s/ and H/sub 1/3/ show considerable difference.

• 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.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1143-1152
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• 2009

A canonical correlation analysis(CCA)-based method is proposed for prediction of future climate change which combines information from ensembles of atmosphere-ocean general circulation models(AOGCMs) and observed climate values. This paper focuses on predictions of future climate on a regional scale which are of potential economic values. The proposed method is obtained by coupling the classical CCA with empirical orthogonal functions(EOF) for dimension reduction. Furthermore, we generate a distribution of climate responses, so that extreme events as well as a general feature such as long tails and unimodality can be revealed through the distribution. Results from real data examples demonstrate the promising empirical properties of the proposed approaches.

• Atmosphere
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• v.29 no.3
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• pp.257-267
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• 2019

This study is to assess the applicability of the Extreme Forecast Index (EFI) algorithm of the ECMWF seasonal forecast system to the Global Seasonal Forecasting System version 5 (GloSea5), operational seasonal forecast system of the Korea Meteorological Administration (KMA). The EFI is based on the difference between Cumulative Distribution Function (CDF) curves of the model's climate data and the current ensemble forecast distribution, which is essential to diagnose the predictability in the extreme cases. To investigate its applicability, the experiment was conducted during the heat-wave cases (the year of 1994 and 2003) and compared GloSea5 hindcast data based EFI with anomaly data of ERA-Interim. The data also used to determine quantitative estimates of Probability Of Detection (POD), False Alarm Ratio (FAR), and spatial pattern correlation. The results showed that the area of ERA-Interim indicating above 4-degree temperature corresponded to the area of EFI 0.8 and above. POD showed high ratio (0.7 and 0.9, respectively), when ERA-Interim anomaly data were the highest (on Jul. 11, 1994 (> $5^{\circ}C$) and Aug. 8, 2003 (> $7^{\circ}C$), respectively). The spatial pattern showed a high correlation in the range of 0.5~0.9. However, the correlation decreased as the lead time increased. Furthermore, the case of Korea heat wave in 2018 was conducted using GloSea5 forecast data to validate EFI showed successful prediction for two to three weeks lead time. As a result, the EFI forecasts can be used to predict the probability that an extreme weather event of interest might occur. Overall, we expected these results to be available for extreme weather forecasting.