• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.797-810
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• 2017

The Korean peninsula is exposed to typhoons every year. Typhoons cause huge socioeconomic damage because tropical cyclones tend to occur with strong winds and heavy precipitation. In order to understand the complex dependence structure between strong winds and heavy precipitation, the copula links a set of univariate distributions to a multivariate distribution and has been actively studied in the field of hydrology. In this study, we carried out analysis using data of wind speed and precipitation collected from the weather stations in Busan and Jeju. Log-Normal, Gamma, and Weibull distributions were considered to explain marginal distributions of the copula. Kolmogorov-Smirnov, Cramer-von-Mises, and Anderson-Darling test statistics were employed for testing the goodness-of-fit of marginal distribution. Observed pseudo data were calculated through inverse transformation method for establishing the copula. Elliptical, archimedean, and extreme copula were considered to explain the dependence structure between strong winds and heavy precipitation. In selecting the best copula, we employed the Cramer-von-Mises test and cross-validation. In Busan, precipitation according to average wind speed followed t copula and precipitation just as maximum wind speed adopted Clayton copula. In Jeju, precipitation according to maximum wind speed complied Normal copula and average wind speed as stated in precipitation followed Frank copula and maximum wind speed according to precipitation observed Husler-Reiss copula.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.2
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• pp.75-82
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• 2008

Heavy rains and typhoons are the most critical meteorological disaster occurred in the Korean peninsular. Due to the global warming, the magnitude of heavy rains and typhoons is becoming heavier resulting in more damage annually. Therefore, it is required to establish a mitigation plan to reduce the damage from meteorological disasters. To do so, in general, it is better to establish a mitigation plan for each district considering the characteristics of a district than a single mitigation plan for the entire districts without considering the characteristics of an individual district. In this study, we provide fundamental data for establishing a mitigation plan from analysis considering the frequency and damage in monetary value by heavy rain and typhoon with the geological and social characteristics of districts. The annual damage reports published by the National Emergency Management Agency, dated from 1994 to 2003, are used for the analysis. The districts are classified into six categories by the geological and social characteristics. Also, the frequency and damage in monetary value are assessed for each district. Based on them, the damage degree by heavy rain and typhoon from 1st to 4th is assigned to each district. The assigned damage degree is, then, analyzed with geological and social characteristics of each district to show the status of damage by meteorological disasters on the district.

• Journal of The Geomorphological Association of Korea
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• v.19 no.3
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• pp.71-82
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• 2012

This research was carried out to estimate annual erosion and retreat rates by using datum-point and to identify the characteristics and causes of seasonal variations of sea-cliff slope in Pado-ri, Taean-gun. In the result, the erosion and retreat rates of sea-cliff were increased from spring to summer. The rates were increased rapidly between August and October, caused by the effects of extreme weather events such as severe rainstorms and typhoons, etc. Since then, the erosion and retreat rates of sea-cliff were decreased gradually, but the rates were increased again in winter due to the storm surge and mechanical weathering resulting from the repeated freezing and thawing actions of bed rocks. The factors that affect erosion and retreat rates of sea-cliff include the number of days with antecedent participation and daily maximum wave height. In particular, it turned out that the erosion is accelerated by strong wave energy during storm surges and typhoons. The annual erosion and retreat rates of study area for the past two years(from May 2010 to May 2012) were approximately 44~60cm/yr in condition of differences in geomorphological and geological characteristics at each point. These erosion and retreat rates were found to be higher than results of previous researches. This is caused by coastal erosion forces strengthened by extreme weather events. The erosion and retreat process of sea-cliff in the study area is composed by denudation of onshore areas in addition to marine erosion(wave energy).

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1247-1260
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• 2018

This study investigated the effect of arctic oscillation by analyzing the cross-correlation characteristics between the arctic oscillation index (AOI) and the number of typhoons occurred in the North Pacific, the number of typhoons affecting South Korea, total rainfall amount and number of rainy days during the monsoon season in South Korea. For this analysis, the monthly AOI data were transformed into the average data about January and seasonal AOI data representing winter, spring, fall and winter. The typhoon data and monsoon data were all those collected annually. The data period for this analysis was determined to be from 1961 to 2016 by considering the data available. Based on this analysis, it was found that the arctic oscillation has a weak but statistically significant effect on the monsoon characteristics of South Korea. However, the level of effect was not consistent over the data period but varied significantly periodically. For example, the cross-correlation coefficient derived for the recent 10 years was estimated to be higher than 0.8, but was simply insignificant during the 30 years before the last decade. The overall effect of arctic oscillation on the occurrence of typhoon was found to be statistically insignificant, but was also fluctuating periodically to show somewhat significant effect. Finally, it should be mentioned that the effect of arctic oscillation on the typhoon and monsoon had been changing by turns from 1960s to 2000s. However, in the 2010s, it happened that the effect of arctic oscillation has become significant on both typhoon and monsoon in South Korea.

• Journal of the Korean earth science society
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• v.40 no.3
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• pp.240-258
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• 2019

Typhoons, torrential rainfall, and heavy snowfall cause catastrophic losses each year in the Republic of Korea. Therefore, if we can know the possibility of this phenomenon in advance through regular observations, it will be greatly beneficial to Korean society. Korea is surrounded by sea on its three sides, and the sea surface temperature (SST) directly or indirectly affects the development of typhoons, heavy rainfall, and heavy snowfall. Therefore, the characteristics of SST variability related to the high impact weather are investigated in this paper. The heavy rainfall in Korea was distributed around Seoul, Gyeonggi, and west and southern coast. The heavy snowfall occurred mainly in the eastern coastal (hereafter Youngdong Heavy Snow) and the southwestern region (hereafter Honam-type heavy snow). The SST variability was slightly different depending on the type and major occurrence regions of the high impact weather. When the torrential rain occurred, the SST variability was significantly increased in the regions extending to Jindo-Jeju island-Ieodo-Shanghai in China. When the heavy snow occurred, the SST variability has reduced in the southern sea of Jeju island, regardless of the type of heavy snowfall, whereas the SST variability has increased in the East Sea near $130^{\circ}E$ and $39^{\circ}N$. Areas with high SST variability are anticipated to be used as a basis for studying the atmospheric-oceanic interaction mechanism as well as for determining the background atmospheric aerosol observation area.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.25-38
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• 2021

Purpose: To reduce the damage caused by continuously occurring typhoons, we proposed a standardized grid so that it could be actively utilized in the prevention and preparation stage of typhoon response. We established grid-based convergence information on the typhoon risk area so that we showed the effectiveness of information used in disaster response. Method: To generate convergent information on typhoon hazard areas that can be useful in responding to typhoon situation, we used various types of data such as vector and raster to establish typhoon hazard area small grid-based information. A standardized grid model was applied for compatibility with already produced information and for compatibility of grid information generated by each local government. Result: By applying the grid system of National branch license plates, a grid of typhoon risk areas in Seoul was constructed that can be usefully used when responding to typhoon situations. The grid system of National branch license plates defines the grid size of a multi-dimensional hierarchical structure. And a grid of typhoon risk areas in Seoul was constructed using grids of 100m and 1,000m. Conclusion: Using real-time 5km resolution grid based weather information provided by Korea Meteorological Administration, in the future, it is possible to derive near-future typhoon hazard areas according to typhoon travel route prediction. In addition, the national branch number grid system can be expanded to global grid systems for global response to various disasters.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.198-210
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• 2022

The southern strait of Jeju is a divergence point of the Tsushima Warm Current (TWC), and it is the starting point of the thermohaline circulation in the waters of the Korean Peninsula, affecting the size and frequency of marine disasters such as typhoons and tsunamis, and has a very important oceanographic impact, such as becoming a source of harmful organisms and radioactively contaminated water. Therefore, for an immediate response to these maritime disasters, real-time ocean observation is required. However, compared to other straits, in the case of southern Jeju, such wide area marine observations are insufficient. Therefore, in this study, surface current field of the southern strait of Jeju was calculated using High-Frequency radar (HF radar). the large surface current field is calculated, and post-processing and data improvement are carried out through APM (Antenna Pattern Measurement) and FOL (First Order Line), and comparative analysis is conducted using actual data. As a result, the correlation shows improvement of 0.4~0.7 and RMSE of about 1~19 cm/s. These high-frequency radar observation results will help solve domestic issues such as response to typhoons, verification of numerical models, utilization of wide area wave data, and ocean search and rescue in the future through the establishment of an open data network.

• The Journal of Bigdata
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• v.8 no.1
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• pp.99-109
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• 2023

Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.338-347
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• 2023

Jinhae Bay, characterized by frequent runaway ships and strong winds during typhoon attacks, poses a high risk of maritime accidents such as ship collisions and groundings. This study aims to determine a safe separation distance between ships in the Jinhae Bay anchorage, considering the unique environmental characteristics of the Korean sea area. Analysis revealed that an average of 100-200 ships anchor in the typhoon avoidance area in Jinhae Bay during typhoon attacks, with approximately 70% of ships experiencing anchor dragging owing to strong external forces exceeding 25 m/s wind speeds. In this study, we analyzed and presented the separation distances between ships during anchoring operations based on domestic and international design standards, separation distances between ships used as actual typhoon shelters in Jinhae Bay, and appropriate safe distances for ships drifting under strong external forces. The analysis indicated that considering the minimum criteria based on the design standards and emergency response time, a minimum safe distance of approximately 400-900 m was required. In cases where ample space was available, the separation distance was recommended to be set between 700 to 900 m. The findings of this study are anticipated to contribute to the development of guidelines for establishing safe separation distances between ships seeking refuge from typhoons in Jinhae Bay in the future.

• Smart Structures and Systems
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• v.32 no.4
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.