• Proceedings of the KSRS Conference
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• v.1
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• pp.278-281
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• 2006

Korea Meteorological Administration(KMA) has issued the tropical storm(typhoon) warning or advisories when it was developed to tropical storm from tropical depression and a typhoon is expected to influence the Korean peninsula and adjacent seas. Typhoon information includes current typhoon position and intensity. KMA has used the Dvorak Technique to analyze the center of typhoon and it's intensity by using available geostationary satellites' images such as GMS, GOES-9 and MTSAT-1R since 2001. The Dvorak technique is so subjective that the analysis results could be variable according to analysts. To reduce the subjective errors, QuikSCAT seawind data have been used with various analysis data including sea surface temperature from geostationary meteorological satellites, polar orbit satellites, and other observation data. On the other hand, there is an advantage of using the Subjective Dvorak Technique(SDT). SDT can get information about intensity and center of typhoon by using only infrared images of geostationary meteorology satellites. However, there has been a limitation to use the SDT on operational purpose because of lack of observation and information from polar orbit satellites such as SSM/I. Therefore, KMA has established Advanced Objective Dvorak Technique(AODT) system developed by UW/CIMSS(University of Wisconsin-Madison/Cooperative Institude for Meteorological Satellite Studies) to improve current typhoon analysis technique, and the performance has been tested since 2005. We have developed statistical relationships to correct AODT CI numbers according to the SDT CI numbers that have been presumed as truths of typhoons occurred in northwestern pacific ocean by using linear, nonlinear regressions, and neural network principal component analysis. In conclusion, the neural network nonlinear principal component analysis has fitted best to the SDT, and shown Root Mean Square Error(RMSE) 0.42 and coefficient of determination($R^2$) 0.91 by using MTSAT-1R satellite images of 2005. KMA has operated typhoon intensity analysis using SDT and AODT since 2006 and keep trying to correct CI numbers.

• Journal of Navigation and Port Research
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• v.33 no.10
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• pp.679-683
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• 2009

Typhoon numbers and intensity according to the sea areas of occurrence(sea area of A : Caroline Marshall Islands and vicinity, sea area of B : north of $20^{\circ}N$, sea area of C : greater coasting area of Philippines, sea area of D : South China Sea) were analyzed for 22years from 1986 to 2007 using the meteorological administration's data. Yearly mean typhoon numbers are 26.3 and are showed decreasing trend in the sea areas of A, B, C and D. The decreasing trend is especially notable in the sea area of A and is slight in the sea area of D. Yearly mean typhoon number is most in the sea area of A(13.8, about 53％ of all), the next orders are the sea area C(5.6, about 21％), sea area of B(3.8, about 14％) and sea area of D(3.1, about 12％). Typhoon intensity is strongest in the sea area of A(mean central minimum pressure : 951hPa), the next orders are the sea area C(970hPa), sea area of B(975hPa) and sea area of D(983hPa). The time series of yearly mean central minimum pressures for whole sea area is showed slightly decreasing trend, it means that typhoon intensity is strengthened gradually. Results of this ste seare in accord with simulated results on typhoon vntrations in the global warming.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.2
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• pp.140-146
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• 2015

This paper analyzed recurvature of typhoons by using 20 years meteorological data from 1992 to 2011. The results of this study are as follows. Yearly numbers of typhoon recurvature showed decreasing tendency gradually with decrease of numbers of typhoon occurrence. Typhoons recurvature were especially many between August and October and number of typhoon recurvature between July and October was occupied counts for 71 % of the whole typhoon recurvature. Life of typhoon recurvature in the North Pacific was most frequent at 5 days and 7 days. Mean life of typhoon recurvature was 6.8 days and this numerical value was longer than mean life of the whole typhoon including recuevatute and non-recurvature. Most of typhoons recurvature changed their direction north-eastwards in 20-34 degrees north latitude and 120-139 degrees east longitude. Mean latitude recurvature and longitude recurvature were 25 degrees north latitude and 135 degrees east longitude, respectively.

• Journal of Navigation and Port Research
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• v.34 no.6
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• pp.453-458
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• 2010

This paper studies relationship between global warming and trends of typhoon variation by using the meteorological long-term data. The results show that yearly mean typhoon's occurrence numbers decrease and maximum wind speeds strengthen gradually. These results are in accord with most of simulated results. While the normal course of typhoon is increased, the westward course of that is decreased. Typhoon trajectories show that the ratios of normal course 6 : westward course 3 : abnormal course 1 in the last 10 years. Among typhoons which affect to the Korea ones pass through the southern coast of Korea are the most. The numbers of typhoon pass through the western coast of Korea are decreased and those pass through the eastern coast of Korea show increasing trend lately. The notable point in relation to the global warming is that typhoon intensity is strengthened gradually. Watch and counterplan in the viewpoint of prevention to the meteorological disasters are required.

• Journal of Environmental Science International
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• v.30 no.9
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• pp.763-777
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• 2021

The spatial characteristics of typhoon-class strong wind during the non-typhoon period were analyzed using, a cluster analysis of the observational data and of special strong wind advisories and, warnings issued by the Korean Meteorological Administration. On the Korean Peninsula, strong winds during non-typhoon periods showed a wide variety of spatial characteristics. In particular, the cluster analysis showed that strong winds could be classified into six clusters on the Korean Peninsula, and that the spatial distribution, occurrence rate of strong winds, and strong wind speed in each cluster were complex and diverse. In addition, our analysis of the frequency of issuance of special strong wind warnings showed a significant difference in the average frequency of strong wind warnings issued in metropolitan cities, with relatively high numbers of warnings issued in Gyeongsangbuk-do and, Jeollanam-do, and low numbers of warning issued inland and in other metropolitan cities. As a result of the changing trend in warnings issued from 2004 to 2019, Ulsan and Busan can be interpreted as having a relatively high number of warnings; the frequency of strong wind warnings issuances and strong wind occurrences in these cities is increasing rapidly. Based on the results of this study, it is necessary to identify areas with similar strong wind characteristics and consider specific regional standards in terms of disaster prevention.

• Ocean and Polar Research
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• v.27 no.1
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• pp.25-34
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• 2005

Impacts of Typhoon Maemi on a soft-coral community located on subtidal cliff at Munseom, Jeju were investigated in this study using underwater photography. Typhoon Maemi hit Jeju Island in late September 2003 and its impact was strong enough to destruct most shallow water sessile benthos including soft corals. To estimate numbers and size of soft-coral colonies, a line transect was installed on the cliff at depth from 3 to 9 m and photographs were taken serially by every 1m. From each $1{\times}1m$ underwater photograph, species and size of soft-coral colony was determined. Number of soft-coral colony and its Percent coverage (PC) in each $1m^2$ quadrat was calculated. Soft corals Scleronephthya gracillium, Dendronephthya gigantea, D. spinulosa and D. castanea were identified from the photographs. Dendronephthya sp. was mainly distributed at 3-6m while S. gracillimum was mostly occurred at $6{sim}9m$. A survey conducted before the typhoon showed that number of the soft-coral colonies at $3{\sim}4m,\;4{\sim}5m,\;5{\sim}6m,\;6{\sim}7m,\;7{\sim}8m\;and\;8{\sim}9m$ was 17, 24, 20, 23, 18 and 30 $colonies/m^2$ or 21, 48, 36, 28, 24 and 43%, respectively. After the typhoon, number of soft-coral colonies in the transect increased, 31, 35, 21, 10, 21 and 50 $colonies/m^2$ while PC was remarkably decreased as 21, 23, 21, 5, 9 and 13%, respectively. Our data suggested that the impact was limited in larger colonies; larger soft coral colonies were selectively destroyed and removed while the small colonies underneath the larger colonies remained undestroyed.

• Journal of Fisheries and Marine Sciences Education
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• v.18 no.2
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• pp.137-149
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• 2006

The typhoon, heavy rain, blizzard, storm and heavy snowfall had the main caused of natural disasters occurred in Korea from 1993 to 2002. Among them, typhoon has responsible for biggest disaster, recording about 47.4% of total economic damage. Typhoons concentrated mostly in the months from June to October. The average occurrence number in those months ranged from 3.9 to 5.5 based on 30 years of record(1971-2000). However, the numbers increased from 4.0 to 6.2 during the most recent 10 years(1991-2000). Jeju province, among others in Korea, was most frequently affected by typhoon which occurred 23 times during the period of 1991-2000. Typhoons which occurred from July to early August have passed mostly through the west of Jeju, whereas, those of late August to September have passed through the center and eastern sea area of Jeju. The typhoons 'Ramasun' and 'Rusa' caused severe damage in Jeju area in September 2003 and the surge heights were +39cm and +77cm, respectively. The main cause of the damage was surge height which was highly associated with the tidal phase at the time of typhoon passage. The damage caused by typhoon on the aquaculture, fishing boat and harbor cosatline wall around Jeju Island which was amounted to be 417 billion won(\) during the recent 3 years(2002-2004)

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.2
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• pp.176-183
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• 1999

This paper is aimed to investigate behaviour of vortex in 2-D step cavity with high Reynolds numbers$(3.2{\times}10^{3},\;10^{4},\;3{\times}10^{4},\;5{\times}10^{4}\;and\;7{\times}10^{4})$. The SOLA algorithm which is MAC type was adopted to solution method computing the flow field on irregular grid. In case of $Re=7{\times}10^{4}$ flow behavior is steady bu periodic unsteady sinusoidal fluctuation of local velocity and kinetic energy is found for $Re=10^{4}$ Continuous movements of small eddies in the secondary flow regions are discov-ered for $3{\times}10^{4}$ Generation of eddies and their active migrating behavior are detected over $Re=5{\times}10^{4}$ resulting in complete unsteady and non-linear flow characteristics Furthermore a typhoon-like vortex(TLV) appears intermittently and rotates along the separation regions and boundary layers.

• Journal of Ocean Engineering and Technology
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• v.35 no.6
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• pp.414-425
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• 2021

Overcrowding of high-rise buildings in urban zones change the airflow pattern in the surrounding areas. This causes building wind, which adversely affects the wind environment. Building wind can generate more serious social damage under extreme weather conditions such as typhoons. In this study, to analyze the wind speed and wind speed ratio quantitatively, we installed five anemometers in Haeundae, where high-rise buildings are dense, and conducted on-site monitoring in the event of typhoon OMAIS to determine the characteristics of wind over skyscraper towers surround the other buildings. At point M-2, where the strongest wind speed was measured, the maximum average wind speed in 1 min was observed to be 28.99 m/s, which was 1.7 times stronger than that at the ocean observatory, of 17.0 m/s, at the same time. Furthermore, when the wind speed at the ocean observatory was 8.2 m/s, a strong wind speed of 24 m/s was blowing at point M-2, and the wind speed ratio compared to that at the ocean observatory was 2.92. It is judged that winds 2-3 times stronger than those at the surrounding areas can be induced under certain conditions due to the building wind effect. To verify the degree of wind speed, we introduced the Beaufort wind scale. The Beaufort numbers of wind speed data for the ocean observatory were mostly distributed from 2 to 6, and the maximum value was 8; however, for the observation point, values from 9 to 11 were observed. Through this study, it was possible to determine the characteristics of the wind environment in the area around high-rise buildings due to the building wind effect.

• Journal of Ocean Engineering and Technology
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• v.36 no.6
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• pp.380-389
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• 2022

In the Haeundae area of Busan, South Korea, damage has continued to occur recently from building wind from caused by dense skyscrapers. Five wind observation stations were installed near LCT residential towers in Haeundae to analyze the effect of building winds during typhoon Omais. The impact of building wind was analyzed through relative and absolute evaluations. At an intersection located southeast of LCT (L-2), the strongest wind speed was measured during the monitoring. The maximum average wind speed for one minute was observed to be 38.93 m/s, which is about three times stronger than at an ocean observation buoy (12.7 m/s) at the same time. It is expected that 3 to 4 times stronger wind can be induced under certain conditions compared to the surrounding areas due to the building wind effect. In a Beaufort wind scale analysis, the wind speed at an ocean observatory was mostly distributed at Beaufort number 4, and the maximum was 8. At L-2, more than 50% of the wind speed exceeded Beaufort number 4, and numbers up to 12 were observed. However, since actual measurement has a limitation in analyzing the entire range, cross-validation with computational fluid dynamics simulation data is required to understand the characteristics of building winds.