• Journal of Astronomy and Space Sciences
• /
• v.31 no.3
• /
• pp.277-283
• /
• 2014

Next Generation Small Satellite-1 (NEXTSat-1) is scheduled to launch in 2017 and Instruments for the Study of Space Storm (ISSS) is planned to be onboard the NEXTSat-1. High Energy Particle Detector (HEPD) is one of the equipment comprising ISSS and the main objective of HEPD is to measure the high energy particles streaming into the Earth radiation belt during the event of a space storm, especially, electrons and protons, to obtain the flux information of those particles. For the design of HEPD, the Geometrical Factor was calculated to be 0.05 to be consistent with the targets of measurement and the structure of telescope with field of view of $33.4^{\circ}$ was designed using this factor. In order to decide the thickness of the detector sensor and the classification of the detection channels, a simulation was performed using GEANT4. Based on the simulation results, two silicon detectors with 1 mm thickness were selected and the aluminum foil of 0.05 mm is placed right in front of the silicon detectors to shield low energy particles. The detection channels are divided into an electron channel and two proton channels based on the measured LET of the particle. If the measured LET is less than 0.8 MeV, the particle belongs to the electron channel, otherwise it belongs to proton channels. HEPD is installed in the direction of $0^{\circ}$, $45^{\circ}$, $90^{\circ}$ against the along-track of a satellite to enable the efficient measurement of high energy particles. HEPD detects electrons with the energy of 0.1 MeV to several MeV and protons with the energy of more than a few MeV. Thus, the study on the dynamic mechanism of these particles in the Earth radiation belt will be performed.

• Atmosphere
• /
• v.23 no.2
• /
• pp.205-220
• /
• 2013

Upper ocean response to typhoon Ewiniar (0603) and its impact on the following typhoon Bilis (0604) are investigated using observational data and numerical experiments. Data used in this study are obtained from the Ieodo Ocean Research Station (IORS), ARGO, and satellite. Numerical simulations are conducted using 3-dimensional Princeton Ocean Model. Results show that when Ewiniar passes over the western North Pacific, unique oceanic responses are found at two places, One is in East China Sea near Taiwan and another is in the vicinity of IORS. The latter are characterized by a strong sea surface cooling (SSC), $6^{\circ}C$ and $11^{\circ}C$ in simulation and observation, under the condition of typhoon with a fast translation speed (8m $s^{-1}$) and lowering intensity (970 hPa). The record-breaking strong SSC is caused by the Yellow Sea Bottom Cold Water, which produces a strong vertical temperature gradient within a shallow depth of Yellow Sea. The former are also characterized by a strong SSC, $7.5^{\circ}C$ in simulation, with a additional cooling of $4.5^{\circ}C$ after a storm's passage mainly due to enhanced and maintained upwelling process by the resonance coupling of storm translation speed and the gravest mode internal wave phase speed. The numerical simulation reveals that the Ewiniar produced a unfavorable upper-ocean thermal condition, which eventually inhibited the intensification of the following typhoon Bilis. Statistics show that 9% of the typhoons in western North Pacific are influenced by cold wakes produced by a proceeding typhoon. These overall results demonstrate that upper ocean response to a typhoon even after the passage is also important factor to be considered for an accurate intensity prediction of a following typhoon with similar track.

• 한국방재학회:학술대회논문집
• /
• 2007.02a
• /
• pp.327-331
• /
• 2007

23 tropical cyclones of tropical storm(TS) intensity or higher formed in the western North Pacific and the South China Sea in 2006. The total number is less than the 30-year $(1971{\sim}2000)$ average frequency of 26.7, Out of 23, 15 cyclones reached typhoon(TY) intensity, three severe tropical storm(STS) intensity, and five TS intensity. The tropical cyclone season in 2006 began in May with the formation of CHANCHU(0601). While convective activity was slightly inactive around the Philippines from late June to early August. In addition, subtropical high was more enhanced than normal over the south of Japan from May to early August. Consequently, most tropical cyclones formed over the sea east of the Philippines after late June, and many of them moved westwards to China. CHANCHU(0601), BILIS(0604), KAEMI(0605), PRAPIROON(0606) and SAOMI(0608) brought damage to China, the Philippines, and Vietnam. On the other hand, EWINIAR(0603) moved northwards and hit the Republic of Korea, causing damage to the country From late August to early September, convective activity was temporarily inactive over the sea east of the Philippines. However, it turned active again after late September. Subtropical high was weak over the south of Japan after late August. Therefore, most tropical cyclones formed over the sea east of the Philippines and moved northwards. WUKONG(0610) and SHANSHAN(0613) hit Japan to bring damage to the country. On the other hand, XANGSANE(0615) and CIMARON(0619) moved westwards in the South China Sea, causing damage to the Philippines, Thailand, and Vietnam. In addition, IOKE(0612) was the first namded cyclone formed in the central North Pacific and moved westwards across longitude 180 degrees east after HUKO(0224).

• Atmosphere
• /
• v.25 no.2
• /
• pp.295-308
• /
• 2015

Based on the CMIP5 historical simulation datasets, we assessed the performance of state-of-the-art climate models in respect to the relationship between interannual variabilities of the North Pacific synoptic eddy (NPSE) and East Asian winter monsoon (EAWM). Observation (ERA-Interim) shows a high negative correlation (-0.73) between the interannual variabilities of East Asian winter monsoon (EAWM) intensity and North Pacific synoptic eddy (NPSE) activity during the period of 1979~2005. Namely, a stronger (weaker) EAWM is related to a weaker (stronger) synoptic eddy activities over the North Pacific. This strong reverse relationship can be well explained by latitudinal distributions of the surface temperature anomalies over East Asian continent, which leads the variation of local baroclinicity and significantly weakens the baroclinic wave activities over the northern latitudes of $40^{\circ}N$. This feature is supported by the distribution of the meridional heat flux (${\overline{{\nu}^{\prime}{\theta}^{\prime}}}$) anomalies, which have negative (positive) values along the latitudes $40{\sim}50^{\circ}N$ for strong(weak) EAWM years. In this study, the historical simulations by 11 CMIP5 climate models (BCC-CSM1.1, CanESM2, GFDL-ESM2G, GFDL-ESM2M, HadGEM2-AO, HadGEM2-CC, IPSL-CM5A-LR, MPI-ESM-LR, MPI-ESM-MR, MRI-CGCM3, and NorESM1-M) are analyzed for DJF of 1979~2005. Correlation coefficient between the two phenomena is -0.59, which is comparable to that of observation. Model-to-model variation in this relationship is relatively large as the range of correlation coefficient is between -0.76 (HadGEM2-CC and HadGEM2-AO) and -0.33 (MRI-CGCM3). But, these reverse relationships are shown in all models without any exception. We found that the multi-model ensemble is qualitatively similar to the observation in reasoning (that is, latitudinal distribution of surface temperature anomalies, variation of local baroclinicity and meridional heat flux by synoptic eddies) of the reverse relationship. However, the uncertainty for weak EAWM is much larger than strong EAWM. In conclusion, we suggest that CMIP5 models as an ensemble have a good performance in the simulation of EAWM, NPSE, and their relationship.

• Korean Journal of Remote Sensing
• /
• v.24 no.4
• /
• pp.359-367
• /
• 2008

TRMM TMI data were used to investigate a relationship between physical parameters from microwave sensor and typhoon intensities from June to September, 2004. Several data such as 85GHz brightness temperature (TB), polarization corrected temperature (PCT), precipitable water, ice content, rain rate, and latent heat release retrieved from the TMI observation were correlated to the maximum wind speeds in the best-track database by RSMC-Tokyo. Correlation coefficient between TB and typhoon intensity was -0.2 - -0.4 with a maximum value in the 2.5 degree radius circle from the center of tropical cyclone. The value of correlation between in precipitable water, rain, latent heat, and typhoon intensity is in the range of 0.2-0.4. Correlation analysis with respect to storm intensity showed that maximum correlation is observed at 1.0-1.5 degree radius circle from the center of tropical cyclone in the initial stage of tropical cyclone, while maximum correlation is shown in 0.5 degree radius in typhoon stage. Correlation coefficient was used to produce regressed intensities and adopted for typhoon Rusa (2002) and Maemi (2003). Multiple regression with 85GHz TB and precipitable water was found to provide an improved typhoon intensity when taking into account the storm size. The results indicate that it may be possible to use TB and precipitable water from satellite observation as a predictor to estimate the intensity of a tropical cyclone.

• Atmosphere
• /
• v.30 no.3
• /
• pp.209-220
• /
• 2020

Seasonal predictability and variability of tropical storms (TCs) simulated in the Global Seasonal Forecast System version 5 (GloSea5) of the Korea Meteorological Administration (KMA) is assessed in Northern Hemisphere in 1996~2009. In the KMA, the GloSea5-Global Atmosphere version 3.0 (GloSea5-GA3) that was previously operated was switched to the GloSea5-Global Coupled version 2.0 (GloSea5-GC2) with data assimilation system since May 2016. In this study, frequency, track, duration, and strength of the TCs in the North Indian Ocean, Western Pacific, Eastern Pacific, and North Atlantic regions derived from the GloSea5-GC2 and GloSea5-GA3 are examined against the best track data during the research period. In general, the GloSea5 shows a good skill for the prediction of seasonally averaged number of the TCs in the Eastern and Western Pacific regions, but underestimation of those in the North Atlantic region. Both the GloSea5-GA3 and GC2 are not able to predict the recurvature of the TCs in the North Western Pacific Ocean (NWPO), which implies that there is no skill for the prediction of landfalls in the Korean peninsula. The GloSea5-GC2 has higher skills for predictability and variability of the TCs than the GloSea5-GA3, although continuous improvements in the operational system for seasonal forecast are still necessary to simulate TCs more realistically in the future.

• Atmosphere
• /
• v.18 no.3
• /
• pp.183-197
• /
• 2008

The purpose of this study is to summarize tropical cyclone activity in 2007. 24 tropical cyclones of tropical storm (TS) intensity or higher formed in the western North Pacific and the South China Sea in 2007. The total number is less than the thirty-year (1971~2000) average frequency of 26.7. Out of twenty four tropical cyclones, 14 TCs reached typhoon (TY) intensity, while the rest 10 only reached severe tropical storm (STS) and tropical storm (TS) intensity - four STS and six TS storms. The tropical cyclone season in 2007 began in April with the formation of KONG-REY (0701). From April to May, two TCs formed in the western North Pacific in response to enhanced convective activity there. From June to July, convective activity turned inactive over the sea around the Philippines and in the South China Sea, and the subtropical high was weak over the south of Japan. MAN-YI (0704) and USAGI (0705) moved northwestward and hit Japan, bringing serious damage to the country. After August, convective activity became enhanced over the sea east of the Philippines, and the subtropical high turned strong over the sea south of Japan. Many TCs, which formed over the sea east of the Philippines and in the South China Sea, moved westward and hit China and Vietnam. PABUK (0706), WUTIP (0707), SEPAT (0708), WIPHA (0712), LEKIMA (0714) and KROSA (0715) brought serious damage to some countries including China, the Philippines and Vietnam. On the other hand, FITOW (0709) and NARI (0711) moved northward, bringing serious damage to Japan and Korea. After HAIYAN (0716), all four TCs except FAXAI (0720) formed over the sea east of $140^{\circ}E$. Three typhoons among them affected Republic of Korea, MAN-YI (0704), USAGI (0705) and NARI (0711). Particularly, NARI (0711) moved northward and made landfall at Goheng Peninsula ($34.5^{\circ}N$, $127.4^{\circ}E$) in 1815 KST 16 September. Due to $11^{th}$ typhoon NARI, strong wind and record-breaking rainfall amount was observed in Jeju Island. It was reported that the daily precipitation was 420.0 mm at Jeju city, Jeju Island on 16 September the highest daily rainfall since Jeju began keeping records in 1927. This typhoon hit the southern part of the Korean peninsula and Jeju Island. 18 people lost their lives, 14,170 people were evacuated and US$ 1.6 billion property damage was occurred.

• Atmosphere
• /
• v.21 no.4
• /
• pp.439-446
• /
• 2011

NCEP reanalysis data were analyzed in order to provide distribution of global wind resource and wind speed in the surface layer for the years 2000-2009. Wind speed at 10 m above ground level (AGL) was converted to wind speed at 80 m above the ground level using the power law. The global average 80 m wind speed shows a maximum value of $13ms^{-1}$ at the storm track region. High wind speed over the land exists in Tibet, Mongolia, Central North America, South Africa, Australia, and Argentina. Wind speed over the ocean increased with a large value in the South China Sea, Southeast Asia, East Sea of the Korea. Sea surface wind in Western Europe and Scandinavia are suitable for wind farm with a value of $7-8ms^{-1}$. Areas with great potential for wind farm are also found in Eastern and Western coastal region of North America. Sea surface wind in Southern Hemisphere shows larger values in the high latitude of South America, South Africa and Australia. The distribution of low-resolution reanalysis data represents general potential areas for wind power and can be used to provide information for high-resolution wind resource mapping.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.147-147
• /
• 2017

본 연구에서는 2003년 태풍 'MAEMI'에 의해 피해를 가장 많이 입은 경남 마산시를 중심으로 폭풍해일 범람도를 작성하였다. 해양과 하천 하류부가 만나는 마산시에서는 해일, 조석, 하천을 동시에 고려해야 하므로 이에 대한 단계적 적용을 통해 범람 중첩효과를 검토하였다. 본 연구에 사용된 수치모델은 네덜란드 Deltares사에서 개발한 준3차원 해수유동 모델 Delft3D이다. Delft3D는 폭풍해일 이외 지진해일, 부유물 이송, 오염물 확산 등 다양한 분야에 적용 가능하며, 파랑, 조석력, 바람에 의한 전단력, 온도, 염도에 의한 밀도류, 대기압 변화, 조간대 모의 등 다양한 영향을 고려할 수 있다. 수치모의시 모델의 안정성과 효율성을 높이기 위해 다중격자기법을 사용(최소 25m 격자)하였으며, 수심 자료는 국토지리정보원 수치지도와 국립해양조사원 수치해도의 수평 수직적 통합을 통해 구성하였다. 태풍 'MAEMI'의 Best Track은 기상청에서 제공하는 3시간 간격의 중심기압, 풍속, 중심위치를 Holland's Model에 적용하여 계산하였다. 조석효과를 고려하기 위해 개방경계에서 TPXO 7.2를 사용한 분조값을 입력하였다. 또한 하천의 흐름을 효과적으로 구현하기 위해 하천 단면에서의 동적 수위경계조건(또는 유량경계조건)을 추가적으로 부여하였다. 수치해석결과, 마산 수위 관측소에서 관측된 태풍 'MAEMI'의 해일고와 유사한 결과가 산출되었다. 범람역 해석결과는 해일, 조석, 하천을 동시적으로 고려하였을 경우에 실제 침수흔적도인 마산시재해침수지도와 가장 유사한 결과를 보였다.

• Journal of Ocean Engineering and Technology
• /
• v.37 no.4
• /
• pp.158-163
• /
• 2023

Objects adrift can cause considerable damage to coastal infrastructure and property during tsunami and storm surge events. Despite the potential for harm, the drifting behavior of these objects remains poorly understood, thereby hindering effective prediction and mitigation of collision damage. To address this gap, this study employed a motion analysis program to track a drifting container's location using images from an existing laboratory experiment. The container's trajectory and velocity were calculated based on the positions of five markers strategically placed at its four corners and center. Our findings indicate that the container's maximum drift velocity and distance are directly influenced by the scale of the solitary wave and inversely related to the container's weight. Specifically, heavier containers are less likely to be displaced by solitary waves, while larger waves can damage coastal structures more. This study offers new insights into container drift behavior induced by solitary waves, with implications for enhancing coastal infrastructure design and devising mitigation strategies to minimize the risk of collision damage.