• 제목/요약/키워드: storm prediction

검색결과 139건 처리시간 0.024초

Hindcasting of Storm Surge at Southeast Coast by Typhoon Maemi

  • KAWAI HIROYASU;KIM DO-SAM;KANG YOON-KOO;TOMITA TAKASHI;HIRAISHI TETSUYA
    • 한국해양공학회지
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    • 제19권2호
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    • pp.12-18
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    • 2005
  • Typhoon Maemi landed on the southeast coast of Korea and caused a severe storm surge in Jinhae Bay and Masan Bay. The tide gage in Masan Port recorded the storm surge of a maximum of more than 2m and the area of more than 700m from the Seo Hang Wharf was flooded by the storm surge. They had not met such an extremely severe storm surge since the opening of the port. Then storm surge was hindcasted with a numerical model. The typhoon pressure was approximated by Myers' empirical model and super gradient wind around the typhoon eye wall was considered in the wind estimation. The land topography surrounding Jinhae Bay and Masan Bay is so complex that the computed wind field was modified with the 3D-MASCON model. The motion of seawater due to the atmospheric forces was simulated using a one-layer model based on non-linear long wave approximation. The Janssen's wave age dependent drag coefficient on the sea surface was calculated in the wave prediction model WAM cycle 4 and the coefficient was inputted to the storm surge model. The result shows that the storm surge hindcasted by the numerical model was in good agreement with the observed one.

RELATIONSHIPS OF THE SOLAR WIND PARAMETERS WITH THE MAGNETIC STORM MAGNITUDE AND THEIR ASSOCIATION WITH THE INTERPLANETARY SHOCK

  • OH SU YEON;YI YU
    • 천문학회지
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    • 제37권4호
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    • pp.151-157
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    • 2004
  • It is investigated quantitative relations between the magnetic storm magnitude and the solar wind parameters such as the Interplanetary Magnetic Field (hereinafter, IMF) magnitude (B), the southward component of IMF (Bz), and the dynamic pressure during the main phase of the magnetic storm with focus on the role of the interplanetary shock (hereinafter, IPS) in order to build the space weather fore-casting model in the future capable to predict the occurrence of the magnetic storm and its magnitude quantitatively. Total 113 moderate and intense magnetic storms and 189 forward IPSs are selected for four years from 1998 to 2001. The results agree with the general consensus that solar wind parameter, especially, Bz component in the shocked gas region plays the most important role in generating storms (Tsurutani and Gonzales, 1997). However, we found that the correlations between the solar wind parameters and the magnetic storm magnitude are higher in case the storm happens after the IPS passing than in case the storm occurs without any IPS influence. The correlation coefficients of B and $BZ_(min)$ are specially over 0.8 while the magnetic storms are driven by IPSs. Even though recently a Dst prediction model based on the real time solar wind data (Temerin and Li, 2002) is made, our correlation test results would be supplementary in estimating the prediction error of such kind of model and in improving the model by using the different fitting parameters in cases associated with IPS or not associated with IPS rather than single fitting parameter in the current model.

How to forecast solar flares, solar proton events, and geomagnetic storms

  • Moon, Yong Jae
    • 천문학회보
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    • 제38권2호
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    • pp.33-33
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    • 2013
  • We are developing empirical space weather (solar flare, solar proton event, and geomagnetic storm) forecast models based on solar data. In this talk we will review our main results and recent progress. First, we have examined solar flare (R) occurrence probability depending on sunspot McIntosh classification, its area, and its area change. We find that sunspot area and its increase (a proxy of flux emergence) greatly enhance solar flare occurrence rates for several sunspot classes. Second, a solar proton event (S) forecast model depending on flare parameters (flare strength, duration, and longitude) as well as CME parameters (speed and angular width) has been developed. We find that solar proton event probability strongly depends on these parameters and CME speed is well correlated with solar proton flux for disk events. Third, we have developed an empirical storm (G) forecast model to predict probability and strength of a storm using halo CME - Dst storm data. For this we use storm probability maps depending on CME parameters such as speed, location, and earthward direction. We are also looking for geoeffective CME parameters such as cone model parameters and magnetic field orientation. We find that all superstorms (less than -200 nT) occurred in the western hemisphere with southward field orientations. We have a plan to set up a storm forecast method with a three-stage approach, which will make a prediction within four hours after the solar coronagraph data become available. We expect that this study will enable us to forecast the onset and strength of a geomagnetic storm a few days in advance using only CME parameters and the WSA-ENLIL model. Finally, we discuss several ongoing works for space weather applications.

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시행 착오법을 활용한 재난 위험도 예측모델 개발 : 폭풍해일 (Development for Prediction Model of Disaster Risk through Try and Error Method : Storm Surge)

  • 김동현;유형주;정석일;이승오
    • 한국방재안전학회논문집
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    • 제11권2호
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    • pp.37-43
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    • 2018
  • 태풍에 의해 발생하는 폭풍해일은 태풍의 경로, 강도, 발생위치 등을 예측하기가 어려운 실정이기 때문에 발생 시나리오를 기반으로 연구가 수행되어왔다. 국내는 다양한 시나리오에 대해 수치모의를 수행하였고 그 결과를 침수 예측지도로 제작하였다. 하지만, 이 같은 방법은 수행한 시나리오 외에 발생가능한 모든 경우에 대해 예측하기 어렵고, 실제로 수치모의 수행시간이 길기 때문에 실시간으로 대응하기 어렵다는 단점이 있다. 따라서 본 연구에서는 기존의 데이터베이스를 활용하여 폭풍해일의 위험도를 예측하는 방법을 개발하였다. 동해안 지역을 대상으로 폭풍해일에 의한 위험도 예측을 수행하였고 예측을 위한 방정식을 산정하기 위해 COMSOL AB사에서 개발한 COMSOL을 이용하였다. 몇 가지 가정사항과 제한조건으로 기본방정식을 유도하였으며 방정식의 계수와 상수는 시행착오법으로 도출하였다. 그 결과, 해일에 의한 침수 예측지도와 공간적 분포는 지도의 상부를 제외하면 매우 유사하게 나타났다. 오차가 큰 지도 상부의 경우 기초 데이터로 사용한 지도의 해상도로 인해 저항상수 k의 값이 제대로 반영되지 못한 것으로 판단된다. SIND 모형은 실시간 예측이 가능한 모형으로 향후 모형의 정확성을 향상시킨다면 이상기후로 인해 재난이 발생하였을 경우 빠르게 대처가 가능할 것으로 기대된다.

합성태풍과 인공지능을 활용한 폭풍해일고 예측 (Prediction of Storm Surge Height Using Synthesized Typhoons and Artificial Intelligence)

  • 엄호식;박종집;정광영;박영민
    • 해양환경안전학회지
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    • 제26권7호
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    • pp.892-903
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    • 2020
  • 태풍 내습 시 신속하고 정확한 해일고 예측은, 연안재해 대응에 필수적인 요소이다. 이러한 해일고의 예측을 위해서 기존에는 태풍예측정보를 수치모델에 적용하여 예측자료를 생산하는 것이 대부분 이였다. 이러한 방법은 대용량의 컴퓨팅 자원과 시간이 소요된다는 단점이 있다. 최근에는 인공지능 기반으로 신속하게 예측자료를 생산하는 연구가 다양한 분야에서 진행되고 있으며, 본 연구에서는 인공지능 기반 해일고 예측을 수행하였다. 인공지능 적용을 위해서는 많은 수의 학습자료가 필요하게 되며, 기왕 발생태풍은 개수가 한정되어 있어 본 연구에서는 TCRM(Tropical Cyclone Risk Model)을 통하여 합성태풍을 생성하고, 이를 폭풍해일 모델에 적용하여 해일고 자료를 생성한 후, 학습자료로 활용하였다. 인공지능으로 예측한 해일고와 실제 발생 태풍에 대한 비교 결과, RMSE(Root Mean Square Error)는 0.09 ~ 0.30 m, CC(Correlation Coefficient)는 0.65 ~ 0.94, 최대 해일고의 ARE(Absolute Relative Error)는 1.0 ~ 52.5 %로 분석되었다. 특정 태풍/지점에서는 다소 오차가 크게 나타나고 있으나, 향후 학습자료의 최적화 등을 통하여 정확도를 개선할 수 있을 것으로 기대된다.

랜덤하중에서의 균열전파속도 추정법에 관한 연구 (A Prediction of Crack Propagation Rate under Random Loading)

  • 표동근;안태환
    • 한국해양공학회지
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    • 제8권2호
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    • pp.115-123
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    • 1994
  • Under variable amplitude loading conditions, retardation or accelerated condition of fatigue crack growth occurs with every cycle, Because fatigue crack growth behavior varied depend on load time history. The modeling of stress amplitude with storm loading acted to ships and offshore structures applied this paper. The crack closure behavior examine by recording the variation in load-strain relationship. By taking process mentioned above, fatigue crack growth rate, crack length, stress intensity factor, and crack closure stress intensity factor were obtained from the stress cycles of each type of storm ; A(6m), B(7m), C(8m), D(9m), E(11m) and F(15m) which was wave height. It showed that the good agreement with between the experiment results and simulation of storm loads. So this estimated method of crack propagtion rate gives a good criterion for the safe design of vessels and marine structure.

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바이모달 트램 모의운행지역에서의 강우에 대한 노선침수 예측 (Prediction of Lane Flooding on a Model Site for Rainfall Safety of Rubber-tired Tram)

  • 박영곤;윤희택;임경재;김종건;박윤식;김태희
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2007년도 추계학술대회 논문집
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    • pp.1209-1212
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    • 2007
  • Urban flooding with surcharges in sewer system was investigated because of unexpected torrential storm events these days, causing significant amounts of human and economic damages. Although there are limitations in forecasting and preventing natural disasters, integrated urban flooding management system using the SWMM(Storm Water Management Model) engine and Web technology will be an effective tool in securing safety in operating rubber-tired transportation system. In this study, the study area, located in Chuncheon, Kangwon province, was selected to evaluate the applicability of the SWMM model in forecasting urban flooding due to surcharges in sewer system The catchment are 21.10 ha in size and the average slope is 2% in lower flat areas. Information of subcatchment, conjunctions, and conduits was used as the SWMM interface to model surface runoff generation, water distribution through the sewer system and amount of water overflow. Through this study, the applicability of the SWMM for urban flooding forecasting was investigated and probability distribution of storm events module was developed to facilitate urban flooding prediction with forecasted rainfall amounts. In addition, this result can be used to the establishment of disaster management system for rainfall safety of rubber-tired tram in the future.

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웹 서비스 기반 GIS 연동 폭풍.해일 시각화 시스템 개발 (Development of a Web Service based GIS-Enabled Storm-surge Visualization System)

  • 김진아;박진아;박광순;권재일
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제14권9호
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    • pp.841-849
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    • 2008
  • 최근 지구온난화 및 해수면 상승으로 인한 태풍의 내습빈도와 강도의 증가로 태풍 내습시 연안지역의 침수 범람과 같은 자연재해로 인한 국민의 재산과 인명 피해가 급증하고 있다. 이에 폭풍 해일 예측을 위한 수치모델의 수립과 개선을 통하여 해일의 높이 및 발생시간, 해일로 인한 침수.범람 지역을 보다 과학적으로 정확하게 예측하려는 연구가 활발히 진행되고 있다. 따라서 본 논문에서는 이러한 예측결과를 일반 국민들에게 보다 효과적으로 전달하여, 연안재해로 인한 피해를 예방하기 위하여 웹 서비스 기반 GIS 연동 폭풍 해일 시각화 시스템을 개발하였다. 또한 수치모델의 정확한 예측결과 및 연안지역의 정밀 지리정보 구축을 위하여 LiDAR 자료를 이용한 GIS 기반 육도-해도 접합을 통한 연안지역 정밀해상도의 DEM을 생성하였다.