• Title/Summary/Keyword: 풍향풍속계

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Oceanic Application of Satellite Synthetic Aperture Radar - Focused on Sea Surface Wind Retrieval - (인공위성 합성개구레이더 영상 자료의 해양 활용 - 해상풍 산출을 중심으로 -)

  • Jang, Jae-Cheol;Park, Kyung-Ae
    • Journal of the Korean earth science society
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    • v.40 no.5
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    • pp.447-463
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    • 2019
  • Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.

A Study on Course Stability of Towed Damaged-ship under Wind Pressure (풍압력하에서 피예항중인 손상선박의 침로안정성에 관한 연구)

  • K.H. Sohn;Y.K. Kim;S.G. Lee;K.S. Choi
    • Journal of the Society of Naval Architects of Korea
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    • v.37 no.2
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    • pp.46-56
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    • 2000
  • This paper is related with one of safety plans to rescue a damaged-ship whether by collision, grounding or internal accident. We discuss the problem on course stability of damaged-ship while towed under severe wind pressure. The characteristic equation to assess the stability on course, is derived from sway and yaw coupled motion of towing and towed vessels with wind effect. Through the numerical calculation on course stability of towing and towed vessels system, the relationship between the course stability of a towed damaged-ship and wind direction or towrope length, is clarified with the parameters of weather and damage conditions.

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Ocean Wind Retrieval from RADAR SAR images in Korean seas (SAR자료를 이용한 해상풍 산출 및 현장 자료간의 비교.검정)

  • Yoon Hong-Joo;Park Kwang-Soon;Kim Sang-Ik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.4
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    • pp.706-711
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    • 2006
  • In order to retrieve ocean wind from SAR() image, and to estimate and validate between SAR-derived wind and in-situ wind, with RADAR SAR ocean images and real time marine meteorological data. It was used images with more than 10km to analyze the band of wind in SAR image by FFT(First Fourier Transformation) method and was used CMOD5 as wind retrieval model to retrieve ocean wind. In this study, generally it showed good results as RMS presented 0.8m/s for speed and 8 degree for direction, and especially when wind was hish speed, it presented very good results.

L-band SAR-derived Sea Surface Wind Retrieval off the East Coast of Korea and Error Characteristics (L밴드 인공위성 SAR를 이용한 동해 연안 해상풍 산출 및 오차 특성)

  • Kim, Tae-Sung;Park, Kyung-Ae;Choi, Won-Moon;Hong, Sungwook;Choi, Byoung-Cheol;Shin, Inchul;Kim, Kyung-Ryul
    • Korean Journal of Remote Sensing
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    • v.28 no.5
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    • pp.477-487
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    • 2012
  • Sea surface winds in the sea off the east coast of Korea were derived from L-band ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) data and their characteristics of errors were analyzed. We could retrieve high-resolution wind vectors off the east coast of Korea including the coastal region, which has been substantially unavailable from satellite scatterometers. Retrieved SAR-wind speeds showed a good agreement with in-situ buoy measurement by showing relatively small an root-mean-square (RMS) error of 0.67 m/s. Comparisons of the wind vectors from SAR and scatterometer presented RMS errors of 2.16 m/s and $19.24^{\circ}$, 3.62 m/s and $28.02^{\circ}$ for L-band GMF (Geophysical Model Function) algorithm 2009 and 2007, respectively, which tended to be somewhat higher than the expected limit of satellite scatterometer winds errors. L-band SAR-derived wind field exhibited the characteristic dependence on wind direction and incidence angle. The previous version (L-band GMF 2007) revealed large errors at small incidence angles of less than $21^{\circ}$. By contrast, the L-band GMF 2009, which improved the effect of incidence angle on the model function by considering a quadratic function instead of a linear relationship, greatly enhanced the quality of wind speed from 6.80 m/s to 1.14 m/s at small incident angles. This study addressed that the causes of wind retrieval errors should be intensively studied for diverse applications of L-band SAR-derived winds, especially in terms of the effects of wind direction and incidence angle, and other potential error sources.

Experimental Study for the Capacity of Ordinary and Emergency Ventilation System in Deeply Underground Subway Station (대심도 지하역사 승강장 및 대합실 평상시/비상시 급·배기 풍량에 대한 실험적 연구)

  • Jang, Yong-Jun;Lee, Ho-Seok;Park, Duck-Shin
    • Journal of the Korean Society for Railway
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    • v.15 no.6
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    • pp.579-587
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    • 2012
  • Shin-gumho station in Seoul underground subway have been selected to be experimentally investigated and analyzed for the real air supply & exhaust capacity compared to the original capacity of ordinary and emergency condition. The depth of Shin-gumho station is 43.6m which consists of the island-type platform ($8^{th}$ floor in underground) and a two-story lobby (first & second floor in underground). An emergency staircase connects between the platform and the lobby. Hot-wire anemometer, capture hood, wind vane & velocity meter and data acquisition systems are employed to perform the automatic measurement in this experiment. For ordinary case, air supply and exhaust capacity in the lobby were reduced by 34% and 46% compared to the original capacity, respectively. Air supply and exhaust capacity in the platform were reduced by 66% and 38%, respectively. For emergency case, air supply in the lobby was reduced by 42% and air exhaust in the platform was reduced by 28% compared to the original capacity. Therefore, air pollution in the station is expected to be worse in the ordinary environment and smoke control capability in the platform will be weakened in case of fire emergency.

Behavior Character Analysis of Super Long Suspension Bridge using GNSS (GNSS를 활용한 초장대 현수교의 거동 특성 분석)

  • Park, Je-Sung;Hong, Seunghwan;Kim, Mi-Kyeong;Kim, Tai-Hoon;Sohn, Hong-Gyoo
    • Korean Journal of Remote Sensing
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    • v.35 no.5_2
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    • pp.831-840
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    • 2019
  • Recently, the span length of long-span bridges is getting longer. As a result, it has been suggested that a new concept called 'super long-span bridge'. In case of super long span bridges, the structure is being complicated and the importance of structural stability is being emphasized. However, until recently, the most commonly used sensors (dual axis clinometer, anemometer, strain gauge, etc.) have got limit about the bridge monitoring. Consequently, we researched the application of a Global Navigation Satellite System (GNSS) to improve the limit of the existing sensors. In this study, the dual axis clinometer, the anemometer and the strain gauge together with the GNSS were used to analyze the behavior of a super-long suspension bridge. Also, we propose the detailed method of bridge monitoring using the GNSS. This study consisted of three steps. First step calculated the absolute coordinates of the towers and the longitudinal axis direction of the study bridge using the GNSS. In second step, through the analysis of the long-term behavior in shortly after construction, we calculated the permanent displacement and evaluated the stability of main towers. Third step analyzed the behavior of bridge by the wind direction and was numerically indicated. Consequently, the bridge measurement using the GNSS appeared that the acquired data is able to easy processing according to the analysis purpose. If we will use together the existing measurement sensors with the GNSS on the maintenance of the super long-span bridge, we figure each error of measurement data and improve the monitoring system through calibration. As a result, we acquire the accurate displacement of bridge and figure the behavior of bridge. Consequently, we identified that it is able to construct the effective monitoring system.

An Analysis and Numerical Simulation on Southwestern Prevailing Wind Phenomenon around Pohang in Winter (포항지역의 겨울철 남서계열 탁월풍 현상에 관한 분석 및 수치모의)

  • Lee, Hwa-Woon;Kim, Hyun-Goo;Jung, Woo-Sik
    • Journal of the Korean earth science society
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    • v.24 no.6
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    • pp.533-548
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    • 2003
  • The prevailing wind phenomenon around Pohang in winter was investigated by using surface and vertical observatory datas and a numerical simulation was carried out to analyse this phenomenon using RAMS. Direction of the prevailing wind was westerly at upper atmosphere. However, near the surface, southwestern wind prevailed in winter. Using the RAMS to simulate a winter wind system numerically, it was found out that this phenomenon was strongly affected by the geographical features such as directions of coastline and low level valley, and distributions of land and sea. To investigate the accuracy of the model results, wind speed, temperature and wind direction of typical continuous southwestern wind occurring days were compared with observation data. Analyzing the characteristics of local circulation system was very hard because of horizontally sparse observation data. But from the result above, a numerical simulation using the RAMS, which satisfies the spatial high resolution, will provide more accurate results.

Characters of Mesoscale Convective Complex Development in Korean Peninsula (한반도 중규모 대류복합체의 발달특성에 관한 연구)

  • Lee Soon-Hwan;Won Hyo-Sung
    • Journal of the Korean earth science society
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    • v.26 no.7
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    • pp.698-705
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    • 2005
  • Heavy rain fall in the Korean Peninsula often occurs in the summer season due to MCC (Mesoscale Convective Complex) with complex mechanism. We analysed the Characteristics and the developing mechanism of MCC occurred at 14 July 2004. The results are as follows: a) There is strong wind inflow from the South-west china sea with heavy moisture and this moisture flux acts as the source of heavy rain, b) Because of the separation of upper and lower atmosphere due to an inversion layer at 600hPa, atmosphere over the Korea Peninsula is suddenly unstable. c) This MCC shows strong shear not with wind direction, but with the wind speed, and this wind shear continues the thermodynamic unstability of the convective system. d) MCC was suddenly developed over Heuksando at 1400LST 14 July 2004. Thus we can say that the topography also was strongly associated with the development of MCC and it is also necessary to clarify the relationship between topography and MCC development. in future research.

Water temperature prediction of Daecheong Reservoir by a process-guided deep learning model (역학적 모델과 딥러닝 모델을 융합한 대청호 수온 예측)

  • Kim, Sung Jin;Park, Hyungseok;Lee, Gun Ho;Chung, Se Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.88-88
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    • 2021
  • 최근 수자원과 수질관리 분야에 자료기반 머신러닝 모델과 딥러닝 모델의 활용이 급증하고 있다. 그러나 딥러닝 모델은 Blackbox 모델의 특성상 고전적인 질량, 운동량, 에너지 보존법칙을 고려하지 않고, 데이터에 내재된 패턴과 관계를 해석하기 때문에 물리적 법칙을 만족하지 않는 예측결과를 가져올 수 있다. 또한, 딥러닝 모델의 예측 성능은 학습데이터의 양과 변수 선정에 크게 영향을 받는 모델이기 때문에 양질의 데이터가 제공되지 않으면 모델의 bias와 variation이 클 수 있으며 정확도 높은 예측이 어렵다. 최근 이러한 자료기반 모델링 방법의 단점을 보완하기 위해 프로세스 기반 수치모델과 딥러닝 모델을 결합하여 두 모델링 방법의 장점을 활용하는 연구가 활발히 진행되고 있다(Read et al., 2019). Process-Guided Deep Learning (PGDL) 방법은 물리적 법칙을 반영하여 딥러닝 모델을 훈련시킴으로써 순수한 딥러닝 모델의 물리적 법칙 결여성 문제를 해결할 수 있는 대안으로 활용되고 있다. PGDL 모델은 딥러닝 모델에 물리적인 법칙을 해석할 수 있는 추가변수를 도입하며, 딥러닝 모델의 매개변수 최적화 과정에서 Cost 함수에 물리적 법칙을 위반하는 경우 Penalty를 추가하는 알고리즘을 도입하여 물리적 보존법칙을 만족하도록 모델을 훈련시킨다. 본 연구의 목적은 대청호의 수심별 수온을 예측하기 위해 역학적 모델과 딥러닝 모델을 융합한 PGDL 모델을 개발하고 적용성을 평가하는데 있다. 역학적 모델은 2차원 횡방향 평균 수리·수질 모델인 CE-QUAL-W2을 사용하였으며, 대청호를 대상으로 2017년부터 2018년까지 총 2년간 수온과 에너지 수지를 모의하였다. 기상(기온, 이슬점온도, 풍향, 풍속, 운량), 수문(저수위, 유입·유출 유량), 수온자료를 수집하여 CE-QUAL-W2 모델을 구축하고 보정하였으며, 모델은 저수위 변화, 수온의 수심별 시계열 변동 특성을 적절하게 재현하였다. 또한, 동일기간 대청호 수심별 수온 예측을 위한 순환 신경망 모델인 LSTM(Long Short-Term Memory)을 개발하였으며, 종속변수는 수온계 체인을 통해 수집한 수심별 고빈도 수온 자료를 사용하고 독립 변수는 기온, 풍속, 상대습도, 강수량, 단파복사에너지, 장파복사에너지를 사용하였다. LSTM 모델의 매개변수 최적화는 지도학습을 통해 예측값과 실측값의 RMSE가 최소화 되로록 훈련하였다. PGDL 모델은 동일 기간 LSTM 모델과 동일 입력 자료를 사용하여 구축하였으며, 역학적 모델에서 얻은 에너지 수지를 만족하지 않는 경우 Cost Function에 Penalty를 추가하여 물리적 보존법칙을 만족하도록 훈련하고 수심별 수온 예측결과를 비교·분석하였다.

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Mutual Adjustment of Oceanographic Measurements from leodo Station and Satellite Data (원격탐사자료와 이어도기지 해양관측자료를 이용한 상호 보정)

  • Kim Chang-Oh;Shim Jae-Seol;Hwang Jong-Sun;Lee Jae-Hak;Kim Soodung;Kim Jeong Woo
    • Korean Journal of Remote Sensing
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    • v.21 no.2
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    • pp.113-120
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    • 2005
  • Oceanographic measurements from Ieodo Ocean Research Station and its vicinity were compared for assessment and mutually adjusted with satellite data. From the Topex/Poseidon and ERS-1/2 radar altimeter and scatterometer data, sea surface height, wind speed and direction were extracted and analyzed. Shipborne wind direction data acquired in June 1995 show good coherence with the satellite data, while sea surface height and wind speed show differences, possibly resulting from the distance between the measurement points. This can be improved by analyzing more satellite data or using other available shipborne data. The recent 3 months of Ieodo Station data between December 2004 and February 2005 were also analyzed and compared with the satellite data. The Ieodo Station data were found to have considerable gaps during the period as well as seriously biased particular when the data were averaged with some abnormal data. The Ieodo Station and satellite data were then mutually adjusted on the basis of their statistics. Ieodo Station oceanographic measurements are very efficient for ground-frothing of satellite data because they are stationary and the station is located far from the coast. On the other hand, the satellite measurements are the only data to fill up gaps and adjust biases of the Ieodo Station data.