• Title/Summary/Keyword: 아극전선

Search Result 5, Processing Time 0.017 seconds

Underwater Acoustic Environment and Low Frequency Acoustic Transmission in the Sub-Polar Front Region of the East Sea (동해 아극전선 해역의 수중음향환경 및 저주파 음파전달 양상)

  • Lim, Se-Han;Ryu, Gun-Hee
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.12 no.4
    • /
    • pp.415-423
    • /
    • 2009
  • To investigate low frequency acoustic transmissions in the Sub-Polar Front(SPF) of the East Sea, numerical experiments are conducted with Range dependent Acoustic Model(RAM) using Circulation Research of the East Asian Marginal Seas(CREAMS) data and Autonomous Profiling Explorer(APEX)) data. Significant seasonal variations of sea water properties are existed across the Sub-Polar Front(SPF) region from the north and the south. The model results show that Transmission Loss(TL) decrease(about 20dB) with ideal front in the warm region whereas TL increase(about 25dB) with ideal front in the cold region. Regardless of season(both in summer and winter), when the sound source is located in the cold region of the SPF, the model results show weak TL, compared to the case of the source in the warm region(Maximum difference of TL reaches 28dB). This difference between the cases when the source is located in the cold region and the warm region, is accounted for from the different vertical profiles of sound speed in both regions.

Temporal and spatial variations of SST and Ocean Fronts in the Korean Seas by Empirical Orthogonal Function (경험직교함수 분석에 의한 한반도 주변해역의 해수면온도 및 수온 전선의 시.공간 변화)

  • Yoon Hong-Joo;Byun Hye-Kyung
    • Proceedings of the KSRS Conference
    • /
    • 2006.03a
    • /
    • pp.101-104
    • /
    • 2006
  • In the Korean seas, Sea Surface Temperature (SST) and Thermal Fronts (TF) were analyzed temporally and spatially during 8 years from 1993 to 2000 using NOAA/AVHRR MCSST. As the result of EOF method applying SST, the variance of the 1st mode was 97.6%. It is suitable to explain SST conditions in the whole Korean seas. Time coefficients were shown annual variations and spatial distributions were shown the closer to the continent the higher SST variations like as annual amplitudes. The 2nd mode presented higher time coefficients of 1993, 94, and 95 than those of other years. Although the influence is a little, that can explain ElNINO effect to the Korean seas. TF were detected by Sobel Edge Detection Method using gradient of SST. Consequently, TF were divided into 4 fronts; the Subpola. Front (SPF) dividing into the north and south part of the East sea, the Kuroshio Front (KF) in the East China Sea (ESC), the South Sea Coastal Front (SSCF) in the South sea, and the Tidal Front in the West sea. TF located in steep slope of submarine topography. The distributions of 1st mode in SST were bounded in the same place, and these results should be considered to influence of seasonal variations. To discover temporal and spatial variations of TF,SST gradient values were analyzed by EOF. The time coefficients fo the 1st mode (variance : 64.55%) showed distinctive annual variations and SPF, KF, and SSCF was significantly appeared in March. the spatial distributions of the 2nd mode showed contrast distribution, as SPF and SSCF had strong '-' value, where KF had strong '+' value. The time of '+' and '-' value was May and October, respectively. Time coefficients of the 3rd mode had 2 peaks per year and showed definite seasonal variations. SPF represented striking '+' value which time was March and October That was result reflected time of the 1st and 2nd mode. We can suggest specific temporal and spatial variations of TF using EOF.

  • PDF

Temporal and spatial variations of SST and Ocean Fronts in the Korean Seas by Empirical Orthogonal Function (경험 직교함수 분석에 의한 한반도 주변해역의 해수면온도 및 수온 전선의 시${\cdot}$공간 변화)

  • Yoon, Hong-Joo;Byun, Hye-Kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • v.9 no.1
    • /
    • pp.397-402
    • /
    • 2005
  • In the Korean seas, Sea Surface Temperature (SST) and Thermal Fronts (TF) were analyzed temporally and spatially during 8 years from 1993 to 2000 using NOAA/AVHRR MCSST As the result of EOF method applying SST, the variance of the 1st mode was 97.6%. It is suitable to explain SST conditions in the whole Korean seas. Time coefficients were shown annual variations and spatial distributions were shown the closer to the continent the higher SST variations like as annual amplitudes. The 2nd mode presented higher time coefficients of 1993, 94, and 95 than those of other years. Although the influence is a little, that tan explain EININO effort to the Korean seas. TF were detected by Sobel Edge Detection Method using gradient of SST. Consequently, TF were divided into 4 fronts; the Subpolar Front (SPF) dividing into the north and south part of the East sea , the Kuroshio Front (KF) in the East China Sea (ESC), the South Sea Coastal Front (SSCF) in the South sea, and the Tidal Front in the West sea. TF located in steep slope of submarine topography. The distributions of 1st mode in SST were bounded in the same place, and these results should be considered to influence of seasonal variations. To discover temporal and spatial variations of TF, SST gradient values were analyzed by EOF. The time coefficients fo the 1st mode (variance : 64.55%) showed distinctive annual variations and SPF, KF, and SSCF was significantly appeared in March. the spatial distributions of the 2nd mode showed contrast distribution, as SPF and SSCF had strong'-'value, where KF had strong'+'value. The time of'+'and'-'value was May and October, respectively. Time coefficients of the 3rd mode had 2 peaks per year and showed definite seasonal variations. SPF represented striking'+'value which time was March and October. That was result reflected time of the 1st and 2nd mode. We can suggest specific temporal and spatial variations of TF using EOF.

  • PDF

Study on the Front Detection Techniques by using Satellite Data (위성 자료를 이용한 전선 탐지 기법 연구)

  • Hwang, Do-Hyun;Bak, Su-Ho;Enkhjargal, Unuzaya;Jeong, Min-Ji;Kim, Na-Kyeong;Park, Mi-So;Kim, Bo-Ram;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.15 no.6
    • /
    • pp.1201-1208
    • /
    • 2020
  • A mass of seawater with similar properties in the ocean is called a water mass, and the front is a sea area where two masses of different properties meet. The gradient algorithm is a method of extracting where the sea water temperature pixel changes rapidly assuming that the slope is large, and the place with the large slope is assumed to be a front. This method is able to process large amounts of satellite data at once. Therefore, in this study, we tried to find the front lines in the sea area around the Korean Peninsula by using a gradient algorithm. The study data used gridded sea surface temperature satellite data. The resolution was 1/4°, and the monthly average data from January 1993 to December 2018 were used. There were major five fronts representatively, China Coastal Front, South Sea Coastal Front, Kuroshio Front/ Kuroshio Extension Front, Subpolar Front and the Subarctic Front. As a result of comparing the distribution of front by season, more types of front were distributed in winter and spring than in summer and autumn, and the distribution range was wider.

Statistical Characteristics of East Sea Mesoscale Eddies Detected, Tracked, and Grouped Using Satellite Altimeter Data from 1993 to 2017 (인공위성 고도계 자료(1993-2017년)를 이용하여 탐지‧추적‧분류한 동해 중규모 소용돌이의 통계적 특성)

  • LEE, KYUNGJAE;NAM, SUNGHYUN;KIM, YOUNG-GYU
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
    • /
    • v.24 no.2
    • /
    • pp.267-281
    • /
    • 2019
  • Energetic mesoscale eddies in the East Sea (ES) associated with strong mesoscale variability impacting circulation and environments were statistically characterized by analyzing satellite altimeter data collected during 1993-2017 and in-situ data obtained from four cruises conducted between 2015 and 2017. A total of 1,008 mesoscale eddies were detected, tracked, and identified and then classified into 27 groups characterized by mean lifetime (L, day), amplitude (H, m), radius (R, km), intensity per unit area (EI, $cm^2/s^2/km^2$), ellipticity (e), eddy kinetic energy (EKE, TJ), available potential energy (APE, TJ), and direction of movement. The center, boundary, and amplitude of mesoscale eddies identified from satellite altimeter data were compared to those from the in-situ observational data for the four cases, yielding uncertainties in the center position of 2-10 km, boundary position of 10-20 km, and amplitude of 0.6-5.9 cm. The mean L, H, R, EI, e, EKE, and APE of the ES mesoscale eddies during the total period are $95{\pm}104$ days, $3.5{\pm}1.5cm$, $39{\pm}6km$, $0.023{\pm}0.017cm^2/s^2/km^2$, $0.72{\pm}0.07$, $23{\pm}21TJ$, and $588{\pm}250TJ$, respectively. The ES mesoscale eddies tend to move following the mean surface current rather than propagating westward. The southern groups (south of the subpolar front) have a longer L, larger H, R, and higher EKE, APE; and stronger EI than those of the northern groups and tend to move a longer distance following surface currents. There are exceptions to the average characteristics, such as the quasi-stationary groups (the Wonsan Warm, Wonsan Cold, Western Japan Basin Warm, and Northern Subpolar Frontal Cold Eddy groups) and short-lived groups with a relatively larger H, higher EKE, and APE and stronger EI (the Yamato Coastal Warm, Central Yamato Warm, and Eastern Japan Basin Coastal Warm eddy groups). Small eddies in the northern ES hardly resolved using the satellite altimetry data only, were not identified here and discussed with potential over-estimations of the mean L, H, R, EI, EKE, and APE. This study suggests that the ES mesoscale eddies 1) include newly identified groups such as the Hokkaido and the Yamato Rise Warm Eddies in addition to relatively well-known groups (e.g., the Ulleung Warm and the Dok Cold Eddies); 2) have a shorter L; smaller H, R, and lower EKE; and stronger EI and higher APE than those of the global ocean, and move following surface currents rather than propagating westward; and 3) show large spatial inhomogeneity among groups.