• Atmosphere
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• v.20 no.2
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• pp.91-100
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• 2010

In accordance with the time series of rainfall in summer (June, July and August) in South and North Korea for recent 28 years (1981-2008), rainfall is substantially increased in South Korea since 1996, while it is significantly decreased in North Korea. In particular, the decreasing tendency of rainfall in summer in North Korea is more definitely observed during the $2^{nd}$ rainy season (late August - mid September) in intraseasonal variation. Such a feature is also confirmed in the spatial distribution of oscillation pattern between South and North Korea on the basis of 1996 which is obtained by empirical orthogonal function analysis using the summer rainfall observed in all weather observation stations in South and North Korea. For the decreasing tendency of rainfall in North Korea, it is found that northeasterlies from anticyclonic circulation centered on around Baikal Lake weaken convective activity during summer. On the contrary, the increasing tendency of rainfall in South Korea is related to the strengthened cyclonic circulation in the southern region of China and accordingly, enhances southwesterlies in South Korea.

• Journal of Environmental Science International
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• v.29 no.11
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• pp.1141-1151
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• 2020

The impact of sound speed variability in the sea is the very important on acoustic propagation for the underwater acoustic systems. Understanding of the temporal and spatial variability of ocean sound speed in the sea around the Ieodo were obtained using oceanographic data (temperature, salinity). from the Korea Oceanographic Data Center, collected by season for 17 years. The vertical distributions of sound speed are mainly related to seasonal variations and various current such as Chinese coastal water, Yellow Sea Cold Water (YSCW), Kuroshio source water. The standard deviations show that great variations of sound speed exist in the upper layer and observation station between 16 and 18. In order to quantitatively explain the reason for sound speed variations, Empirical Orthogonal Function (EOF) analysis was performed on sound speed data at the Line 316 covering 68 cruises between 2002 and 2018. Three main modes of EOFs respectively revealed 55, 29, and 5% the total variance of sound speed. The first mode of the EOFs was associated with influence of surface heating. The second EOFs pattern shows that contributions of YSCW and surface heating. The first and second modes had seasonal and inter-annul variations.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.1-8
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• 2024

For measuring the performance of passive sonars, we usually consider the maximum Detection Range (DR) under the environment and system parameters in operation. In shallow water, where sound waves inevitably interacts with sea surface or bottom, detection generally maintains up to the maximum range. In deep water, however, sound waves may not interact with sea surface or/and bottom, and thus there may exist shadow zones where sound waves can hardly reach. In this situation, DR alone may not completely define the performance of each sonar. For complete description of sonar performance, we employ the concept 'Robustness Of Detection (ROD)'. In the coastal region of the East Sea, the spatial variations of water masses have close relations with DR and ROD, where the two parameters show reverse spatial variations in general. The spatial and temporal analysis of the temperature by employing the Empirical Orthogonal Function (EOF) shows that the 1-st mode represents typical pattern of seasonal variation and the 2-nd mode represents strength variations of mixed layers and currents. The two modes are estimated to explain about 92 % of the variations. Assuming two types of targets located at the depths of 5 m (shallow) and 100 m (deep), the passive sonar performance (DR) gives high negative correlations (about -0.9) with the first two modes. Most of temporal variations of temperature occur from the surface up to 200 m in the water column so that when we assume a target at 100 m, we can expect detection performance of little seasonal variations with passive sonars below 100 m.

• Ocean and Polar Research
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• v.30 no.3
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• pp.313-324
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• 2008

In order to understand the variation of ENSO-related oceanic environments in the tropical and North Pacific Ocean, spatio-temporal variations of sea surface temperature anomaly (SSTA) and sea surface height anomaly (SSHA) are analyzed from distributions of complex empirical orthogonal functions (CEOF). Correlations among warm pool variation, southern oscillation index, and ocean surface currents were also examined with respect to interannual variability of the warm pool in western tropical Pacific. Spatio-temporal distributions of the first CEOF modes for SSTA and SSHA indicate that their variabilities are associated with ENSO events, which have a variance over 30% in the North Pacific. The primary reasons for their variabilities are different; SST is predominantly influenced by the change of barrier layer thickness, while SSH fluctuates with the same phase as propagation of an ENSO episode in the zonal direction. Horizontal boundary of warm pool area, which normally centered around $149^{\circ}E$ in the tropics, seemed to be expanded to the middle and eastern tropical regions by strong zonal currents through the mature phase of an ENSO episode.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.282-282
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• 2016

지표수문해석모형이란 전 지구를 대상으로 수문해석 및 예측이 가능한 분포형 수문모형이다. 본 연구에서는 CSEOF(Cyclostationary Empirical Orthogonal Functions) 분석 방법을 이용하여 지표수문해석 모형 중 하나인 VIC(Variable Infiltration Capacity)모형의 토양수분 모의 성능을 평가해보고자 한다. 이를 위하여 먼저 남한에 대한 VIC 모형으로 모의한 토양수분 예측 결과와 관측자료를 수집하였다. 모의 성능 평가 기간은 1976년부터 2006년까지이다. 이후 본 연구에서는 수집된 VIC 모형의 예측 결과와 관측 자료에 대한 CSEOF 분석을 수행하여 각 자료의 월별 주된 변동 특성을 추출하였다. VIC 모형의 예측 결과와 관측자료의 상관관계는 CSEOF 분석 결과에 대한 Pattern Correlation으로 정량화되었다. 이와 더불어 본 연구에서는 모형의 모의 성능 평가에 주로 사용되는 NRMSE(Nomalized Root Mean Square Error)를 산정하여 예측 결과의 오차를 평가하였다. Pattern Correlation과 NRMSE를 모두 고려하여 VIC 모형의 성능을 평가해본 결과, 건기에 해당하는 기간과 우기에 해당하는 기간의 모의 성능이 다르게 나타났다. 본 연구의 결과는 추후에 지표수문해석 모형의 예측 결과를 이용하는 기후변화 관련 연구에 활용될 수 있을 것으로 판단된다.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.2
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• pp.939-951
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• 2019

A novel empirical mode decomposition strategy based on Fourier transform and band-pass filter techniques, contributing to efficient instantaneous vibration analyses, is developed in this study. Two key improvements are proposed. The first is associated with the adoption of a band-pass filter technique for intrinsic mode function sifting. The primary characteristic of decomposed components is that their bandwidths do not overlap in the frequency domain. The second improvement concerns an attempt to design narrowband constraints as the essential requirements for intrinsic mode function to make it physically meaningful. Because all decomposed components are generated with respect to their intrinsic narrow bandwidth and strict sifting from high to low frequencies successively, they are orthogonal to each other and are thus suitable for an instantaneous frequency analysis. The direct Hilbert spectrum is employed to illustrate the instantaneous time-frequency-energy distribution. Commendable agreement between the illustrations of the proposed direct Hilbert spectrum and the traditional Fourier spectrum was observed. This method provides robust identifications of vibration modes embedded in vibration processes, deemed to be an efficient means to obtain valuable instantaneous information.

• 한국해양학회지
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• v.24 no.1
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• pp.1-14
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• 1989

This study analyzes the interannual periodicity by using the statistical techniques of probability, spectral analysis, empirical orthogonal function analysis (EOF), and coherency analysis. The data base for this study is the time series of 1971-1985 temperature, salinity in the southern waters of the East Sea, 1960-1986 mean sea level at Pusan and Izuhara, and 1960-1986 sea level atmospheric pressure at Pusan. The appearances of anomalous temperatures higher and lower than 15-year mean monthly average with one standard deviation are about 30% of total data. The significant interannual period for temperature, salinity and sea level fluctuation is 36.6, and 23.3 months. The empirical orthogonal function analyses show that the 1st mode of the EOFs is responsible for more than 90% of total variance of the surface temperature variations, while in near-bottom waters, the relative importance of the higher EOF modes is much greater explaining more than 30% of total variance. The coherency between normalized temperatures and salinities is significant at the interannual period of 36.6 and 21.3 months.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.25-43
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• 2018

The effects of hydro-meteorological and surface variables on the frequency of Asian dust events (FAE) were investigated using ground station and satellite-based data. Present weather codes 7, 8, and 9 derived from surface synoptic observations (SYNOP)were used for counting FAE. Surface wind speed (SWS), air temperature (Ta), relative humidity (RH), and precipitation were analyzed as hydro-meteorological variables for FAE. The Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), and snow cover fraction (SCF) were used to consider the effects of surface variables on FAE. The relationships between FAE and hydro-meteorological variables were analyzed using Z-score and empirical orthogonal function (EOF) analysis. Although all variables expressed the change of FAE, the degrees of expression were different. SWS, LST, and Ta (indices applicable when Z-score was < 0) explained about 63.01, 58.00, and 56.17% of the FAE,respectively. For NDVI, precipitation, and RH, Asian dust events occurred with a frequency of about 55.38, 67.37, and 62.87% when the Z-scores were > 0. EOF analysis for the FAE showed the seasonal cycle, change pattern, and surface influences related to dryness condition for the FAE. The intensity of SWS was the main cause for change of FAE, but surface variables such as LST, SCF, and NDVI also were expressed because wet surface conditions suppress FAE. These results demonstrate that not only SWS and precipitation, but also surface variables, are important and useful precursors for monitoring Asian dust events.

• Korean Journal of Remote Sensing
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• v.21 no.6
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• pp.469-482
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• 2005

China Coastal Waters (CCW) usually appears in the seas surrounding Jeju Island annually(June to October) and is very pronounced in August. Generally, low-salinity water appears to the western seas of Jeju Island from June through October and gradually propagates to the eastern seas, where CCW meets the Tsushima Current. Empirical orthogonal function (EOF) analysis of SLAs and SSTs indicated that the variance in SLAs and SSTs was $95.01\%$(the first mode to third mode) and $98.09\%$(the first mode), respectively. The PSD of the western waters for the first mode of EOF analysis of SLAs was stronger than that of the eastern waters because of the influence of CCW. The PSD for the EOF analysis of SSTs was similar in all areas (the Yangtze Estuary and the seas to the west and east of Jeju Island), with a period of approximately 260 days.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.85-95
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• 2021

Recently, as data mining and artificial neural network techniques are developed, analyzing large amounts of data is proposed to reduce the dimension of the data. In general, empirical orthogonal function (EOF) used to reduce the dimension in the ocean data and recently, Self-organizing maps (SOM) algorithm have been investigated to apply to the ocean field. In this study, both algorithms used the monthly Sea level anomaly (SLA) data from 1993 to 2018 around the East Asia Coasts. There was dominated by the influence of the Kuroshio Extension and eddy kinetic energy. It was able to find the maximum amount of variance of EOF modes. SOM algorithm summarized the characteristic of spatial distributions and periods in EOF mode 1 and 2. It was useful to find the change of SLA variable through the movement of nodes. Node 1 and 5 appeared in the early 2000s and the early 2010s when the sea level was high. On the other hand, node 2 and 6 appeared in the late 1990s and the late 2000s, when the sea level was relatively low. Therefore, it is considered that the application of the SOM algorithm around the East Asia Coasts is well distinguished. In addition, SOM results processed by SLA data, it is able to apply the other climate data to explain more clearly SLA variation mechanisms.