• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.3
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• pp.255-269
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• 2023

Surface water temperature of a bay (from the south to the north) increases in spring and summer, but decreases in autumn and winter. Due to shallow water depth, freshwater outflow, and weak current, the water temperature in the central to northern part of the bay is greatly affected by the land coast and air temperature, with large fluctuations. Water temperature variations are large in the north-east coast of the bay, but small in the south-west coast. The difference between water temperature and air temperature is greater in winter and in the south-central part of the bay than that in the north to the eastern coast of the bay where sea dykes are located. As the bay goes from south to north, the range of water temperature fluctuation and the phase show increases. When fresh water is released from the sea dike, the surrounding water temperature decreases and then rises, or rises and then falls. The first mode of empirical orthogonal function (EOF) represents seasonal variation of water temperature. The second mode represents the variability of water temperature gradient in east-west and north-south directions of the bay. In the first mode, the maximum and the minimum are shown in autumn and summer, respectively, consistent with seasonal distribution of surface water temperature variance. In the second mode, phases of the coast of Seosan~Boryeong and the east coast of Anmyeon Island are opposite to each other, bordering the center of the deep bay. Periodic fluctuation of the first mode time coefficient dominates in the one-day and half-day cycle. Its daily fluctuation pattern is similar to air temperature variation. Sea conditions and topographical characteristics excluding air temperature are factors contributing to the variation of the second mode time coefficient.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.295-303
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• 2010

The variability of vegetation is strongly related to the variability of hydrometeorological factors such as precipitation, temperature, runoff and so on. Analysis of the variability of vegetation will aid to understand the regional impact of climate change. Thus we analyzed the spatial-temporal variability of NOAA(National Oceanic and Atmospheric Administration)/AVHRR(Advanced Very High Resolution Radiometer) NDVI(Normalized Difference Vegetation Index). In the results from Mann-Kendall test, there is no significant linear trend of annual NDVI from 1982 to 2006 in the most area except the downward trend on the significance level 90% in the Guem-river basin area. In addition, using EOF(Empirical Orthogonal Function) analysis, the variability of NDVI in the region of higher latitude and altitude is higher than that in the other region since the spatial variability of NDVI follows the latitudinal gradient. Also we could get higher NDVI in June, July, August and September. We had the highest NDVI in Han-river basin area and the lowest in Je-Ju island.

• Proceedings of the KSRS Conference
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• v.1
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• pp.450-453
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• 2006

Hydrographic data including particulate organic carbon (POC) from the Northeastern Gulf of Mexico (NEGOM) study were used along with remotely sensed data obtained from NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to develop POC algorithms to estimate POC concentration based on empirical and model-based principal component analysis (PCA) methods. In Case I and II waters empirical maximized simple ratio (MSR) and model-based PCA algorithms using full wavebands (blue, green and red wavelengths) provide more robust estimates of POC. The predicted POC concentrations matched well the spatial and seasonal distributions of POC measured in situ in the Gulf of Mexico. The ease in calculating the MSR algorithm compared to PCA analysis makes MSR the preferred algorithm for routine use. In order to determine the inter-annual variations of POC, MSR algorithms applied to calculate 100 monthly mean values of POC concentrations (September 1997-December 2005). The spatial and temporal variations of POC and sea surface temperature (SST) were analyzed with the empirical orthogonal function (EOF) method. POC estimates showed inter-annual variation in three different locations and may be affected by El $Ni{\tilde{n}}o/Southern$ Oscillation (ENSO) events.

• Atmosphere
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• v.21 no.2
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• pp.143-149
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• 2011

A new multi-timescale analysis method, Ensemble Empirical Mode Decomposition (EEMD), is used to diagnose the variation of the MJO activity determined by 850hPa and 200hPa zonal winds from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data for the 56-yr period from 1950 to 2005. The results show that MJO activity can be decomposed into 9 quasi-periodic oscillations and a trend. With each level of contribution of the quasi-periodic oscillation discussed, the bi-seasonal oscillation, the interannual oscillation and the trend of the MJO activity are the most prominent features. The trend increases almost linearly, so that prior to around 1978 the activity of the MJO is lower than that during the latter part. This may be related to the tropical sea surface temperature(SST). It is speculated that the interdecadal change in the MJO activity appeared in around 1978 is related to the warmer SST in the equatorial warm pool, especially over the Indian Ocean.

• Proceedings of the KSRS Conference
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• v.1
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• pp.344-347
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• 2006

China Coastal Water (CCW) usually appears in the seas surrounding Jeju Island annually (June?October) and is very pronounced in August. The power spectrum density (PSD), sea level anomalies (SLAs), and sea surface temperatures (SSTs) were found to peak annually and semiannually. The peaks at intervals of 80-, 60-, and 43-days are considered to be influenced by CCW and the Kuroshio Current. Generally, low-salinity water appears to the west of Jeju Island from June through October and gradually propagates to the east, where CCW meets the Tsushima Current. Empirical orthogonal function (EOF) analysis of SLAs and SSTs indicated that the variance in SLAs and SSTs was 55.70 and 98.09% in the first mode, respectively. The PSD for the first mode of EOF analysis of SLAs was stronger in the western than in 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 waters to the west and east of Jeju Island), with a period of approximately 260 days.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.433-438
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• 2002

연안역의 천해 해저면에 설치된 ADCP(Acoustic Doppler Current Profiler, 300kHz, 1200kHz)를 이용, 천해에서 체적 산란강도(volume scattering strength) 수직분포의 시간적인 변동 특성을 알아보았다. 수심 85m와 113m에서 ADCP로 측정한 산란강도의 일주기 변동성은 동물플랑크톤(zooplankton)으로 추측되는 산란체의 일주기 수직 이동(daily vertical migration)의 원인으로 추정되었다. 그러나 수심 20m의 천해에서 관측된 산란강도의 시변동성은 경험적 직교 함수(Empirical Orthogonal Function, EOF) 분석 결과 해저면 부근의 변화가 천해 체적 산란의 변동성에 큰 영향을 주는 것으로 나타났다.

• Journal of the Korean earth science society
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• v.40 no.5
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• pp.476-486
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• 2019

This study examines the controlling role of synoptic disturbances on $PM_{10}$ spring variability in the Korean Peninsula by using empirical orthogonal function (EOF) and back trajectory analyses. Three leading EOF modes are identified, and a lead-lag analysis suggests that $PM_{10}$ variabilities be closely related to the synoptic weather systems. The first EOF shows the spatially homogeneous distribution of $PM_{10}$, which is influenced by travelling anticyclonic disturbance with negative precipitation and descending motion. The second and third modes exhibit the dipole structures of $PM_{10}$, being associated with propagating cyclones. Furthermore, the back-trajectory analysis suggests that the transport of pollutants by anomalous winds associated with synoptic disturbances also contribute to the altered $PM_{10}$ concentration. Hence, a substantial synoptic control should be considered in order to fully understand the $PM_{10}$ spatiotemporal variability.

• Journal of the Korean earth science society
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• v.30 no.6
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• pp.721-733
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• 2009

A pattern of tropical cyclone (TC) movement in the western North Pacific area was studied using the empirical orthogonal function (EOF) and the best track data from 1951 to 2007. The independent variable used in this study was defined as the frequency of tropical cyclone passage in 5 by 5 degree grid. The $1^{st}$, $2^{nd}$ and $3^{rd}$ modes were the east-west, north-south and diagonal variation patterns. Based on the time series of each component, the signs of first and second mode changed in 1997 and 1991, respectively, which seems to be related to the fact that the passage frequency was higher in the South China Sea for 20 years before 1990s, and recent 20 years in the East Asian area. When the eigen vectors were negative values in the first and second modes and TC moves into the western North Pacific, TC was formed mainly at the east side relatively compared to the case of the positive eigen vectors. The first mode seems to relate to the pressure pattern at the south of Lake Baikal, the second mode the variation pattern around $30^{\circ}N$, and the third mode the pressure pattern around Japan. The first mode was also closely related to the ENSO and negatively related to the $Ni\tilde{n}o$-3.4 index in the correlation analysis with SST anomalies.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.4
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• pp.225-242
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• 2012

This is the first attempt to produce simultaneous surface current field from satellite altimeter data for the entire East Sea and to provide surface current information to users with formal description. It is possible to estimate surface geostrophic current field in near real-time because satellite altimeters and coastal tide gauges supply sea level data for the whole East Sea. Strength and location of the major currents and meso-scale eddies can be identified from the estimated surface geostrophic current field. The mean locations of major surface currents were explicated relative to topographic, ocean-surface and undersea features with schematic representation of surface circulation. In order to demonstrate the practical use of this surface current information, exemplary descriptions of annual, seasonal and monthly mean surface geostrophic current distributions were presented. In order to objectively classify surface circulation patterns in the East Sea, empirical orthogonal function (EOF) analysis was performed on the estimated 16-year (1993-2008) surface current data. The first mode was associated with intensification or weakening of the East Korea Warm Current (EKWC) flowing northward along the east coast of Korea and of the anti-cyclonic circulation southwest of Yamato Basin. The second mode was associated with meandering paths of the EKWC in the southern East Sea with wavelength of 300 km. The first and second modes had inter-annual variations. The East Sea surface circulation was classified as inertial boundary current pattern, Tsushima Warm Current pattern, meandering pattern, and Offshore Branch pattern by the time coefficient of the first two EOF modes.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.20 no.2
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• pp.89-94
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• 1987

The fluctuations of sea surface temperatures (SST) and their anomalies in the Tsushima Current region are studied by means of empirical orthogonal function (EOF) analysis of the monthly SST data for 30 years (1941-1970) at 8 coastal stations. The overall features of the seasonal variation of SST are described by the first EOF mode, which explains $97.2\%$ of the total variance. Annual ranges of seasonal variation of SST and root-mean-square amplitudes of SST anomalies in the downstream of the Tsushima Current are larger than those in the upstream. The SST anomalies in the Tsushima Current region consist of simultaneous fluctuations, which explain $40.9\%$ of the total variance, and 'see-saw' fluctuations of which rise and fall in the upstream are opposite to those in the downstream. The latter second EOF mode explains $19.3\%$ of the total variance. We generated the low-pass (periods longer than 24 months), band-pass (periods between 6 and 24 months) and high-pass (periods shorter than 6 months) SST anomaly series and analyzed them by EOF method. The spatial distributions of the first and second EOF modes of all filtered SST anomalies are similar to each other.