• Journal of Korean Association for Spatial Structures
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• v.19 no.2
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• pp.101-108
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• 2019

In this paper, the characteristic of intrinsic mode function(IMF) and its orthogonalization of ensemble empirical mode decomposition(EEMD), which is often used in the analysis of the non-linear or non-stationary signal, has been studied. In the decomposition process, the orthogonal IMF of EEMD was obtained by applying the Gram-Schmidt(G-S) orthogonalization method, and was compared with the IMF of orthogonal EMD(OEMD). Two signals for comparison analysis are adopted as the analytical test function and El Centro seismic wave. These target signals were compared by calculating the index of orthogonality(IO) and the spectral energy of the IMF. As a result of the analysis, an IMF with a high IO was obtained by GSO method, and the orthogonal EEMD using white noise was decomposed into orthogonal IMF with energy closer to the original signal than conventional OEMD.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1143-1152
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• 2009

A canonical correlation analysis(CCA)-based method is proposed for prediction of future climate change which combines information from ensembles of atmosphere-ocean general circulation models(AOGCMs) and observed climate values. This paper focuses on predictions of future climate on a regional scale which are of potential economic values. The proposed method is obtained by coupling the classical CCA with empirical orthogonal functions(EOF) for dimension reduction. Furthermore, we generate a distribution of climate responses, so that extreme events as well as a general feature such as long tails and unimodality can be revealed through the distribution. Results from real data examples demonstrate the promising empirical properties of the proposed approaches.

• Proceedings of the KSRS Conference
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• v.2
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• pp.913-916
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• 2006

Spatial distribution, seasonal and interannual variability of chlorophyll a concentration in Okhotsk Sea from SeaWiFS data between 2001 and 2004 were describe. An Empirical Orthogonal Function method was applied for analysis data. The ten modes described about 85% of total variance. Two maxima were defined - more intensive in spring and weaker in autumn. The first mode showed zones with chlorophyll a concentration during maximum bloom. The second mode specified timing of spring bloom in various regions in Okhotsk Sea. Analysis of SeaWiFS data indicated connection between highest chlorophyll a concentration and sea surface temperature limits during spring bloom. Similar relation was not found during fall bloom.

• Journal of the Korean Geographical Society
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• v.44 no.1
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• pp.1-16
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• 2009

This study aims to classify climate zones using Empirical Orthogonal Function and clustering analyses considering both air temperature and rainfall features in South Korea. When examining climatic characteristics of air temperature and rainfall by seasons, the distribution of air temperature is affected by topography and latitude for all seasons in South Korea. The distribution of rainfall demonstrated that the Yeongdong area, the southern coastal area and Jeju island have higher rainfall while the central area in Gyeongsangbuk-do is the least rainfall area. Clustering analyses of average linkage method and Ward's method was carried out using input variables derived from principal component scores calculated through Empirical Orthogonal Function analysis for air temperature and rainfall. Ward's method showed the best result of classification of climate zones. It was well reflected effects of topography, latitude, sea, the movement of surface pressure systems, and an administrative district.

• Atmosphere
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• v.19 no.2
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• pp.107-125
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• 2009

Statistical downscaled surface temperature datasets by employing the cyclostationary empirical orthogonal function (CSEOF) analysis and multiple linear regression method are examined. For evaluating the efficiency of this statistical downscaling method, monthly surface temperature of the ECMWF has been downscaled into monthly temperature having a fine spatial scale of ~20km over the Korean peninsula for the 1973-2000 period. Monthly surface temperature of the ECHOG has also been downscaled into the same spatial scale data for the same period. Comparisons of temperatures between two datasets over the Korean peninsula show that annual mean temperature of the ECMWF is about $2^{\circ}C$ higher than that of the ECHOG. After applying to the statistical downscaling method, the difference of two annual mean temperatures reduces less than $1^{\circ}C$ and their spatial patterns become even close to each other. Future downscaled data shows that annual temperatures in the A1B scenario will increase by $3.5^{\circ}C$ by the late 21st century. The downscaled data are influenced by the ECHOG as well as observation data which includes effects of complicated topography and the heat island.

• 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.

• 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.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.213-219
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• 2005

In the Korean seas, Sea Surface Temperature (SST) and Thermal ronts (TF) were analyzed temporally and spatially during 8 years from 1993 to 2000 using NOAA/AVHRR MCSST. In the application of EOF analysis for SST, the variance of the 1st mode was 97.6%. Temporal components showed annual variations, and spatial components showed that where it is closer to continents, the SST variations are higher. Temporal components of the 2nd mode presented higher values of 1993, 94 and 95 than those of other years. Although these phenomena were not remarkable, they could be considered ELNI . NO effects to the Korean seas as the time was when ELNI . NO occurred. The Sobel Edge Detection Method (SEDM) delineated four fronts: the Subpolar Front (SPF) separating the northern and southern parts of the East Sea; the Kuroshio Front (KF) in the East China Sea, the South Sea Coastal Front (SSCF) in the South Sea, and the Tidal Front (TDF) in the West Sea. TF generally occurred over steep bathymetry slopes, and spatial components of the 1st mode in SST were bounded within these frontal areas. EOF analysis of SST gradient values revealed the temporal and spatial variations of the TF. The SPF and SSCF were most intense in March and October; the KF was most significant in March and May.

• 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.