• Atmosphere
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• v.24 no.4
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• pp.541-554
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• 2014

Historical, RCP4.5 and RCP8.5 scenarios from HadGEM2-AO are dynamically downscaled over the northeast East Asia with WRFV3.4. The horizontal resolution of the produced data is 12.5 km and the periods of integration are 1979~2010 for historical and 2019~2100 for both RCP4.5 and RCP8.5. We analyze the time series, climatology, EOF and extreme climate in terms of 2 m-temperature and precipitation during 30-year for the Historical (1981~2010) and RCP4.5 and RCP8.5 (2071~2100) scenarios. According to the result, the temperature of the northeast Asia centered at the Korean Peninsula increase 2.9 and $4.6^{\circ}C$ in the RCP4.5 and RCP8.5 scenarios, respectively, by the end of the 21st century. The temperature increases with latitude and the increase is larger in winter rather than in summer. The annual mean precipitation is expected to increase by about $0.3mm\;day^{-1}$ in RCP4.5 scenario and $0.5mm\;day^{-1}$ in RCP8.5 scenario. The EOF analysis is also performed for both temperature and precipitation. For temperature, the EOF $1^{st}$ modes of all scenarios in summer and winter show that temperature increase with latitude. The $2^{nd}$ mode of EOF of each scenario shows the natural variability, exclusive of the global warming. The summer precipitation over the Korean Peninsula projected increases in EOF $1^{st}$ modes of all scenarios. For extreme climate, the increment of the number of days with daily maximum temperature above $30^{\circ}C$ per year ($DAY_{TX30}$) is 25.3 and 49.7 days in RCP4.5 and RCP8.5 respectively over the Korean Peninsula. The number of days with daily precipitation above $20mm\;day^{-1}$ per year ($DAY_{PR20}$) also increases 3.1 and 3.5 days in RCP4.5 and RCP8.5 respectively.

• 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.27 no.1
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• pp.55-65
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• 2017

This study investigates how Eurasian snow cover in spring (March and April) is associated with Korean temperature during summer (June-July-August). Two leading modes of Eurasian snow cover variability in spring for 1979~2015 are obtained by Empirical Orthogonal Function (EOF) analysis. The first EOF mode of Eurasian snow cover is characterized by a zonally elongated pattern over the whole Eurasian region and its principal component is more correlated with Korean temperature during June. On the other hand, the second EOF mode of Eurasian snow cover is characterized by an east-west dipole-like pattern, showing positive anomalies over eastern Eurasian region and negative anomalies over western Eurasian region. This dipole-like pattern is related with Korean temperature during August. The first leading mode of Eurasian snow cover is associated with anomalous high (low) pressure over Korea (Sea of Okhotsk) during June, which might be induced by much evaporation of soil moisture in Eurasia during March. On the other hand, the second mode of Eurasian snow cover is associated with a wave train resembling with Eurasian (EU)-like pattern in relation to the Atlantic sea surface temperature forcing, leading to the anomalous high pressure over Korea during August. Understanding these two leading modes of snow cover in Eurasian continent in spring may contribute to predict Korean summer temperature.

• 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.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.549-560
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• 2019

The effects of the coal-fired power plant emissions, as the biggest point source of air pollutants, on spatiotemporal surface air pollution over the remote area are investigated in this study, based on a set of date selection and statistical technique to consider meteorological and geographical effects in the emission-concentration (source-receptor) relationship. We here proposed the sophisticated technique of data processing to separate and quantify the effects. The data technique comprises a set of data selection and statistical analysis procedure that include data selection criteria depending on meteorological conditions and statistical methods such as Kolmogorov-Zurbenko filter (K-Z filter) and empirical orthogonal function (EOF) analysis. The data selection procedure is important for filtering measurement data to consider the meteorological and geographical effects on the emission-concentration relationship. Together with meteorological data from the new high resolution ECMWF reanalysis 5 (ERA5) and the Korea Meteorological Administration automated surface observing system, air pollutant emission data from the telemonitoring system (TMS) of Dangjin and Taean power plants as well as spatio-temporal air pollutant concentrations from the air quality monitoring system are used for 4 years period of 2014-2017. Since all the data used in this study have the temporal resolution of 1 hour, the first EOF mode of spatio-temporal changes in air pollutant concentrations over the Seoul metropolitan area (SMA) due to power plant emission have been analyzed to explain over 97% of total variability under favorable meteorological conditions. It is concluded that SO₂, NO₂, and PM₁₀ concentrations over the SMA would be decreased by 0.468, 1.050 ppb, and 2.045 ㎍ m^-3 respectively if SO₂, NO₂, and TSP emissions from Dangjin power plant were reduced by 10%. In the same way, the 10% emission reduction in Taean power plant emissions would cause SO₂, NO₂, and PM₁₀ decreased by 0.284, 0.842 ppb, and 1.230 ㎍ m^-3 over the SMA respectively. Emissions from Dangjin power plant affect air pollution over the SMA in higher amount, but with lower R value, than those of Taean under the same meteorological condition.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.2
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• pp.188-202
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• 1997

The seasonal variability of the sea surface winds over the last Sea of Korea (Japan Sea) is investigated by means of empirical orthogonal function (EOF) analysis. The combined representation of fields of three climatic variables by empirical orthogonal functions is discussed. The eigenvectors are derived from daily sea level pressure, wind speed and 10-day mean sea surface temperature (SST) during 15 years $(1978\~1992)$. The spatial patterns of the mean pressure are characterized by the high pressure in the western part and the low pressure in the eastern part. The spatial distribution of the standard deviation (SD) of pressure are characterized by max SD of 6.6 mb near the Vladivostok, and minima along the coast of the Japan. In Vladivostok, the maxima of SD of SST and south-north wind (WV) were also occurred. The representation of fields of individual meteorological variables by EOF shows that the first mode of the west-east wind (WU) explain over $47.3\%$ of the variance and the second mode of WU represents $30\%$. Especially, the first mode of the WV explain $70.9\%$ of the variance and their time series coefficients show 1-cpy, 0.5-cpy frequency spectrum. The spatial distribution of the first mode eigenvectors of SST are characterized by maximum near Vladivostok. The combined representation of fields of several variables (pressure, wind, SST) reveals that the first mode magnitudes of the variance of the combined eigenvectors (WU-PR) are increased. By means of this result, the 1-year peak and the 6-months peak are remarkable. In the three combined patterns (wind, pressure, SST), the second mode of the eigenvector (wind) is affected by the SST. Their time coefficients of the first mode show noticeable 1-year peak. The spectral analysis of the second mode shows broad seasonal signal with the period of 4-months and a significant peak of variability at 3-month period.

• 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.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.4
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• pp.121-132
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• 2023

Marine heatwaves (MHWs), referring to anomalously high sea surface temperatures, have drawn significant attention from marine scientists due to their broad impacts on the surface marine ecosystem, fisheries, weather patterns, and various human activities. In this study, we examined the impact of the distribution of Changjiang diluted water (CDW), a significant factor causing oceanic property changes in the East China Sea (ECS) during the summer, on MHWs. The surface salinity distribution in the ECS indicates that from June to August, the eastern extension of the CDW influences areas as far as Jeju Island and the Korea Strait. In September, however, the CDW tends to reside in the Changjiang estuary. Through the Empirical Orthogonal Function analysis of the cumulative intensity of MHWs during the summer, we extracted the loading vector of the first mode and its principal component time series to conduct a correlation analysis with the distribution of the CDW. The results revealed a strong negative spatial correlation between areas of the CDW and regions with high cumulative intensity of MHWs, indicating that the reinforcement of stratification due to low-salinity water can increase the intensity and duration of MHWs. This study suggests that the CDW may still influence the spatial distribution of MHWs in the region, highlighting the importance of oceanic environmental factors in the occurrence of MHWs in the waters surrounding the Korean Peninsula.

• 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.

• 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.