• 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.

• Proceedings of the KSRS Conference
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• v.2
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• pp.831-835
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• 2006

NOAA/AVHRR data were used to analyze sea surface temperatures (SSTs) and thermal fronts (TFs) in the Korean seas. Temporal and spatial analyses were based on data from 1993 to 2000. Harmonic analysis revealed mean SST distributions of $10{\sim}25^{\circ}C$. Annual amplitudes and phases were $4{\sim}11^{\circ}C$ and $210{\sim}240^{\circ}$, respectively. Inverse distributions of annual amplitudes and phases were found for the study seas, with the exception of the East China Sea, which is affected by the Kuroshio Current. Areas with high amplitudes (large variations in SSTs) showed 'low phases' (early maximum SST); areas with low amplitudes (small variations in SSTs) had 'high phases' (late maximum SST). Empirical orthogonal function (EOF) analyses of SSTs revealed a first-mode variance of 97.6%. Annually, greater SST variations occurred closer to the continent. Temporal components of the second mode showed higher values in 1993, 1994, and 1995. These phenomena seemed to the effect of El $Ni{\tilde{n}}o$. 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 a tidal front (TDF) in the West Sea. Thermal fronts generally occurred over steep bathymetric slopes. Annual amplitudes and phases were bounded within these frontal areas. EOF analysis of SST gradient values revealed the temporal and spatial variations in the TFs. The SPF and SSCF were most intense in March and October; the KF was most significant in March and May.

• Atmosphere
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• v.22 no.4
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• pp.483-488
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• 2012

The monsoon front lies on East Asian region, but it gradually propagates to the north during the boreal summer. The equivalent potential temperature (EPT) reveals the thermodynamical features of air masses and monsoon front. Therefore, this study considered the thermodynamical EPT and dynamical wind fields to clarify the peculiarity of East Asian summer monsoon (EASM) variations in June and July, respectively. Western North Pacific subtropical high (WNPSH) and Okhotsk sea high (OSH) both play the crucial role to interannual variations of EASM frontal activity and amount of rainfall. The OSH is important in June, but the WNPSH is key factor in July. Furthermore, the OSH (June) is affected by North Atlantic tripolar sea surface temperature (SST) pattern and WNPSH (July) is influenced by North Indian Ocean SST warming.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.696-700
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• 2004

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 harmonic analysis, distributions of the mean SST were $10~25^{\circ}C,$ and generally SST decreased as latitude increased. SST increased in the order as following; the South Sea $(20\~23^{\circ}C),$ the East Sea $(17\~19^{\circ}C)$, and the West $Sea(13\~16^{\circ}C).$ Annual amplitudes and phases were $4\~11^{\circ}C,\;210\~240^{\circ}$ and high values were shown as following; the West Sea $(A1,\;9\~11^{\circ}C),$ the Northern East Sea $(A5,\;8\~9^{\circ}C),$ the Southern East Sea $(A4,\;6\~8^{\circ}C),$ the South Sea $(A3,\;6\~7^{\circ}C),$ the East China Sea $(A2,\;4\~7^{\circ}C)$ and phases; $A3\;(238\~242^{\circ}),\;A4\;(235\~240^{\circ}),\;A5\;(225\~235^{\circ}),\;Al\;(220\~230^{\circ}),\;A2\;(210\~235^{\circ}),$ respectively, Both of them were related inversely except the area A2, therefore the rest areas were affected by seasonal variations. TF were detected by Soble Edge Detection Method using gradient of SST. Consequently, TF were divided into 4 fronts; the Subpolar Front (SPF) based on the Cold Water Mass (low SST and salinity Subartic Water), resulting from the North Korea Cold Current (NKCC) and the East Sea Proper Cold Water in the middle and low layer, and the Warm Water Mass (high SST and salinity Subtropical Water), resulting from the Tsushima Warm Current (TWC) in area A4 and 5, the Kuroshio Front (KF) based on the Kuroshio Current (KC) and shelf waters in the East China Sea (ESC) in A2, and the South Sea Coastal Front (SSCF) based on the South Sea Coastal Water (SSCW) and TWC in A3. Also, the Tidal Front was weakly appeared in AI. TF located in steep slope of submarine topography. Annual amplitudes and phases were bounded in the same place, and these results should be considered to influence of seasonal variations.

• Journal of environmental and Sanitary engineering
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• v.21 no.4 s.62
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• pp.61-76
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• 2006

A Line Density algorithm was developed to quantify the sea surface temperature distribution using NOAA Sea Surface Temperature(SST) data and Geographic Information Systems(GIS), In addition, a GIS based automation model was designed to extract the Line Density Indices were determined by applying K-means Cluster. SST data in terms of March to May obtained on the coastal area of the Uljin from 2001 to 2004 in spring were used to make two data sets of average sea water temperature map in terms of year as well as month. From the result it was formed that water temperature gradient in April was the strongest among the other months, In particular very strog formation of oceanic front as well as temperature gradients were observed in front of the coastal area around Wonduk and Jukbyeon countries. Because those coastal area is a confront zone of two cold and a warm. It is expected that the development of a Line Density Algorithm would contribute to quantify of the SST for the research of Sea Surface Front(SSF) related to marine life management and the sea environmental conservation.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.655-655
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• 2002

Spatial distribution of phytoplankton pigment concentration (PPC) and sea surface temperature (SST) around the East Korean Warm Current (EKWC) was described, using both ocean color images and advanced very high resolution radiometer (AVHRR) images. Water mass in this region can be classified into five categories in the horizontal profile of PPC and SST, nLw(normalized water-leaving radiance) images: (1) coastal cold water region associated with concentrations of dissolved organic material or yellow colored substances and suspended sediments, (2) cold water region of thermal frontal occurred by a combination of phytoplankton absorption and suspended materials, (3) warm water overlay region by the phytoplankton absorption than the suspended materials; (4) warm water region occurred by the low phytoplankton absorption, and (5) offshore region occurred by the high phytoplankton absorption. In particular, the highest PPC area appeared in the ocean color and SST images with a band shaped distribution of the thermal front and ocean color front region, which is located the coastal cold waters along western thermal front of the warm streamer of the EKWC.

• Proceedings of the KSRS Conference
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• v.2
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• pp.740-743
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• 2006

We identify two distinct finer-scale frontal bands: 'Mainland China Coastal Front' (MCCF) and 'Kuroshio Front' (KF). The MCCF is along the 50-m isobath with large temperature gradient. The front is a boundary between the Mainland China Coastal Current and the offshore shelf waters. On the other hand, the KF is extending from the northeastern coast of Taiwan toward the northeast and into the shelf of south ECS. It forms a broad semicircle-shape and curving along 100-m isobath, it also deviates from eastward at around 26.5N-122E and leaves the shelf of ECS. This front should be the boundary between the Kuroshio water and the other shelf waters.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.227-238
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• 2006

Line density index(LDI) was developed to quantify a densely isothermal line rate as standard index in the ocean environment. Theoretical background on the LDI development process restricting index range 0 to 100 was described. And validation test was done for the LDI application condition that total line length is not greater than 1/10 of unit area. NOAA SST(Sea Surface Temperature) data were used for the experimental application of LDI in the South Sea of Korea. Using GIS, $0.1^{\circ}C$ isothermal lines were linearized as vector data form SST raster data, and unit area were built as polygon data. For the LDI calculation, spatial overlapping(line in polygon) was implemented. To analyze the effect of unit area size for the LDI distribution, two cases of unit area size were designed and descriptive statistics was calculated including performing normality test. The results showed no change of LDI's essential characteristics such as mean and normality except for the range of value, variance and standard deviation. Accordingly, it was found that complex structure of thermal front and even smaller scale of front width than unit area size could influence on the LDI distribution. Also, correlation analysis performed between LDI and difference of temperature(${\Delta}T^{\circ}C$), and horizontal thermal gradient(${\Delta}T^{\circ}C/km$) on the front was obtained from linear regression model. This obtained value was compared with the results from previous researches. Newly developed LDI can be used to compare the thermal front regions changing spatio-temporally in the ocean environment using absolute index value. It is considered to be significant to analyze the relationship between thermal front and marine environment or front and marine organisms in a quantitative approach described in this study.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1179-1192
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• 2018

In order to detect the Antarctic Polar Front (PF) among the main fronts in the Southern Ocean, this study is based on the combinations of satellite-based sea surface temperature (SST) and height (SSH) observations. For accurate PF detection, we classified the signals as front or non-front grids based on the Bayesian decision theory from daily SST and SSH datasets, and then spatio-temporal synthesis has been performed to remove primary noises and to supplement geographical connectivity of the front grids. In addition, sea ice and coastal masking were employed in order to remove the noise that still remains even after performing the processes and morphology operations. Finally, we selected only the southernmost grids, which can be considered as fronts and determined as the monthly PF by a linear smoothing spline optimization method. The mean positions of PF in this study are very similar to those of the PFs reported by the previous studies, and it is likely to be well represents PF formation along the bottom topography known as one of the major influences of the PF maintenance. The seasonal variation in the positions of PF is high in the Ross Sea sector (${\sim}180^{\circ}W$), and Australia sector ($120^{\circ}E-140^{\circ}E$), and these variations are quite similar to the previous studies. Therefore, it is expected that the detection approach for the PF position applied in this study and the final composite have a value that can be used in related research to be carried out on the long term time-scale.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.721-732
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• 2016

The accuracy and error characteristics of microwave Sea Surface Temperature (SST) measurements in the Northwest Pacific were analyzed by utilizing 162,264 collocated matchup data between GCOM-W1/AMSR2 data and oceanic in-situ temperature measurements from July 2012 to August 2016. The AMSR2 SST measurements had a Root-Mean-Square (RMS) error of about $0.63^{\circ}C$ and a bias error of about $0.05^{\circ}C$. The SST differences between AMSR2 and in-situ measurements were caused by various factors, such as wind speed, SST, distance from the coast, and the thermal front. The AMSR2 SST data showed an error due to the diurnal effect, which was much higher than the in-situ temperature measurements at low wind speed (<6 m/s) during the daytime. In addition, the RMS error tended to be large in the winter because the emissivity of the sea surface was increased by high wind speeds and it could induce positive deviation in the SST retrieval. Low sensitivity at colder temperature and land contamination also affected an increase in the error of AMSR2 SST. An analysis of the effect of the thermal front on satellite SST error indicated that SST error increased as the magnitude of the spatial gradient of the SST increased and the distance from the front decreased. The purpose of this study was to provide a basis for further research applying microwave SST in the Northwest Pacific. In addition, the results suggested that analyzing the errors related to the environmental factors in the study area must precede any further analysis in order to obtain more accurate satellite SST measurements.