• Atmosphere
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• v.26 no.4
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• pp.635-647
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• 2016

The effects of sea surface temperature (SST) gradient induced by the previous typhoon on the following typhoon motion over East Asia have been investigated using Weather Research and Forecasting (WRF) model for the previous Typhoon Bolaven (1215) and following Typhoon Tembin (1214). It was observed that Typhoon Bolaven remarkably reduced SST by about $7^{\circ}C$ at Yellow Sea buoy (YSbuoy). Using the WRF experiments for the imposed cold wake over West of Tembin (WT) and over East of Tembin (ET), this study demonstrates that the effects of eastward SST gradient including cold wake over WT is much significant rather than that over ET in relation to unexpected Tembin's eastward deflection. This difference between two experiments is attributed to the fact that cold wake over WT increases the magnitude of SST gradient under the eastward SST gradient around East Asia and the resultant asymmetric flow deflects Typhoon Tembin eastward, which is mainly due to the different atmospheric response to the SST forcing between ET and WT. Therefore, it implies that the enhanced eastward SST gradient over East Asia results in larger typhoon deflection toward the region of warmer SST according to the location of the cold wake effect. This result can contribute to the improvement of track prediction for typhoons influencing the Korean Peninsula

• Journal of the Korean earth science society
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• v.27 no.1
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• pp.61-72
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• 2006

Numerical studies on the influence of interaction between atmosphere and ocean on the variation of Karman vortex at the lee side of Jeju Island were carried out. Karman vortex tends to be occurred at limited height associated with Hanla mountain. And we can find clear Karman vortex at 900 hPa height in this study. One big vortex cell occurred at lee side of Jeju Island in the begging stage of its development and the cell was divided into three small cells as time goes by. And the strength and lifetime of small vortexes depend on the distribution of SST (Sea Surface Temperature). Weak gradient of SST makes long-lasting Karman vortex but produces weak potential vorticity at lee side of Jeju-do in comparison with the vortex under strong SST gradient. Strong SST gradient also increases not only the mixing depth but also the mixing ratio at lower level of troposphere. And the increased atmospheric mixing decreases the mechanical forcing due to isolated topography. Then the strength of Karman vortex at the lee side of Jeju Island becomes weak under strong gradient of SST. Thus the evolution of Karman vortex is closely related to distribution of SST around the isolated island.

• Journal of the Korean earth science society
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• v.28 no.3
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• pp.343-356
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• 2007

This paper explored the characteristics of the interannual sea surface temperature (SST) variability in the equatorial Pacific by analyzing the simulated data from a newly coupled general circulation model (CGCM). The CGCM simulates well the realistic ENSO variability as well as the mean climatologies including SST, seasonal cycle, precipitation, and subsurface structures. It is argued that the zonal gradient of SST in the equatorial Pacific is responsible for the over-energetic SST variability near the equatorial western boundary in the model. This variability could also be related to the strong westward propagation of SST anomalies which resulted from the enhanced the zonal advection feedback. The simple two-strip model supports this by sensitivity tests. Analysis of the relationship between zonal mean thermocline depth and NINO3 SST index suggested that the ENSO variability is controlled by the recharge-discharge oscillator of the model. The lead-lag regression result reveals that heat buildup process in the western equatorial Pacific associated with the increase of the barrier layer thickness (BLT) is a precedent condition for El $Ni\widetilde{n}o$ to develop.

• 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 Remote Sensing
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• v.11 no.1
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• pp.19-29
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• 1995

The surface velocities were estimated by the Maximum Cross Correlation(MCC) method and an inverse method from AVHRR/SST. In the results of MCC, discontinuous flow fields were estimated in the case that cross correlation coefficient was above 0.5 but these flow pattern disappeared when cross correlation coefficient was above 0.9. This estimation was conspicuous near SST patterns of eddies. In the results of inverse method, flow field was continuous and eddy motion was estimated definitely but the velocity was overstimated in compared with MCC result over the area of small temperature gradient. This result may be due to temperature error included in SST calculated and spatial variation of heat flux.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.392-393
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• 2005

Due to the temporal and spatial simultaneity and the high-frequency repetition, the data set retrieved from the satellite observation is considered to be the most desirable ones for the study of air-sea interaction. With rapidly developing sensor technology, satellite-retrieved data has experienced improvement in the accuracy and the number of parameters. Nevertheless, since it is still impossible to directly measure the heat fluxes between air and sea, the bulk method is an exclusive way for the evaluation of the heat fluxes at the sea surface. It was noted that the large deviation of air temperature in the winter season by the linear regression despite good correlation coefficients. We propose a new algorithm based on the Fourier series with which the SST and the air temperature. We found that the mean of air temperature is a function of the mean of SST with the monthly gradient of SST inferred from the latitudinal variation of SST and the spectral energy of air temperature is related linearly to that of SST. An algorithm to obtain the air temperature over the sea was completed with a proper analysis on the relation between of air temperature and of SST. This algorithm was examined by buoy data and therefore the air temperature over the sea can be retrieved based on just satellite data.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.21 no.1
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• pp.1-10
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• 1988

The vertical temperature profiles of the Yellow Sea in summer are investigated by means of the nine air temperature (AT) patterns which are classified with the AT of winter and summer. The sea surface temperature (SST) is high when the AT of summer is high, and vice versa. The gradient of thermocline in the offshore region is higher than that in the coastal region and is not always favorable with the AT patterns. The relation between sea bottom temperature (SBT) and the AT of winter is favorable when the SBT is averaged in the coastal and offshore stations. In addition, the SST of coastal stations is higher than that of offshore stations because of the strong mixing by the tidal current in the coastal region. The correlation between the AT and the SST of August is favorable (r=0.44-0.69), while the correlation between the AT of February and the SBT of August is not favorable except the stations, A2 (r=0.57) and B2 (r=0.61).

• 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.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.4
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• pp.304-315
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• 2009

Numerical simulations were carried out to understand the effect of Sea Surface Temperature (SST) spatial distribution on regional circulation. A three-dimensional non-hydrostatic atmospheric model RAMS, version 6.0, was applied to examine the impact of SST forcing on regional circulation. New Generation Sea Surface Temperature (NGSST) data were implemented to RAMS to compare the results of modeling with default SST data. Several numerical experiments have been undertaken to evaluate the effect of SST for initialization. First was the case with NGSST data (Case NG), second was the case with RAMS monthly data (Case RM) and third was the case with seasonally averaged RAMS monthly data (Case RS). Case NG showed accurate spatial distributions of SST but, the results of RM and RS were $3{\sim}4^{\circ}C$ lower than buoy observation data. By analyzing practical sea surface conditions, large difference in horizontal temperature and wind field for each run were revealed. Case RM and Case RS showed similar horizontal and vertical distributions of temperature and wind field but, Case NG estimated the intensity of sea breeze weakly and land breeze strongly. These differences were due to the difference of the temperature gradient caused by different spatial distributions of SST. Diurnal variations of temperature and wind speed for Case NG indicated great agreement with the observation data and statistics such as root mean squared error, index of agreement, regression were also better than Case RM and Case RS.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.