• 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.

• Ocean and Polar Research
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• v.23 no.4
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• pp.361-376
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• 2001

The characteristics of SST variability in the East Sea are analyzed using NOAA/AVHRR weekly SST data with about $0.18^{\circ}{\times}0.18^{\circ}$ resolution ($1981{\sim}2000$) and reconstructed historical monthly SST data with $2^{\circ}{\times}2^{\circ}$ resolution $(1950{\sim}1998)$. The distinct feature of wintertime SST is high variability in the western and eastern parts of $38^{\circ}{\sim}40^{\circ}$ latitudinal band, which are the northern boundary of warm current in the East Sea during winter. However, summertime SST exhibits variability with similar magnitude in the entire region of the East Sea. The analysis of remote correlation also shows that SST in the East Sea is closely correlated with that in the region of Kuroshio in winter, but in summer is related with that in the western and eastern regions of the same latitudes. From these results it is postulated that the SST variability in the East Sea may be related with the variations of East Korean Warm Current and Tsushima Warm Current in winter, but in summer probably with the variations of atmospheric components. In the analysis of ENSO related SST anomaly, a significant negative correlation between SST anomalies in the East Sea and SST anomalies in the tropical Pacific is found in the months of August-October (ASO). The SST in the ASO period shows more significant cooling in E1 $Ni\~{n}o$ events than warming in La $Ni\~{n}a$ events. Also, the regional analysis shows by the Student's t-test that the negative SST anomalies in the E1 $Ni\~{n}o$ events are more significant in the southwestern part of the East Sea.

• Ocean Science Journal
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• v.41 no.1
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• pp.1-10
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• 2006

Total sea surface temperature (SST) in a coupled GCM is diagnosed by separating the variability into signal variance and noise variance. The signal and the noise is calculated from multi-decadal simulations from the COLA anomaly coupled GCM and the interactive ensemble model by assuming both simulations have a similar signal variance. The interactive ensemble model is a new coupling strategy that is designed to increase signal to noise ratio by using an ensemble of atmospheric realizations coupled to a single ocean model. The procedure for separating the signal and the noise variability presented here does not rely on any ad hoc temporal or spatial filter. Based on these simulations, we find that the signal versus the noise of SST variability in the North Pacific is significantly different from that in the equatorial Pacific. The noise SST variability explains the majority of the total variability in the North Pacific, whereas the signal dominates in the deep tropics. It is also found that the spatial characteristics of the signal and the noise are also distinct in the North Pacific and equatorial Pacific.

• Ocean and Polar Research
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• v.28 no.4
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• pp.415-423
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• 2006

Interannual variation and long-term trends of coastal sea surface temperature (SST) in Korea were investigated by analyzing 27 coastal SST time series from 1969 to 2004. Long-term linear increasing trend was remarkable with the rate over $0.02^{\circ}C/year$ at almost all the stations. The slope of long-term linear trend was larger at the stations along the eastern coast than in the western and southern regions. It was also noticeable that there was a common tendency of interannual variability with the period of 3-5 years at most of the stations. SST was lower in the 1970's and early 1980's while it was higher in the 1990's and early 2000's after the increase in the late 1980's. The pattern of the interannual variability of SST was similar to that of air temperature. Increasing trend of minimum SST in winter was obvious at most stations na it was larger along the eastern coast, while the linear trend of maximum SST in summer was less definite. Therefore, the decreasing tendency of annual amplitude was mainly due to the increasing tendency of SST in winter.

• Atmosphere
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• v.20 no.2
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• pp.211-219
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• 2010

The interannual variability of the tropical Indian Ocean SST is investigated by analyzing the ocean assimilation data. It is significant that since 1970, ENSO events frequently followed the Indian Ocean Dipole event. The SST tendency due to the dynamical SST advections over the tropical Indian Ocean sufficiently overwhelms that due to other thermodynamic process during the fall and winter of ENSO. Especially, the strong cooling due to the anomalous vertical advection by the mean upwelling and the warming due to the horizontal advection are attributed to the cold SST during the fall and the warm SST during the winter, respectively. The significant warming between winter and spring over the southwestern Indian Ocean turns out to be due to the vertical advection of the mean subsurface temperature by the anomalous upwelling during the winter and the vertical advection of the anomalous subsurface temperature by the mean upwelling from winter to spring. We speculate that when the Indian Ocean Dipole events concurred with the ENSO, the surface wind is so strong enough as to generate the change in the SST dynamically and overwhelm the SST changes associated with other effects.

• Journal of the Korean earth science society
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• v.40 no.3
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• pp.240-258
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• 2019

Typhoons, torrential rainfall, and heavy snowfall cause catastrophic losses each year in the Republic of Korea. Therefore, if we can know the possibility of this phenomenon in advance through regular observations, it will be greatly beneficial to Korean society. Korea is surrounded by sea on its three sides, and the sea surface temperature (SST) directly or indirectly affects the development of typhoons, heavy rainfall, and heavy snowfall. Therefore, the characteristics of SST variability related to the high impact weather are investigated in this paper. The heavy rainfall in Korea was distributed around Seoul, Gyeonggi, and west and southern coast. The heavy snowfall occurred mainly in the eastern coastal (hereafter Youngdong Heavy Snow) and the southwestern region (hereafter Honam-type heavy snow). The SST variability was slightly different depending on the type and major occurrence regions of the high impact weather. When the torrential rain occurred, the SST variability was significantly increased in the regions extending to Jindo-Jeju island-Ieodo-Shanghai in China. When the heavy snow occurred, the SST variability has reduced in the southern sea of Jeju island, regardless of the type of heavy snowfall, whereas the SST variability has increased in the East Sea near $130^{\circ}E$ and $39^{\circ}N$. Areas with high SST variability are anticipated to be used as a basis for studying the atmospheric-oceanic interaction mechanism as well as for determining the background atmospheric aerosol observation area.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.1
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• pp.1-10
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• 2016

Currently available surface seawater partial pressure carbon dioxide ($pCO_2$) data sets in the East Sea are not enough to quantify statistically the carbon dioxide flux through the air-sea interface. To complement the scarcity of the $pCO_2$ measurements, we construct a neural network (NN) model based on satellite data to map $pCO_2$ for the areas, which were not observed. The NN model is constructed for the Ulleung Basin, where $pCO_2$ data are best available, to map and estimate the variability of $pCO_2$ based on in situ $pCO_2$ for the years from 2003 to 2012, and the sea surface temperature (SST) and chlorophyll data from the MODIS (Moderate-resolution Imaging Spectroradiometer) sensor of the Aqua satellite along with geographic information. The NN model was trained to achieve higher than 95% of a correlation between in situ and predicted $pCO_2$ values. The RMSE (root mean square error) of the NN model output was $19.2{\mu}atm$ and much less than the variability of in situ $pCO_2$. The variability of $pCO_2$ with respect to SST and chlorophyll shows a strong negative correlation with SST than chlorophyll. As SST decreases the variability of $pCO_2$ increases. When SST is lower than $15^{\circ}C$, $pCO_2$ variability is clearly affected by both SST and chlorophyll. In contrast when SST is higher than $15^{\circ}C$, the variability of $pCO_2$ is less sensitive to changes in SST and chlorophyll. The mean rate of the annual $pCO_2$ increase estimated by the NN model output in the Ulleung Basin is $0.8{\mu}atm\;yr^{-1}$ from 2003 to 2014. As NN model can successfully map $pCO_2$ data for the whole study area with a higher resolution and less RMSE compared to the previous studies, the NN model can be a potentially useful tool for the understanding of the carbon cycle in the East Sea, where accessibility is limited by the international affairs.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1620-1624
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• 2010

The NLCCA has been applied to analyze the East Asia sea surface temperature (SST) and Korea monthly precipitation, where the eight leading PCs of the SST and the eight PCs of the precipitation during 1973-2007 were inputs to an NLCCA model. The first NLCCA mode is plotted in the PC spaces of the Korea precipitation and the world SST present a curve linking the nonlinear relationship between the first three leading PCs of Korea precipitation and world SST forthright. The correlation coefficient between canonical variate time series u and v is 0.8538 for the first NLCCA mode. And there are some areas' climate variability have higher relationship with Korea precipitation, especially focus on the north of East Sea' climate variability have represented the higher canonical correlation with Korea precipitation, with the correlation coefficient is 0.871 and 0.838. Likewise in Korea, most stations display similarly uniform distributing characteristic and less difference, in particular the inshore stations have display identical distributing characteristic. In correlation variables' scores, the fluctuation and variation trend are also seasonal oscillation with high frequency.

• Ocean and Polar Research
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• v.31 no.2
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• pp.177-187
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• 2009

This study examined the multi-scale variabilities of sea surface temperature (SST) and salinity in the Japan/East Sea (JES) based on statistical analyses of observational data, with a focus on the northwestern part of the sea. The regionality of JES SST variability was estimated for different frequency ranges on semimonthly (11-17 days), monthly to seasonal (30-90 days), quasi-semiannual (157-220 days), and quasi-biennial (1.5-3 years) time scales using cluster analyses of daily gridded SST data for 1996 to 2007 from the Japan Meteorological Agency (JMA). Several significant peaks and regional cores were found in each frequency range of the SST anomaly (SSTA) oscillations. Quasi-semiannual SSTA oscillations with high amplitude were found in the south-southwestern part of the Japan Basin ($41-43^{\circ}N$) and were amplified in the area adjacent to Peter the Great Bay. Oscillations with periods of 79 and 55 days also prevailed over the southwest Japan Basin between the Yamato Rise and the continental slope. A similar method was applied to classify SST and the annual cycle of surface salinity using Generalized Digital Environmental Model (GDEM) gridded data. The Tatarskii Strait and adjacent area showed the most specific annual cycles and variability in salinity on interannual to interdecadal time scales. The most significant inverse relationship between surface salinity in the Tatarskii Strait and southern JES areas was found on the interdecadal time scale. Linkages of sea water salinity in the Tatarskii Strait with Amur River discharge and wind velocity over Amurskii Liman were also revealed.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.4
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• pp.509-518
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• 2019

Analyses with various Sea Surface Temperature (SST) products indicate that the interannual variability of the area-averaged SST in the East/Japan Sea (EJS) is well correlated to that of Pacific Decadal Oscillation (PDO) during 1979-2018, especially in the autumn. The regression analysis with the wind vectors at 200 hPa, where the strongest jet stream flows, suggests that the long-term variability of the intensity as well as the meridional movement of the jet stream are related to the coupling of the autumn EJS SST and PDO. When the axis of the jet stream moves poleward (equatorward) with its weakening (strengthening), both the EJS SST and North Pacific SST increase (decrease). This suggests that both the intensity and meridional movement of the jet stream are possibly related to the coupling of the autumn EJS SST and PDO. However, effects of a weak jet stream during the summer and the strong East Asian winter monsoon make weak coupling between the EJS SST and PDO.