• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.49-70
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• 2022

Sea Surface Temperature (SST), one of the ocean features, has a significant impact on climate, marine ecosystem and human activities. Therefore, SST prediction has been always an important issue. Recently, deep learning has drawn much attentions, since it can predict SST by training past SST patterns. Compared to the numerical simulations, deep learning model is highly efficient, since it can estimate nonlinear relationships between input data. With the recent development of Graphics Processing Unit (GPU) in computer, large amounts of data can be calculated repeatedly and rapidly. In this study, Short-term SST will be predicted through Convolutional Neural Network (CNN)-based U-Net that can handle spatiotemporal data concurrently and overcome the drawbacks of previously existing deep learning-based models. The SST prediction performance depends on the seasonal and interannual SST variabilities around the southern coast of Korea. The predicted SST has a wide range of variance during spring and summer, while it has small range of variance during fall and winter. A wide range of variance also has a significant correlation with the change of the Pacific Decadal Oscillation (PDO) index. These results are found to be affected by the intensity of the seasonal and PDO-related interannual SST fronts and their intensity variations along the southern Korean seas. This study implies that the SST prediction performance using the developed deep learning model can be significantly varied by seasonal and interannual variabilities in SST.

• 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.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.599-616
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• 2020

Sea-surface temperature (SST) is one of the most important oceanic variables for understanding air-sea interactions, heat flux variations, and oceanic circulation in the global ocean. Extremely low SSTs from 0℃ down to -2℃ should be more important than other normal temperatures because of their notable roles in inducing and regulating global climate and environmental changes. To understand the temporal and spatial variability of such extremely low SSTs in the global ocean, the long-term SST climatology was calculated using the daily SST database of satellites observed for the period from 1982 to 2018. In addition, the locations of regions with extremely low surface temperatures of less than 0℃ and monthly variations of isothermal lines of 0℃ were investigated using World Ocean Atlas (WOA) climatology based on in-situ oceanic measurements. As a result, extremely low temperatures occupied considerable areas in polar regions such as the Arctic Ocean and Antarctic Ocean, and marginal seas at high latitudes. Six earth science textbooks were analyzed to investigate how these extremely low temperatures were visualized. In most textbooks, illustrations of SSTs began not from extremely low temperatures below 0℃ but from a relatively high temperature of 0℃ or higher, which prevented students from understanding of concepts and roles of the low SSTs. As data visualization is one of the key elements of data literacy, illustrations of the textbooks should be improved to ensure that SST data are adequately visualized in the textbooks. This study emphasized that oceanic literacy and data literacy could be cultivated and strengthened simultaneously through visualizations of oceanic big data by using satellite SST data and oceanic in-situ measurements.

• Journal of the Korean earth science society
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• v.29 no.1
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• pp.45-59
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• 2008

This study aims to analyze the interdecadal variation of relationship between Indian Ocean sea surface temperature (SST) and East Asian summer monsoon (EASM) during the period of 1948-2005. In the pre-period, which is from 1948 to 1975, the relationship between Indian Ocean SST and East Asian summer rainfall anomaly (EASRA) is very weak. However, in the post-period, which is trom 1980 to 2005, Indian Ocean SST is significantly positively correlated with EASRA. The equatorial Indian Ocean SST has a significantly positive correlation with EASM in spring, while Indian Ocean SST near the bay of Bengal has a positive relationship in summer for the post-period. Also the interdecadal variation of the correlation between Indian Ocean SST and EASRA is significant, but that between EASRA and the El $Ni{\tilde{n}}o$-Southern Oscillation (ENSO) is not. Atmospheric general circulation model (AGCM) test results show the pattern of increased precipitation in the zonal belt region including South Korea and Japan and the pattern of decreased precipitation in the northeastern part of Asia, which are similar to the real climate. The increase of the precipitation in August from the model run is also similar to the real climate variation. Model results indicate that the Indian Ocean SST warming could intensify the convection over the vicinity of the Philippines and the Bay of Bengal, which forces to move northward the convection center. This warming strengthens the EASM and weakens the WNPM.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.360-366
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• 2009

AQUA/AMSR-E 인공위성 자료를 활용하여 3차원 최적내삽 해수면온도 합성장을 생산하였고 시간평균장과 비교하여 문제점과 한계점을 기술하였다. 3-D SST 합성장은 북태평양 중앙부에서 전체적으로 $0.05^{\circ}C$ 이하의 작은 오차를 보였으나, 위성 결측이 있는 연안에서는 $0.4^{\circ}C$ 이상의 비교적 큰 오차를 유발하였다. 강한 강수나 구름으로 인한 결측이 있는 부분에서는 $0.1\sim0.15^{\circ}C$에 달하는 오차를 보였다. 시간평균장과 비교한 결과, 구름 부근의 화소에서는 해수면온도를 낮게 계산하는 경향이 있었으며, 해수면온도의 공간적 구배를 감소시키는 평활화가 전체적으로 나타났다. 저위도에서 OI SST는 실제 해수면온도에는 없는 불연속성을 만드는 경향이 있었고, 이는 OI 과정에서 사용한 윈도우의 크기와 해양 현상의 수평 규모가 위도에 따라 변화하는데서 기인하였다. 현상의 공간 규모의 척도인 로스비 내부 변형 반경은 북태평양에서 O(1) 정도로 위도에 따른 공간적 변화가 큰 것으로 나타났다. 본 연구는 SST 합성장 생산 과정에 위도와 해수의 수직적 밀도 구조와 밀접한 관련이 있는 해양 현상의 수평적 규모의 시공간적 변동 특성을 고려해야 함을 제시한다.

• Journal of the Korean Society for Marine Environment & Energy
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• v.9 no.1
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• pp.55-62
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• 2006

Correlations between air-temperature variation and SST variation around Jeju Island have been studied with data JRMO($1924{\sim}2004$) and NFRDI($l971{\sim}2000$). Air-temperature has increased about $0.02^{circ}C/year$ for the period of $1924{\sim}2004$ but relatively high 0.035/year for the last 30 years. SST has increased about $0.024^{circ}C/year$ for the period of $1971{\sim}2000$ and relatively high $0.047^{circ}C/year$ in December. According to the analysis of time series of the two kind of variation, the SST and air-temperature are positively correlated. They are generally in phase, and SST anomaly is similar to air-temperature anomaly as well. Consequently, SST variation has high correlation with air-temperature variation around Jeju Island.

• Journal of the Korean association of regional geographers
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• v.4 no.2
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• pp.151-164
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• 1998

I analyzed the correlation between El-Nino phenomenon and our country's temperature and precipitation laying the stress on the anomaly, and the result of this analysis is as follows: (1) The extraction of the occurrences of El-Nino at the place of sea surface around Nino.3 which was known as the sea area under observation for El-Nino reveals that there are 9 years (1969, 1970, 1973, 1977, 1987, 1992, 1995, 1998) when the temperature anomaly in January is more than 1.0 during the period of research years ($1969{\sim}1998$). (2) The tendency of change of sea surface temperature around Nino.3 and that of our country are about the same, but the anomaly of Pusan and Inchon was much greater than that of Jangki in the East Coast. (3) The anomaly of sea surface temperature around Nino.3 and that of the ground temperature showed the similar changing tendency, the temperature of our country has something to do with that of sea surface as the correlation of ground temperature with the temperature of sea surface showed 0.31. Anomaly warm winter has something to do with El-Nino because the temperature of our country was high when El-Nino phenomenon appeared. (4) As for the precipitation, we can see that it has generally increased after 1989 when the phenomenon of warm climate was intense than before that year. But as we study the change of anomaly, the precipitation has less correlation in comparison with the ground temperature. The precipitation in 1973, 1983 and 1987 which were El-Nino years was correlated with El-Nino. While the change of sea surface temperature has showed a tendency of plus(+)increase since 1990, the precipitation has showed a tendency of minus (-)decrease. Therefore it seems that the temperature of sea surface has little correlation with the amount of rainfall.

• Journal of the Korean earth science society
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• v.24 no.6
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• pp.558-567
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• 2003

The regional dependency of cloud-radiative forcing at the top of atmosphere is studied using ERBE (Earth Radiation Budget Experiment), ISCCP (International Satellite Cloud Climatology Project) and NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data for 60 months from January 1985 to December 1989 over tropical ocean. In the interannual time scale, the dependency of cloud-radiative forcing on the sea surface temperature over the equatorial eastern Pacific ocean is about 7.4Wm$^{-2}$K$^{-1}$ for longwave radiation and about -4.4Wm$^{-2}$K$^{-1}$ for shortwave radiation, respectively. This shows that the net cloud-radiative forcing due to the increase of sea surface temperature over the equatorial eastern Pacific ocean heats the atmosphere. But the dependency is reversed over tropical oceans with -3.4Wm$^{-2}$K$^{-1}$ for longwave and 1.9WmWm$^{-2}$K$^{-1}$ for shortwave radiation, indicating that the net cloud-radiative forcing cools the atmosphere over tropical oceans. In raw data including seasonal cycle, the dependency of cloud-radiative forcing over the equatorial eastern Pacific ocean is very similar to that in interannual time scale in both the magnitude and the sign. But the dependency of cloud-radiative forcing on the sea surface temperature over tropical oceans is about 0.2Wm$^{-2}$K$^{-1}$ for longwave and 2.7Wm$^{-2}$K$^{-1}$ for shortwave radiation, respectively. These results represent that the role of seasonal cycle on the cloud radiative forcing is gradually more important than role of interannual time scale as the ocean area is broadening from the tropical central Pacific to the tropical ocean.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.632-645
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• 2021

Satellite sea surface temperature (SST) composites provide important data for numerical forecasting models and for research on global warming and climate change. In this study, six types of representative SST composite database were collected from 2007 to 2018 and the characteristics of spatial structures of SSTs were analyzed in seas around the Korean Peninsula. The SST composite data were compared with time series of in-situ measurements from ocean meteorological buoys of the Korea Meteorological Administration by analyzing the maximum value of the errors and its occurrence time at each buoy station. High differences between the SST data and in-situ measurements were detected in the western coastal stations, in particular Deokjeokdo and Chilbaldo, with a dominant annual or semi-annual cycle. In Pohang buoy, a high SST difference was observed in the summer of 2013, when cold water appeared in the surface layer due to strong upwelling. As a result of spectrum analysis of the time series SST data, daily satellite SSTs showed similar spectral energy from in-situ measurements at periods longer than one month approximately. On the other hand, the difference of spectral energy between the satellite SSTs and in-situ temperature tended to magnify as the temporal frequency increased. This suggests a possibility that satellite SST composite data may not adequately express the temporal variability of SST in the near-coastal area. The fronts from satellite SST images revealed the differences among the SST databases in terms of spatial structure and magnitude of the oceanic fronts. The spatial scale expressed by the SST composite field was investigated through spatial spectral analysis. As a result, the high-resolution SST composite images expressed the spatial structures of mesoscale ocean phenomena better than other low-resolution SST images. Therefore, in order to express the actual mesoscale ocean phenomenon in more detail, it is necessary to develop more advanced techniques for producing the SST composites.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1117-1120
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• 2009

최근 이상기후와 같은 기후변화로 인한 기온, 강수 등의 변화는 안정적인 수자원 확보에 큰 영향을 미칠 것으로 판단되고 수자원을 필요로 하는 사회 모든 분야에 있어 큰 영향을 끼친다. 특히 농업, 공업, 도시의 용수 공급에 있어 변화는 더욱 심해질 것으로 판단되며 기후변화로 인한 기온, 강수 등의 변화의 정확한 분석이 필요로 한다. 따라서 본 연구에서는 동아시아 해수면 온도와 우리나라 강수량에 대한 MSSA (Multi-channel Singular Spectrum Analysis)를 실시함으로 두 시계열 사이에 공통적으로 나타나는 변화, 즉 특정 상관 주기 변동을 분석함으로 두 변수 사이에 변화 상관 분석을 실시하였다. 우리나라 강수량 자료로는 현재 기상청에서 운영 중인 지상 기상관측소 76개소 중 가용관측소 61개소 자료에 대하여 1973년 1월부터 2008년 12월까지의 자료를 수집하여 월 평균값을 사용하였고 동아시아 해수면 온도 자료로는 한반도 근해 해수면 온도 변화, 남중국해 해수면 온도 변화, 인도양 해수면 온도 변화, 적도 해수면 온도 변화 등을 선택하여 관측시점부터 2008년 12월까지 자료를 수집하여 사용하였다. 분석 자료에 대해 선형 회귀분석을 통한 선형추세 제거와 정규화한 자료를 사용하여 각각의 지수에 대해 MSSA 분석을 실시하였다. 이때 window length는 Vautard 등(1992)이 제시한 N/5$^{\sim}$N/3의 값인 108의 값을 사용하였고 이때 각각의 고유치는 전체 공분산에 대한 각 요소의 비율을 설명한다. 상관분석 결과는 각 지수와 강수자료 사이에 높은 상관성을 가지는 장단주기 변화가 존재함을 보여주었다. 그럼에도 불구하고 우리나라 월강수자료의 전체 변화는 계절변화를 제외하고도 장단 주기를 가지는 시간변화가 자료 전체 변화의 절반에 해당하며 장주기 변화가 나타내는 부분이 미미하다. 이는 계절 주기를 제외한 자료들 사이의 상관변화가 설명할 수 있는 부분이 미미 하며 여러 기상지수들과 국내 강수량사이의 MSSA 분석을 통하여 제시 할 수 있는 변화의 정량적 정도가 매우 제한됨을 보여준다. 그럼에도 불구하고 이러한 접근을 통하여 강수 변화의 불확실성을 줄여나가는 노력이 필요하다고 하겠다.