• Journal of Environmental Science International
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• v.15 no.7
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• pp.653-657
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• 2006

Based on the monthly weather report of Korea Meteorological Administration (KMA) and daily sea surface temperature (SST) data from National Fisheries Research and Development Institute (NFRDI) (1995-2004), mean heat fluxes were estimated at the port of Yeosu. Net heat flux was transported from the air to the sea surface during February to September, and it amounts to $205 Wm^{-2}$ in daily average value in May. During October to January, the transfer of net heat flux was conversed from the sea surface to the air with $-70 Wm^{-2}$ in minimum of daily average value in December. Short wave radiation was ranged from $167 Wm^{-2}$ in December to $300 Wm^{-2}$ in April. Long wave radiation (Sensible heat) was ranged from $27 (-14) Wm^{-2}$ in July to $90 (79) Wm^{-2}$ in December. Latent heat showed $42 Wm^{-2}$ with its minimum in July and $104 Wm^{-2}$ with its maximum in October in daily average value.

• Journal of Korea Water Resources Association
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• v.44 no.5
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• pp.339-350
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• 2011

This study developed a climate informed Bayesian nonstationary frequency model which allows us to forecast seasonal summer rainfall at Nakdong River. We constructed a 37-year summer rainfall data set from 10 weather stations within Nakdong river basin, and two climate indices from sea surface temperature (SST) and outgoing longwave radiation (OLR) were derived through correlation analysis. The selected SST and OLR have been widely acknowledged as a climate driver for summer rainfall. The developed model was applied first to the 2010-year summer rainfall (888.1 mm) in order to assure ourself. We demonstrated model performance by comparing posterior distributions. It was confirmed that the proposed model is able to produce a reasonable forecast. The forecasted value is about 858.2 mm, and the difference between forecast and observation is about 30 mm. As the second case study, 2011-year summer rainfall forecast was made using an observed winter SSTs and an assumed 50% value of OLRs. The forecasted value is 967.7 mm and associated exceedance probability over average summer rainfall 680 mm is 92.9%. In addition, 50-year return period for summer rainfall was projected through the nonstationary frequency model. An exceedance probability over 1,400 mm corresponding to the 50-year return level is about 73.7%.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.18 no.6
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• pp.497-505
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• 1985

We studied the annual and interannual fluctuations of sea surface temperature (SST) for 30 years ($1941{\sim}1970$) at 9 coastal stations in the Tsushima Current and the Kuroshio regions by means of harmonic analysis, correlation analysis, and spectral analysis. The fluctuations of annual mean and amplitude are 0.3 to $0.7^{\circ}C$, and those of annual phase are 3 to 4 days. The SST anomalies are about $1^{\circ}C$, and they are relatively large in summer and winter than in spring and fall. The SST anomalies in the Tsushima Current and the Kuroshio regions are related with each other. The predominant periods of SST anomalies differ slightly from station to station. The quasi-biennial (26 months) and pole tide (14 months) oscillations are found in the spectra of SST anomalies.

• Journal of Environmental Health Sciences
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• v.43 no.6
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• pp.516-524
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• 2017

Objectives: The annual catch of the common squid Todarodes pacificus in Korean coastal waters has gradually increased since the late 1980s. We investigated the long-term effects of climate variability on the variation in catches of the squid in the offshore fisheries of Korea. Methods: Moving average method, correlation analysis, and regression analysis were used to determine the relationship between the environmental factors and fluctuation in the catch of the squid during the past 30 years (1981- 2010). A ten-year moving average was calculated and used for each variable. Results: Squid catches in Korean coastal waters increased over time, and there were significant variations within every ten years (p < 0.001). Air temperature, atmospheric pressure, and wind grade among the meteorological factors, alongside sea surface temperature (SST) and concentrations of phosphate phosphorous, and nitrite/nitrate nitrogen in the sea water increased and were positively related with the catch size of squid (p < 0.001). However, salinity decreased and was negatively related with the catch size (p < 0.001). The increase in air temperature and SST was almost parallel, although there was a time lag between the two factors. Conclusion: These results suggest that there is a causal association between climate change and squid populations. Climate change, especially ocean warming, appears to have been largely favorable for squid range expansion into Korean seas. Although the expansion may be helpful for the human food supply, the safety of the squid caught should be monitored since the concentrations of phosphorous and nitrogen in the sea water increased, which indicates that Korean seas have grown gradually more polluted.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.7
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• pp.811-818
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• 2014

This study was aimed to detect Submarine Groundwater Discharge (SGD) distribution image of Sea Surface Temperature (SST) using infrared band of Landsat-7 ETM+ around Jeju island. It is used to analyze SST distribution that DN value of satellite images converted into temperature. The estimation of SGD location is that extracting range of $15{\sim}17^{\circ}C$ from SST. The summer season images(July 28. 2006, Aug. 29. 2006 and Sep. 19. 2008) were used to analyze big difference between SST and temperature of SGD. The results, estimated SGD locations were occurred part of coastal area in northeastern of Jeju island.

• Journal of the Korean Geographical Society
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• v.28 no.2
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• pp.112-122
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• 1993

Since more than 50${\%}$ of annual precipitation in Korea falls during Changma, the rainy season of early summer, and Late Changma, the rainy season of late summer, forcasting the onset days Changmas, and the amount related rainfalls would be necessary not only for agriculture but also for flood-control. In this study the authors attempted to build a prediction model for the forecast of the onset date of Changmas. The onset data of each Changma was derived out of daily rainfall data of 47 stations for 30 years(1961~1990) and weather maps over East Asia. Each station represent any of the 47 districts of local forecast under the Korea Meteorological Administration. The average onset dates of Changma during the period was from 21 through 26 June. The dates show a tendency to be delayed in El Ni${\~{n}}o years while they come earlier than the average in La Nina years. In 1982, the year of El Ni${\~{n}}o, the date was 9 Julu, two weeks late compared with the average. The relation of sea surface temperature(SST) over Pacific and Northern hemispheric 500mb height to the Changma onset dates was analyzed for the prediction model by polynomial regression. The onset date of Changma over Korea was correlated with SST in May(SST${_(5)}{^\circ}$C) of the district (8${^\circ}$~12${^\circ}S, 136${^\circ}~148${^\circ}W)of equatirial middle Pacific and the 500mb height in March (MB${_(3)}$"\;"m)over the district of the notrhern Hudson Bay. The relation between this two elements can be expressed by the regression: Onset=5.888SST${_5}"\;"+"\;"0.047MB${_(3)}$"\;"-251.241. This equation explains 77${\%}$ of variances at the 0.01${\%}$ singificance level. The onset dates of Late Changma come in accordance with the degeneration of the Subtro-pical High over northern Pacific. They were 18 August in average for the period showing positive correlation(r=0.71) with SST in May(SST)${_(i5)}{^\circ}$C) over district of IndiaN Ocean near west coast of Australia (24${^\circ}$~32${^\circ}$S, 104${^\circ}$~112${^\circ}$E), but negativ e with SST in May(SST${_(p5)}{^\circ}$ over district (12${^\circ}$~20${^\circ}$S,"\;"136${^\circ}$~148${^\circ}$W)of equatorial mid Pacific (r=-0.70) and with the 500mb height over district of northwestern Siberia (r=-0.62). The prediction model for Late Changma can be expressed by the regression: Onset=706.314-0.080 MB-3.972SST${_(p5)}+3.896 SST${_(i5)}, which explains 64${\%}$ of variances at the 0.01${\%}$ singificance level.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.543-551
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• 2023

As climate change continues to prompt an increasing demand for advancements in disaster and safety management technologies to address abnormal high water temperatures, typhoons, floods, and droughts, sea surface temperature has emerged as a pivotal factor for swiftly assessing the impacts of summer harmful algal blooms in the seas surrounding Korean Peninsula and the formation and dissipation of cold water along the East Coast of Korea. Therefore, this study sought to gauge predictive performance by leveraging statistical methods and deep learning algorithms to harness sea surface temperature data effectively for marine anomaly research. The sea surface temperature data employed in the predictions spans from 2018 to 2022 and originates from the Heuksando Tidal Observatory. Both traditional statistical ARIMA methods and advanced deep learning models, including long short-term memory (LSTM) and gated recurrent unit (GRU), were employed. Furthermore, prediction performance was evaluated using the attention LSTM technique. The technique integrated an attention mechanism into the sequence-to-sequence (s2s), further augmenting the performance of LSTM. The results showed that the attention LSTM model outperformed the other models, signifying its superior predictive performance. Additionally, fine-tuning hyperparameters can improve sea surface temperature performance.

• 한국해양학회지
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• v.20 no.3
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• pp.6-19
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• 1985

Hydrographic data and daily time series of longshore wind, sea level and sea surface temperature were used in order to explain why the upwelling effect in SST is especially prominent near Ulgi-Gampo although the sea level records along the whole southeast coast show a nearly uniform upwelling-downwelling response to wind. Regional difference in intensity of the wind-induced upwelling represented by the SST decrease is attributed to the combined influence of two factors; one is the baroclinic tilting of isotherms due to the East Korea Warm Current (EKWC) near the Ulgi-Gampo coast, the other is the topographic effects around the southeast coast. Baroclinic tilting effect of EKWC which is generally strongest near the coast of Ulgi to Gampo results in both of the shoaling of cold water and the westward trapping of the coldest bottom water over the shallower shelf rather than the deepest troough region off that coast regardless of the season. Therefore, becacse of the cold water ready for upwelling at the subsurface layer, SST responds very rapidly to the upwelling-favorable winds of summer only off the Ulgi-Gampo coast. Spreading isobaths from Pusan to Gempo can reinforce the upwelling of the cold bottom water and its westward trapping.