• Journal of the Korean earth science society
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• v.39 no.6
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• pp.555-567
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• 2018

In order to identify the characteristics of sea surface temperature (SST) differences between microwave SST from GCOM-W1/AMSR2 and in-situ measurements in the western coast of Korea, a total of 6,457 collocated matchup data were produced using the in-situ temperature measurements from marine buoy stations (Deokjeokdo, Chilbaldo, and Oeyeondo) from July 2012 to December 2017. The accuracy of satellite microwave SSTs was presented by comparing the ocean buoy data of Deokjeokdo, Chilbaldo, and Oeyeondo stations with the AMSR2 SST data more than five years. The SST differences between the microwave SST and the in-situ temperature measurements showed some dependence on environmental factors, such as wind speed and water temperature. The AMSR2 SSTs were tended to be higher than the in-situ temperature measurements during the daytime when the wind speed was low ($<6ms^{-1}$). On the other hand, they showed positive deviation increasingly as the wind speed increased for nighttime. In addition, increasing tendency of SST differences was related to decreasing sensitivity of microwave sensors at low temperatures and data contamination by land. A monthly analysis of the SST difference showed that unlike the previous trend, which was known to be the largest in winter when strong winds were blowing, the SST difference was largest in summer in Deokjeokdo and Chilbaldo buoy stations. This seemed to be induced by differential tidal mixing at the collocated matchup points. This study presented problems and limitations of the use of microwave SSTs with high contribution to the SST composites in the western coastal region off the Korean peninsula.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.273-287
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• 2008

Characteristics of skin-bulk sea surface temperature (SST) differences in the Northeast Asia seas were analyzed by utilizing 845 collocated matchup data between NOAA/AVHRR data and oceanic in-situ temperature measurements for selected months from 1994 to 2003. In order to understand diurnal variation of SST within a few meters of the upper ocean, the matchup database were classified into four categories according to day-night and drifter-shipboard measurements. Temperature measurements from daytime drifters showed a good agreement with satellite MCSST (Multi-Channel Sea Surface Temperature) with an RMS error of about $0.56^{\circ}C$. Poor accuracy of SST with an rrns error of $1.12^{\circ}C$ was found in the case of daytime shipboard CTD (Conductivity, Temperature, Depth) measurements. SST differences between MCSST and in-situ measurements are caused by various errors coming from atmospheric moist effect, coastal effect, and others. Most of the remarkable errors were resulted from the diurnal variation of vertical temperature structure within a few meters as well as in-situ oceanic temperatures at different depth, about 20 cm for a satellite-tracked drifting buoy and a few meters for shipboard CTD or moored buoy. This study suggests that satellite-derived SST shows significant errors of about ${\pm}3^{\circ}C$ in some cases and therefore it should be carefully used for one's purpose on the base of in-depth understanding of skin-bulk SST difference and vertical temperature structure in regional sea.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.525-532
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• 2021

In the ocean, it is difficult to separate the effects of one cause due to the multiple causes, but the self-organizing map can be analyzed by adding other factors to the cluster result. Therefore, in this study, the results of the clustering of sea level data were applied to sea surface temperature. Sea level data was clustered into a total of 6 nodes. The difference between sea surface temperature and sea level height has a one-month delay, which applied sea surface temperature data a month ago to the clustered results. As a result of comparing the mean of sea surface temperature of 140 to 150°E, where the sea surface temperature was variously distributed, in the case of nodes 1, 3, and 5, it was possible to find a meandering sea surface temperature distribution that is clearly distinguished from the sea level data. While nodes 2, 4 and 6, the sea surface temperature distribution was smooth. In this study, sea surface temperature data were applied to the clustered results of sea level data, but later it is necessary to apply wind or geostrophic velocity data to compare.

• 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.

• 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.

• Journal of the Korean earth science society
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• v.43 no.5
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• pp.604-617
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• 2022

Sea surface temperature (SST) is a key variable that can be used to understand ocean-atmosphere phenomena and predict climate change. Satellite microwave remote sensing enables the measurement of SST despite the presence of clouds and precipitation in the sensor path. Therefore, considering the high utilization of microwave SST, it is necessary to continuously verify its accuracy and analyze its error characteristics. In this study, the validation of the microwave global precision measurement (GPM)/GPM microwave imager (GMI) SST around the Northwest Pacific and Korean Peninsula was conducted using surface drifter temperature data for approximately eight years from March 2014 to December 2021. The GMI SST showed a bias of 0.09K and an average root mean square error of 0.97K compared to the actual SST, which was slightly higher than that observed in previous studies. In addition, the error characteristics of the GMI SST were related to environmental factors, such as latitude, distance from the coast, sea wind, and water vapor volume. Errors tended to increase in areas close to coastal areas within 300 km of land and in high-latitude areas. In addition, relatively high errors were found in the range of weak wind speeds (<6 m s^-1) during the day and strong wind speeds (>10 m s^-1) at night. Atmospheric water vapor contributed to high SST differences in very low ranges of <30 mm and in very high ranges of >60 mm. These errors are consistent with those observed in previous studies, in which GMI data were less accurate at low SST and were estimated to be due to differences in land and ocean radiation, wind-induced changes in sea surface roughness, and absorption of water vapor into the microwave atmosphere. These results suggest that the characteristics of the GMI SST differences should be clarified for more extensive use of microwave satellite SST calculations in the seas around the Korean Peninsula, including a part of the Northwest Pacific.

• Journal of Korea Water Resources Association
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• v.43 no.5
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• pp.471-482
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• 2010

Rainfall events in the hydrologic circulation are closely related with various meteorological factors. Therefore, in this research, correlation relationship was analyzed between sea surface temperature of typical meteorological factor and monthly rainfall on Korean peninsula. The cluster analysis was performed monthly average rainfall data, longitude and latitude observed by rainfall observatory in Korea. Results from cluster analysis using monthly rainfall data in South Korea were divided into 4 regions. The principal components of monthly rainfall data were extracted from rainfall stations separated cluster regions. A correlation analysis was performed with extracted principal components and sea surface temperatures. At the results of correlation analysis, positive correlation coefficients were larger than negative correlation coefficients. In addition, The 3 month of principal components on monthly rainfall predicted by locally weighted polynomial regression using observed data of sea surface temperature where biggest correlation coefficients have. The result of forecasting through the locally weighted polynomial regression was revealed differences in accuracy. But, this methods in the research can be analyzed for forecasting about monthly rainfall data. Therefore, continuous research need through hydrological meteorological factors like a sea surface temperature about forecasting of the rainfall events.

• Journal of the Korean earth science society
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• v.29 no.3
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• pp.280-289
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• 2008

An extensive set of both in-situ and satellite data regarding oceanic sea surface temperatures in Northeast Asian seas, collected over a 10-year period, was collocated and surveyed to assess the accuracy of satellite-observed sea surface temperatures (SST) and investigate the characteristics of satellite measured SST errors. This was done by subtracting insitu SST measurements from multi-channel SST (MCSST) measurements. 845 pieces of collocated data revealed that MCSST measurements had a root-mean-square error of about 0.89$^{\circ}C$ and a bias error of about 0.18$^{\circ}C$. The SST errors revealed a large latitudinal dependency with a range of $\pm3^{\circ}C$ around 40$^{\circ}N$, which was related to high spatial and temporal variability from smaller eddies, oceanic currents, and thermal fronts at higher latitudes. The MCSST measurements tended to be underestimated in winter and overestimated in summer when compared to in-situ measurements. This seasonal dependency was discovered from shipboard and moored buoy measurements, not satellite-tracked surface drifters, and revealed the existence of a strong vertical temperature gradient within a few meters of the upper ocean. This study emphasizes the need for an effort to consider and correct the significant skin-bulk SST difference which arises when calculating SST from satellite data.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.21 no.1
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• pp.47-54
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• 1993

The major positive sea surface temperature(SST) anomalies not only occur in the region with the most moisture increase, but also in the flank of the area with sinking motion in the Subtropics. As the large amount of water vapor has been increased by the SST anomaly, the increased of the SST is expected to destabilize the air and leads under moist adiabatic unstable conditions, to an enhanced development of moisture cluster. The 4.0 K change of SST causes the positive difference of Brightness Temperature(TB) of about 10.0k for water vapor channels of TOVS over the north eastern and central tropical Pacific Ocean, but the negative difference of TB of about 7.5 K is shifted southward and southeastward to Southern Pacific Ocean along the equator correspondingly. The difference of the TBs for IR water vapor channel $11(7.3{\mu}m)$ and $12(6.7{\mu}m)$ of TOVS indicative of the moisture distribution during two time periods(January 1983 and 1984), leads us to infer significant changes in the entire tropospheric circulations and the dynamic processes over the Pacific Ocean.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.617-629
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• 2020

Sea surface temperature (SST), which plays an important role in climate change and global environmental change, can be divided into skin sea surface temperature (SSST) observed by satellite infrared sensors and the bulk temperature of sea water (BSST) measured by instruments. As sea surface temperature products distributed by many overseas institutions represent temperatures at different depths, it is essential to understand the relationship between the SSST and the BSST. In this study, we constructed an observation system of infrared radiometer onboard a marine research vessel for the first time in Korea to measure the SSST. The calibration coefficients were prepared by performing the calibration procedure of the radiometer device in the laboratory prior to the shipborne observation. A series of processes were applied to calculate the temperature of the layer of radiance emitted from the sea surface as well as that from the sky. The differences in skin-bulk temperatures were investigated quantitatively and the characteristics of the vertical structure of temperatures in the upper ocean were understood through comparison with Himawari-8 geostationary satellite SSTs. Comparison of the skin-bulk temperature differences illustrated overall differences of about 0.76℃ at Jangmok port in the southern coast and the offshore region of the eastern coast of the Korean Peninsula from 21 April to May 6, 2020. In addition, the root-mean-square error of the skin-bulk temperature differences showed daily variation from 0.6℃ to 0.9℃, with the largest difference of 0.83-0.89℃ at 1-3 KST during the daytime and the smallest difference of 0.59℃ at 15 KST. The bias also revealed clear diurnal variation at a range of 0.47-0.75℃. The difference between the observed skin sea surface temperature and the satellite sea surface temperature showed a mean square error of approximately 0.74℃ and a bias of 0.37℃. The analysis of this study confirmed the difference in the skin-bulk temperatures according to the observation depth. This suggests that further ocean shipborne infrared radiometer observations should be carried out continuously in the offshore regions to understand diurnal variation as well as seasonal variations of the skin-bulk SSTs and their relations to potential causes.