• Journal of Environmental Science International
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• v.18 no.5
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• pp.489-499
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• 2009

In an effort to examine the Regional Atmospheric Modeling System (RAMS ver. 4.3) to the initial meteorological input data, detailed observational data of NOAA satellite SST (Sea Surface Temperature) was employed. The NOAA satellite SST which is currently provided daily as a seven-day mean value with resolution of 0.1 $^{\circ}$ grid spacing was used instead of the climatologically derived monthly mean SST using in RAMS. In addition, the RAMS SST data must be changed new one because it was constructed in 1993. For more realistic initial meteorological fields, the NOAA satellite SST was incorporated into the RAMS-preprocess package named ISentropic Analysis package (ISAN). When the NOAA SST data was imposed to the initial condition of prognostic RAMS model, the resultant performance of near surface atmospheric fields was discussed and compared with that of default option of SST. We got the good results that the new SST data was made in a standard RAMS format and showed the detailed variation of SST. As the modeling grid became smaller, the SST differences of the NOAA SST run and the RAMS SST43 (default) run in diurnal variation were very minor but this research can apply to further study for the realistic SST situation and the development in predicting regional atmospheric field which imply the regional circulation due to differential surface heating between sea and land or climatological phenomenon.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2265-2270
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• 2008

It was studied to the displacement and the amount of catch for migratory fishes with NOAA/AVHRR SST(Sea Surface Temperature) from 1988 to 2000 in the Korean Seas. The analyzed results from SST data showed generally the oceanic warming trend in the Korean Seas. On the increasement of SST, the distributed areas of migratory fishes which living in the warm waters were displaced gradually to the northward directions(high latitude) and then the amount of catch was increased during this studied periods against to migratory fishes which living in the cold waters.

• 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.

• Proceedings of the KSRS Conference
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• v.2
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• pp.993-996
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• 2006

NOAA operational bulk SST product (Reynolds et al, 2002) is very popular global SST data sets and is extensively used for various studies. However, the original time resolution is weekly and relatively large. On the other hand, there exist many new global SST data sets at present. In this study, we compare many global SST data sets including NOAA operational bulk SST product, CAOS OI SST product, Microwave Optimum Interpolation (MWOI) SST, Real Time Global (RTG) SST and JMA merged satellite and in situ Global Daily (MGD) SST.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.183-188
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• 2001

The NOAA AVHRR remotely sensed SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the sea near korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple SST images, all of images must be consistent exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which automatically detects cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$3$^{\circ}C$ as a criterion of SST anomalies). The remotely sensed SST data are tuned by comparing remotely sensed data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel and the SST anomalies are studied by statistical method. It was found that the SST anomalies are rather persistent for one or two months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST. In the Markov lprocess model of SST anomalies, autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. The developed algorithm with automatic cloud pixel detection and rediction of future SST is expected to be incorporated to the operational real time service of SST around Korea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2818-2826
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• 2010

To study the spatial and temporal variations of sea surface temperature(SST) in the Northeast Asia sea during the period of 1985 to 2009. At first, the buoy data from Korea Meteorological Administration(KMA) and the satellite data have been matched up eight points. The root mean square error and the bias were increased towards the coastal shallow region. The study area which is divided 7 regions from Japan Meteorological Agency(JMA). We analyzed NOAA/AVHRR data by harmonic analysis which is comparison and analysis the center of the each regions. The mean SST varied between $8^{\circ}C$ to $26.0^{\circ}C$. The annual amplitude varied between $7^{\circ}C$ to $24^{\circ}C$. And the annual phase varied between end of July to end of August. Cross-correlation coefficients of mean SST, annual amplitude, and annual phase varied 0.57 to 0.85, -0.04 to 0.81 and 0.35 to 0.80 at all study area, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.290-294
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• 2001

Satellite data, with Sea Surface Temperature(SST) by NOAA and Sea Level(SL) by Topex/poseidon, are used to estimate characteristics on the variations and correlations of SST and SL in the East Asian Seas from January 1993 through May 1998. In the oceanic climate, the variations of SL shown the high values in the main current of Kuroshio and the variations of SST shown not the remarkable seasonal variations because of the continuos compensation of warm current by Kuroshio. In the continental climate, SL shown high variations in the estuaries(the Yellow River, the Yangtze River) with the mixing the fresh water in the mouth of estuaries of the saline water in the coasts of continent and SST shown highly the seasonal variations due to the climatic effect of continents. In the steric variations in summer, the eastern sea of Japan, the East China Sea and the western sea of Korea shown the increment of sea level with 10~20cm. But the Bohai bay in China shown relatively the high values of 20~30cm due to the continental climate. Generally the trends of SST and SL increased during all periods. That is say, the slopes of SST and SL presented 0.29$^{\circ}C$/year and 0.84cm/year, respectively. The annual and semi-annual amplitudes shown a remarkable variations in the western sea of Korea and the eastern sea of Japan.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.45-59
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• 2009

This research presents the effect of Asian dust on the derived sea surface temperature (SST) from measurements of the Advanced Very High Resolution Radiometer (AVHRR) instrument flown onboard NOAA polar orbiting satellites. To analyze the effect, A VHRR infrared brightness temperature (TB) is estimated from simulated radiance calculated from radiative transfer model on various atmospheric conditions. Vertical profiles of temperature, pressure, and humidity from radiosonde observation are used to build up the East Asian atmospheric conditions in spring. Aerosol optical thickness (AOT) and size distribution are derived from skyradiation measurements to be used as inputs to the radiative transfer model. The simulation results show that single channel TB at window region is depressed under the Asian dust condition. The magnitude of depression is about 2K at nadir under moderate aerosol loading, but the magnitude reaches up to 4K at slant path. The dual channel difference (DCD) in spilt window region is also reduced under the Asian dust condition, but the reduction of DCD is much smaller than that shown in single channel TB simulation. Owing to the depression of TB, SST has cold bias. In addition, the effect of AOT on SST is amplified at large satellite zenith angle (SZA), resulting in high variance in derived SSTs. The SST depression due to the presence of Asian dust can be expressed as a linear function of AOT and SZA. On the basis of this relationship, the effect of Asian dust on the SST retrieval from the conventional daytime multi-channel SST algorithm can be derived as a function of AOT and SZA.

• Proceedings of the KSRS Conference
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• v.2
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• pp.1027-1030
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• 2006

Development of diurnal warming in the open Okhotsk Sea during the daytime and calm conditions was studied using sea surface temperature (SST) fields retrieved from NOAA AVHRR, Terra and Aqua MODIS, Aqua AMSR-E and ADEOS-II AMSR data. Sea surface wind fields were estimated from AMSR-E/AMSR measurements as well as were obtained from QuikSCAT scatterometer. Weak winds and cloudless conditions were observed in the central area of anticyclone, which moved slowly on 28-30 June 2003 east off Sakhalin. The area where the amplitude of the diurnal SST signal ${\Delta}T$ was significant also shifted slowly and had or circular or elongated shape. The ${\Delta}T$ was estimated relative to the SST values in the areas surrounding the centre of anticyclone where wind speed W exceeded 5- 6 m/s. The diurnal variations of SST, day-night differences were computed using NOAA-12 and NOAA-16 AVHRRderived data. Analysis of simultaneous SST and W fields showed that the increase of W from 0 to 5-6 m/s causes the decrease of ${\Delta}T$ to zero. Maximum warming exceeded $8^{\circ}C$ and was observed in the centre of anticyclone where W = 0 m/s. So strong heating was likely due to the increased chlorophyll a concentration in the area under study that follows from analysis of satellite ocean colour data.

• Korean Journal of Remote Sensing
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• v.3 no.1
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• pp.41-54
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• 1987

Accurate determination of Sea Surface Temperature (SST) is essential for ocean and climate studies. This paper estimated SST in the sea region around the Korea from the Advenced Very High Resolution Radiometer(AVHRR) channel 4 data on board NOAA-9 satellite. The processing procedure used to derive SSTs utilized: 1) Ascending node prediction of satellite orbit 2) Geometric correction 3) Radiometric calibration and radiance to temperature conversion look up table 4) Removing cloudy area. SST product results are displayed as colored video and hardcopy. In this processing, geometric correction is derived from equator crossing time, ascending time and subpoint coordinate information. Also, normalized response function of infrared 10.5-11.5$\mu\textrm{m}$ wavelength is used for temperature conversion. The SST derived from this processing is relatively similar to the measurements made by ship data, but because of water vapor attenuation SST from satellite are in general 2$^{\circ}$- $^{\circ}C$ lower than the ship data.