• Journal of the Korean earth science society
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• v.45 no.1
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• pp.19-36
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• 2024

The global seasonal forecasting system version 6 (GloSea6) operated by the Korea Meteorological Administration for 1- and 3-month prediction products does not include complex atmospheric chemistry-aerosol physical processes (UKCA). In this study, low-resolution GloSea6 and GloSea6 coupled with UKCA (GloSea6-UKCA) were installed in a CentOS-based Linux cluster system, and preliminary prediction results for the spring of 2000 were examined. Low-resolution versions of GloSea6 and GloSea6-UKCA are highly needed to examine the effects of atmospheric chemistry-aerosol owing to the huge computational demand of the current high resolution GloSea6. The spatial distributions of the surface temperature and daily precipitation for April 2000 (obtained from the two model runs for the next 75 days, starting from March 1, 2000, 00Z) were compared with the ERA5 reanalysis data. The GloSea6-UKCA results were more similar to the ERA5 reanalysis data than the GloSea6 results. The surface air temperature and daily precipitation prediction results of GloSea6-UKCA for spring, particularly over East Asia, were improved by the inclusion of UKCA. Furthermore, compared with GloSea6, GloSea6-UKCA simulated improved temporal variations in the temperature and precipitation intensity during the model integration period that were more similar to the reanalysis data. This indicates that the coupling of atmospheric chemistry-aerosol processes in GloSea6 is crucial for improving the spring predictions over East Asia.

• Journal of the Korean earth science society
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• v.45 no.3
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• pp.192-202
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• 2024

Ocean reanalysis data are extensively used in ocean circulation and climate research by integrating observational data with numerical models. This approach overcomes the spatial and temporal limitations of observational data and provides high-resolution gridded information that considers the physical interactions between ocean variables. In this study, I extended the previously produced 12-year (2011-2022) Northwest Pacific regional ocean reanalysis data to create a long-term reanalysis dataset (K-ORA22E) with a horizontal resolution of 1/24° spanning 30 years (1993-2022). These data were analyzed to diagnose long-term ocean climate change in the Korean marginal seas. Analysis of the K-ORA22E data revealed that the axis of the Kuroshio extension has shifted northward by approximately 6 km per year over the past 30 years, with a significant increase in sea surface temperature north of the Kuroshio axis. Among the waters surrounding the Korean Peninsula, the East Sea exhibited the most significant temperature increase. In the East Sea, the temperature increase was more pronounced in the middle layer than in the surface layer, with the East Korea Warm Current showing a rate two to three times higher than the global average. In the central Yellow Sea, where the Yellow Sea Bottom Cold Water appears, temperatures increased over the long-term, but decreased along the west and south coasts of the Korean Peninsula. These spatial differences in long-term temperature changes appear to be closely related to the heat transport pathways of warm water from the Kuroshio Current. High-resolution regional ocean reanalysis data, such as the K-ORA22E produced in this study, are essential foundational data for understanding long-term variability in the Korean marginal seas and analyzing the impacts of climate change.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.613-623
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• 2019

Over the past decades, daily sea surface temperature (SST) composite data have been produced using periodically and extensively observed satellite SST data, and have been used for a variety of purposes, including climate change monitoring and oceanic and atmospheric forecasting. In this study, we evaluated the accuracy and analyzed the error characteristic of the SST composite data in the sea around the Korean Peninsula for optimal utilization in the regional seas. We evaluated the four types of multi-satellite SST composite data including OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis), OISST (Optimum Interpolation Sea Surface Temperature), CMC (Canadian Meteorological Centre) SST, and MURSST (Multi-scale Ultra-high Resolution Sea Surface Temperature) collected from January 2016 to December 2016 by using in-situ temperature data measured from the Ieodo Ocean Research Station (IORS). Each SST composite data showed biases of the minimum of 0.12℃ (OISST) and the maximum of 0.55℃ (MURSST) and root mean square errors (RMSE) of the minimum of 0.77℃ (CMC SST) and the maximum of 0.96℃ (MURSST) for the in-situ temperature measurements from the IORS. Inter-comparison between the SST composite fields exhibited biases of -0.38-0.38℃ and RMSE of 0.55-0.82℃. The OSTIA and CMC SST data showed the smallest error while the OISST and MURSST data showed the most obvious error. The results of comparing time series by extracting the SST data at the closest point to the IORS showed that there was an apparent seasonal variation not only in the in-situ temperature from the IORS but also in all the SST composite data. In spring, however, SST composite data tended to be overestimated compared to the in-situ temperature observed from the IORS.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.33-36
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• 2007

We have persistently constructed gridded products of surface wind/wind stress over the world ocean using satellite scatterometer (ERS and Qscat). They are available for users as the Japanese Ocean Flux data sets with Use of Remote sensing Observation (J-OFURO) data together with heat flux components. Recently, a new version data of the Qscat/SeaWinds based on improved algorithm for rain flag and high wind-speed range have been delivered, and allowed us to reconstruct gridded product with higher spatial resolution. These products are validated by comparisons with in-situ measurement data by mooring buoys such as TAO/TRITON, NDBC and the Kuroshio Extension Observation (KEO) buoys, together with numerical weather prediction model products such as the NCEP-1 and 2. Results reveal that the new product has almost the same magnitude in mean difference as the previous version of Qscat product and much smaller than the NCEP-1 and 2. On the other hand, it is slightly larger root-mean-square (RMS) difference than the previous one and NCEPs for the comparison using the KEO buoy data. This may be due to the deficit of high wind speed data in the buoy measurement. The high resolution product, together with sea surface temperature (SST) one, is used to examine a new type of relationship between the lower atmosphere and upper ocean in the Kuroshio Extension region.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.797-807
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• 2014

The Sea Surface Temperature (SST) is one of the most important oceanic environmental factors in determining the change of marine environments and ecological activities. Satellite thermal infrared images can be effective for understanding the global trend of sea surface temperature due to large scale. However, their low spatial resolution caused some limitations in some areas where complicated and refined coastal shapes due to many islands are present as in the Korean Peninsula. The coastal ocean is also very important because human activities interact with the environmental change of coastal area and most aqua farming is distributed in the coastal ocean. Thus, low-cost airborne thermal infrared remote sensing with high resolution capability is considered for verifying its possibility to extract SST and to monitor the changes of coastal environment. In this study, an airborne thermal infrared system was implemented using a low-cost and ground-based thermal infrared camera (FLIR), and more than 8 airborne acquisitions were carried out in the western coast of the Korean Peninsula during the periods between May 23, 2012 and December 7, 2013. The acquired thermal infrared images were radiometrically calibrated using an atmospheric radiative transfer model with a support from a temperature-humidity sensor, and geometrically calibrated using GPS and IMU sensors. In particular, the airborne sea surface temperature acquired in June 25, 2013 was compared and verified with satellite SST as well as ship-borne thermal infrared and in-situ SST data. As a result, the airborne thermal infrared sensor extracted SST with an accuracy of $1^{\circ}C$.

• Korean Journal of Remote Sensing
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• v.5 no.1
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• pp.41-56
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• 1989

Improvement of the multichannel sea surface temperature(MCSST) software, which had been developed for the purpose of operating under mainframe computer system, was seeked in order to operate effectively in a mini computer system. CPU time and processing time, which is not a major factor under mainframe computer system, become a critical factor in real time image processing under mini computer system. Due to fixed kernel size(3$\times$4) of the old MCSST software, high spatial resolution characteristics of the original image received from satellites were apparently degraded when images are transformed into a cartesian coordinate system after geometrical distortions of the image due to earth curvature are removed. CPU and processing time were reduced to 0.13 and 0.15~0.22 comparing with the old MCSST's, respectively, by applying disk block I/O and M/T queue I/O method under VAX-11/750 computer. The high resolution quality (1.1km in AVHRR) of the processed image was guaranted using 2$\times$2 kernel size and applying moving window techniques without sacrificing CPU and processing time much.

• Journal of the Korean earth science society
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• v.45 no.4
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• pp.327-337
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• 2024

The ocean is linked to long-term climate variability, but there are very few methods to assess the short-term performance of forecast models. This study analyzes the short-term prediction performance regarding ocean temperature and salinity of the Global Seasonal prediction system version 5 (GloSea5). GloSea5 is a historical climate re-creation (2001-2010) performed on the 1st, 9th, 17th, and 25th of each month. It comprises three ensembles. High-resolution hindcasts from the three ensembles were compared with the Array for Real-Time Geostrophic Oceanography (ARGO) float data for the period 2001-2010. The horizontal position was preprocessed to match the ARGO float data and the vertical layer to the GloSea5 data. The root mean square error (RMSE), Brier Score (BS), and Brier Skill Score (BSS) were calculated for short-term forecast periods with a lead-time of 10 days. The results show that sea surface temperature (SST) has a large RMSE in the western boundary current region in Pacific and Atlantic Oceans and Antarctic Circumpolar Current region, and sea surface salinity (SSS) has significant errors in the tropics with high precipitation, with both variables having the largest errors in the Atlantic. SST and SSS had larger errors during the fall for the NINO3.4 region and during the summer for the East Sea. Computing the BS and BSS for ocean temperature and salinity in the NINO3.4 region revealed that forecast skill decreases with increasing lead-time for SST, but not for SSS. The preprocessing of GloSea5 forecasts to match the ARGO float data applied in this study, and the evaluation methods for forecast models using the BS and BSS, could be applied to evaluate other forecast models and/or variables.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.309-312
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• 2008

The advent of high resolution products of surface wind and temperature derived by satellite data has permitted us to investigate ocean and atmosphere interaction studies in detail. Especially the Kuroshio extension region of the western North Pacific is considered to be a key area for such studies. We have constructed gridded products of surface wind/wind stress over the world ocean using satellite scatterometer (Qscat/SeaWinds), available as the Japanese Ocean Flux data sets with Use of Remote sensing Observation (J-OFURO). Using new data based on improved algorithm which have been recently delivered, we are reconstructing gridded product with higher spatial resolution. Intercomparison of this product with the previous one reveals that there are some discrepancies between them in short-period and high wind-speed ranges especially in the westerly wind region. The products are validated by not only comparisons with in-situ measurement data by mooring buoys such as TAO/TRITON in the tropical Pacific and the Kuroshio Extension Observation (KEO) buoys, but also intercomparison with numerical weather prediction model (NWPM) products (the NRA-1 and 2). Our products have much smaller mean difference in the study areas than the NWPM ones, meaning higher reliability compared with the NWPM products. Using the high resolution products together with sea surface temperature (SST) data, we examine a new type of relationship between the lower atmosphere and upper ocean in the Kuroshio Extension region. It is suggested that the spatial relation between the wind speed and SST depends upon, more or less, the surrounding oceanic condition.

• Journal of Environmental Science International
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• v.9 no.3
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• pp.215-221
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• 2000

The relationship between the distribution of sea surface temperature(SST) and dinoflagellate(Cochlodinium polykrikoides) bloom areas were studied. The SST data were derived from the infrared channels of AVHRR(Advanced Very High Resolution Radiometer) sensor on NOAA(National Oceanic and Atmospheric Administration) 12 and 14 satellites during 1995-1998. The initial water temperature at C. polykrikoides bloom was about 21${\circ}C$ at the coastal areas of the South Sea and along the shore of the East Sea of Korea during the summer season of 1995. The northern limit of red tides was coincident with that of 21${\circ}C$ isothermal line in the East Sea. The red tides that initially bloomed at the coast of Pohang on September 21, 1995 moved to the coast of Uljin on September 26, 1995. The skipped appearance of the red tides in the areas between Pohang and Uljin was due to the East Korean Warm Current, which was moving offshore from Pohang to approach to Uljin. The cold water which was formed by tidal front in the western coast of the South Sea and by upwelling water from deep layer in the southeastern coast of the Korean peninsula played a role in blocking the spreading of red tides during summer season in 1997 and 1998. In conclusion, the distribution of red tides appeared to be dependent on the initial water temperature at red tides bloom. The SST at the red tides varied from 21${\circ}C$ to 25${\circ}C$; 21${\circ}C$, 23${\circ}C$, 24 and 24-25${\circ}C$ in 1995, 1996, 1997 and 1998, respectively.

• 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.