• Ocean and Polar Research
• /
• v.31 no.4
• /
• pp.401-414
• /
• 2009

Yellow Sea Buoy (YSB) was moored in the center of the Yellow Sea at 35$^{\circ}$51'36"N, 124$^{\circ}$34'42"E, on 12 September 2007. YSB is a large buoy of 10 m diameter, and as such is more durable against collision by ships and less likely to be lost or removed by fishing nets compared to small ordinary buoys of 2.3 m diameter. YSB is equipped with 12 kinds of oceanic and meteorologic instruments, and transfers its realtime observation data to KORDI through ORBCOMM system every 1 hour. Data on ocean winds, air temperature, air pressure, and sea temperature appear to be accurate, while water property sensors (AAQ1183), which are sensitive to fouling, are producing errors. YSB (2007), Ieodo ocean research station (2003), and Gageocho ocean research station, which was completed in October 2009, will establish the 2 degrees interval by latitude in the Yellow Sea, and they will contribute though the 'Operational Oceanography System' as the important realtime observation network.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.22 no.3
• /
• pp.118-134
• /
• 2017

The radiation observation data will be used importantly in research field such as climatology, weather, architecture, agro-livestock and marine science. The Ieodo Ocean Research Station (IORS) is regarded as an ideal observatory because its location can minimize the solar radiation reflection from the surrounding background and also the data produced here can serve as a reference data for radiation observation. This station has the potential to emerge as a significant observatory and join a global radiation observation group such as the Baseline Surface Radiation Network (BSRN), if the surrounding of observatory is improved and be equipped with the essential radiation measuring instruments (pyaranometer and pyrheliometer). IORS has observed the solar radiation using a pyranometer since November 2004 and the data from January 1, 2005 to December 31, 2015 were analyzed in this study. During the period of this study, the daily mean solar radiation observed from IORS decreased to $-3.80W/m^2/year$ due to the variation of the sensor response in addition to the natural environment. Since the yellow sand and fine dust from China are of great interest to scientists around the world, it is necessary to establish a basis of global joint response through the radiation data obtained at the Ieodo as well as at Sinan Gageocho and Ongjin Socheongcho Ocean Research Station. So it is an urgent need to improve the observatory surrounding and the accuracy of the observed data.

• Atmosphere
• /
• v.22 no.1
• /
• pp.97-107
• /
• 2012

To investigate variation of aerosol number concentration at each different size with three-dimensional (3D) wind components in ocean area, aerosol particles and 3D wind components were measured in the Ieodo Ocean Research Station, which is located to 419 km southwest from Marado, the southernmost island of Korea, from 25 June to 8 July 2010. The Laser Particle Counter (LPC) and ultrasonic anemometer were used to measure the size of aerosol particles and 3D wind components (zonal (u), meridional (v), and vertical (w) wind) respectively. Surface weather chart, NCEP/NCAR reanalysis data and sounding data were used to analyze the synoptic condition. The distribution of aerosol number concentration had a large variation from bigger particles more than 1.0 ${\mu}m$ in diameter by wind direction during precipitation. In the number concentration of aerosol particles with respect to the weather conditions, particles larger than 1.0 ${\mu}m$ in size were decreased and sustained to the similar concentration at smaller particles during precipitation. The increase in aerosol number concentration was due to the sea-salt particles which was suspended by southwesterly and upward winds. In addition, the aerosol number concentration with vertical wind flow could be related with the occurrence and increasing mechanism of aerosol in marine boundary layer.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.17 no.4
• /
• pp.297-305
• /
• 2014

In this study, we installed the Automatic Identification System (AIS) receiver on the Ieodo Ocean Research Station (IORS) from November 21 to 30, 2013 in order to monitor marine traffic and fishery activity in the jurisdictional sea area. The collected AIS raw data consist of static data report (MMSI, IMO NO., Call Sign, Ship Name, etc.) and position information report (position, speed, course, etc.), and the developed program was applied to classify ships according to ship flag and type information. The nationalities are released from the first three-digit numbers (MID) of MMSI, but in general most of small ships do not send an exact ship flag through Class B type AIS, a simplified and low-power equipment. From AIS data with flag information, ships under the flag of China had the highest frequency and the second was Korean flag, while in ship type cargo and fishing vessels were dominant in sequence. As for the ships without flag information, we compared the tracks with others in order to estimate ship flags. It can be said that fleets of ships with Chinese frequently appear sail together for fisheries over the waters, because the unknown ships followed a similar moving pattern with Chinese fishing vessels.

• Journal of Navigation and Port Research
• /
• v.28 no.6
• /
• pp.557-564
• /
• 2004

The WAM wave model has been widely used for wave hindcasting in the ocean by many domestic and foreign researchers due to its relative simplicity and high accuracy. As this model was originally developed for the condition of deepwater and comparatively coarse grid size covering wide area, it might produce in a fault result caused by the improper distribution of directional spreading. We extensively investigated involved problems based on WAM Cycle 4 model and suggested the improved WAM model so that it is applicable to both shallow water sea and fine mesh wave simulation The modified W AM model is verified here by comparing the computed result with and the observed data at Ieodo Ocean Research Station for September of 2003.

• Journal of the Korean earth science society
• /
• v.41 no.5
• /
• pp.469-477
• /
• 2020

Salinity is not only an important variable that determines the density of the ocean but also one of the main parameters representing the global water cycle. Ocean salinity observations have been mainly conducted using ships, Argo floats, and buoys. Since the first satellite salinity was launched in 2009, it is also possible to observe sea surface salinity in the global ocean using satellite salinity data. However, the satellite salinity data contain various errors, it is necessary to validate its accuracy before applying it as research data. In this study, the salinity accuracy between the Soil Moisture Active Passive (SMAP) satellite salinity data and the in-situ salinity data provided by the Ieodo ocean research station was evaluated, and the error characteristics were analyzed from April 2015 to August 2020. As a result, a total of 314 match-up points were produced, and the root mean square error (RMSE) and mean bias of salinity were 1.79 and 0.91 psu, respectively. Overall, the satellite salinity was overestimated compare to the in-situ salinity. Satellite salinity is dependent on various marine environmental factors such as season, sea surface temperature (SST), and wind speed. In summer, the difference between the satellite salinity and the in-situ salinity was less than 0.18 psu. This means that the accuracy of satellite salinity increases at high SST rather than at low SST. This accuracy was affected by the sensitivity of the sensor. Likewise, the error was reduced at wind speeds greater than 5 m s^-1. This study suggests that satellite-derived salinity data should be used in coastal areas for limited use by checking if they are suitable for specific research purposes.

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

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.23 no.1
• /
• pp.1-19
• /
• 2018

In order to compare significant wave height (SWH) data from multi-satellites (GFO, Jason-1, Envisat, Jason-2, Cryosat-2, SARAL) and SWH measurements from Ieodo Ocean Research Station (IORS), we constructed a 12 year matchup database between satellite and IORS measurements from December 2004 to May 2016. The satellite SWH showed a root mean square error (RMSE) of about 0.34 m and a positive bias of 0.17 m with respect to the IORS wave height. The satellite data and IORS wave height data did not show any specific seasonal variations or interannual variability, which confirmed the consistency of satellite data. The effect of the wind field on the difference of the SWH data between satellite and IORS was investigated. As a result, a similar result was observed in which a positive biases of about 0.17 m occurred on all satellites. In order to understand the effects of topography and the influence of the construction structures of IORS on the SWH differences, we investigated the directional dependency of differences of wave height, however, no statistically significant characteristics of the differences were revealed. As a result of analyzing the characteristics of the error as a function of the distance between the satellite and the IORS, the biases are almost constant about 0.14 m regardless of the distance. By contrast, the amplitude of the SWH differences, the maximum value minus the minimum value at a given distance range, was found to increase linearly as the distance was increased. On the other hand, as a result of the accuracy evaluation of the satellite SWH from the Donghae marine meteorological buoy of Korea Meteorological Administration, the satellite SWH presented a relatively small RMSE of about 0.27 m and no specific characteristics of bias such as the validation results at IORS. In this paper, we propose a conversion formula to correct the significant wave data of IORS with the satellite SWH data. In addition, this study emphasizes that the reliability of data should be prioritized to be extensively utilized and presents specific methods and strategies in order to upgrade the IORS as an international world-wide marine observation site.

• Journal of the Korean earth science society
• /
• v.42 no.5
• /
• pp.524-535
• /
• 2021

Rapid climate change and oceanic warming have increased the variability of oceanic wave heights over the past several decades. In addition, the extreme wave heights, such as the upper 1% (or 5%) wave heights, have increased more than the heights of the normal waves. This is true for waves both in global oceans as well as in local seas. Satellite altimeters have consistently observed significant wave heights (SWHs) since 1991, and sufficient SWH data have been accumulated to investigate 100-year return period SWH values based on statistical approaches. Satellite altimeter data were used to estimate the extreme SWHs at the Ieodo Ocean Research Station (IORS) for the period from 2005 to 2016. Two representative extreme value analysis (EVA) methods, the Initial Distribution Method (IDM) and Peak over Threshold (PoT) analysis, were applied for SWH measurements from satellite altimeter data and compared with the in situ measurements observed at the IORS. The 100-year return period SWH values estimated by IDM and PoT analysis using IORS measurements were 8.17 and 14.11 m, respectively, and those using satellite altimeter data were 9.21 and 16.49 m, respectively. When compared with the maximum value, the IDM method tended to underestimate the extreme SWH. This result suggests that the extreme SWHs could be reasonably estimated by the PoT method better than by the IDM method. The superiority of the PoT method was supported by the results of the in situ measurements at the IORS, which is affected by typhoons with extreme SWH events. It was also confirmed that the stability of the extreme SWH estimated using the PoT method may decline with a decrease in the quantity of the altimeter data used. Furthermore, this study discusses potential limitations in estimating extreme SWHs using satellite altimeter data, and emphasizes the importance of SWH measurements from the IORS as reference data in the East China Sea to verify satellite altimeter data.

• Journal of Environmental Science International
• /
• v.18 no.7
• /
• pp.721-733
• /
• 2009

To examine the fluctuations of aerosol number concentration with different size in the boundary layer of marine area during summer season, aerosol particles were assayed in the Ieodo Ocean Research Station, which is located 419 km southwest of Marado, the southernmost island of Korea, from 24 June to 4 July, 2008. The Laser Particle Counter (LPC) was used to measure the size of aerosol particles and NCEP/NCAR reanalysis data and sounding data were used to analyze the synoptic condition. The distribution of aerosol number concentration had a large variation from bigger particles more than 3 ${\mu}m$ in diameter to smaller particles more than 1 ${\mu}m$ in diameter with wind direction during precipitation. The aerosol number concentration decreased with increasing temperature. An increase (decrease) of small size of aerosol (0.3${\sim}$0.5 ${\mu}m$ in diameter) number concentration was induced by convergence (divergence) of the wind fields. The aerosol number concentration of bigger size more than 3 ${\mu}m$ in diameter after precipitation was removed as much as 89${\sim}$94% compared with aerosol number concentration before precipitation. It is considered that the larger aerosol particles would be more efficient for scavenging at marine boundary layer. In addition, the aerosol number concentration with divergence and convergence could be related with the occurrence and mechanism of aerosol in marine boundary layer.