• Korean Journal of Remote Sensing
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• v.18 no.5
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• pp.243-253
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• 2002

Time-mean and absolute geostrophic velocities of the Kuroshio current south of Japan are derived from TOPEX/Poseidon altimeter data using a Gaussian jet model. When compared with simultaneous measurements from a shipboard acoustic Doppler current profiler (ADCP) at two intersection points, the altimetric and ADCP absolute velocities correlate well with the correlation coefficient of 0.55 to 0.74. The accuracy of time-mean velocity ranges from 1 cm s$^{-1}$ to 5 cm s$^{-1}$. The errors in the absolute and the mean velocities are similar to those reported previously for other currents. The comparable performance suggests the Gaussian jet model is a promising methodology for determining absolute geostrophic velocities, noting that in this region the Kuroshio does not meander sufficiently and thus provides unfavorable environment for the performance of the Gaussian jet model.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.610-614
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• 2002

Time-mean and absolute geostrophic velocities of the Kuroshio current south of Japan are derived from TOPEX/Poseidon altimeter data using a Gaussian jet model. When compared with simultaneous measurements from a shipboard acoustic Doppler current profiler (ADCP) at two intersection points, the altimetric and ADCP absolute velocities correlate well with the correlation of 0.55 to 0.74. The time-mean velocity is accurate to 1 cm s$^{-1}$ to 5 cm s$^{-1}$. The errors in the absolute and the mean velocities are similar to those reported previously far other currents. The comparable performance suggests the Gaussian jet model is a promising methodology for determining absolute geostrophic velocities, noting that in this region the Kuroshio does not meander sufficiently, which provides unfavorable environment for the performance of the Gaussian jet model.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.3
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• pp.325-330
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• 2016

Sea level is upward trend since the end of 19th century, it is accelerating after 20th century. Because sea level height has regional differences, we concerned sea level change in Korean Peninsula. We used Topex/Poseidon, Jason-1 and Jason-2 satellite altimetry data which has $1/4^{\circ}$ resolution. From 1993 to 2013, for 21 years, monthly mean sea level anomaly was negative between January and April, positive between March and October. Bohai Bay in China, affected the continental climate, showed big sea level changes. Mean sea level data showed remarkably affecting the continental climate in Bohai Bay in China, the Kuroshio Current and eddy affects the sea level change.

• Proceedings of the KSRS Conference
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• v.2
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• pp.672-675
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• 2006

The geostrophic current component is estimated from the sea surface velocity observed by the long-range High-Frequency Ocean Radar (HF radar) system in the upstream of the Kuroshio, by comparing with geostrophic velocity determined from along-track T/P and Jason-1 altimetry data. However, the sea surface velocity of the HF radar (HF velocity) contains not only the geostrophic current but also the ageostrophic current such as tidal current and wind-driven Ekman current. Tidal current component is first extracted by the harmonic analysis of the time series of the HF velocity. Then, the Ekman current is further estimated from daily wind data of IFREMER by applying the least-square method to the residual difference between the HF velocity and the altimetry geostrophic velocity. As a result, the Ekman current in the HF velocity is estimated as 1.32 % of the wind speed and as rotated 45$^{\circ}$ clockwise to the wind direction. These parameters are found almost common in the Kuroshio area and in the Open Ocean. After these corrections, the geostrophic velocity component in the HF velocity agrees well with the altimetry geostrophic velocity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.181-192
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• 2015

Bathymetry change due to the 2011 Tohoku (M9.0) earthquake was investigated through satellite altimetry-derived free-air gravity anomalies (SAFAGA) and shipborne measurements. The earthquake occurred at the plate boundaries near the northeastern coast of Japan, where the oceanic plate subducts beneath the continental plate along deep-sea trench. Data analyzed in this study include SAFAGA from Scripps Institution of Oceanography (SIO), shipborne bathymetry (SB) from the U.S. National Geophysical Data Center (NGDC) and the Japan Agency for Marine-Earth-Science And Technology (JAMSTEC). To estimate the bathymetry change, a reference bathymetry before the earthquake was predicted by gravity-geologic method (GGM) and Smith & Sandwell’s (SAS) method. In comparison with the bathymetry models before the earthquake, GGM bathymetry model generated by a tuning density contrast of 17.04 g/cm³ by downward continuation method was selected because it shows better bathymetry in the short wavelength below about 6 km. From the results, remarkable bathymetry change of about ±50 m was found on the west side of the Japan Trench caused by the earthquake.

• Economic and Environmental Geology
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• v.40 no.6
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• pp.751-759
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• 2007

To better understand the subsurface geological structure of the Kunsan Basin in the Yellow Sea, the mean depths of the density discontinuous layers (DDLs) of the Kunsan Basin were calculated by power spectrum analysis using satellite altimetry gravity data. The calculated mean depths of DDLs were -1.1km, -3.4km, -9.1km and -31.0km. The mean depth of -1.1km DDL was interpreted as regional unconformity shown in about 1 second in two way travel time (TWTT) in the seismic reflection profiles, and the mean depth of -3.4km DDL was also interpreted as top of the acoustic basement in the seismic reflection profiles. Comparing with well data, seismic reflection profiles and regional geology in the study area, the mean depth of -9.1km DDL was interpreted as top of the igneous origin basement. This means that the acoustic basement of the study area is composed mainly of sediments which are disregarded in previous study. The mean depth of -31.0km DDL was interpreted as the Moho discontinuity because this mean depth is similar to one of the normal continental crust thickness. The detection of top of the igneous origin basement suggests that oil gas potential analysis in Kunsan Basin needs to be extended to the deeper part of sediments (acoustic basement).

• Proceedings of the KSRS Conference
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• v.1
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• pp.39-42
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• 2006

The paper reports on the first experimental evidence for space-observed manifestation of the open ocean tsunami in the microwave radar backscatter (in C- and Ku-bands). Significant variations of the radar cross section synchronous with the sea level anomaly were found in the geophysical data record of the altimetry satellite Jason-1 for the track which crossed the head wave of the catastrophic tsunami of 26 December 2004. The simultaneous analysis of the available complementary data provided by the satellite three-channel radiometer enabled us to exclude meteorological factors as possible causes of the observed signal modulation. A possible physical mechanism of modulation of short wind waves due to transformation of the thin boundary layer in the air by a tsunami wave is discussed. The results open new possibilities of monitoring tsunamis from space..

• Korean Journal of Remote Sensing
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• v.21 no.1
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• pp.73-81
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• 2005

We construct improved geocentric digital elevation model (DEM), estimate tidal dynamics and ice stream velocity over Sulzberger Ice Shelf, West Antarctica employing differential interferograms from 12 ERS tandem mission Synthetic Aperture Radar (SAR) images acquired in austral fall of 1996. Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry profiles acquired in the same season as the SAR scenes in 2004 are used as ground control points (GCPs) for Interferometric SAR (InSAR) DEM generation. 20 additional ICESat profiles acquired in 2003-2004 are then used to assess the accuracy of the DEM. The vertical accuracy of the OEM is estimated by comparing elevations with laser altimetry data from ICESat. The mean height difference between all ICESat data and DEM is -0.57m with a standard deviation of 5.88m. We demonstrate that ICESat elevations can be successfully used as GCPs to improve the accuracy of an InSAR derived DEM. In addition, the magnitude and the direction of tidal changes estimated from interferogram are compared with those predicted tidal differences from four ocean tide models. Tidal deformation measured in InSAR is -16.7cm and it agrees well within 3cm with predicted ones from tide models. Lastly, ice surface velocity is estimated by combining speckle matching technique and InSAR line-of-sight measurement. This study shows that the maximum speed and mean speed are 509 m/yr and 131 m/yr, respectively. Our results can be useful for the mass balance study in this area and sea level change.

• Proceedings of the KSEEG Conference
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• 2000.04b
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• pp.140-142
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• 2000

• Journal of the Korean earth science society
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• v.42 no.4
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• pp.445-458
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• 2021

Gravity Recovery and Climate Experiment (GRACE) gravimeter satellites observed the Earth gravity field with unprecedented accuracy since 2002. After the termination of GRACE mission, GRACE Follow-on (GFO) satellites successively observe global gravity field, but there is missing period between GRACE and GFO about one year. Many previous studies estimated terrestrial water storage (TWS) changes using hydrological models, vertical displacements from global navigation satellite system observations, altimetry, and satellite laser ranging for a continuity of GRACE and GFO data. Recently, in order to predict TWS changes, various machine learning methods are developed such as artificial neural network and multi-linear regression. Previous studies used hydrological and climate data simultaneously as input data of the learning process. Further, they excluded linear trends in input data and GRACE/GFO data because the trend components obtained from GRACE/GFO data were assumed to be the same for other periods. However, hydrological models include high uncertainties, and observational period of GRACE/GFO is not long enough to estimate reliable TWS trends. In this study, we used convolutional neural networks (CNN) method incorporating only climate data set (temperature, evaporation, and precipitation) to predict TWS variations in the missing period of GRACE/GFO. We also make CNN model learn the linear trend of GRACE/GFO data. In most river basins considered in this study, our CNN model successfully predicts seasonal and long-term variations of TWS change.