• Economic and Environmental Geology
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• v.44 no.3
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• pp.229-238
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• 2011

S-wave, which provides lithology and pore fluid information, plays a key role in estimating gas-hydrate saturation. In general, P- and S-wave velocities increase in the presence of gas-hydrate and the P-wave velocity decreases in the presence of free gas under the gas-hydrate layer. Whereas there are very small changes, even slightly increases, in the S-wave velocity in the free gas layer because S-wave is not affected by the pore fluid when propagating in the free gas layer. To verify those velocity properties of the BSR (bottom-simulating reflector) depth in the gas-hydrate prospect area in the Ulleung Basin, P- and S-wave velocity profiles were derived from multi-component ocean-bottom seismic data which were acquired by Korea Institute of Geoscience and Mineral Resources (KIGAM) in May 2009. OBS (ocean-bottom seismometer) hydrophone component data were modeled and inverted first through the traveltime inversion method to derive P-wave velocity and depth model of survey area. 2-D multichannel stacked data were incorporated as an initial model. Two horizontal geophone component data, then, were polarization filtered and rotated to make radial component section. Traveltimes of main S-wave events were picked and used for forward modeling incorporating Poisson's ratio. This modeling provides S-wave profiles and Poisson's ratio profiles at every OBS site. The results shows that P-wave velocities in most OBS sites decrease beneath the BSR, whereas S-wave velocities slightly increase. Consequently, Poisson's ratio decreased strongly beneath the BSR indicating the presence of a free gas layer under the BSR.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.1-14
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• 2008

We present a method for interpreting seismic records with arrivals and waveforms having characteristics which could be generated by extremely inhomogeneous velocity structures, such as non-typical oceanic crust, decollement at subduction zones, and seamounts in oceanic regions, by comparing them with synthetic waveforms. Recent extensive refraction and wide-angle reflection surveys in oceanic regions have provided us with a huge number of high-resolution and high-quality seismic records containing characteristic arrivals and waveforms, besides first arrivals and major reflected phases such as PmP. Some characteristic waveforms, with significant later reflected phases or anomalous amplitude decay with offset distance, are difficult to interpret using only a conventional interpretation method such as the traveltime tomographic inversion method. We find the best process for investigating such characteristic phases is to use an interactive interpretation method to compare observed data with synthetic waveforms, and calculate raypaths and traveltimes. This approach enables us to construct a reasonable structural model that includes all of the major characteristics of the observed waveforms. We present results here with some actual observed examples that might be of great help in the interpretation of such problematic phases. Our approach to the analysis of waveform characteristics is endorsed as an innovative method for constructing high-resolution and high-quality crustal structure models, not only in oceanic regions, but also in the continental regions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.1
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• pp.39-50
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• 2014

This paper reviews the results of recent observations in the Yeonsuri valley of Mt. Youngmun during springtime (March to May) in 2012. Automated weather stations were installed at twelve sites in the valley to measure temperature and 2, 3 dimensional wind. We examined temporal and spatial characteristics of temperatures and wind data. The Yeonsuri valley springtime average temperature lapse rate between the top and bottom of the entire period is $-0.44^{\circ}C/100$ m. It can be changed by the synoptic weather conditions, the lapse rates is greatest in order of clear days ($-0.48^{\circ}C/100$ m), rainy ($-0.41^{\circ}C/100$ m) and cloudy days ($-0.40^{\circ}C/100$ m). In the night, the temperature inversion layer (thermal belt) and the cold pool are formed within the valley. In addition, we measured temperature and wind distribution from the bottom to 3.5 m, the cold layers existed up to 1.5 m, which were affected by ground mixed layer. The results will provide useful guidance on agricultural practices as well as model simulations.