• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.153-153
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• 2022

Large-scale and accurate observations at fine spatial resolution through a means of remote sensing offer an effective tool for capturing rainfall variability over the traditional rain gauges and weather radars. Although satellite rainfall products (SRPs) derived using two major estimation approaches were evaluated worldwide, their practical applications suffered from limitations. In particular, the traditional top-down SRPs (e.g., IMERG), which are based on direct estimation of rain rate from microwave satellite observations, are mainly restricted with their coarse spatial resolution, while applications of the bottom-up approach, which allows backward estimation of rainfall from soil moisture signals, to novel high spatial resolution soil moisture satellite sensors over South Korea are not introduced. Thus, this study aims to evaluate the performances of a state-of-the-art bottom-up SRP (the self-calibrated SM2RAIN model) applied to the C-band SAR Sentinel-1, a statistically downscaled version of the conventional top-down IMERG SRP, and their integration for a targeted high spatial resolution of 0.01° (~ 1-km) over central South Korea, where the differences in climate zones (coastal region vs. mainland region) and vegetation covers (croplands vs. mixed forests) are highlighted. The results indicated that each single SRP can provide plus points in distinct climatic and vegetated conditions, while their drawbacks have existed. Superior performance was obtained by merging these individual SRPs, providing preliminary results on a complementary high spatial resolution SRP over central South Korea. This study results shed light on the further development of integration framework and a complementary high spatial resolution rainfall product from multi-satellite sensors as well as multi-observing systems (integrated gauge-radar-satellite) extending for entire South Korea, toward the demands for urban hydrology and microscale agriculture.

• Proceedings of the KSRS Conference
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• v.1
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• pp.43-46
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• 2006

The main tsunami wave triggered by the December 2004 Sumatra tsunami was detected in the ocean south of India by satellite altimeters on Jason, Topex/Poseidon and Envisat. All three altimeters also detected shorter-wavelength (10 to 100 km), slower-propagating surface waves, spreading from the site of the earthquake. The shorter waves give additional information about the tsunami event, and can be used to better define the generating region in this, and future tsunamis. The properties of the area of shorter tsunami-generated waves may also be important in designing a future satellite-based detection system.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.14-17
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• 2005

Global latent heat flux data sets are crucial for many studies such as those related to air-sea interaction and climate variation. Currently, various global latent heat flux data sets are constructed using satellite data. Japanese Ocean Flux data sets with Use of Remote sensing Observations (J-OFURO) includes one of the satellite-derived global latent heat flux data (Kubota et aI., 2000). In this study, we review future development of J-OFURO global latent heat flux data set. In particular, we investigate usage of multi-satellite data for estimating accurate global latent heat flux. Accurate estimation of surface wind speeds over the global ocean is one of key factors for the improved estimation of global latent heat flux. First, we demonstrate improvement of daily wind speed estimation using multi-satellites data from microwave radiometers and scatterometers such as DMSP/SSMI, ERS/AMI, QuikSCAT/SeaWinds, AqualAMSR-E, ADEOS2/AMSR etc. Next, we demonstrate improvement of global latent heat flux estimation using the wind speed data derived from multi-satellite data.

• Atmosphere
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• v.27 no.1
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• pp.93-104
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• 2017

The effect of Advanced Microwave Sounding Unit-A (AMSU-A) observations on the short-range forecast in East Asia (EA) was investigated for the Northern Hemispheric (NH) summer and winter months, using the Forecast Sensitivity to Observations (FSO) method. For both periods, the contribution of radiosonde (TEMP) to the EA forecast was largest, followed by AIRCRAFT, AMSU-A, Infrared Atmospheric Sounding Interferometer (IASI), and the atmospheric motion vector of Communication, Ocean and Meteorological Satellite (COMS) or Multi-functional Transport Satellite (MTSAT). The contribution of AMSU-A sensor was largely originated from the NOAA 19, NOAA 18, and MetOp-A (NOAA 19 and 18) satellites in the NH summer (winter). The contribution of AMSU-A sensor on the MetOp-A (NOAA 18 and 19) satellites was large at 00 and 12 UTC (06 and 18 UTC) analysis times, which was associated with the scanning track of four satellites. The MetOp-A provided the radiance data over the Korea Peninsula in the morning (08:00~11:30 LST), which was important to the morning forecast. In the NH summer, the channel 5 observations on MetOp-A, NOAA 18, 19 along the seaside (along the ridge of the subtropical high) increased (decreased) the forecast error slightly (largely). In the NH winter, the channel 8 observations on NOAA 18 (NOAA 15 and MetOp-A) over the Eastern China (Tibetan Plateau) decreased (increased) the forecast error. The FSO provides useful information on the effect of each AMSU-A sensor on the EA forecasts, which leads guidance to better use of AMSU-A observations for EA regional numerical weather prediction.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.2
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• pp.334-343
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• 2017

The optimum design of an SAR (Synthetic Aperture Radar) satellite constellation is developed herein using a genetic algorithm. The performance of Earth observations using a satellite constellation can be improved by minimizing the maximum revisit time. Classical orbit design using analytic methods has limitations when addressing orbit dynamics due to various disturbances. To overcome this issue, an optimization technique based on a genetic algorithm is used. STK (Systems Tool Kit) is utilized to propagate the satellite orbit when considering external disturbances, and the maximum revisit time on the earth observation area is calculated. By minimizing the performance index using a genetic algorithm, the optimum orbit of the satellite constellation is designed. Numerical results are provided to demonstrate the performance of the proposed method.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.786-789
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• 2003

The detection of sandstorms and industrial pollutants has been the emphasis of this study. Data obtained from meteorological satellites, NOAA and GMS, have been used for detailed analysis. MODIS and Landsat images are also used for the application of future KOMPSAT- 2. Verification of satellite observations has been made with air pollution data obtained by ground-level monitors. It was found that satellite measurements agree well with concentrations and variations of air pollutants measured on the ground, and that satellite technique is a very useful device for monitoring large-scale air pollution in East Asia. The quantitative analysis of satellite image data on air pollution is the goal in the future studies.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.493-507
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• 2018

Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.89-98
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• 2009

In this study, the YLPODS (Yonsei Laser-ranging Precision Orbit Determination System) is developed for POD using SLR (Satellite Laser Ranging) NP (Normal Point) observations. The performance of YLPODS is tested using SLR NP observations of TOPEX/POSEIDON and CHAMP satellite. JPL's POE (Precision Orbit Ephemeris) is assumed to be true orbit, the measurement residual RMS (Root Mean Square) and the orbit accuracy (radial, along-track, cross-track) are investigated. The validation of POD using GPS (Global Positioning System) raw data is achieved by YLPODS performance and highly accurate SLR NP observations. YGPODS (Yonsei GPS-based Precision Orbit Determination System) is used for generating GPS based precise orbits for TOPEX/POSEIDON. The initial orbit for YLPODS is derived from the YGPODS results. To validate the YGPODS results the range residual of the first adjustment of YLPODS is investigated. The YLPODS results using SLR NP observations of TOPEX/POSEIDON and CHAMP satellite show that the range residual is less than 10 cm and the orbit accuracy is about 1 m level. The validation results of the YGPODS orbits using SLR NP observations of the TOPEX/POSEIDON satellite show that the range residual is less than 10 cm. This result predicts that the accuracy of this GPS based orbits is about 1m level and it is compared with JPL's POE. Thus this result presents that the YLPODS can be used for POD validation using SLR NP observations such as STSAT-2 and KOMPSAT-5.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.422-425
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• 2007

Traditionally, surface energy fluxes are obtained by model simulations or empirical equations with auxiliary meteorological data. These methods may not effectively represent the surface heat fluxes in a regional scale due to scene variability. On the other hand, remote sensing has the advantage to acquire data of a large area in an instantaneous view. The remotely sensed data can be further used to retrieve surface radiation and heat fluxes over a large area. In this study, the airborne and satellite images in conjunction with meteorological data and ground observations were used to estimate the surface heat fluxes over Taiwan's Chaiyi Plain. The results indicate that surface heat fluxes can be properly determined from both airborne and satellite images. The correlation coefficient of surface heat fluxes with in situ corresponding observations is over 0.60. We also observe that the remotely sensed data can efficiently provide a long term monitoring of surface heat fluxes over Taiwan's Chaiyi Plain.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.72.3-73
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• 2017

The spatial distribution of sub-halos in a large host halo is usually described as isotropic in the ${\Lambda}CDM$ cosmology. Recent observations, however, show that satellite galaxies around massive galaxies are often located within a preferred plane. In order to understand the origin of such planar alignment, we investigate the spatial distribution of sub-halos around their hosts by using the hydrodynamic cosmological simulation, Illustris. In particular, we analyze the systems resembling the Milky Way (MW) and its satellites, i.e. consisting of MW-sized central galaxy and its at least 11 satellites. The result shows that ~10 % of MW-like systems have the anisotropic satellite galaxy distribution at z = 0. The satellites that are accreted more recently tend to form a flattened structure more frequently, indicating a link of satellite distribution to the surrounding environment. We discuss the physical origin of the anisotropic satellite distribution from the viewpoint of the ${\Lambda}CDM$ paradigm.