• Journal of the Korean earth science society
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• v.32 no.6
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• pp.586-594
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• 2011

Gravity Recovery and Climate Experiment (GRACE), launched in April, 2002, makes it possible to monitor Earth's mass redistribution with its time-varying gravity observation. GRACE provides monthly gravity solutions as coefficients of spherical harmonics, and thus ones need to convert the gravity spectrum to gravity grids (or mass grids) via the spherical harmonics. GRACE gravity solutions, however, include spatial alias error as well as noise, which requires to suppress in order to enhance signal to noise ratio. In this study, we present the GRACE data processing procedures and introduce some applications of time-varying gravity, which are studies of terrestrial water storage changes, Antarctic and Greenland ice melting, and sea level rise. Satellite missions such as GRACE will continue up to early 2020, and they are expected to be an essential resource to understand the global climate changes.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.2
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• pp.75-83
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• 2005

NASA/DLR Gravity Recovery and Climate Experiment (GRACE) mission, which consists of two co-orbiting low altitude satellites, is to measure the Earth gravity field with unprecedented accuracy. Its key instruments include inter-satellite ranging systems and three-axis accelerometers. For the preliminary design and requirements analysis, extensive instrument simulation models are developed. These modeling techniques and orbit-gravity field estimation techniques are described.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.8
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• pp.58-68
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• 2003

Accurate estimation of the Earth gravity field plays an important role in understanding the Earth geodynamic activities. After brief discussion on the objective of the gravity estimation, dedicated satellite missions for this purpose are described. Recently launched NASA/DLR Gravity Recovery and Climate Experiment (GRACE) mission, which consists of two co-orbiting low altitude satellites, is described. For the performance analysis, full numerical simulation was performed. The simulation procedure and its key instrument modelings are described. From the simulation results, a significant improvement on the Earth gravity field accuracy is expected.

• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.255-264
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• 2006

GRACE (Gravity Recovery and Climate Experiment) is the first dedicated gravity mapping mission. Its primary measurements are the distance changes between two co-orbiting low earth satellites. GRACE is a joint development by NASA and German DLR and was launched in March 2002. GRACE improves the Earth gravity model accuracy by nearly two factor of magnitude over pre-launch models. After brief description of the GRACE primary instrument, inter-satellite ranging system, its flight status and preliminary performance evaluation is presented. Ranging system error models, which were not included in the pre-launch performance model and design specifications, are identified through analyzing the flight data. Base on this analysis, future research topics on the GRACE instrument performance analysis are discussed.

• Korean Journal of Remote Sensing
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• v.21 no.1
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• pp.51-57
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• 2005

The currently operating NASA/GFZ Gravity Recovery and Climate Experiment (GRACE) mission is designed to measure small mass changes over a large spatial scale, including the mapping of continental water storage changes and other geophysical signals in the form of monthly temporal gravity field. The European Space Agency's Gravity field and steady state Ocean Circulation Explorer (GOCE) space gravity gradiometer (SGG) mission is anticipated to determine the mean Earth gravity field with an unprecedented geoid accuracy of several cm (rms) with wavelength of 130km or longer. In this paper, we present a summary of present GRACE studies for the recovery of hydrological signals in the Amazon basin using alternative processing and filtering techniques, and local inversion to enhance the temporal and spatial resolutions by two-folds or better. Simulation studies for the potential GRACE detection of slow deformations due to Nazca-South America plate convergence and glacial isostatic adjustment (GIA) signals show that these signals are at present difficult to detect without long-term data averaging and further improvement of GRACE measurement accuracy.

• Journal of Astronomy and Space Sciences
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• v.28 no.1
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• pp.63-70
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• 2011

The needs for satellite formation flying are gradually increasing to perform the advanced space missions in remote sensing and observation of the space or Earth. Formation flying in low Earth orbit can perform the scientific missions that cannot be realized with a single spacecraft. One of the various techniques of satellite formation flying is the determination of the precise baselines between the satellites within the formation, which has to be in company with the precision validation. In this paper, the baseline of Gravity Recovery and Climate Experiment (GRACE) A and B was determined with the real global positioning system (GPS) measurements of GRACE satellites. And baseline precision was validated with the batch and sequential processing methods using K/Ka-band ranging system (KBR) biased range measurements. Because the proposed sequential method validate the baseline precision, removing the KBR bias with the epoch difference instead of its estimation, the validating data (KBR biased range) are independent of the data validated (GPS-baseline) and this method can be applied to the real-time precision validation. The result of sequential precision validation was 1.5~3.0 mm which is similar to the batch precision validation.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.46-46
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• 2023

돌발가뭄 (Flash drought)은 일반적인 가뭄과 달리 기후변화에 따른 기상 이상으로 인해 단기간 급속하게 발생하는 가뭄이다. 짧은 기간에 식생 스트레스가 증가하며, 작물생산량의 감소로 인해 농업 생태계에 피해를 야기하며, 과도한 증발 수요 및 급격한 토양수분의 감소는 수문학적 영향을 미치게 된다. 본 연구에서는 최근 개발된 Flash Drought Intenisty Index (FDII, 2021)를 활용하여 2014년부터 2018년까지 5년간 발생한 돌발가뭄에 분석하였다. FDII는 가뭄 심화속도, 평균 심각도의 두 가지 요소를 곱하여 나타내며, 일반적으로 가뭄 및 비가뭄에 대한 정도를 나타내는 아노말리 (Anomaly) 대신 백분위수 (Percentile)를 활용한다. 국내 돌발가뭄 분석을 위하여 Gravity Recovery and Climate Experiment (GRACE) 위성영상 기반 근역층 토양수분 자료를 활용하였다. 2014년부터 2018년까지 전국 8도 (경기, 강원, 충남, 충북, 전남, 전북, 경남, 경북)를 대상으로 돌발가뭄 사상에 대하여 토양수분 백분위수의 월별 공간분포 및 FDII를 산정하여 국내 돌발가뭄의 강도를 정량화하였다. 지역 및 시기별로 다르게 발생하는 돌발가뭄을 대상으로 FDII를 활용하여 돌발가뭄의 초기 발생, 가뭄 전이 현상 등 시공간적 특성을 분석하고자 한다. 향후 대상 지역의 세분화 및 장기적인 관점에서의 FDII 적용으로 신뢰성 높은 국내 돌발가뭄 모니터링 및 분석 기술로 활용할 수 있을 것으로 기대된다.

• 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.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.285-291
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• 2020

The Noah 3.3 Land Surface Model (LSM) was used to estimate the global soil moisture in this study and these soil moisture datasets were assessed against satellite-based and reanalysis soil moisture products. The Noah 3.3 LSM simulated soil moistures in four soil layers and root-zone soil moistures defined as a depth-weighted average in the first three soil layers (i.e., up to 1.0 m deep). The Noah LSM soil moisture products were then compared with a satellite-based soil moisture dataset (European Space Agency Climate Change Initiatives (ESA CCI) SM v04.4) and reanalysis soil moisture datasets (ERA-interim). In addition, the five major basins (Yangtze, Mekong, Mississippi, Murray-Darling, Amazon) were selected for the assesment with the Gravity Recovery and Climate Experiment (GRACE)-based Total Water Storage Anomaly (TWSA) and TWS Change (TWSC). The results revealed that high anomaly correlations were found in most of the Asia-Pacific regions including East Asia, South Asia, Australia, and Noth and South America. While the anomaly correlations in the Murray-Darling basin were somewhat low, relatively higher anomaly correlations in the other basins were found. It is concluded that this study can be useful for the development of soil moisture based drought indices and subsequently can be helpful to reduce damages from drought by timely providing an efficacious strategy.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.17 no.1
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• pp.52-57
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• 2009

One of the error sources for microwave ranging is the instability of the oscillator that drives the microwave signals. Dual one-way ranging (DOWR) minimizes the oscillator effect by combining two one-way carrier phase signals from two transmitter/receiver instrument. The DOWR is first implemented in the GRACE (Gravity Recovery and Climate Experiment) satellites. Direct evaluation of the DOWR is not possible due to its extremely high accuracy. The flight performance of the GRACE DOWR is analyzed by applying several indirect methods. Comparison with the design noise level is discussed.