The re-analysis on the raw data processing of KBR and LRI on GRACE-FO

<div> The KBR (K-Band ranging instrument) and LRI (Laser Interferometer) are used to measure the distance variations between the twin spacecraft, which is one of the most important observations used for temporal gravity field recovery. The data pre-processing from raw or so-called Level-1A into the Level-1B format, which is suited for gravity field recovery, is a key step. Although Level-1B files are made publicly available by the GRACE-FO Science Data System (SDS), it has been shown that alternative Level-1B datasets may yield improved the results of gravity field[1]. Investigations of the pre-processing may allow us to improve the gravity recovery strategy and are essential to support developments of gravimetric satellite missions in China, such as TianQin-2 project. The pre-processing normally includes the time-tag synchronization, filtering and resampling, and other corrections, e.g. light-time correction for both instruments and antenna offset correction for KBR. We re-processed the Level-1A data of KBR and LRI to the Level1B using code developed at IGG/Wuhan. The results show good agreement in case of the RL04 KBR data, i.e. the differences between IGG-KBR1B and SDS-KBR1B are about three orders of magnitude lower than the instrument noise level for KBR. For the LRI, we found that phase jumps are not removed completely in the SDS-LRI1B products. As shown by Abich[2], these phase jumps in the LRI phase observations are mainly coincident with thruster activations. Our work will analyze the impacts of different processing methods of the raw data on post-fit residuals and the gravity field recovery based on IGG-KBR1B and IGG-LRI1B datasets. &#160; <div> [1] Wiese, D.: SDS Level-2/-3 JPL, GRACE/GRACE-FO Science Team Meeting 2020, online, 27 October&#8211;29 Oct 2020, GSTM2020-75, https://doi.org/10.5194/gstm2020-75, 2020. [2]&#160;&#160;&#160; Abich K, Abramovici A, Amparan B, et al. In-Orbit Performance of the GRACE Follow-on Laser Ranging Interferometer [J]. Phys Rev Lett, 2019, 123(3): 031101, https://doi.org/10.1103/PhysRevLett.123.031101. </div> </div>&#160;

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The Impact of Temporal Gravity Variations on GOCE Gravity Field Recovery

Observation of the Earth System from Space ◽

10.1007/3-540-29522-4_18 ◽

2006 ◽

pp. 255-269 ◽

Cited By ~ 3

Author(s):

Oleg Abrikosov ◽

Focke Jarecki ◽

Jürgen Müller ◽

Svetozar Petrovic ◽

Peter Schwintzer

Keyword(s):

Gravity Field ◽

Gravity Field Recovery ◽

Gravity Variations ◽

The Impact ◽

Temporal Gravity

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Gravity Recovery and Interior Laboratory Simulations of Static and Temporal Gravity Field

Journal of Spacecraft and Rockets ◽

10.2514/1.a32117 ◽

2012 ◽

Vol 49 (2) ◽

pp. 390-400 ◽

Cited By ~ 16

Author(s):

Ryan S. Park ◽

Sami W. Asmar ◽

Eugene G. Fahnestock ◽

Alex S. Konopliv ◽

Wenwen Lu ◽

...

Keyword(s):

Gravity Field ◽

Laboratory Simulations ◽

Gravity Recovery ◽

Temporal Gravity

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An alternative derivation of the GRACE Follow-On LRI1B product: current status

10.5194/gstm2020-27 ◽

2020 ◽

Author(s):

Laura Müller ◽

Vitali Müller ◽

Malte Misfeldt ◽

Henry Wegener ◽

Gerhard Heinzel

Keyword(s):

Attitude Control ◽

Albert Einstein ◽

Current Status ◽

Science Data ◽

Data Set ◽

Alternative Processing ◽

Gravity Field Recovery ◽

Processing Strategies ◽

Time Correction ◽

The Common

The new Laser Ranging Interferometer (LRI) on GRACE Follow-On is measuring, just like the microwave instrument (MWI), the distance variations between the two satellites, but with a significantly higher precision. The Albert Einstein Institute (AEI) in Hannover was involved in the development of the LRI and is currently concerned with instrument operation and data analysis. &#160;In order to verify and validate the correctness of the Science Data System (SDS) derived LRI1B data product, currently available as release 04, we started to implement an own processing chain to convert data from raw level0 or level 1A to level1B, where the latter is usually employed in gravity field recovery. Besides the validation, we are interested in testing alternative processing strategies, which could improve the data quality and that might get adopted by official processing centers at some point. We will provide an overview on our processing strategy, which includes five major steps 1) Deglitching of the piston phase in order to remove phase jumps that occur when the attitude control thrusters are activated. 2) Conversion of time-tags from LRI time to GPS time and forming the phase difference of master and transponder measurements. &#160;This removes the common 10 MHz ramp in the measurements. 3) Conversion of the phase to a physical length, the non-instantaneous biased range 4) Filtering and down-sampling of the data to the LRI1B rate of 0.5 Hz. &#160;5) Finally, the light time correction (LTC) is calculated and allows to transform the non-instantaneous biased range and its derivatives to the instantaneous or corrected biased range. We will highlight the main differences in our processing to the RL04 processing, as far as known to us. In the end, we compare the RL04 and our data set at the 1B level, which shows a slightly lower noise and uses less empirical parameters.

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Gravity Field Recovery Using High-Precision, High–Low Inter-Satellite Links

Remote Sensing ◽

10.3390/rs11050537 ◽

2019 ◽

Vol 11 (5) ◽

pp. 537 ◽

Cited By ~ 3

Author(s):

Markus Hauk ◽

Roland Pail

Keyword(s):

Gravity Field ◽

Radial Component ◽

Mass Variation ◽

The North ◽

Alternative Processing ◽

Gravity Field Recovery ◽

Satellite Links ◽

Error Behavior ◽

The Impact ◽

Temporal Gravity

Past temporal gravity field solutions from the Gravity Recovery and Climate Experiment (GRACE), as well as current solutions from GRACE Follow-On, suffer from temporal aliasing errors due to undersampling of the signal to be recovered (e.g., hydrology), which arise in terms of stripes caused by the north–south observation direction. In this paper, we investigate the potential of the proposed mass variation observing system by high–low inter-satellite links (MOBILE) mission. We quantify the impact of instrument errors of the main sensors (inter-satellite link and accelerometer) and high-frequency tidal and non-tidal gravity signals on achievable performance of the temporal gravity field retrieval. The multi-directional observation geometry of the MOBILE concept with a strong dominance of the radial component result in a close-to-isotropic error behavior, and the retrieved gravity field solutions show reduced temporal aliasing errors of at least 30% for non-tidal, as well as tidal, mass variation signals compared to a low–low satellite pair configuration. The quality of the MOBILE range observations enables the application of extended alternative processing methods leading to further reduction of temporal aliasing errors. The results demonstrate that such a mission can help to get an improved understanding of different components of the Earth system.

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Static and temporal gravity field recovery using grace potential difference observables

Advances in Geosciences ◽

10.5194/adgeo-1-19-2003 ◽

2003 ◽

Vol 1 ◽

pp. 19-26 ◽

Cited By ~ 14

Author(s):

S.-C. Han ◽

C. Jekeli ◽

C. K. Shum

Keyword(s):

Gravity Field ◽

Time Variable ◽

Potential Difference ◽

Gps Tracking ◽

Orbital Parameter ◽

Energy Relation ◽

Disturbing Potential ◽

Gravity Field Recovery ◽

Grace Mission ◽

Temporal Gravity

Abstract. The gravity field dedicated satellite missions like CHAMP, GRACE, and GOCE are supposed to map the Earth’s global gravity field with unprecedented accuracy and resolution. New models of Earth’s static and time-variable gravity field will be available every month as one of the science products from GRACE. Here we present an alternative method to estimate the gravity field efficiently using the in situ satellite-to-satellite observations at the altitude and show results on static as well as temporal gravity field recovery. Considering the energy relation between the kinetic energy of the satellite and the gravitational potential, the disturbing potential difference observations can be computed from the orbital parameter vectors in the inertial frame, using the high-low GPS-LEO GPS tracking data, the low-low satelliteto- satellite GRACE measurements, and data from 3-axis accelerometers (Jekeli, 1999). The disturbing potential observation also includes other potentials due to tides, atmosphere, other modeled signals (e.g. N-body) and the geophysical fluid signals (hydrological and oceanic mass variations), which should be recoverable from GRACE mission with a monthly resolution. The simulation results confirm that monthly geoid accuracy is expected to be a few cm with the 160 km resolution (up to degree and order 120) once other corrections are made accurately. The time-variable geoids (ocean and ground water mass) might be recovered with a noise-to-signal ratio of 0.1 with the resolution of 800 km every month assuming no temporal aliasing.Key words. GRACE mission, Energy integral, Geopotential, Satellite-to-satellite tracking, Temporal gravity field

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Gravity Field Recovery and Error Analysis for the MOCASS Mission Proposal Based on Cold Atom Interferometry

Pure and Applied Geophysics ◽

10.1007/s00024-021-02756-5 ◽

2021 ◽

Author(s):

Mirko Reguzzoni ◽

Federica Migliaccio ◽

Khulan Batsukh

Keyword(s):

Gravity Field ◽

Ocean Circulation ◽

Cold Atom ◽

Gravity Gradient ◽

Sea Level Changes ◽

Earth Gravity ◽

Gravity Field Recovery ◽

Gravity Measurements ◽

Gravity Recovery ◽

The Mathematical Model

AbstractSatellite missions providing data for a continuous monitoring of the Earth gravity field and its changes are fundamental to study climate changes, hydrology, sea level changes, and solid Earth phenomena. GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) mission was launched in 2018 and NGGM (Next Generation Gravity Mission) studies are ongoing for the long-term monitoring of the time-variable gravity field. In recent years, an innovative mission concept for gravity measurements has also emerged, exploiting a spaceborne gravity gradio-meter based on cold atom interferometers. In particular, a team of researchers from Italian universities and research institutions has proposed a mission concept called MOCASS (Mass Observation with Cold Atom Sensors in Space) and conducted the study to investigate the performance of a cold atom gradiometer on board a low Earth orbiter and its impact on the modeling of different geophysical phenomena. This paper presents the analysis of the gravity gradient data attainable by such a mission. Firstly, the mathematical model for the MOCASS data processing will be described. Then numerical simulations will be presented, considering different satellite orbital altitudes, pointing modes and instrument configurations (single-arm and double-arm); overall, data were simulated for twenty different observation scenarios. Finally, the simulation results will be illustrated, showing the applicability of the proposed concept and the improvement in modeling the static gravity field with respect to GOCE (Gravity Field and Steady-State Ocean Circulation Explorer).

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Revisiting the light time correction in gravimetric missions like GRACE and GRACE follow-on

Journal of Geodesy ◽

10.1007/s00190-021-01498-5 ◽

2021 ◽

Vol 95 (5) ◽

Author(s):

Yihao Yan ◽

Vitali Müller ◽

Gerhard Heinzel ◽

Min Zhong

Keyword(s):

Gravity Field ◽

Center Of Mass ◽

Precise Orbit Determination ◽

Relativistic Effects ◽

Gravity Field Recovery ◽

General Relativistic ◽

Time Correction ◽

The Difference ◽

Electro Magnetic ◽

Lower Noise

AbstractThe gravity field maps of the satellite gravimetry missions Gravity Recovery and Climate Experiment (GRACE ) and GRACE Follow-On are derived by means of precise orbit determination. The key observation is the biased inter-satellite range, which is measured primarily by a K-Band Ranging system (KBR) in GRACE and GRACE Follow-On. The GRACE Follow-On satellites are additionally equipped with a Laser Ranging Interferometer (LRI), which provides measurements with lower noise compared to the KBR. The biased range of KBR and LRI needs to be converted for gravity field recovery into an instantaneous range, i.e. the biased Euclidean distance between the satellites’ center-of-mass at the same time. One contributor to the difference between measured and instantaneous range arises due to the nonzero travel time of electro-magnetic waves between the spacecraft. We revisit the calculation of the light time correction (LTC) from first principles considering general relativistic effects and state-of-the-art models of Earth’s potential field. The novel analytical expressions for the LTC of KBR and LRI can circumvent numerical limitations of the classical approach. The dependency of the LTC on geopotential models and on the parameterization is studied, and afterwards the results are compared against the LTC provided in the official datasets of GRACE and GRACE Follow-On. It is shown that the new approach has a significantly lower noise, well below the instrument noise of current instruments, especially relevant for the LRI, and even if used with kinematic orbit products. This allows calculating the LTC accurate enough even for the next generation of gravimetric missions.

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Revisiting the Light Time Correction in Gravimetric Missions Like GRACE and GRACE Follow-On

10.5194/gstm2020-4 ◽

2020 ◽

Author(s):

Yihao Yan ◽

Vitali Müller ◽

Gerhard Heinzel ◽

Min Zhong

Keyword(s):

Gravity Field ◽

Electromagnetic Waves ◽

Classical Method ◽

Relativistic Effects ◽

Gravity Field Recovery ◽

Iterative Equations ◽

General Relativistic ◽

Time Correction ◽

The Difference ◽

Lower Noise

The satellite gravimetry missions GRACE (Gravity Recovery and Climate Experiment) and GRACE Follow-On provide the global and monthly gravity field for almost 17 years, which plays an irreplaceable role in understanding the mass transport of the Earth system. The key observation is the biased inter-satellite range, which is measured primarily by a K-Band Ranging system (KBR) in GRACE and GRACE Follow-On. The GRACE Follow-On satellites are additionally equipped with a Laser Ranging Interferometer (LRI), which provides measurements with lower noise compared to the KBR. However, the measured biased range which is directly measured by the inter-satellite ranging systems differs from the instantaneous biased range which is usually required for gravity field recovery. The difference is called the Light Time Correction (LTC) and arises from the non-zero travel time of electromagnetic waves between the spacecraft. We re-analyzed the LTC calculation from first principles considering general relativistic effects and state-of-the-art models of Earth&#8217;s potential field, and different types of orbital data. By analyzing the iterative equations in the LTC calculation of KBR and LRI, a novel analytical expression method is obtained to avoid the numerical limitation of the classical method. The dependency of the LTC on geopotential models and on the parameterization is further studied, and afterwards the results are compared against the LTC provided in the official datasets of GRACE and GRACE Follow-On. It is shown that the new approach has significantly lower noise, well below the instrument noise of current instruments, especially relevant for the LRI, and even if used with kinematic orbit products. This allows calculating the LTC accurate enough even for the next generation of gravimetric missions.

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Multiresolution wavelet analysis applied to GRACE range-rate residuals

Geoscientific Instrumentation Methods and Data Systems ◽

10.5194/gi-8-197-2019 ◽

2019 ◽

Vol 8 (2) ◽

pp. 197-207 ◽

Cited By ~ 1

Author(s):

Saniya Behzadpour ◽

Torsten Mayer-Gürr ◽

Jakob Flury ◽

Beate Klinger ◽

Sujata Goswami

Keyword(s):

Wavelet Analysis ◽

Gravity Field ◽

Recovery Process ◽

Ocean Tide ◽

Discrete Wavelet ◽

Error Sources ◽

Gravity Field Recovery ◽

Range Rate ◽

Process Observation ◽

Gravity Recovery

Abstract. For further improvements of gravity field models based on Gravity Recovery and Climate Experiment (GRACE) observations, it is necessary to identify the error sources within the recovery process. Observation residuals obtained during the gravity field recovery contain most of the measurement and modeling errors and thus can be considered a realization of actual errors. In this work, we investigate the ability of wavelets to help in identifying specific error sources in GRACE range-rate residuals. The multiresolution analysis (MRA) using discrete wavelet transform (DWT) is applied to decompose the residual signal into different scales with corresponding frequency bands. Temporal, spatial, and orbit-related features of each scale are then extracted for further investigations. The wavelet analysis has proven to be a practical tool to find the main error contributors. Besides the previously known sources such as K-band ranging (KBR) system noise and systematic attitude variations, this method clearly shows effects which the classic spectral analysis is hardly able or unable to represent. These effects include long-term signatures due to satellite eclipse crossings and dominant ocean tide errors.

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V04 Level-1 data processing status for GRACE and GRACE Follow-On

10.5194/egusphere-egu2020-10626 ◽

2020 ◽

Author(s):

Tamara Bandikova ◽

Hui Ying Wen ◽

Meegyeong Paik ◽

William Bertiger ◽

Mark Miller ◽

...

Keyword(s):

Data Processing ◽

Gravity Field ◽

Attitude Determination ◽

Precise Orbit Determination ◽

Sensor Data ◽

Satellite Mission ◽

Gravity Field Recovery ◽

Grace Data ◽

Level 1 ◽

Gravity Recovery

On May 22, 2020, the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), will celebrate two years of successful in-orbit operation. The primary goal of this satellite mission is to provide information about time variations of the Earth&#8217;s gravity field. This is possible due to precise orbit determination and inter-satellite ranging by determining the relative clock alignment of the USOs, precise attitude determination and accelerometry. High quality satellite observations are one of the fundamental requirements for successful gravity field recovery. NASA/Caltech Jet Propulsion Laboratory is the official Level-1 data processing and analysis center. The GRACE-FO Level-1 data are currently being processed with software version V04. This software will be used also for final reprocessing of the GRACE (2002-2017) Level-1 data. Here we present the analysis of two years of GRACE-FO sensor data as well as a preview of the reprocessed GRACE data, and discuss the measurement performance.

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