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

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.

[1]  Thomas Gruber,et al.  Propagation of atmospheric model errors to gravity potential harmonics—impact on GRACE de-aliasing , 2010 .

[2]  Jürgen Kusche,et al.  The updated ESA Earth System Model for future gravity mission simulation studies , 2015, Journal of Geodesy.

[3]  Pieter Visser,et al.  Estimating low resolution gravity fields at short time intervals to reduce temporal aliasing errors , 2011 .

[4]  Frank Flechtner,et al.  What Can be Expected from the GRACE-FO Laser Ranging Interferometer for Earth Science Applications? , 2016, Surveys in Geophysics.

[5]  J. Lemoine,et al.  The CHAMP-only earth gravity field model EIGEN-2 , 2003 .

[6]  S. Swenson,et al.  Post‐processing removal of correlated errors in GRACE data , 2006 .

[7]  Jürgen Kusche,et al.  Evaluation of GRACE filter tools from a hydrological perspective , 2009 .

[8]  M. Watkins,et al.  The gravity recovery and climate experiment: Mission overview and early results , 2004 .

[9]  Roland Pail,et al.  Treatment of ocean tide aliasing in the context of a next generation gravity field mission , 2014 .

[10]  V. M. Tiwari,et al.  Dwindling groundwater resources in northern India, from satellite gravity observations , 2009 .

[11]  Nico Sneeuw,et al.  Space-borne gravimetric satellite constellations and ocean tides: aliasing effects , 2010 .

[12]  Roland Pail,et al.  Treatment of temporal aliasing effects in the context of next generation satellite gravimetry missions , 2017 .

[13]  Duane E. Waliser,et al.  Gravity Recovery and Climate Experiment (GRACE) alias error from ocean tides , 2008 .

[14]  C. Shum,et al.  Time‐variable aliasing effects of ocean tides, atmosphere, and continental water mass on monthly mean GRACE gravity field , 2004 .

[15]  O. Andersen,et al.  Correcting GRACE gravity fields for ocean tide effects , 2002 .

[16]  P. Visser.  Designing Earth Gravity Field Missions for the Future: A Case Study , 2010 .

[17]  Pieter Visser,et al.  Champ precise orbit determination using GPS data , 2003 .

[18]  Shin-Chan Han,et al.  Expected improvements in determining continental hydrology, ice mass variations, ocean bottom pressure signals, and earthquakes using two pairs of dedicated satellites for temporal gravity recovery , 2011 .

[19]  A James.  Energetic Particles in the Earth's External Magnetic Field , 2013 .

[20]  Byron D. Tapley,et al.  Seasonal variations in low degree zonal harmonics of the Earth's gravity field from satellite laser ranging observations , 1999 .

[21]  O. Baur.  Greenland mass variation from time‐variable gravity in the absence of GRACE , 2013 .

[22]  Karsten Danzmann,et al.  Intersatellite laser ranging instrument for the GRACE follow-on mission , 2012, Journal of Geodesy.

[23]  Roland Pail,et al.  Gravity field recovery in the framework of a Geodesy and Time Reference in Space (GETRIS) , 2017 .

[24]  Robert L. Spencer.  Lageos*—A Geodynamics Tool in the Making , 1977 .

[25]  Isabella Velicogna,et al.  Regional acceleration in ice mass loss from Greenland and Antarctica using GRACE time‐variable gravity data , 2014 .

[26]  F. Sansò,et al.  First GOCE gravity field models derived by three different approaches , 2011 .

[27]  D. Kucharski,et al.  Optical response of nanosatellite BLITS measured by the Graz 2 kHz SLR system , 2011 .

[28]  Riko Oki,et al.  The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation , 2015 .

[29]  Srinivas Bettadpur,et al.  Impact of short period, non‐tidal, temporal mass variability on GRACE gravity estimates , 2004 .

[30]  A. Jäggi,et al.  Gravity field models derived from Swarm GPS data , 2016, Earth, Planets and Space.

[31]  Roland Pail,et al.  Gravity field processing with enhanced numerical precision for LL-SST missions , 2014, Journal of Geodesy.

[32]  M. Watkins,et al.  Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons , 2015 .

[33]  J. Kusche.  Approximate decorrelation and non-isotropic smoothing of time-variable GRACE-type gravity field models , 2007 .