Multi-approach gravity field models from Swarm GPS data

Abstract. Although the knowledge of the gravity of the Earth has improved considerably with CHAMP, GRACE and GOCE satellite missions, the geophysical community has identified the need for the continued monitoring of the time-variable component with the purpose of estimating the hydrological and glaciological yearly cycles and long-term trends. Currently, the GRACE-FO satellites are the sole dedicated provider of these data, while previously the GRACE mission fulfilled that role for 15 years. There is a data gap spanning from July 2017 to May 2018 between the end of the GRACE mission and start the of GRACE-FO, while the Swarm satellites have collected gravimetric data with their GPS receivers since December 2013. We present high-quality gravity field models from Swarm data that constitute an alternative and independent source of gravimetric data, which could help alleviate the consequences of the 10-month gap between GRACE and GRACE-FO, as well as the short gaps in the existing GRACE and GRACE-FO monthly time series. The geodetic community has realized that the combination of different gravity field solutions is superior to any individual model and set up a Combination Service of Time-variable Gravity Fields (COST-G) under the umbrella of the International Gravity Field Service (IGFS), part of the International Association of Geodesy (IAG). We exploit this fact and deliver to the highest quality monthly-independent gravity field models, resulting from the combination of four different gravity field estimation approaches. All solutions are unconstrained and estimated independently from month to month. We tested the added value of including Kinematic Baselines (KBs) in our estimation of Gravity Field Models (GFMs) and conclude that there is no significant improvement. The non-gravitational accelerations measured by the accelerometer on-board Swarm-C were also included in our processing to determine if this would improve the quality of the GFMs, but observed that is only the case when the amplitude of the non-gravitational accelerations is higher than during the current quiet period in solar activity. Using GRACE data for comparison, we demonstrate that the geophysical signal in the Swarm gravity field models is largely restricted to Spherical Harmonic degrees below 12. A 750 km smoothing radius is suitable to retrieve the temporal variations of Earth’s gravity field over land areas since mid-2015 with roughly 4 cm Equivalent Water Height (EWH) agreement with respect to a GRACE-derived parametric model. Over ocean areas, we illustrate that a more intense smoothing with 3000 km radius is necessary to resolve large scale gravity variations, which agree with the aforementioned parametric model under 2 cm EWH, while at these spatial scales the model represents variations with amplitudes between 2 and 3.5 cm EWH. The agreement with GRACE and GRACE-FO over nine selected large basins under analyses is 1.19 cm, 0.60 cm/year and 0.75 in terms of temporal mean, trend and correlation coefficient, respectively.

[1]  Torsten Mayer-Gürr,et al.  International Combination Service for Time-Variable Gravity Fields (COST-G) , 2020, International Association of Geodesy Symposia.

[2]  A. Jäggi,et al.  Combination of GRACE monthly gravity fields on the normal equation level , 2019, Journal of Geodesy.

[3]  Qile Zhao,et al.  A New Approach to Earth's Gravity Field Modeling Using GPS-Derived Kinematic Orbits and Baselines , 2019, Remote. Sens..

[4]  S. Luthcke,et al.  Improved Earth Oblateness Rate Reveals Increased Ice Sheet Losses and Mass‐Driven Sea Level Rise , 2019, Geophysical Research Letters.

[5]  Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space , 2019 .

[6]  Torsten Mayer-Gürr,et al.  European Gravity Service for Improved Emergency Management (EGSIEM)—from concept to implementation , 2019, Geophysical Journal International.

[7]  Ulrich Meyer,et al.  SLR, GRACE and Swarm Gravity Field Determination and Combination , 2019, Remote. Sens..

[8]  A. Jäggi,et al.  Mitigation of ionospheric signatures in Swarm GPS gravity field estimation using weighting strategies , 2018, Annales Geophysicae.

[9]  A. Bezděk,et al.  Calibration of Swarm accelerometer data by GPS positioning and linear temperature correction , 2018, Advances in Space Research.

[10]  Pieter Visser,et al.  The impact of GPS receiver modifications and ionospheric activity on Swarm baseline determination , 2018 .

[11]  S. Schön,et al.  On filtering ionospheric effects in GPS observations using the Matérn covariance family and its impact on orbit determination of Swarm satellites , 2018, GPS Solutions.

[12]  A. Jäggi,et al.  Combination of GRACE monthly gravity field solutions from different processing strategies , 2018, Journal of Geodesy.

[13]  J. Kusche,et al.  Time-variable gravity fields and ocean mass change from 37 months of kinematic Swarm orbits , 2017 .

[14]  R. König,et al.  A new high-resolution model of non-tidal atmosphere and ocean mass variability for de-aliasing of satellite gravity observations: AOD1B RL06 , 2017 .

[15]  P. Visser,et al.  Impact of GPS antenna phase center and code residual variation maps on orbit and baseline determination of GRACE , 2017 .

[16]  Adrian Jäggi,et al.  Impact of tracking loop settings of the Swarm GPS receiver on gravity field recovery , 2017 .

[17]  Validation of Swarm accelerometer data by modelled nongravitational forces , 2017 .

[18]  Oliver Montenbruck,et al.  Reduced-dynamic and kinematic baseline determination for the Swarm mission , 2017, GPS Solutions.

[19]  John C. Ries,et al.  The unexpected signal in GRACE estimates of $$C_{20}$$C20 , 2017 .

[20]  Norbert Zehentner,et al.  Kinematic orbit positioning applying the raw observation approach to observe time variable gravity , 2017 .

[21]  Beate Klinger,et al.  The role of accelerometer data calibration within GRACE gravity field recovery: Results from ITSG-Grace2016 , 2016 .

[22]  A. Bezděk,et al.  Time-variable gravity fields derived from GPS tracking of Swarm , 2016 .

[23]  Eelco Doornbos,et al.  Swarm accelerometer data processing from raw accelerations to thermospheric neutral densities , 2016, Earth, Planets and Space.

[24]  O. Montenbruck,et al.  Impact of Swarm GPS receiver updates on POD performance , 2016, Earth, Planets and Space.

[25]  Beate Klinger,et al.  The new ITSG-Grace2016 release , 2016 .

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

[27]  R. Dach,et al.  CODE final product series for the IGS , 2016 .

[28]  Beate Klinger,et al.  ITSG-Grace2016 - Monthly and Daily Gravity Field Solutions from GRACE , 2016 .

[29]  H. Bock,et al.  Swarm kinematic orbits and gravity fields from 18 months of GPS data , 2016 .

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

[31]  Torsten Mayer-Gürr,et al.  Precise orbit determination based on raw GPS measurements , 2016, Journal of Geodesy.

[32]  J. Ijssel,et al.  Processing of Swarm Accelerometer Data into Thermospheric Neutral Densities , 2015 .

[33]  C. Shum,et al.  GRACE time-variable gravity field recovery using an improved energy balance approach , 2015 .

[34]  R. Dach,et al.  Bernese GNSS Software Version 5.2 , 2015 .

[35]  Pieter Visser,et al.  Precise science orbits for the Swarm satellite constellation , 2015 .

[36]  C. Shum,et al.  On the formulation of gravitational potential difference between the GRACE satellites based on energy integral in Earth fixed frame , 2015 .

[37]  Srinivas Bettadpur,et al.  The pole tide and its effect on GRACE time‐variable gravity measurements: Implications for estimates of surface mass variations , 2015 .

[38]  F. Lyard,et al.  FES 2014, a new tidal model on the global ocean with enhanced accuracy in shallow seas and in the Arctic region , 2015 .

[39]  Torsten Mayer-Gürr,et al.  The combined satellite gravity field model GOCO05s , 2015 .

[40]  Christopher Jekeli,et al.  On the energy integral formulation of gravitational potential differences from satellite-to-satellite tracking , 2015 .

[41]  Nils Olsen SCARF - The Swarm Satellite Constellation Application and Research Facility , 2014 .

[42]  P. Kuchynka,et al.  The Planetary and Lunar Ephemerides DE430 and DE431 , 2014 .

[43]  A. Bezděk,et al.  Gravity field models from kinematic orbits of CHAMP, GRACE and GOCE satellites , 2014 .

[44]  Gernot Plank,et al.  The Swarm Satellite Constellation Application and Research Facility (SCARF) and Swarm data products , 2013, Earth, Planets and Space.

[45]  S. Bruinsma "GOCE+ Theme 3: Air density and wind retrieval using GOCE data" , 2013 .

[46]  P. Barneveld Orbit determination of satellite formations , 2012 .

[47]  Torsten Mayer-Gürr,et al.  New approach to estimate time variable gravity fields from high-low satellite tracking data , 2012 .

[48]  Oliver Montenbruck,et al.  Inter-agency comparison of TanDEM-X baseline solutions , 2012 .

[49]  E. Doornbos Thermospheric Density and Wind Determination from Satellite Dynamics , 2012 .

[50]  U. Hugentobler,et al.  Impact of Earth radiation pressure on GPS position estimates , 2012, Journal of Geodesy.

[51]  Minkang Cheng,et al.  Variations of the Earth's figure axis from satellite laser ranging and GRACE , 2011 .

[52]  A. Bezděk Calibration of accelerometers aboard GRACE satellites by comparison with POD-based nongravitational accelerations , 2010 .

[53]  L. Mervart,et al.  The celestial mechanics approach: theoretical foundations , 2010 .

[54]  A. Eicker,et al.  ITG-Grace2010: the new GRACE gravity field release computed in Bonn , 2010 .

[55]  O. Montenbruck,et al.  GPS High Precision Orbit Determination Software Tools (GHOST) , 2010 .

[56]  R. Floberghagen,et al.  Simulation of free fall and resonances in the GOCE mission , 2009 .

[57]  L. Mervart,et al.  Assessment of GPS-only Observables for Gravity Field Recovery from GRACE , 2009 .

[58]  P. Ditmar,et al.  On a Feasibility of Modeling Temporal Gravity Field Variations from Orbits of Non-dedicated Satellites , 2009 .

[59]  Michael G. Sideris International Association of Geodesy Symposia , 2009 .

[60]  Paul B. Hays,et al.  An empirical model of the Earth's horizontal wind fields: HWM07 , 2008 .

[61]  Gordon G. Shepherd,et al.  DWM07 global empirical model of upper thermospheric storm-induced disturbance winds , 2008 .

[62]  William J. Burke,et al.  A New Empirical Thermospheric Density Model JB2008 Using New Solar and Geomagnetic Indices , 2008 .

[63]  Torsten Mayer-Gürr,et al.  Gravitationsfeldbestimmung aus der Analyse kurzer Bahnbögen am Beispiel der Satellitenmissionen CHAMP und GRACE , 2008 .

[64]  Roseanne,et al.  A New High , 2008 .

[65]  H. Lühr,et al.  Swarm An Earth Observation Mission investigating Geospace , 2008 .

[66]  W. Bosch,et al.  EOT11A - Empirical Ocean Tide Model from Multi-Mission Satellite Altimetry , 2008 .

[67]  Scott B. Luthcke,et al.  FAST TRACK PAPER: Tide model errors and GRACE gravimetry: towards a more realistic assessment , 2006 .

[68]  O. Francis,et al.  Modelling the global ocean tides: modern insights from FES2004 , 2006 .

[69]  Roland Klees,et al.  Frequency-dependent data weighting in global gravity field modeling from satellite data contaminated by non-stationary noise , 2006 .

[70]  R. Kroes,et al.  Precise relative positioning offormation flying Spacecraft using GPS , 2006 .

[71]  U. Hugentobler,et al.  Pseudo-Stochastic Orbit Modeling Techniques for Low-Earth Orbiters , 2006 .

[72]  Gerhard Beutler,et al.  Precise orbit determination for GRACE using undifferenced or doubly differenced GPS data , 2006 .

[73]  R. Biancale,et al.  Mean annual and seasonal atmospheric tide models based on 3-hourly and 6-hourly ECMWF surface pressure data , 2006 .

[74]  G. Hulot,et al.  Swarm- The Earth's Magnetic Field and Environment Explorers , 2004 .

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

[76]  Nico Sneeuw,et al.  Energy integral method for gravity field determination from satellite orbit coordinates , 2003 .

[77]  D. Drob,et al.  Nrlmsise-00 Empirical Model of the Atmosphere: Statistical Comparisons and Scientific Issues , 2002 .

[78]  C. Jekeli The determination of gravitational potential differences from satellite-to-satellite tracking , 1999 .

[79]  P. Teunissen The least-squares ambiguity decorrelation adjustment: a method for fast GPS integer ambiguity estimation , 1995 .

[80]  Robert Benjamin Lee,et al.  Earth Radiation Budget Experiment , 1990 .

[81]  C. Reigber,et al.  Gravity field recovery from satellite tracking data , 1989 .

[82]  B. Tapley,et al.  Earth radiation pressure effects on satellites , 1988 .

[83]  G. Louis Smith,et al.  The Earth Radiation Budget Experiment: Science and implementation , 1986 .

[84]  P. K. Seidelmann,et al.  1980 IAU Theory of Nutation: The final report of the IAU Working Group on Nutation , 1982 .

[85]  T. Lederle,et al.  Expressions for the precession quantities based upon the IAU /1976/ system of astronomical constants , 1977 .

[86]  C. Wunsch,et al.  The Pole Tide , 1973 .

[87]  Lee H. Sentman,et al.  FREE MOLECULE FLOW THEORY AND ITS APPLICATION TO THE DETERMINATION OF AERODYNAMIC FORCES , 1961 .

[88]  R Jastrow,et al.  Satellite Orbits. , 1961, Science.