EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Geocenter Motion from a Combination of GRACE Mascon and SLR Data

Claudio Abbondanza, Toshio M Chin, Richard S Gross, Michael B Heflin, Jay W Parker, Benedikt S Soja, David N Wiese, and Xiaoping Wu
Claudio Abbondanza et al.
  • Jet Propulsion Laboratory, California Institute of Technology, Pasadena (CA), United States of America (

GRACE and GRACE Follow-On (FO) Level 2 data provide quasi-monthly, band-limited estimates of Stokes (geopotential, spherical harmonic) coefficients mostly reflecting surface mass variability due to non-tidal atmosphere, ocean, and continental hydrology.    
Although space gravimetry does not directly provide CM-related degree-1 Stokes coefficients, GRACE data have been successfully used over the years to complement time series of station positions from global space-geodetic (SG) network when inverting for Center-of-Mass to Center-of-Network (CM-CN) displacements (Wu et al, 2006).

Surficial mass variability observed through GRACE/GRACE-FO can be conveniently converted into load-induced (ENU) deformations at SG observing sites by adopting a spectral (i.e. load Love-number based) formalism and assuming Earth’s response is fully elastic and isotropic. GRACE-derived elastic displacements at observing sites would represent, if accurate, band-limited (degree 2 to 96, or higher if Mascon solutions are adopted) load-induced deformations that can be removed from SG-derived station displacements  in order to more accurately recover degree-1 surface deformation signature (and therefore geocenter motion). 

In this study, we adopt GRACE JPL Mascon RL06 data in conjunction with Preliminary Reference Earth Model-derived load Love numbers to infer elastic displacement at SG sites and remove them from SLR inherently geocentric time series of station positions.
In so doing, the residual SLR station displacements, consistently expressed in a geocentric frame, would in principle reflect a degree-1 deformation signature that can be recovered via either surface deformation (Chanard et al, 2018) or translational approach.

We will compare the SLR/GRACE (CM-CN) determined in this study to standard estimates of geocenter motion such as ILRS’s and JTRF2014’s estimated via translational approach and spectrally inverted solutions (CM-CF).

Chanard K et al, (2018). JGR-Sol Ea doi:10.1002/2017JB015245 
Wu X et al, (2006). JGR-Sol Ea doi:10.1029/2005JB004100. 

How to cite: Abbondanza, C., Chin, T. M., Gross, R. S., Heflin, M. B., Parker, J. W., Soja, B. S., Wiese, D. N., and Wu, X.: Geocenter Motion from a Combination of GRACE Mascon and SLR Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10369,, 2020


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displays version 2 – uploaded on 02 May 2020
Version description: Readability has been improved by enlarging World Maps showing MASCON-derived elastic displacements. A slide[...]
  • CC1: Comment on EGU2020-10369, Hongjuan Yu, 06 May 2020

    Hi, Claudio, The amplitudes in the Tx and Ty are obviously smaller than those of Net Shift, particularly, 2mm smaller in the Ty,

    do you think the geocenter motion in the Y is underestimated by using Degree 1 method?

    • AC1: Reply to CC1, Claudio Abbondanza, 08 May 2020

      Hello Hongjuan,

      Thanks for your comment.
      Yes, you're absolutely right in pointing
      out the much smaller amplitude of the
      seasonal geocentre motion signal in

      Methods computing geocentre motion (GM)
      based on spectral inversions
      (in the spherical harmonic domain)
      tend to recover amplitudes of the
      annual GM that are consistently smaller
      than GM derived from pure LAGEOS-1/2

      In this exercize, the annual amplitude
      of the signal is even smaller than, for
      instance, that reported by Xiaoping Wu's
      inversions in many of his papers.

      Keep in mind that we are using an experimental
      solution for SLR in this case. One in which
      station-to-satellite range biases
      (for each station of the SLR network) are being
      fixed, during the data reduction, to some
      pre-determined values.

      This ILRS analysis scheme
      seems to have an impact on geocentre motion in
      that it produces an attenuation of the GM annual
      signal on all of the three components.
      The "attenuation" has to be interpreted as
      "decrease" of the amplitude of GM signal
      compared to standard-pre-ITRF2020 ILRS analyses (where
      only a smaller number of range biases
      were fixed/estimated).

      Since we are considering an SLR data set
      that has "smaller" GM oscillations to
      begin with, when we remove GRACE-derived elastic
      displacements, we end up having smaller amplitudes
      of GM (compared to what we would get if we were to
      adopt standard-pre-ITRF2020 ILRS solutions).
      GRACE-derived displacements are here reconstructed
      by removing GIA signals and by restoring the
      de-aliasing products (GFZ analysis).

      This exercize will be repeated (and the results
      will be carefully double-checked) as soon as
      ILRS will release its entirely reprocessed
      data set (for ITRF2020).
      Also, JPL Mascons have been recently
      updated with a longer data set including
      GRACE-FO fields.

      Whether or not spectral inversions are downestimating
      GM signal is hard to tell.
      Some scholars have opposing views claiming that SLR
      (LAGEOS1-2) actually tends to overestimate
      GM signal and the ~7-mm annual oscillation we see on
      SLR (LAGEOS1-2)-derived axial geocentre is somehow
      "contaminated" by noise.
      And so your question in the end boils down to the issue of
      accuracy of one methodology (this exercize) versus
      others (pure SLR solutions, spectral inversions).
      And frankly I do not have an answer to that effect.

      List of Acronyms
      (*) GM stands for Geocentre Motion. Not to be confused with the
          product of the Gravitational Constant and mass of a "heavenly body".
      (*) SLR stands for Satellite Laser Ranging. Not to be confused with
      (*) ILRS is the International Laser Ranging Service.
      (*) MASCON stands for Mass Concentration.
      (*) GIA is Glacial Isostatic Adjustment.

  • CC2: Comment on EGU2020-10369, Alvaro Santamaría-Gómez, 07 May 2020

    Hi Claudio,

    Very nice work again. Saddly, we did not have the time to discuss during the session.

    So, would you like to comment on the sensitiviy of the geocenter series you got with different GRACE and SLR solutions? It may be significant or maybe not. In case it is, how would you suggest tackling the problem? Maybe with a combined GRACE and SLR solutions?


  • AC2: Comment on EGU2020-10369, Claudio Abbondanza, 08 May 2020

    Hello Alvaro,

    Thanks for your interest in the EGU display
    and I am sorry I was not able to answer properly your
    question in the chat-room.

    To answer your question on the sensitivity of
    these results on the GRACE/SLR solutions
    adopted, I would say it is significant,
    in the sense that if one were to change
    the datasets, either GRACE
    or SLR, one would see changes in the
    seasonal geocentre motion estimates
    in the order of a few mm.

    GRACE Mascon solutions are less (if not at
    all) affected by North-South spatially
    correlated errors and generally
    characterized by higher spatial
    Standard Spherical Harmonic solutions
    require smoothing/destriping be applied
    and this produces an attenuation of the
    geophysical signal.
    So to use GRACE standard Spherical
    Harmonics Solution (e.g. RL06) vs
    MASCON would produce differences in geocentre
    motion. I do not have numbers to
    share as to the differences
    GRACE MASCON vs GRACE RL06 for this
    test as of now. But I am positive there
    might be.

    Likewise, the SLR solution adopted
    in this exercize has an impact on the
    final geocentre.
    In the current SLR reprocessing, ILRS
    has introduced fixed
    station-to-satellite range biases for all
    of the stations. This is something new that
    was never done before by ILRS.
    And the impact of this processing strategy
    on seasonal geocentre
    motion could be significant: we're talking
    about attenuations of the annual signal
    amplitude in the order of 2-mm for
    axial geocentre.
    If I were to repeat this exercize
    with old-style SLR solutions, I would
    probably get larger geocentre

    As to combining GRACE/SLR at the observation
    level, not sure about the potential improvement.
    In gravity literature, GRACE and SLR are
    generally viewed as "complementary"
    missions: SLR, on the hand, is
    good at constraining the lower degrees
    of the gravity field.
    GRACE, on the other, does a good job with
    the higher degrees.
    Zonal coefficients from degree 2 up to degree 5/6
    determined via GRACE (and in particular GRACE-FO) are
    known for being rather noisy, if not inaccurate
    at all. So my gut feeling in this respect would
    be that mixing together normal equations
    from SLR and GRACE/GRACE-FO could degrade
    the quality of C_{l0}, unless the weighting
    strategy adopted when building the NEQs
    is such to favour SLR. And if we did
    that, then we would resort to a situation
    where SLR constraints the lower-degree gravity
    whereas GRACE takes care of the rest.
    But I am not expert on inversion of
    SLR/GRACE NEQs. And these
    considerations are purely speculative
    and not grounded on actual analyses.

    Thanks again for your interest,

    List of Acronyms
    RL06 - Release 06 (for GRACE/GRACE-FO and de-aliasing products)
    NEQ - Normal Equations
    Mascon - Mass Concentratios
    SLR - Satellite Laser Ranging
    ILRS - International Laser Ranging Service.

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