Journal of Geodesy

, Volume 89, Issue 5, pp 505–513 | Cite as

The updated ESA Earth System Model for future gravity mission simulation studies

  • Henryk DobslawEmail author
  • Inga Bergmann-Wolf
  • Robert Dill
  • Ehsan Forootan
  • Volker Klemann
  • Jürgen Kusche
  • Ingo Sasgen
Short Note


A new synthetic model of the time-variable global gravity field is now available based on realistic mass variability in atmosphere, oceans, terrestrial water storage, continental ice-sheets, and the solid Earth. The updated ESA Earth System Model is provided in Stokes coefficients up to degree and order 180 with a temporal resolution of 6 h covering the time period 1995–2006, and can be readily applied as a source model in future gravity mission simulation studies. The model contains plausible variability and trends in both low-degree coefficients and the global mean eustatic sea level. It depicts reasonable mass variability all over the globe at a wide range of frequencies including multi-year trends, year-to-year variability, and seasonal variability even at very fine spatial scales, which is important for a realistic representation of spatial aliasing and leakage. In particular on these small spatial scales between 50 and 250 km, the model contains a range of signals that have not been reliably observed yet by satellite gravimetry. In addition, the updated Earth System Model provides substantial high-frequency variability at periods down to a few hours only, thereby allowing to critically test strategies for the minimization of temporal aliasing.


Time-variable gravity field Future satellite gravity missions GRACE-FO 



This study was performed under contract No. 4000109421 with the European Space Agency (ESA). We thank M. R. van den Broeke for providing output of RACMO2. We also thank Deutscher Wetterdienst, Offenbach, Germany, and the European Centre for Medium-Range Weather Forecasts, Reading, UK, for providing data from ECMWF’s latest re-analysis ERA-Interim. Numerical simulations were performed at Deutsches Klimarechenzentrum, Hamburg, Germany.


  1. Bergmann-Wolf I, Dill R, Forootan E, Klemann V, Kusche J, Sasgen I, Dobslaw H (2014a) Updating ESAs earth system model for gravity mission simulation studies: 2. Comparison with the original model, Tech. rep., Scientific Technical Report 14/08. GFZ, Potsdam. doi: 10.2312/GFZ.b103-14088
  2. Bergmann-Wolf I, Zhang L, Dobslaw H (2014) Global eustatic sea-level variations for the approximation of geocenter motion from grace. J Geod Sci 4(1):37–48. doi: 10.2478/jogs-2014-0006 Google Scholar
  3. Biancale R et al (2000) A new global Earth’s gravity field model from satellite orbit perturbations: GRIM5-S1. Geophys Res Lett 27(22):3611–3614CrossRefGoogle Scholar
  4. Dee DP et al (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q J Roy Met Soc 137(656):553–597. doi: 10.1002/qj.828 CrossRefGoogle Scholar
  5. Dill R (2008) Hydrological model LSDM for operational earth rotation and gravity field variations hydrological, Tech. rep., Scientific Technical Report 08/09. GFZ, Potsdam. doi: 10.2312/GFZ.b103-08095
  6. Dobslaw H, Flechtner F, Bergmann-Wolf I, Dahle C, Dill R, Esselborn S, Sasgen I, Thomas M (2013) Simulating high-frequency atmosphere-ocean mass variability for dealiasing of satellite gravity observations: AOD1B RL05. J Geophys Res 118(7):3704–3711. doi: 10.1002/jgrc.20271 CrossRefGoogle Scholar
  7. Dobslaw H, Bergmann-Wolf I, Dill R, Forootan E, Klemann V, Kusche J, Sasgen I (2014) Updating ESAs earth system model for gravity mission simulation studies: 1. Model description and validation, Tech. rep., Scientific Technical Report 14/07. GFZ, Potsdam. doi: 10.2312/GFZ.b103-14079
  8. Elsaka B, Raimondo J-C, Brieden P, Reubelt T, Kusche J, Flechtner F, Iran Pour S, Sneeuw N, Müller J (2014) Comparing seven candidate mission configurations for temporal gravity field retrieval through full-scale numerical simulation. J Geodesy 88(1):31–43. doi: 10.1007/s00190-013-0665-9 CrossRefGoogle Scholar
  9. Ettema J, van den Broeke MR, van Meijgaard E, van de Berg WJ, Bamber JL, Box JE, Bales RC (2009) Higher surface mass balance of the Greenland ice-sheet revealed by high-resolution climate modeling. Geophys Res Lett 36(12):L12,501. doi: 10.1029/2009GL038110
  10. Flechtner F, Dobslaw H (2013) GRACE AOD1B product description document for product release 05, Tech. rep., Rev. 4.0, GRACE Document 327–750. GeoForschungsZentrum PotsdamGoogle Scholar
  11. Flechtner F, Morton P, Watkins M, Webb F (2014) Status of the GRACE follow-on mission, in IAG symposium gravity, geoid, and height systems, pp IAGS-D-12-00,141Google Scholar
  12. Gruber T et al (2011) Simulation of the time-variable gravity field by means of coupled geophysical models. Earth Syst Sci Data 3(1):19–35. doi: 10.5194/essd-3-19-2011 CrossRefGoogle Scholar
  13. Hagemann S, Dümenil L (1998) A parametrization of the lateral waterflow for the global scale. Clim Dyn 31(14):17–31Google Scholar
  14. Hagemann S, Dümenil L (2003) Improving a subgrid runoff parameterization scheme for climate models by the use of high-resolution data derived from satellite observations. Clim Dyn 2 (3–4):349–359. doi: 10.1007/s00382-003-0349-x
  15. Han S, Shum C, Bevis M, Ji C, Kuo C (2006) Crustal dilatation observed by GRACE after the 2004 Sumatra–Andaman earthquake. Science 313:658–662CrossRefGoogle Scholar
  16. Klemann V, Martinec Z (2011) Contribution of glacial-isostatic adjustment to the geocenter motion. Tectonophysics 511(3–4):99–108. doi: 10.1016/j.tecto.2009.08.031 CrossRefGoogle Scholar
  17. Loomis BD, Nerem RS, Luthcke SB (2011) Simulation study of a follow-on gravity mission to GRACE. J Geodesy 86(5):319–335. doi: 10.1007/s00190-011-0521-8 CrossRefGoogle Scholar
  18. Lorenz C, Kunstmann H (2012) The hydrological cycle in three state-of-the-art reanalyses: intercomparison and performance analysis. J Hydrometeorol 13:1397–1420CrossRefGoogle Scholar
  19. Reigber C et al (2002) A high-quality global gravity field model from CHAMP GPS tracking data and accelerometry (EIGEN1S). Geophys Res Lett 29(14):94–97Google Scholar
  20. Rummel R (2003) How to climb the gravity wall. Space Sci Rev 108(1–2):1–14CrossRefGoogle Scholar
  21. Rummel R, Yi W, Stummer C (2011) GOCE gravitational gradiometry. J Geodesy 85(11):777–790. doi: 10.1007/s00190-011-0500-0 CrossRefGoogle Scholar
  22. Springer A, Kusche J, Hartung K, Ohlwein C, Longuevergne L (2014) New estimates of variations in water flux and storage over Europe based on regional (Re)analyses and multisensor observations. J Hydrometeorol:1–54. doi: 10.1175/JHM-D-14-0050.1
  23. Storch J-SV, Eden C, Fast I, Haak H, Hernández-Deckers D, Maier-Reimer E, Marotzke J, Stammer D (2012) An estimate of the Lorenz energy cycle for the world ocean based on the STORM/NCEP simulation. J Phys Oceanogr 42(12):2185–2205. doi: 10.1175/JPO-D-12-079.1 CrossRefGoogle Scholar
  24. Tapley BD, Bettadpur S, Ries JC, Thompson PF, Watkins M (2004a) GRACE measurements of mass variability in the Earth system. Science 305(5683):503–505. doi: 10.1126/science.1099192 CrossRefGoogle Scholar
  25. Tapley BD, Bettadpur S, Watkins M, Reigber C (2004b) The gravity recovery and climate experiment: mission overview and early results. Geophys Res Lett 31(9):607. doi: 10.1029/2004GL019920
  26. Thomas M, Sündermann J, Maier-Reimer E (2001) Consideration of ocean tides in an OGCM and impacts on subseasonal to decadal polar motion. Geophys Res Lett 28(12):2457–2460CrossRefGoogle Scholar
  27. Velicogna I, Wahr J (2006) Acceleration of Greenland ice mass loss in spring 2004. Nature 443(7109):329–31. doi: 10.1038/nature05168 CrossRefGoogle Scholar
  28. Visser PNAM (2010) Designing earth gravity field missions for the future: a case study. IAG commission 2: GRAVITY. Geoid and Earth Observation, Chania, pp 131–138Google Scholar
  29. Wiese DN, Nerem RS, Lemoine FG (2011) Design considerations for a dedicated gravity recovery satellite mission consisting of two pairs of satellites. J Geodesy 86(2):81–98. doi: 10.1007/s00190-011-0493-8 CrossRefGoogle Scholar
  30. Wolff JO, Maier-Reimer E, Legutke S (1997) The Hamburg Ocean Primitive Equation Model, 13. DKRZ, pp 1–110Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Henryk Dobslaw
    • 1
    Email author
  • Inga Bergmann-Wolf
    • 1
  • Robert Dill
    • 1
  • Ehsan Forootan
    • 2
  • Volker Klemann
    • 1
  • Jürgen Kusche
    • 2
  • Ingo Sasgen
    • 1
  1. 1.Department 1: Geodesy and Remote SensingDeutsches GeoForschungsZentrum GFZPotsdamGermany
  2. 2.Institute of Geodesy and GeoinformationBonn UniversityBonnGermany

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