Journal of Geodesy

, Volume 92, Issue 4, pp 443–451 | Cite as

Short note: the experimental geopotential model XGM2016

  • R. Pail
  • T. Fecher
  • D. Barnes
  • J. F. Factor
  • S. A. Holmes
  • T. Gruber
  • P. Zingerle
Short Note


As a precursor study for the upcoming combined Earth Gravitational Model 2020 (EGM2020), the Experimental Gravity Field Model XGM2016, parameterized as a spherical harmonic series up to degree and order 719, is computed. XGM2016 shares the same combination methodology as its predecessor model GOCO05c (Fecher et al. in Surv Geophys 38(3): 571–590, 2017. doi: 10.1007/s10712-016-9406-y). The main difference between these models is that XGM2016 is supported by an improved terrestrial data set of \(15^\prime \times 15^\prime \) gravity anomaly area-means provided by the United States National Geospatial-Intelligence Agency (NGA), resulting in significant upgrades compared to existing combined gravity field models, especially in continental areas such as South America, Africa, parts of Asia, and Antarctica. A combination strategy of relative regional weighting provides for improved performance in near-coastal ocean regions, including regions where the altimetric data are mostly unchanged from previous models. Comparing cumulative height anomalies, from both EGM2008 and XGM2016 at degree/order 719, yields differences of 26 cm in Africa and 40 cm in South America. These differences result from including additional information of satellite data, as well as from the improved ground data in these regions. XGM2016 also yields a smoother Mean Dynamic Topography with significantly reduced artifacts, which indicates an improved modeling of the ocean areas.


Gravity Combined gravity field model Spherical harmonics Full normal equation systems High-performance computing 



We acknowledge the provision of extensive supercomputing resources by the Leibniz Supercomputing Centre (LRZ; Address: Boltzmannstraße 1, 85748 Garching bei München, Germany). We also acknowledge the valuable comments of three unknown reviewers.


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Institute of Astronomical and Physical GeodesyMunichGermany
  2. 2.United States National Geospatial-Intelligence Agency (NGA)ArnoldUSA
  3. 3.SGT Inc.GreenbeltUSA

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