JTRF2014, the JPL Kalman filter and smoother realization of the International Terrestrial Reference System

We present and discuss JTRF2014, the Terrestrial Reference Frame (TRF) the Jet Propulsion Laboratory constructed by combining space‐geodetic inputs from very long baseline interferometry (VLBI), satellite laser ranging (SLR), Global Navigation Satellite Systems (GNSS), and Doppler orbitography and radiopositioning integrated by satellite submitted for the realization of ITRF2014. Determined through a Kalman filter and Rauch‐Tung‐Striebel smoother assimilating position observations, Earth orientation parameters, and local ties, JTRF2014 is a subsecular, time series‐based TRF whose origin is at the quasi‐instantaneous center of mass (CM) as sensed by SLR and whose scale is determined by the quasi‐instantaneous VLBI and SLR scales. The dynamical evolution of the positions accounts for a secular motion term, annual, and semiannual periodic modes. Site‐dependent variances based on the analysis of loading displacements induced by mass redistributions of terrestrial fluids have been used to control the extent of random walk adopted in the combination. With differences in the amplitude of the annual signal within the range 0.5–0.8 mm, JTRF2014‐derived center of network‐to‐center of mass (CM‐CN) is in remarkable agreement with the geocenter motion obtained via spectral inversion of GNSS, Gravity Recovery and Climate Experiment (GRACE) observations and modeled ocean bottom pressure from Estimating the Circulation and Climate of the Ocean (ECCO). Comparisons of JTRF2014 to ITRF2014 suggest high‐level consistency with time derivatives of the Helmert transformation parameters connecting the two frames below 0.18 mm/yr and weighted root‐mean‐square differences of the polar motion (polar motion rate) in the order of 30 μas (17 μas/d).

[1]  Pascal Willis,et al.  The International DORIS Service contribution to the 2014 realization of the International Terrestrial Reference Frame , 2016 .

[2]  Z. Altamimi,et al.  ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions , 2016 .

[3]  Z. Altamimi,et al.  Assessment of the accuracy of global geodetic satellite laser ranging observations and estimated impact on ITRF scale: estimation of systematic errors in LAGEOS observations 1993–2014 , 2016, Journal of Geodesy.

[4]  Harald Schuh,et al.  Determination of a terrestrial reference frame via Kalman filtering of very long baseline interferometry data , 2016, Journal of Geodesy.

[5]  J. Ray,et al.  The IGS contribution to ITRF2014 , 2016, Journal of Geodesy.

[6]  D. Thaller,et al.  IVS contribution to ITRF2014 , 2016, Journal of Geodesy.

[7]  M. Marcos,et al.  Vertical land motion as a key to understanding sea level change and variability , 2016 .

[8]  M. Heflin,et al.  A global assessment of accelerations in surface mass transport , 2015 .

[9]  Y. Bar-Sever,et al.  Realizing a terrestrial reference frame using the Global Positioning System , 2015 .

[10]  Johannes Bouman,et al.  Second-degree Stokes coefficients from multi-satellite SLR , 2015, Journal of Geodesy.

[11]  T. M. Chin,et al.  KALREF—A Kalman filter and time series approach to the International Terrestrial Reference Frame realization , 2015 .

[12]  Felix W. Landerer,et al.  GPS as an independent measurement to estimate terrestrial water storage variations in Washington and Oregon , 2015 .

[13]  D. Cayan,et al.  Ongoing drought-induced uplift in the western United States , 2014, Science.

[14]  Angelyn W. Moore,et al.  The Antarctica component of postglacial rebound model ICE-6G_C (VM5a) based on GPS positioning, exposure age dating of ice thicknesses, and relative sea level histories , 2014 .

[15]  M. Heflin,et al.  Horizontal motion in elastic response to seasonal loading of rain water in the Amazon Basin and monsoon water in Southeast Asia observed by GPS and inferred from GRACE , 2013 .

[16]  Matt A. King,et al.  Detecting offsets in GPS time series: First results from the detection of offsets in GPS experiment , 2013 .

[17]  Pieter Visser,et al.  Calibration and validation of individual GOCE accelerometers by precise orbit determination , 2012, Journal of Geodesy.

[18]  J. Ray,et al.  Geocenter motion and its geodetic and geophysical implications , 2012 .

[19]  Manuela Seitz,et al.  The 2008 DGFI realization of the ITRS: DTRF2008 , 2012, Journal of Geodesy.

[20]  Jim R. Ray,et al.  Sub-daily alias and draconitic errors in the IGS orbits , 2011, GPS Solutions.

[21]  Xavier Collilieux,et al.  ITRF2008 plate motion model , 2011 .

[22]  Z. Martinec,et al.  Contribution of glacial-isostatic adjustment to the geocenter motion , 2011 .

[23]  Thomas A. Herring,et al.  Transient signal detection using GPS measurements: Transient inflation at Akutan volcano, Alaska, during early 2008 , 2011 .

[24]  P. Sarti,et al.  Improved geodetic European very-long-baseline interferometry solution using models of antenna gravitational deformation , 2011 .

[25]  Z. Altamimi,et al.  ITRF2008: an improved solution of the international terrestrial reference frame , 2011 .

[26]  Chung-Yen Kuo,et al.  Geodetic Observations and Global Reference Frame Contributions to Understanding Sea‐Level Rise and Variability , 2010 .

[27]  T. Dixon,et al.  Accelerating uplift in the North Atlantic region as an indicator of ice loss , 2010 .

[28]  Xavier Collilieux,et al.  Impact of loading effects on determination of the International Terrestrial Reference Frame , 2010 .

[29]  Xavier Collilieux,et al.  Global sea-level rise and its relation to the terrestrial reference frame , 2009 .

[30]  Pascal Willis,et al.  IDS contribution to ITRF2008 , 2009 .

[31]  Guillaume Ramillien,et al.  Detecting hydrologic deformation using GRACE and GPS , 2009 .

[32]  J. Ray,et al.  Effect of the satellite laser ranging network distribution on geocenter motion estimation , 2009 .

[33]  W. Peltier,et al.  Constraining Models of Postglacial Rebound Using Space Geodesy , 2008 .

[34]  Norden E. Huang,et al.  A review on Hilbert‐Huang transform: Method and its applications to geophysical studies , 2008 .

[35]  S. Ravi.  Bayesian Logical Data Analysis for the Physical Sciences: a Comparative Approach with Mathematica® Support , 2007 .

[36]  Z. Altamimi,et al.  ITRF2005 : A new release of the International Terrestrial Reference Frame based on time series of station positions and Earth Orientation Parameters , 2007 .

[37]  M. Greff-Lefftz,et al.  Fluid core dynamics and degree-one deformations: Slichter mode and geocenter motions , 2007 .

[38]  J. Wahr,et al.  A comparison of annual vertical crustal displacements from GPS and Gravity Recovery and Climate Experiment (GRACE) over Europe , 2007 .

[39]  Raúl Rueda,et al.  Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica Support by P. C. Gregory. Hardcover: 486 pages. Cambridge University Press. ISBN: 052184150X, $75.00 , 2007 .

[40]  Michael B. Heflin,et al.  Seasonal and interannual global surface mass variations from multisatellite geodetic data , 2006 .

[41]  D. Simon.  Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches , 2006 .

[42]  Peter J. Clarke,et al.  Geocenter motions from GPS: A unified observation model , 2006 .

[43]  Jürgen Kusche,et al.  Surface mass redistribution inversion from global GPS deformation and Gravity Recovery and Climate Experiment (GRACE) gravity data , 2005 .

[44]  Jim R. Ray,et al.  Evaluation of co-location ties relating the VLBI and GPS reference frames , 2005 .

[45]  Philip C. Gregory,et al.  Bayesian Logical Data Analysis for the Physical Sciences: Acknowledgements , 2005 .

[46]  T. van Dam,et al.  Effects of atmospheric pressure loading and seven-parameter transformations on estimates of geocenter motion and station heights from space geodetic observations , 2005 .

[47]  T. M. Chin,et al.  Modeling and forecast of the polar motion excitation functions for short-term polar motion prediction , 2004 .

[48]  Luca Vittuari,et al.  Surveying co-located space-geodetic instruments for ITRF computation , 2004 .

[49]  Jeffrey P. Walker,et al.  THE GLOBAL LAND DATA ASSIMILATION SYSTEM , 2004 .

[50]  G. Blewitt.  Self‐consistency in reference frames, geocenter definition, and surface loading of the solid Earth , 2003 .

[51]  Geoffrey Blewitt,et al.  Effect of annual signals on geodetic velocity , 2002 .

[52]  G. Blewitt,et al.  A New Global Mode of Earth Deformation: Seasonal Cycle Detected , 2001, Science.

[53]  Claude Boucher,et al.  A review of algebraic constraints in terrestrial reference frame datum definition , 2001 .

[54]  M. Watkins,et al.  Glacial isostatic adjustment observed using very long baseline interferometry and satellite laser ranging geodesy , 1999 .

[55]  Ichiro Fukumori,et al.  Assimilation of TOPEX/Poseidon altimeter data into a global ocean circulation model: How good are the results? , 1999 .

[56]  John Langbein,et al.  Continuous monitoring of surface deformation at Long Valley Caldera, California, with GPS , 1997 .

[57]  T. van Dam,et al.  PREDICTIONS OF CRUSTAL DEFORMATION AND OF GEOID AND SEA-LEVEL VARIABILITY CAUSED BY OCEANIC AND ATMOSPHERIC LOADING , 1997 .

[58]  J. Zumberge,et al.  Precise point positioning for the efficient and robust analysis of GPS data from large networks , 1997 .

[59]  Alexey Kaplan,et al.  Mapping tropical Pacific sea level : Data assimilation via a reduced state space Kalman filter , 1996 .

[60]  J. Ray,et al.  Measurements of length of day using the Global Positioning System , 1996 .

[61]  D. Argus.  Postglacial rebound from VLBI geodesy: On establishing vertical reference , 1996 .

[62]  Michael B. Heflin,et al.  Plate motion and crustal deformation estimated with geodetic data from the Global Positioning System , 1995 .

[63]  P. Malanotte‐Rizzoli,et al.  An approximate Kaiman filter for ocean data assimilation: An example with an idealized Gulf Stream model , 1995 .

[64]  J. Wahr,et al.  The viscoelastic relaxation of a realistically stratified earth, and a further analysis of postglacial rebound , 1995 .

[65]  Michael B. Heflin,et al.  Global coordinates with centimeter accuracy in the International Terrestrial Reference Frame using GPS , 1992 .

[66]  W. Press,et al.  Fast algorithm for spectral analysis of unevenly sampled data , 1989 .

[67]  Stephen M. Lichten,et al.  Strategies for high-precision Global Positioning System orbit determination , 1987 .

[68]  A.H. Haddad,et al.  Applied optimal estimation , 1976, Proceedings of the IEEE.

[69]  Nikita P. Zelensky,et al.  Impact of ITRS 2014 realizations on altimeter satellite precise orbit determination , 2018 .

[70]  D. Angermann,et al.  Validation of DTRF2014, ITRF2014 and JTRF2014 by precise orbit determination of SLR and altimetry satellites , 2017 .

[71]  J. Ries,et al.  Reconciling Estimates of Annual Geocenter Motion from Space Geodesy , 2016 .

[72]  Geoffrey Blewitt,et al.  Terrestrial Reference Frame Requirements for Studies of Geodynamics and Climate Change , 2015 .

[73]  M. Tamisiea,et al.  On seasonal signals in geodetic time series , 2012 .

[74]  Zuheir Altamimi,et al.  Strategies to mitigate aliasing of loading signals while estimating GPS frame parameters , 2011, Journal of Geodesy.

[75]  J. Ray.  Dependence of IGS Products on the ITRF Datum , 2011 .

[76]  Gerhard Beutler,et al.  Integrated scientific and societal user requirements and functional specifications for the GGOS , 2009 .

[77]  M. Rothacher,et al.  The Global Geodetic Observing System , 2007 .

[78]  Zuheir Altamimi,et al.  Variance Component Estimation for Combination of Terrestrial Reference Frames , 2007 .

[79]  Richard S. Gross,et al.  A Kalman-filter-based approach to combining independent Earth-orientation series , 1998 .

[80]  J. Wahr,et al.  Effect of melting glaciers on the Earth's rotation and gravitational field: 1965–1984 , 1992 .

[81]  Marvin H. J. Guber.  Bayesian Spectrum Analysis and Parameter Estimation , 1988 .