International GNSS Service

2nd Data Reprocessing Campaign

second full reanalysis of all IGS GPS data collected since 1994


By late 2013, the Analysis Centers (ACs) of the International GNSS Service will begin the second reanalysis of the full history of GPS data collected by the IGS global network since 1994 in a fully consistent way using the latest models and methodology. This effort follows the successful first full reprocessing by the IGS, which provided the IGS input for ITRF2008, among other things.
to be
in red)
The expected Analysis Center and combined IGS products include:
    daily GPS & GLONASS orbits & GPS satellite clocks
    • 15-minute intervals (SP3c format)
    • so far: COD, ESA and maybe GFZ will contribute GLONASS orbits (SP3c format)
    • GPS satellite clocks in IGS timescale (loosely aligned to GPS time)
    • no GLONASS clock products until a convention to handle inter-frequency & inter-system biases is adopted
    daily GPS satellite & tracking station clocks
    • 5-minute intervals (clock RINEX format)
    • also 30-second intervals for satellite clocks (clock RINEX format) -- so far EMR, ESA, GRG, JPL, MIT, ULR and maybe GFZ plan to contribute
    • in IGS timescale (loosely aligned to GPS time)
    daily Earth rotation parameters (ERPs)
    • from SINEX (official product) & classic orbit combinations (for comparison only) (IGS erp format)
    • x & y coordinates of pole
    • rate-of-change of x & y pole coordinates
    • excess length-of-day (LOD)
    terrestrial coordinate frames with ERPs
    • with full variance-covariance matrix (SINEX format)
    • also include Z-offset parameters for satellite antennas (with removable constraints to official igs08.atx values)
    • past products have always been weekly integrations, but the IGS moved to daily frame solutions starting GPS Wk 1702 (19 August 2012); see below
    • daily frame products will also be provided in repro2
    possible other products ?
    • ionosphere maps, tropospheric zenith path delays, etc ???
    • new bias products ???
The possible Analysis Centers contributing complete solutions to this effort are:
    CODE — Center for Orbit Determination in Europe, Switzerland (TBC)
    EMR — Natural Resources Canada, Canada (TBC)
    ESA — European Space Operations Centre (ESOC), ESA, Germany
    GFZ — GeoForschungsZentrum/Potsdam, Germany (TBC)
    GRGS — Groupe de Recherche de Géodésie Spatiale - CNES/CLS, Toulouse, France
    JPL — Jet Propulsion Laboratory, USA
    MIT — Massachusetts Institute of Technology, USA
    NGS — National Geodetic Survey, NOAA, USA
    SIO — Scripps Institution of Oceanography, USA (TBC)

In addition, some centers might provide SINEX solutions to help densify the terrestrial reference frame, particularly for GPS stations located near tide gauges (associated with the TIGA Pilot Project):

    GTZ — GFZ TIGA, Germany (TBC)
    ULR — University of La Rochelle, France

Summaries of the analysis strategies and procedures for each AC are posted at the IGS Central Bureau.

in red)
IERS Conventions (2010) — generally should be implemented
use IGb08 reference frame (aligned to ITRF2008)
use updated igs08.atx "absolute" antenna calibrations time argument
  • as usual, GPS time (a realization of terrestrial time, TT) is used for all output analysis products
clock center-of-network (CLK:CoN) convention
  • AC clocks must be delivered with apparent geocenter motion removed by, for example, using your AC adjusted orbits and fixed IGb08 station coordinates at epoch of observations--this is the so-called clock center-of-network (CLK:CoN) convention in the SP3 files introduced by G. Gendt; more details at:
        — position paper from 2004 IGS Workshop, esp. Recommendations 10 & 11
        — and resulting action for SP3 file comment lines
P1-C1 satellite code biases phase wind-up correction
  • RHC phase rotations due to geometric changes should follow the model of J.T. Wu, S.C. Wu, G.A. Hajj, W.I. Bertiger, and S.M Lichten ("Effects of antenna orientation on GPS carrier phase", Manuscripta Geodaetica, 18, 91-98, 1993)
  • the Wu et al. model was conveniently restated by J. Kouba (2009) in his "A Guide to Using IGS Products"; see section 5.1.2
yaw attitude variations
  • changes in GPS satellite orientation during eclipse periods will follow the model of J. Kouba (2009) or equivalent
  • this is especially important for consistent satellite clock estimates
  • new yaw-attitude model under development for GPS Block II-F satellites by F. Dilssner (2010)
  • new yaw-attitude model for GLONASS-M satellites published by F. Dilssner (2010)
  • to implement these models, J. Kouba (2011, private communication) has provided the Fortran routine eclips.f (version updated January 2014) together with a EclipseReadMe.pdf file containing usage information
    — note that the August 2011 version has been updated to use yaw rates for the Block II/IIA satellites during the period 1996-2008 that are based on weighted averages of the JPL repro1 yaw-rate solutions; see yrates.pdf for details
    — the September 2011 version has been updated to fix a bug related to night maneuvers for IIF satellites at high beta angles
    — note also that Block II/IIA shadow eclipsing model is valid only after 5 November 1995 when the orientation control of the satellites was updated to be biased by +0.5 degrees in order to produce shadow behavior that is predictable; prior to that date, shadow-crossing data should not be used
    — the December 2013 version has been updated to correct the Block IIF shadow crossing according to the U.S. AF documentation, which states that the shadow crossing yaw rate is computed from the shadow start and end nominal yaw angles and the shadow crossing time interval. Also included in the December update are models for recently noticed anomolous IIF and IIA noon turns for small negative (>-0.9 deg) and positive (< 0.9 deg) sun (beta) angles, respectively. So the now current version should correctly model eclipsing of IIA/IIF/IIR and GLONASS satellites. More info is provided in EclipseDec2013Update.pdf.
    — the December 2013 version has been updated to fix a bug related to noon turn end for a small positive sun beta angle (<0.9 deg)
  • utilization of the yaw attitude model should consider changes in the phase wind-up correction (see section above) as well as changes in the location of the antenna phase center relative to the satellite center-of-mass due to non-zero X offsets for some spacecraft; see "A Guide to Using IGS Products" by J. Kouba (2009) for details; note that data from Block IIA GPS satellites should also be deleted for an interval following shadow exits
modeling of orbit dynamics
  • rotational errors are a major limit to the accuracy of all IGS orbit products; see:
    J. Ray & J. Griffiths, 2010
    J. Ray & J. Griffiths, 2011
  • these are probably due mostly to shortcomings of present once-per-rev empirical parameterizations commonly used to absorb unmodeled accelerations & lead to the flicker noise background documented in station coordinate time series
  • errors in the IERS model for subdaily EOP variations contribute also & both factors lead to aliased orbit errors at draconitic harmonics that contaminate all IGS products (see J. Ray & J. Griffiths, 2011)
  • other errors, especially in the IERS model for subdaily EOP variations, also contribute to subdaily orbit rotation errors that alias to annual, ~29, ~14, ~9, & ~7 days when sampled daily
  • reflected (albedo) & retransmitted radiation from the Earth may cause scale (1 - 2 cm) & translational effects at GNSS altitudes; see:
    C.J. Rodriguez-Solano, 2009
    U. Hugentobler et al., 2009
    C. Rodriguez-Solano, 2011et al., 2011
    website at Technische Universität München (TUM)
  • a recommended model for these effects, in the form of Fortran source code developed within the scope of the IGS Orbit Modeling Working Group, is available for download here (30 March 2011)
    — an update of the routine ERPFBOXW.f was posted by C. Rodriguez-Solano (21 September 2011) to account for Block-dependent transmitter thrust values for the GPS satellites (updated again 13 June 2012 for bug fixes)
    — a compilation of the calculated & estimated GPS transmit power levels is posted here
  • any albedo models might be proposed or implemented should be carefully evaluated for their impacts on other parameter estimates (e.g., on the terrestrial reference frame)
EGM2008 geopotential field now recommended
  • updated values for time-variations of low-degree coefficients given in IERS Conventions (2010) Chapter 6
  • new model for the mean pole trajectory given in IERS Conventions (2010) section 7.1.4 should be used for both geopotential and station displacement variations; see eqn (7.25) & Table 7.7
  • geopotential ocean tide model updated for FES2004 model
  • new model introduced for ocean pole tide (also for station displacements)
  • [OPEN TOPIC] impacts on IGS products from seasonal variations in geopotential
tidal displacements of station positions
  • current recommendations for solid Earth & ocean tidal loading should already be implemented
    site-dependent load coefficients recommended using FES2004 ocean tide model
    — corrections for counter-balancing center-of-mass motion of the solid Earth should be included in site coefficients ("Do you want to correct your loading values for [geocenter] motion?" YES)
    whole-Earth center-of-mass corrections should also be applied in generating SP3 orbits as described in IERS Conventions (2010) section 7.1.2
  • new model for the mean pole trajectory should be used for pole tide correction; see IERS Conventions (2010) eqn (7.25) & Table 7.7
  • ocean pole tide loading model given in IERS Conventions (2010) section 7.1.5
  • [NO LONGER RECOMMENDED] new model for S1 & S2 atmosphere pressure loading given in IERS Conventions (2010) section 7.1.3
    — effect is small but aliases into GPS orbit parameters otherwise
    — note center-of-mass frame corrections for SP3 orbits (similar to ocean tidal loading); see Table 7.6
no non-tidal loading displacements should be applied to station positions
  • since a key geoscience application of IGS station time series is to monitor non-tidal loading effects, these should be fully retained in products unless 1) it can be shown that there are strong reasons not to do this and 2) any corrections removed a priori are accurately known and can also be restored a posteriori
  • other reasons not to apply a priori modeled loading estimates to raw GNSS data are (see also Ray et al. 2007):
    — global circulation models do not reliably account for dynamic oceanic response for periods < ~10 days
    — discrepancies among global circulation models & among load computations are significant compared to geodetic accuracies (see e.g., T. van Dam, 2005 & L. Koot et al., 2006)
    — topographic corrections, which can exceed 100% of the total effect in mountainous areas, are not properly modeled by operational services (T. van Dam et al., 2010)
    — models must be free of tidal effects (since these are handled separately), which is usually not the case
    — long-term model biases, such as lack of overall mass conservation, will corrupt reference frame
    — inability to remove or modify models applied by ACs at the observation level
    — significant discrepancies remain between non-linear GNSS observations & models, even at annual periods, implying important systematic errors yet to be understood (see, e.g., X. Collilieux et al., submitted 2011)
  • if useful, non-tidal loading corrections can be applied in long-term stacking of GNSS weekly frames to minimize possible aliasing of Helmert parameters
    — see, e.g., X. Collilieux et al., submitted 2011
    — this use is efficient & fully reversible, unlike corrections at the observation level
  • due to the level of high-frequency non-tidal atmosphere loading variance, it is necessary to move from weekly to daily frame integrations in order to fully preserve loading signals in IGS position time series without significant attenuation
    — this change was made operationally starting with Wk 1702 products
    — this can be seen in the plot below, which shows dUp power spectra for atmospheric pressure loading at 415 globally distributed IGS stations computed from the NCEP reanalysis pressure fields (courtesy of T. van Dam, 2011)
    atml spectra
    — the stacked mean PSD for this ensemble of stations is shown by the turquoise line, which follows a power-law with spectral index of -4 for frequencies >0.4 cpd (ignoring the strong S1 & S2 tidal lines; the S2 line is broadened by being at the Nyquist sampling limit)
    — the fit for the mean atmosphere pressure loading trend from 0.4 cpd upward (but omitting the tidal bands around 1.0 & from 1.13 cpd onward) is approximately:
    PSDUp = 0.013 mm2/cpd * f -4
    indicated by the dotted line in the plot above
    — integrating this power law from 1/1 cpd to infinity & from 1/7 cpd to infinity, assuming the same -4 power law extends to the highest possible frequencies, gives these variances, respectively:
    Var (1/1 -> inf)Up = 0.00433 mm2
    Var (1/7 -> inf)Up = 1.486 mm2
    or equivalently these scatters, respectively:
    RMS (1/1 -> inf)Up = 0.066 mm
    RMS (1/7 -> inf)Up = 1.219 mm
    — for a GPS dUp measurement with a basement error of about 2.2 mm for weekly observations (as found from the IGS repro1 results), one must expect daily measurements to have errors no smaller than sqrt(7) times larger if there are no temporal error correlations (higher otherwise) or about 5.8 mm; so the actual atmospheric pressure dUp loading variations are much smaller than the GPS detection limit for 1 d intervals (by about two orders of magnitude on average) but the average load variations are within a factor of ~2 of the GPS WRMS noise floor for weekly dUp integrations & can even exceed the GPS noise floor at some extreme stations (considering the spatial variation in PSD spans about a factor of 10 upward and downward, or equivalently a factor of 3 to 4 in RMS)
    — consequently, this suggests that there is some loss, on average, in GPS sensitivity to atmosphere loading with the present IGS weekly integrations when load corrections are not applied, but this would not be the case with daily frame integrations
tidal EOP variations
  • most current models & recommendations should already be implemented
  • this includes the subdaily polar motion libration terms introduced in 2005 & previously called "high-frequency nutation", which can be computed using fortran routines PMsdnut.f or PMSDNUT2.f
  • key exception is the addition of UT1 libration effects, introduced in late 2009
  • see IERS Conventions (2010) Table 5.1b for coefficients of 11 largest semidiurnal UT1 libration terms or use the new fortran routine UTLIBR.F from A. Brzezinski
  • note that the maximum UT1 libration effect is 105 µas (peak-to-peak) or 13 mm at GPS altitude, which probably aliases strongly into the orbit parameters
  • standard IGS Earth rotation parameterization should be used, with daily (noon) estimates for the x,y coordinates of polar motion, their time derivatives over the 24 hr surrounding each noon, & (nominal) length-of-day (LOD) variations over the 24 hr surrounding each noon
  • each set of daily ERPs should be determined freely, without any a priori or continuity constraints
tropospheric propagation delays
  • for details, refer to IERS Conventions (2010) section 9.2
  • a priori meteorological data sources:
      [1] local sensor met files (which however are only available for a few sites), or
      [2] the fortran routine GPT2.f returns location- & season-dependent values for local pressure, temperature, temperature lapse rate, water vapor pressure, hydrostatic and wet mapping function coefficients ah & aw, and geoid undulation based on a 5 x 5 degree gridded fit to a long history of ECMWF fields; this updated version gives much better spatial and temporal resolution than the prior GPT.f model available at the IERS Conventions website; please refer to the README comments for further information; the associated external grid file is available here & should be placed in the directory where the routine is run or else the subroutine open call modified
      [3] retrieved from a numerical weather model, as for the ECMWF global values provided by the service at the Technical University of Vienna in the form of gridded hydrostatic zenith delays; for details, see the README file
  • a priori hydrostatic delays in the zenith direction should be computed from the surface pressure from any of the sources above according to the formula of Saastamoinen (1972) as given by Davis et al. (1985) & shown as eqn (9.11) in IERS Conventions (2010) Chapter 9
  • a priori wet delays in the zenith direction can also be computed provided that the local temperature and water vapor pressure are known (see above):
      — a fortran routine for this computation is available at WETSAAS.f
      — the fortran routine WETPP.f might be helpful to convert between relative humidity and water vapor partial pressure
  • using the sum of the a priori hydrostatic and wet zenith delays will ensure that the tropospheric parameter adjustments that are more nearly zero-mean
      — a test at NGS using a week of data from about 235 globally distributed stations found that using GPT2 for a priori meteo values improved the residual zenith tropo delay adjustments from 42 +/- 64 mm (assuming a relative humidity of 0.50 everywhere) to 3 +/- 54 mm
  • a priori azimuthally symmetric line-of-sight delays should be computed using either:
  • a priori asymmetric line-of-sight delays caused by the mean troposphere distribution (represented by a spherical harmonic expansion to degree and order 9) can be evaluated using the fortran routine APG
      — note that the north & east gradients from this routine should be used with the gradient model by G. Chen & T.A. Herring ("Effects of atmospheric azimuthal asymmetry on the analysis of space geodetic data", J. Geophys. Res., 102(B9), 20,489-20,502, doi: 10.1029/97JB01739, 1997), also described in APG
      — note also that test results using the APG model have not verified its usefulness, so it is not recommended for general adoption at this time
  • note that using the simpler GPT2 routine (with VMF1_HT) rather than more realistic a prioris derived from in situ data or numerical weather models can partially compensate for sub-seasonal atmospheric pressure loading effects at a level probably smaller than ~1 mm in annual height variation (see J. Kouba, 2009 & P. Steigenberger et al., 2009); this effect arises due to systematic limitations of the GPT2 model that fail to capture the full measure of spatial and temporal variations of the troposphere (together with small differences in the dry & wet mapping functions, which are very sharp functions of elevation cutoff angle); consequently, the magnitude of this compensation effect is a strong function of the AC elevation cutoff angle; in this respect note also that the Steigenberger et al. analysis included GPS data with elevation angles down to 3 degree (with elevation-dependent weighting); ACs with higher elevation cutoff angles will experience smaller loading compensation
  • but note further that ray-tracing of direct a priori slant delays using spatially & temporally high-resolution troposphere models should be superior, in principle, but sufficient global models are not yet available; however, it has not been found so far that residual troposphere parameters can be eliminated from space geodetic solutions, a step that would bring significant precision improvements if the slant delays can be determined accurately enough
  • residual tropospheric delays should be parameterized in the GNSS data analysis on the assumption that they are predominantly due to unmodeled variations in the wet component of the troposphere zenith delay (that is, using wet mapping function partials) as well as unmodeled azimuthal gradients
    — GNSS data are sensitive to zenith delay changes over intervals as short as the observation sampling, but parameterization at hourly intervals is much more efficient & usually satisfactory
    — a minimal gradient parameterization involves one N-S & one E-W parameter at the beginning & end of each day of data for each station, with continuous linear variation during the day
    — the Chen-Herring (1997) gradient mapping function is recommended; see updated IERS Conventions (2010) section 9.2:
    mg(e) = 1 / [sin(e)tan(e) + 0.0031]
    where "e" is the observation elevation angle. Unlike other gradient mapping functions, this one is not affected by a singularity at very low elevations & should also be used with the APG a priori gradient model.
    — for gradient estimation, an elevation cutoff angle no higher than 10 degrees is recommended; otherwise station height accuracies will suffer
    a priori parameter constraints are not needed & are strongly discouraged
higher-order ionospheric corrections
  • for details, refer to IERS Conventions (2010) section 9.4
  • a software package has been developed by M. Hernandez Pajares & colleagues to compute the 2nd order ionosphere correction; it is available at this site
  • the software is entirely new, with contributions & debugging from an informal working group of volunteers
  • only the 2nd order correction, which is larger & for which there is a clear consensus on how it should be applied, is included currently; additional higher-order terms can be incorporated in the future
analysis constraints
  • a limitation in IGS operational & repro1 products is the application of unremovable constraints by some ACs (see R. Ferland, 2010)
  • unremovable continuity constraints, for example, can act as biased filters & cause significant signal distortions (see J. Ray, 2008)
  • these can be particulary insidious when applied to pre-reduced parameters, such as orbit estimates, & are especially difficult to justify for GNSS processing where almost every parameter is highly observable
  • consequently, some AC contributions are routinely excluded from IGS product combinations
  • for repro2, ACs are asked to avoid any solution over-constraints, applying pre-removed or unremovable constraints no tighter than noise levels & ensuring that any other constraints are strictly removable -- see reprocessing recommendations on p. 10 of the IGS 2010 Workshop in Newcastle
  • failure to meet this condition may force full AC exclusion from the product combinations
  • each AC will be asked to certify its compliance with these standards, noting specific areas of deviation
  • all AC metadata errors reported in the weekly SINEX combination reports should be corrected
  • all ACs should also ensure that their analysis processing summary files at the IGS Central Bureau are up to date
Repro2 preliminary product combinations for evaluation:
The IGS contribution to ITRF2013 - Preliminary results from the IGS repro2 SINEX combinations (2014) by P. Rebischung et al., a presentation at the Fall 2014 American Geophysical Union Meeting
Preliminary Analysis of IGS 2nd Reprocessed Orbits by K. Choi, a poster presentation at the 2015 European Geosciences Union

Repro2 TRF combinations:
Combination of the IGS repro2 Terrestrial Frames by P. Rebischung et al., a poster presentation at the 2015 European Geosciences Union

The IGS Contribution to ITRF2014 (2015)
by P. Rebischung, B. Garayt, Z. Altamimi, X. Collilieux, a presentation at the 26th IUGG General Assembly, Prague, 28 June 2015

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