1. OVERVIEW OF IGS PRODUCTS & ANALYSIS CENTER MODELING Jim Ray, NOAA/NGS Jake Griffiths, NOAA/NGS Status of core products – focus on Ultra-rapid predicted orbits – issues with current products Comparisons of AC analysis strategies – evidence for systematic errors, esp. fortnightly harmonics Recommendations IGS 2008 Workshop, Miami Beach, 2 June 2008

2. SUMMARY OF IGS CORE PRODUCTS PRODUCT SUITES # ACs CURRENT PRECISION LATENCYUPDATESSAMPLE INTERVAL QUALITY ASSESSMENT Ultra-Rapid (predicted) orbits SV clocks ERPs 7 (2)* 4 7 (2)* < 5 cm ~5 ns < ~1 mas real time03, 09, 15, 21 UTC 15 min 6 hr marginally robust extremely poor very weak Ultra-Rapid (observed) orbits SV clocks ERPs 7 (2)* 4 7 (2)* ~3 cm ~0.2 ns ~0.1 mas 3 - 9 hr03, 09, 15, 21 UTC 15 min 6 hr fairly robust weak fairly robust Rapid orbits SV, stn clocks ERPs 858858 ~2.5 cm ~0.1 ns ~0.06 mas 17 - 41 hrdaily 15 min 5 min daily robust marginally robust robust Final orbits GLO orbits SV, stn clocks ERPs terr frame 8468884688 ~2.5 cm < ~15 cm ? ~0.1 ns ~0.03 mas 3 (h), 6 (v) mm 13 - 20 dweekly 15 min 5 min, 30 s daily weekly robust not robust robust for 5 min robust * indicates AC contributions that are weaker than others

3. Predicted IGU Orbit WRMS WRMS of IGU orbit predictions have improved to <5 cm RMS IGU Orbits (1st 6 hr of predictions) wrt IGR Orbits PRN29 (IIA) decommissioned GOP solutions improved

4. Scale & Rotations of Predicted IGU Orbits Z rotations (UT1 prediction error) reach 1 mas level equivalent to equatorial shift of 12.9 cm at GPS altitude (shifted) IGU Orbits (24 h of predictions) wrt IGR Orbits

5. Issues with Current Products IGU orbit combination only marginally robust –sometimes AC predictions are better than combo Ultra-Rapid IGS Orbit Comparison for 1478_6_06 (10 May 2008 06h) CENT STA| DX DY DZ RX RY RZ SCL RMS WRMS MEDI | [mm] [mm] [mm] [uas] [uas] [uas] [ppb] [mm] [mm] [mm] --------+-------------------------------------------------------- cou 73| 11 -1 -4 536 -389 254 -.29 64 34 33 emu 49| 7 0 0 486 38 -60.03 84 44 21 esu 95| 4 5 -2 -396 687 -72.13 77 77 29 gfu 65| 1 -2 -2 302 -21 127 -.34 77 78 29 gou 82| -5 -4 -1 260 334 48 -.35 89 78 31 siu 62| 0 17 -33 -221 1068 730.02 130 131 71 usu 33| 19 9 0 297 -394 -20.14 123 111 56 igu n/a| 5 0 -5 283 103 45 -.08 74 79 18 –would benefit from more high-quality ACs –accuracy now limited by ERP predictions, mostly may also apply to IGR orbits (but less severe) IGU combined clocks are very poor –clock predictions no better than BRDC –not enough clock ACs even IGR clocks sometimes weak when some ACs miss

6. COMPARISON OF AC DATA USAGE ANALYSIS CENTER OBS TYPEORBIT DATA ARC LENGTH DATA RATE ELEVATION CUTOFF ELEVATION INVERSE WGTS CODE DbDiff ( weak redundant) 24 + 24 + 24 h3 min3 deg1/cos 2 (z) EMR UnDiff24 h5 min15 degnone ESA UnDiff24 h5 min10 deg1/sin 2 (e) GFZ UnDiffn x 24 h n = 3 (Rapid = 2) 5 min7 deg1/2sin(e) for e < 30 deg GRGS (new) UnDiff48 h15 min10 deg1/cos 2 (z) JPL UnDiff3 + 24 + 3 h5 min15 deg → 7 degnone MIT DbDiff (weak redundant) 24 h (SRPs over 9d) 2 min10 dega 2 + (b 2 /sin 2 (e)) a,b from site residuals NGS DbDiff (redundant) 24 h30 s10 deg[5 + (2/sin(e)) cm] 2 PDR (Repro) DbDiff (weak redundant) 24 + 24 + 24 h3 min3 deg1/cos 2 (z) SIO DbDiff (weak redundant) 24 h2 min10 dega 2 + (b 2 /sin 2 (e)) a,b from site residuals

7. effect of 15-deg cutoff

8. COMPARISON OF AC TIDAL MODELS ANALYSIS CENTER SOLID EARTH EARTH POLE OCEAN LOAD OCEAN POLE OCEAN CMC SUBDAILY EOPs CODE IERS 2003; dehanttideinel.f eqn 23a/b mean pole FES2004; hardisp.f nonesites & SP3IERS 2003; subd nutation EMR IERS 2003eqn 23a/b mean pole FES2004; gipsy nonesites & SP3IERS 1996; no subd nutation ESA IERS 2003; dehanttideinel.f eqn 23a/b mean pole FES2004; hardisp.f nonesites & SP3IERS 2003 & PMsdnut.for GFZ IERS 1992eqn 23a/b mean pole FES2004; hardisp.f nonesites & SP3IERS 2003; subd nutation GRGS (new) IERS 2003nominal mean PM FES2002none IERS 2003 & PMsdnut.for JPL IERS 2003eqn 23a/b mean pole FES2002; gipsy nonenone → sites & SP3 IERS 1996 → IERS 2003 MIT IERS 2003eqn 23a/b mean pole FES2004nonesites & SP3IERS 2003 & PMsdnut.for NGS IERS 2003; dehanttideinel.f eqn 23a/b mean pole FES2004; hardisp.f nonesites & SP3IERS 2003 & PMsdnut.for PDR (Repro) IERS 2003; dehanttideinel.f fixed mean pole GOT00.2 w/ 11 terms none IERS 2003; no subd nutation SIO IERS 2003eqn 23a/b mean pole FES2004nonesites & SP3IERS 2003 & PMsdnut.for

9. Aliased Tidal Peaks in PM Discontinuities Spectra of polar motion day-boundary discontinuities show signatures of aliased O1, Q1, & N2 tides + unknown 7.2 d line Peaks in PM Differences AC14 d9 d7 d EMR PM-x ± 14.2 0.2 9.35 0.09 7.18 0.05 EMR PM-y ± 14.1 0.2 9.6 & 9.0 0.1 7.16 0.05 GFZ PM-x ± 14.2 0.2 9.4 0.1 7.21 0.05 GFZ PM-y ± 14.2 0.2 9.6 & 8.9 0.1 7.14 0.05 JPL PM-x ± 14.2 0.2 9.4 0.1 7.23 0.05 JPL PM-y ± 14.2 0.2 9.2 0.1 7.26 0.05

10. VLBI (1-hr) UT1 residuals VLBI (1-hr) UT1 residuals – white over full frequency range 14.19-d periodic 14.19-d periodic – treated as GPS artifact – amplitude varies between 5 & 11 μs – phase varies linearly w/ time due to changing period GPS LOD residuals GPS LOD residuals – approximately white – with small peak at 13.7 d – possible difference in a priori tidal models wrt VLBI Gauss-Markov values for GPS LOD biasesGauss-Markov values for GPS LOD biases – peak-to-peak range = ± 40 μs – RMS = 9 μs EMR analysis upgrade Kalman Filter of VLBI UT1 + GPS LOD (Senior, Kouba, Ray – EGU 2008)

11. 14.12 d signal in IGS & C04 probably due to mix of GPS errors LODS – (AAM+OAM) spectra Fortnightly Band – Spurious IGS LOD (Senior, Kouba, Ray – EGU 2008)

12. Day-boundary Orbit Discontinuities Orbit discontinuities between days show temporally correlated errors & broad fortnightly spectral peak From Griffiths & Ray (AGU 2007)

13. COMPARISON OF AC GRAVITY FORCE MODELS ANALYSIS CENTER GRAVITY FIELD EARTH TIDES EARTH POLE OCEAN TIDES OCEAN POLE RELATIVITY EFFECTS CODE JGM3; C21/S21 due to PM IERS 2003 CSR 3.0nonedynamic corr & bending applied EMR JGM3; C21/S21 due to PM freq-depend. Love # IERS 2003 CSRnoneno dynamic corr; bending applied ESA EIGEN; C21/S21 due to PM IERS 2003 nonedynamic corr & bending applied GFZ JGM2; C21/S21 due to PM Wahr Love #GFZ model GEM-T1nonedynamic corr & bending applied GRGS (new) EIGEN; C21/S21 due to PM IERS 2003 FES 2004nonedynamic corr applied; no bending JPL JGM3; C21/S21 due to PM IERS 2003 CSR → FES2004 nonedynamic corr & bending applied MIT EGM96; C21/S21 due to PM IERS 1992; Eanes Love # none no dynamic corr; bending applied NGS GEM-T3; C21/S21 due to PM IERS 1992; Eanes Love # none no dynamic corr; bending applied PDR (Repro) JGM3; constant C21/S21 IERS 2003 except step 2 IERS96; fixed pole CSR 3.0nonedynamic corr & bending applied SIO EGM96; C21/S21 due to PM IERS 1992; Eanes Love # none no dynamic corr; bending applied

14. COMPARISON OF AC SATELLITE DYNAMICS ANALYSIS CENTER NUTATION & EOPs SRP PARAMS VELOCITY BRKs ATTITUDESHADOW ZONES EARTH ALBEDO CODE IAU 2000; BuA ERPs D,Y,B scales; B 1/rev every 12 hr + constraints noneE+M: umbra & penumbra none EMR IAU 1980; extrap. past 3d X,Y,Z scales stochastic noneyaw rates estimated E: umbra & penumbra none ESA IAU 2000; BuA ERPs D,Y,B scales; B 1/rev none; Along, Along 1/rev accelerations noneE+M: umbra & penumbra applied + IR GFZ IAU 2000; GFZ ERPs D,Y scales@ 12:00 + constraints yaw rates estimated E: umbra & penumbra none GRGS (new) IAU 2000; C04 + BuA ERPs D,Y,B scales; D,B 1/rev none E+M: umbra & penumbra applied + IR JPL IAU 1980; BuB ERPs → BuA X,Y,Z scales stochastic nonenominal yaw rates used E+M: umbra & penumbra applied MIT IAU 2000; BuA ERPs D,Y,B scales; B(D,Y) 1/rev none; 1/rev constraints nominal yaw rates used E+M: umbra & penumbra none NGS IAU 2000; IGS PM; BuA UT1 D,Y,B scales; B 1/rev @ 12:00 + constraints none; delete eclipse data E+M: umbra & penumbra none PDR (Repro) IAU 2000; BuA ERPs D,Y,B scales; B 1/rev every 12 hr + constraints noneE+M: umbra & penumbra none SIO IAU 2000; BuA ERPs D,Y,B scales; D,Y,B 1/rev none; 1/rev constraints nominal yaw rates used E+M: umbra & penumbra none

15. COMPARISON OF AC TROPOSPHERE MODELS ANALYSIS CENTER METEO DATA ZENITH DELAY MAPPING FNCT GRAD MODEL ZENITH PARAMS GRAD PARAMS CODE GPTSaastamoinen dry GMF dry none2-hr contin. w/ GMF wet 24-hr NS + EW continuous EMR ECMWF 6-hr grids ECMWF dry + wet NMF dry + wet none5-min stochastic ZTD 5-min stochastic ESA GPTSaastamoinen dry GMF dry none2-hr contin. w/ GMF wet none GFZ GPTSaastamoinen dry + wet? GMF dry + wet ? none1-hr constants w/ GMF ? 24-hr NS + EW constants GRGS (new) ECMWF 6-hr grids ECMWF dry + wet Guo dry + wet none2.4-hr contin. w/ Guo dry none JPL none → GPT dry=hgt scale wet=0.1 m NMF → GMFnone5-min stochastic ZTD 5-min stochastic MIT GPTSaastamoinen dry + wet GMF dry + wet none2-hr contin. w/ GMF wet NS + EW vary linearly NGS GPTSaastamoinen dry + wet GMF dry + wet none1-hr constants w/ GMF wet NS + EW vary linearly PDR (Repro) Berg (1948) Saastamoinen dry IMF dry w/ ECMWF z200 none2-hr contin. w/ NMF wet 24-hr NS + EW continuous SIO GPTSaastamoinen dry + wet GMF dry + wet none2-hr contin. w/ GMF wet NS +EW vary linearly

16. Conclusions Despite huge progress by IGS since 1994, numerous small systematic errors remain in products –see EGU 2008 presentation by J. Ray http://www.ngs.noaa.gov/IGSWorkshop2008/docs/igs-errs_egu08.pdf Applications to cutting-edge science are currently limited –need to focus on identifying, understanding, & mitigating errors –should avoid rush to premature science conclusions –must renew basic GNSS research efforts, not just in geophysical applications –requires accurate knowledge of AC processing strategies Improvements will probably require better station installations (to reduce near-field multipath biases) & analysis upgrades –more research into field configuration effects badly needed –need better leadership to popularize lessons learned –need better cooperation & coordination between analysts & network

17. Recommendations For more robust products: –recruit new or improved IGU ACs & more IGR clock ACs –investigate improved near-RT & predicted ERPs –should IGS start (UT1 + LOD) service ? (à la Senior et al., EGU08) Reject GGOS UAW actions for: –SINEX parameter & naming extensions –piecewise, continuous segment parameterization as SINEX standard Reject rigidly standardized AC procedures & parameterizations –would lead to stagnation & end of progress –would eliminate basis for multi-solution product combinations –but ACs must agree on conventional choices & use of modern models Instead, set up inter-service SINEX & combinations WG –investigate technique-specific systematic errors –maintain SINEX format

18. Recommendations (cont’d) Updated AC summaries are required: –EMR23 Jan 2002 –GFZ27 Feb 2003 –JPL13 Apr 2004 –SIO31 Oct 2005 –(USNO12 Sep 2006) Suggest suspending ACs with no updates by 30 Sep 2008 –if processing summary is older than 2 years –submissions would be rejected from IGS products after Sep 2008 Rescind AC status if no updates by 31 Dec 2008 –would need to formally rejoin IGS ACs after Dec 2008 Or ask above ACs for effective alternative proposal

19. Backup Slides 1

20. A SURVEY OF SOME SYSTEMATIC ERRORS IN IGS PRODUCTS Jim Ray, NOAA/National Geodetic Survey Clock jumps at day boundaries & near-field multipath Position time series show N * 1.04 cpy harmonics N/S distortions in IGS frames Earth rotation parameters smoothed & filtered Spurious tidal lines in EOPs Orbit discontinuities have fortnightly variations EGU 2008 General Assembly, Paper G4 #A-01694, Vienna, 15 April 2008

21. Context GPS errors are propagated formally but true data noise is unknown –highly site-dependent & not white noise –e.g., variances of AC frame solutions differ by > x 100 dealt with by empirical rescaling of covariance matrix Evidence for systematic effects in IGS product covariances is well known –e.g., user velocity errors are routinely inflated to account for temporal correlation of position errors but methods are purely empirical Objective: Survey systematic errors in some IGS product values –underlying causes mostly unknown or not confirmed

22. 1) Day-boundary Clock Jumps clock bias accuracy is based on mean of code data per arc for 24-hr arc with code σ = 1 m, clock accuracy should be ~120 ps can study local code biases via clock jumps at day boundaries (H-maser stations only) observed clock jumps vary hugely among stations: 110 ps to >1500 ps presumably caused mainly by local code multipath conditions, esp. in near-field of antenna

23. Near-field Multipath Mechanism expect largest & longest-period MP errors when height H of antenna is small [Elósegui et al., 1995] may have special problems when H is near multiples of λ/4 reflected RCP GPS signals enter from behind as LCP choke-ring design esp sensitive to L2 reflections from below [Byun et al. 2002] most IGS RF antennas mounted over flat surfaces!

24. Correlated Clock & Position Effects: ALGO ALGO day-boundary clock jumps increase in winters every winter ALGO also has large position anomalies –IGS deletes outliers >5 σ implies common near-field multipath effect is likely (phase & code)

25. Probably better to mount antennas away from close reflecting surfaces! worse better

26. Other Hardware Choices Also Important receiver health, firmware, antenna model, & cables also affect day-boundary clock jumps Rogue SNR-8000 receiverAshtech UZ-12 receiver AOA firmware 3.2.32.8 3.2.32.11 AOA D/M_T antenna ASH701945E_M antenna + new cables PIE1

27. 2) Stacked/Smoothed Spectra of Site Residuals for 167 IGS sites with >200 weekly points in 1996.0 – 2006.0 large annual + semi-annual variations plus harmonics in all components at N * (1.040 ± 0.008) cpy flicker noise spectra down to periods of ~few months (shifted)

28. Position Harmonics Linked to GPS Year 1.040 ± 0.008 cpy fundamental does not match any expected alias or geophysical frequency –also not seen in VLBI, SLR, or fluid load spectra Closely matches GPS “draconitic” year –rotation period of Sun w.r.t. GPS nodes (viewed from Earth) –GPS nodal drift is -14.16° per year (due to Earth’s oblateness) –period = 351.4 day or frequency = 1.039 cpy Two possible coupling mechanisms suggested: 1) direct orbit modeling errors (e.g., related to eclipse periods & planes) 2) alias of site position biases (e.g., near-field phase multipath) due to beating of 24-hr processing arc against 23.93-hr GPS repeat period –useful distinguishing tests not yet made

29. 3) N/S Distortions of IGS Frames N E U Weekly mean biases of IGS frames compared to long-term frame

30. IGS Frame Distortions N/S mean component of IGS weekly frames shows largest annual variation –after weekly 7-parameter Helmert alignment –also largest dispersion among ACs in N/S direction Not likely to be caused by annual inter-hemisphere fluid load cycle –load signal should be largest in heights, not N/S Could possibly be related to along-track GPS orbit errors –but no mechanism identified Likelier explanation: possible neglected 2 nd order ionospheric effect

31. 4) High-frequency Smoothing of EOPs Day-boundary continuity constraint by some ACs smoothes & filters EOP estimates near Nyquist limit

32. Filter/Smoother by Continuity Constraints Some ACs estimate EOPs (& others) by continuous linear segments –attenuates power by factor 4 at Nyquist limit –smoothes estimates –filters certain phase components To avoid contaminating IGS combination, such EOP solutions rejected since January 2008 (wk 1460) –but effects on other parameters probably still present Past high-frequency studies should be reconsidered Can use GFZ polar motion to estimate background, non-tidal, sub-daily variance: 13.6 to 20.7 μas 2

33. 5) Aliased Tidal Peaks in EOP Discontinuities Spectra of polar motion day-boundary discontinuities show signatures of aliased O1, Q1, & N2 tides + unknown 7.2 d line Peaks in PM Differences AC14 d9 d7 d EMR PM-x ± 14.2 0.2 9.35 0.09 7.18 0.05 EMR PM-y ± 14.1 0.2 9.6 & 9.0 0.1 7.16 0.05 GFZ PM-x ± 14.2 0.2 9.4 0.1 7.21 0.05 GFZ PM-y ± 14.2 0.2 9.6 & 8.9 0.1 7.14 0.05 JPL PM-x ± 14.2 0.2 9.4 0.1 7.23 0.05 JPL PM-y ± 14.2 0.2 9.2 0.1 7.26 0.05

34. 6) Day-boundary Orbit Discontinuities Orbit discontinuities between days show temporally correlated errors & broad fortnightly spectral peak

35. Conclusions Despite huge progress by IGS since 1994, numerous small systematic errors remain in products Applications to cutting-edge science must recognize limitations –need to focus on identifying, understanding, & mitigating errors –must renew basic GNSS research efforts, not just in geophysical applications –should avoid rush to premature science conclusions Improvements will probably require better station installations (to reduce near-field multipath) & analysis upgrades –more research into field configuration effects badly needed –need better leadership to popularize lessons learned –need better cooperation & coordination between analysts & network