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Reprocessing GPS data at the observation level for tide gauge monitoring: G. Wöppelmann, Tilo Schöne IGS Analysis Center Workshop 2008, 2-6 June 2008,

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Presentation on theme: "Reprocessing GPS data at the observation level for tide gauge monitoring: G. Wöppelmann, Tilo Schöne IGS Analysis Center Workshop 2008, 2-6 June 2008,"— Presentation transcript:

1 Reprocessing GPS data at the observation level for tide gauge monitoring: G. Wöppelmann, Tilo Schöne IGS Analysis Center Workshop 2008, 2-6 June 2008, Miami Beach, Florida, USA Main “raison d’être” of TIGA

2 I. What are the sea-level applications requirements? II. The TIGA Pilot Project III. An example: Reprocessing Strategy at ULR IV. Some important issues to do with cGPS@TG V. Outlooks Overview

3 IPCC (2007) 1.1 mm/yr 1.8 mm/yr IPCC (2001) Sum of climatic contributions to sea level rise: ~0.7mm/yr “Sea-level enigma” (Munk 2002) Analyses of tide gauge records ~1.5mm/yr I. Long term sea level trends WRCP Workshop in 2006  Reducing uncertainties in past and present sea level rise…

4  Vertical land motion at tide gauges →Stockholm : Post-glacial rebound →Nezugaseki : 1964 earthquake →Bangkok : Ground water pumping →Manila : Sedimentation “Important issues to do with long term sea level trends” ( e.g. Woodworth 2006, in Phil. Trans. R. Soc. )  Motivation for GPS reprocessing →To use the best available data and most accurate models to reduce errors in the estimates of coordinates →To use them all over the data span (models, parameterization…) in order to derive consistent sets of station coordinates, and to limit spurious signals in their time series  Challenges →Rates in sea-level change: ~1-2 mm/yr →Standard errors several times smaller to be useful in these studies! (Glacial isostatic adjustment) (Co-seismic displacement) (Groundwater extraction) (Sedimentation) (No evidence of land motion)

5  4 closest passes to the tide gauge (Ǿ<160km)  Closest points to the tide gauges over each pass, with valid SLA content: 70% of valid values w.r.t. the total # of cycles  Altimetric data  Tide gauge data  Time series > 2 years  Interpolation at the epoch of altimetric pass  Data editing (Mitchum 2000) I… Radar altimetry calibration  Minimum correlation: 0.3 (SLA Alt / TG)  Maximum RMS differnces: 100mm

6  “Tide Gauge Benchmark Monitoring”  103 TOS, 2 TDC, 6 TAC, TAAC (?)  Goals  Establish, maintain and expand a global cGPS@TG network  Compute precise station parameters for the cGPS@TG stations with a high latency  Reprocess all previously collected GPS data, if possible back to 1993  Promote the establishment of links to other geodetic sites (DORIS, SLR, VLBI,… AG) (Initiated in 2001, on a best-effort basis) http://adsc.gfz-potsdam.de/tiga/index_TIGA.html II. The TIGA pilot project ETG AUT DGF GFT CTA ULR

7  Total # of GPS stations: 225  IGS05 stations: 91  Time span: 1997.0 - 2006.9  205 time series > 3.5 years  160 are co-located with TG  90 CGPS@TG are not IGS III. An example: ULR Analysis Centre

8 III… Reprocessing analysis strategy at ULR Stacking of the weekly station coordinate solutions using Altamimi et al. (2002, 2007) approach published in JGR. OUTPUTS  station positions and velocities at t 0 (2001/346), as well as,  time series of post-fit residuals (station coordinates),  time series of transformation parameters, between each weekly solution and the final stacked one  discontinuities estimates (iterative procedure to detect outliers and discontinuities)

9 III… GPS velocities at TG... How well do they work? For details: Wöppelmann et al. Poster to be displayed Thursday… also, paper published in Global and Planetary Change (2007) ICE5Gv1.2 + VM4 models (Peltier 2004)

10 Table1 from Wöppelmann et al. 2007 (Glob. Planet. Change) 1.28 ± 1.341.69 ± 1.491.56 ± 2.05 ITRF2000 1999.0-2005.7 6.7 years

11 Updated from our recent GPS re-analysis 1.28 ± 1.341.69 ± 1.49 1.37 ± 1.25 1.68 ± 1.15 New uncertainties

12  Working hypotheses 1. Land movements are linear over the tide gauge records length 2. GPS antenna vertical movement  Tide gauge land movement  Some examples… IV. Some important issues to do with cGPS@TG  Local land motion monitoring (stability)  geodetic link between GPS antenna and TGBM  ancillary local information (equipment changes, topography…) specially, if the GPS was not installed for sea level studies!  Leadership issue raised at EGU 2008, Vienna.

13 IV… Assessing the quality of the GPS results VERTICAL -0.75  0.01 -0.64  0.01  75 GPS stations in common with > 200 weekly points over the 1997.0-2006.0 period  Lomb-Scargle periodogram (Press et al. 2001)  Normalized spectra stacked and filtered following Ray et al. (2008) approach (annual and semi-annual fits have been removed prior to spectra computation) Stacked periodograms for filtered GPS position time series

14 -0.48  0.01 -0.71  0.01 EAST Stacked periodograms for filtered GPS position time series IV… Assessing the quality of our GPS results  75 GPS stations in common with > 200 weekly points over the 1997.0-2006.0 period  Lomb-Scargle periodogram (Press et al. 2001)  Normalized spectra stacked and filtered following Ray et al. (2008) approach (annual and semi-annual fits have been removed prior to spectra computation)

15 NORTH -0.58  0.01 -0.70  0.01 Stacked periodograms for filtered GPS position time series IV… Assessing the quality of our GPS results Detection of anomalous harmonics… (Ray et al. 2008)

16 ITRF2000 versus ITRF2005 Impact on the vertical velocities… Which reference frame? IV. Some important issues to do with cGPS@TG TG+GPS (mm/yr)TG-GIA SolutionGPS 1 ITRF2000 1999.0-2005.7 GPS 2 ITRF2000 1997.0-2006.9 GPS 3 ITRF2005 1997.0-2006.9 Sea level trends scatter 1.341.251.151.49 Global Sea level trend 1.31±0.301.38±0.281.56±0.191.83±0.21 Summary of the long-term sea level trend study Douglas & Peltier (2001): 1.84  0.35mm/yr it05 it00 

17 Impact on vertical velocities: using ITRF2005 datum or ITRF2000 IV… ITRF2000 versus ITRF2005 datum

18 -0.1 ± 0.2 -0.3 ± 0.2 -0.8 ± 0.2 0.5 ± 0.2 -8.1 ± 0.2 -1.7 ± 0.2 0.89 ± 0.03 0.13 ± 0.03 -0.041±0.007 -0.004±0.007 0.023±0.007 -0.003±0.007 -0.052±0.008 -0.010±0.008 Transformation parameters estimated from our GPS solutions (ITRF2005 → ITRF2000) ~ 0.83 mm/yr IV… ITRF2000 versus ITRF2005 datum

19 IV… Vertical land motion to be interpreted Inferred from PSMSL (2005) and Holgate & Woodworth (2004) Shennan & Horton (2002)

20 Promising scientific results Combined TIGA solution pending (provided soon…).  Reprocessing with absolute PCV ongoing  Volunteers for combination analyses needed Trying to secure long(er)-term funding for processing and combination  So far best-effort basis Efforts are needed for meta-data information (e.g. leveling between benchmarks and TG zero)  Leadership issue… Need for a more robust and stable ITRF  Current accuracy: 1-2 mm/yr origin, 0.1 ppb/yr scale  Target accuracy: 0.1 mm/yr origin, 0.01 ppb/yr scale V. Conclusions and Outlooks

21 Current (103) and potential (300) cGPS@TG stations Towards an improved reprocessing (VMF1,…) Upgrade the reprocessing capabilities (1 year  1 week) Potential for 300 cGPS@TG  Access to data and meta-data  Clustering in populated areas

22 Thank you for your attention ! View of La Rochelle

23 d’après Altamimi et al. (2007)

24 Inputs :  Weekly solutions (…) X(t s ) – SINEX files (Each individual solution defines its own reference frame...) Model : Outputs :  Combined solution : positions X itrf (t 0 ), and velocities  Time series of transformation parameters between each individual solution and the combined one (T x, T y, T z, D, R x, R y, R z )  Time series of post-fit residuals (station coordinates…) The reference frame is defined by applying minimal constraints Model implemented in CATREF (Altamimi, 2004) Stacking of weekly GPS solutions in SINEX format

25 Transformation parameters between each weekly solution and the combined one expressed in ITRF2000 or ITRF2005

26  Many geophysical phenomena can be described using a power-law process of the form (Agnew, 1992):  : spectral index.  = 0 White Noise (WN);  =-1 Flicker Noise (FN);  =-2, Random Walk Noise (RWN)  Methods:  MLE, Maximum Likelihood Estimation e.g. Williams et al. (2003, 2004,…)  SPECTRAL ANALYSIS e.g. Zhang et al. (1997), Mao et al. (1999)  ALLAN VARIANCE Stability of atomic clocks, e.g. Allan (1966) Method adapted to geodetic data, e.g. Le-Bail (2006), Feissel-Vernier et al. (2007) Noise in GPS position time series Motivation: Compute realistic uncertainties on GPS velocities. Zhang et al. (1997):

27  Very preliminary results… to be confirmed and further investigated  Comparable drifts for Jason-1, T/P and GFO missions →Drifts between 0.5 - 1.0 mm/yr without land motion correction →Drifts closer to 0 mm/yr with GPS-derived corrections from GPC solution.  Only Envisat still shows a significant drift Other altimetry missions… Without GPS-velocities corrections With GPS-velocities corrections


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