Analysis of Seasonal Signals in GPS Position Time Series.ppt

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1、Analysis of Seasonal Signals in GPS Position Time Series,Peng Fang Scripps Institution of Oceanography University of California, San Diego, USA,Toulouse Workshop, Sept. 2002 CGPSTG Working Group,Credit,Anatomy of apparent seasonal variations from GPS-derived site position time series, JGR Vol. 107,

2、No. B4, ETG 9-1, 2002D. Dong, JPL, California Inst. of Technology, Pasadena, USA P. Fang, IGPP, SIO, Univ. of Calif. San Diego, La Jolla, USA Y. Bock, IGPP, SIO, Univ. of Calif. San Diego, La Jolla, USA M. K. Cheng, CSR, Univ. of Texas Austin, Austin, USA S. Miyazaki, Earthquake Res. Inst., Univ. of

3、 Tokyo, Tokyo, Japan,OUTLINE,Signal Categorization Data Processing Analysis Verification Discussion and Summary,I. Gravitational excitation,Rotational displacements due to seasonal polar motion Universal time corrected for polar motion (UT1) variation Loading induced displacement due to solid Earth

4、tides, ocean tides, and atmospheric tides Pole tide,II. Thermal origin coupled with hydrodynamics,Atmospheric pressure, non-tidal sea surface fluctuations, and ground water (liquid and solid) Thermal expansion of bedrock, and wind shear,III. Various errors,Satellite orbital models, atmospheric model

5、s, water vapor distribution models, phase center variation models, thermal noise of the antenna, local multi-path, and snow cover on the antenna,Data,Long observation history (4.5 year time span starting from 1996) Good geographical distribution,128 (out of 429 total) high quality sites are selected

6、 for the final analysis,Processing,Orbit/EOP tightly constrained ITRF reference frame used Distributed mode (subnetworks) Tropospheric delay estimated Antenna phase center corrected Solid Earth tide removed GAMIT/Globk software,Analysis,Parameters for each component at each site with t0 = 1996.0: Bi

7、as Velocity Aannualsin(w(t-t0) + fannual) Asemiannualsin(w(t-t0) + fsemiannual),Offsets due to earthquake or instrument setup change are treated separately,Resulting Time Series,Vertical: 4-10mm formal error 1mm Horizontal: 1-3mm formal error 0.5mm Annual phase (Vertical): 5-10o Annual phase (Horizo

8、ntal): 7-15o,These are typical signal range,Phases are counted counterclockwise from east Ellipses represent 95% confidence level,Seasonal Terms,Pole Tide McCarthy, 1996 dl = 9.0 cos q (xp sin l + yp cos l) dq = -9.0 cos 2q (xp cos l - yp sin l) dr = -32.0 sin 2q (xp cos l - yp sin l),Be very carefu

9、l with the sign of dq, positive for SOUTH,q is colatitude,Seasonal Terms (Cont.),Ocean tide Scherneck, 1991 Coefficients of 11 tides (amp. & phases): M2, S2, N2, K2, K1, O1, P1, Q1, MF, MM, SSA,Mostly vertical, typically in mm range,After pole tide and ocean tide terms corrected,Seasonal Terms (Cont

10、.),Atmospheric mass loading Farrell, 1972, vanDam and Wahr, 1987 Green function approach Re-analysis of surface pressure by National Center for Environment Prediction (NCEP), 6 hour sampling Inverted barometer (IB) model ECMWF land-ocean mask model,Horizontal 0.5mm Vertical 1.0 mm typical Eurasian,

11、Arabian Peninsula 4.0 mm,Seasonal Terms (Cont.),Non-tidal ocean mass loading Interaction of surface wind, atmospheric pressure, heat and moisture exchange, hydrodynamics Time-varying ocean topography from TOPEX/Poseidon altimeter, 1x1o 10 days, Tapley, 1994 Correction term: seasonal steric variation

12、 due to salinity and temperature variations above thermocline (no contribution to mass variation). Dynamic Height -Specific volume anomaly (Gill, 1982) - WOA-94 model (Levitus and Boyer, 1994) with 19 depths.,Vertical: Typical 1mm, low latitude islands/coasts 2-3mm,Seasonal Terms (Cont.),Snow/soil m

13、oisture mass loading Snow cover/soil moisture model NCEP/DOE reanalysis (Kanamitsu et al, 1999, Roads et al, 1999) - Climate Data Assimilation System-1 reanalysis NCEP/NCAR + adjusted soil moisture from Climate Prediction Center Merged Analysis of Precipitation (CMAP) Ice/snow capped reg. treated se

14、parately,Vertical: BRAZ 7mm, most 2-3mm, island sites submm (underestimated due to model problem),After all mass loading terms corrected,Terms not counted for,Atmospheric modeling Imperfect, separate studies Bedrock thermal expansion Appendix B, 0.5mm, 45o behind Phase center & environmental factor

15、HOLP example, Hatanaka, 2001 Glacier surge & internal ice flow Alaska region, Sauber et al, 2000 Antarctica, Cazenave et al, 2000,Note: Signal may not be sinusoidal,Verification,JPL solution (GIPSY) GEONET solution (Bernese),Different data processing methods,JPL solution with all mass loading terms

16、corrected,Summary,The modeled loading and nonloading terms can explain 66% (if pole tide is included) or 42% (pole tide excluded) the observed power (mean amplitude squared). Some candidate terms for the residual signal are proposed. Impact on other related geodetic and geophysical problems are discussed.,Atmosphere (purple arrow), non-tidal ocean (red arrow), snow (green arrow) and soil wetness (blue arrow) caused vertical annual variations of site coordinates.,