Detecting hydrologic deformation using GRACE and GPS

[1] Hydrological processes cause variations in gravitational potential and surface deformations, both of which are detectable using space geodetic techniques. We computed elastic deformation using continental water load estimates derived from the Gravity Recovery and Climate Experiment and compared to 3D deformation estimated from GPS observations. The agreement is very good in areas where large hydrologic signals occur over broad spatial scales, with correlation in horizontal components as high as 0.9. Agreement is also observed at smaller scales, including across Europe. This suggests that: a) both techniques are perhaps more accurate than previously thought and b) a large percentage of the non-linear variations seen in our GPS time series are most likely related to geophysical processes rather than analysis error. Low correlation at some sites suggests that local processes or site specific analysis errors dominate the GPS deformation estimates rather than the broad-scale hydrologic signals detected by GRACE.

[1]  Pedro Elosegui,et al.  Climate‐driven deformation of the solid Earth from GRACE and GPS , 2004 .

[2]  H. Schuh,et al.  Global Mapping Function (GMF): A new empirical mapping function based on numerical weather model data , 2006 .

[3]  D. Alsdorf,et al.  Seasonal fluctuations in the mass of the Amazon River system and Earth's elastic response , 2005 .

[4]  T. Herring,et al.  Introduction to GAMIT/GLOBK , 2006 .

[5]  Guillaume Ramillien,et al.  Glacial isostatic adjustment and nonstationary signals observed by GRACE , 2009 .

[6]  J. Ray,et al.  Anomalous harmonics in the spectra of GPS position estimates , 2008 .

[7]  Paul Tregoning,et al.  Atmospheric effects and spurious signals in GPS analyses , 2009 .

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

[9]  Peter J. Clarke,et al.  Choice of optimal averaging radii for temporal GRACE gravity solutions, a comparison with GPS and satellite altimetry , 2006 .

[10]  Richard D. Ray,et al.  Atmospheric pressure corrections in geodesy and oceanography: A strategy for handling air tides , 2002 .

[11]  H. Munekane Ocean mass variations from GRACE and tsunami gauges , 2007 .

[12]  K. Lambeck,et al.  GRACE estimates of sea surface height anomalies in the Gulf of Carpentaria, Australia , 2008 .

[13]  F. Bryan,et al.  Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible detection using GRACE , 1998 .

[14]  W. Farrell Deformation of the Earth by surface loads , 1972 .

[15]  O. Francis,et al.  Modelling the global ocean tides: modern insights from FES2004 , 2006 .

[16]  Jean-Charles Marty,et al.  Temporal gravity field models inferred from GRACE data , 2007 .

[17]  Thomas A. Herring,et al.  Impact of a priori zenith hydrostatic delay errors on GPS estimates of station heights and zenith total delays , 2006 .

[18]  Florent Lyard,et al.  Modeling the barotropic response of the global ocean to atmospheric wind and pressure forcing ‐ comparisons with observations , 2003 .

[19]  Paul Tregoning,et al.  Impact of solid Earth tide models on GPS coordinate and tropospheric time series , 2006 .

[20]  Mike P. Stewart,et al.  GPS height time series: Short‐period origins of spurious long‐period signals , 2007 .

[21]  S. Pagiatakis The response of a realistic earth to ocean tide loading , 1990 .

[22]  M. Watkins,et al.  The gravity recovery and climate experiment: Mission overview and early results , 2004 .

[23]  H. Schuh,et al.  Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium‐Range Weather Forecasts operational analysis data , 2006 .