HR: 0800h
AN: G21B-0493 INVITED    [Abstracts]
TI: Empirically-Derived Estimates of Glacial Isostatic Adjustment
AU: * Tamisiea, M E
EM: mtam@pol.ac.uk
AF: Proudman Oceanographic Laboratory, 6 Brownlow Street, Liverpool, L7 7AZ, United Kingdom
AU: Davis, J L
EM: jdavis@cfa.harvard.edu
AF: Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138, United States
AU: Hill, E M
EM: ehill@cfa.harvard.edu
AF: Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138, United States
AU: Latychev, K
EM: latychev@physics.utoronto.ca
AF: Department of Physics, University of Toronto, 60 St. George Street, Toronto, ON M5S 1A7, Canada
AB: Generating numerical predictions of glacial isostatic adjustment (GIA) in North America is complicated by difficulties associated with constraining the full history of the ice sheet, as well as the 3D variations of mantle viscosity and lithospheric structure, with limited sets of observations. Moreover, many GIA predictions are calculated with spherically-symmetric Earth models, which may fail to capture the full range of possible crustal motions. However, most geodetic applications only require accurate estimates of the present-day variations in crustal displacement and gravity associated with GIA. Thus, Davis et al., 2006, developed a data assimilation technique to obtain a present-day estimate of GIA. The technique combines GPS and GRACE observations with the covariance of these signals derived from a set of forward model predictions. This approach has the advantage of allowing the data to improve the GIA estimate without having to associate these results with changes in input ice-sheet history and viscosity structure, which may be inadequate due to model limitations to describe the actual motions. To examine the robustness of the solutions resulting from this technique, we investigate the impact of the starting model used in the determination of the model covariances. In addition, we explore sampling issues and the ability to recover motions caused by lateral Earth structure by using input from a 3D numerical Earth model prediction sampled in the same manner as the GPS and GRACE inputs.
DE: 1213 Earth's interior: dynamics (1507, 7207, 7208, 8115, 8120)
DE: 1217 Time variable gravity (7223, 7230)
DE: 1229 Reference systems
DE: 1295 Integrations of techniques
SC: Geodesy [G]
MN: 2007 Fall Meeting