Signal and noise in Gravity Recovery and Climate Experiment (GRACE) observed surface mass variations

• Published in: Journal of Geophysical Research
• Main Authors: Schrama, E.J.O. (author), Wouters, B. (author), Lavallée, D.A. (author)
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union 2007
• Subjects: GRACE; temporary gravity; spherical harmonics; error analysis; empirical orthogonal functions; GPS; Ice Sheet
• Online Access: https://doi.org/10.1029/2006JB004882; http://resolver.tudelft.nl/uuid:96f4f149-de9f-451f-9a69-b9d66e4704a2

The Gravity Recovery and Climate Experiment (GRACE) product used for this study consists of 43 monthly potential coefficient sets released by the GRACE science team which are used to generate surface mass thickness grids expressed as equivalent water heights (EQWHs). We optimized both the smoothing radius and the level of approximation by empirical orthogonal functions (EOFs) and found that 6.25° and three modes are able to describe more than 73.5% of the variance. The EQWHs obtained by the EOF method describe all known variations in the continental hydrology, present?day ice sheet melting, and global isostatic adjustment. To assess the quality of the estimated grids, we constructed degree error spectra of EQWHs. We conclude that a significant part of the errors in GRACE can be explained by a scaling factor of 0.85 relative to degree error estimates provided by the GGM02C gravity model but that the present?day errors in the GRACE data are a factor 2 to 5 larger than forecasted by tide model differences and atmospheric pressure differences. Comparison to a network of 59 International GNSS Service (IGS) stations confined the filter parameter settings to three EOF modes and 5° or 6.25° smoothing radius. Residuals that remain after the EOF method do exhibit S2 aliasing errors and a semiannual continental hydrology signal contained in the Global Land Data Assimilation Systems (GLDAS) model. Further analysis of the residual EOF signal revealed alternating track correlation patterns that are partially explained by the GRACE covariance matrix and the handling of nuisance parameters in the GRACE data processing. Space Engineering Aerospace Engineering