Statistically optimal estimation of degree-1 and C20 coefficients based on GRACE data and an ocean bottom pressure model

Yu Sun*, Pavel Ditmar, Riccardo Riva

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

18 Citations (Scopus)
121 Downloads (Pure)

Abstract

In this study, we develop a methodology to estimate monthly variations in degree-1 andC20 coefficients by combing Gravity Recovery and Climate Experiment (GRACE) data withoceanic mass anomalies (combination approach).With respect to the method by Swenson et al.,the proposed approach exploits noise covariance information of both input data sets and thusproduces stochastically optimal solutions supplied with realistic error information. Numericalsimulations show that the quality of degree-1 and -2 coefficients may be increased in this wayby about 30 per cent in terms of RMS error.We also proved that the proposed approach can bereduced to the approach of Sun et al. provided that the GRACE data are noise-free and noise inoceanic data is white. Subsequently, we evaluate the quality of the resulting degree-1 and C20coefficients by estimating mass anomaly time-series within carefully selected validation areas,where mass transport is small. Our validation shows that, compared to selected Satellite LaserRanging (SLR) and joint inversion degree-1 solutions, the proposed combination approachbetter complementsGRACE solutions. The annual amplitude of the SLR-based C10 is probablyoverestimated by about 1 mm. The performance of the C20 coefficients, on the other hand, issimilar to that of traditionally used solution from the SLR technique.

Original languageEnglish
Article numberggx241
Pages (from-to)1305-1322
Number of pages18
JournalGeophysical Journal International
Volume210
Issue number3
DOIs
Publication statusPublished - 1 Sept 2017

Keywords

  • Geopotential theory
  • Global change from geodesy
  • Reference systems
  • Satellite geodesy
  • Satellite gravity
  • Time variable gravity

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