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Regularization and error characterization of GRACE mascons.

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A new NASA GSFC mascon solution from GRACE data improves gravity field modeling. This method accurately quantices mass changes and sea level budgets, incorporating leakage errors for precise uncertainty assessments.

Keywords:
GRACEestimator biasmasconsmodel resolutionrange-accelerationregularizationtime-variable gravity

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Area of Science:

  • Geodesy
  • Earth Science
  • Climate Science

Background:

  • Accurate estimation of Earth's time-variable gravity field is crucial for understanding mass transport.
  • The Gravity Recovery and Climate Experiment (GRACE) mission provides essential data for monitoring these changes.
  • Previous mascon solutions faced challenges with regularization biases and accurate uncertainty quantification.

Purpose of the Study:

  • To develop a novel global time-variable gravity mascon solution using GRACE Level 1B data.
  • To improve the accuracy of mass change estimates and sea level budget closure.
  • To provide a robust method for quantifying mascon uncertainties, including leakage errors.

Main Methods:

  • Utilized an iterative solution strategy with geographical binning of inter-satellite range-acceleration residuals.
  • Developed time-dependent regularization matrices for mascon parameter inversion.
  • Reprocessed GRACE Level 1B data to generate post-fit residuals for convergence confirmation and uncertainty validation.
  • Derived leakage errors from monthly resolution operators for total uncertainty assessment.

Main Results:

  • Introduced a new NASA Goddard Space Flight Center (GSFC) mascon solution with improved accuracy.
  • Demonstrated that regularized mascon solutions are biased and quantified this leakage error.
  • Presented a method to compute total uncertainty for individual mascons and regional analyses.
  • Validated the new solution against independent mascon products and calibrated Stokes uncertainties.

Conclusions:

  • The new GSFC mascon solution accurately captures global mass trends and annual amplitudes.
  • The method successfully closes the global mean sea level budget by reconciling ocean mass, steric component, and altimetry data.
  • Updated trends for the global ocean, ice sheets, and terrestrial water storage were computed, highlighting the utility of the new product.