Data for: Filling the data gaps within GRACE missions using Singular Spectrum Analysis

Despite previous attempts to handle this problem, a general all-purpose gap-filling solution is still lacking. Here we propose a non-parametric, data-adaptive and easy-to-implement approach - composed of the Singular Spectrum Analysis (SSA) gap-filling technique, cross-validation, and spectral testing for significant components - to produce reasonable gap-filling results in the form of spherical harmonic coefficients (SHCs).

We demonstrate that this approach is adept at inferring missing data from long-term and oscillatory changes extracted from available observations. A comparison in the spectral domain reveals that the gap-filling result resembles the product of GRACE missions below spherical harmonic degree 30 very well. As the degree increases above 30, the amplitude per degree of the gap-filling result decreases more rapidly than that of GRACE/GRACE-FO SHCs, showing effective suppression of noise.