Filling the data gaps within GRACE missions using Singular Spectrum Analysis

Abstract:

Dozens of missing epochs in the monthly gravity product of the satellite mission Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) mission greatly inhibit the complete analysis and full utilization of the data. 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, demonstrating effective suppression of noise. As a result, our approach can reduce noise in the oceans without sacrificing resolutions on land. The performance of our approach is exhibited through examples of both time series and maps, and its limitations are discussed as well. The gap-filling result outperforms the Swarm product in terms of data quality and consistency with the GRACE/GRACE-FO product. This study makes a ready-to-use gap-filling product together with proper error estimates available.