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Data-driven gap filling and spatio-temporal filtering of the GRACE/GRACE-FO records
  • Louis-Marie Gauer,
  • Kristel Chanard,
  • Luce Fleitout
Louis-Marie Gauer

Corresponding Author:gauer@ipgp.fr

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Kristel Chanard
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Luce Fleitout
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Gravity Recovery And Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) global monthly measurements of Earth’s gravity field have led to significant advances in the quantification of mass transfer on Earth. Yet, a long temporal gap between missions prevents interpretation of long-term mass variations. Moreover, instrumental and processing errors translate into large non-physical stripes polluting geophysical signals. We use Multichannel Singular Spectrum Analysis (M-SSA) to overcome both issues by exploiting spatio-temporal information of multiple Level-2 GRACE/GRACE-FO solutions. We statistically replace missing data and outliers using iterative M-SSA on Equivalent Water Height (EWH) time series processed by CSR, GFZ, GRAZ, and JPL to form a combined evenly spaced solution. Then, M-SSA is applied to retrieve common signals between each EWH time series and its neighbours to reduce residual spatially uncorrelated noise. We develop a complementary filter, based on the residual noise between fully processed data and a parametric fit to observations, to further reduce persisting stripes. Comparing GRACE/GRACE-FO M-SSA solution with SLR low-degree Earth’s gravity field and hydrological model demonstrates its ability to statistically fill missing observations. Our solution reaches a noise level comparable to mass concentration (mascon) solutions over oceans, without requiring \textit{a priori} information or regularisation. While short-wavelength signals are hampered by filtering of spherical harmonics solutions or challenging to capture using mascon solutions, we show that our technique efficiently recovers localized mass variations using well-documented mass transfers associated with reservoir impoundments.