Mon Dec 15, F. Flechtner
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Peng, Zhenran, Wang, Linsong, Du, Jinsong, and Chen, Chao, 2025. Stepwise iterative enhanced destriping of GRACE/GRACE-FO data for improving global water mass estimation. Geophysical Journal International, 243(1):ggaf336, doi:10.1093/gji/ggaf336.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025GeoJI.243..336P,
author = {{Peng}, Zhenran and {Wang}, Linsong and {Du}, Jinsong and {Chen}, Chao},
title = "{Stepwise iterative enhanced destriping of GRACE/GRACE-FO data for improving global water mass estimation}",
journal = {Geophysical Journal International},
keywords = {Satellite geodesy, Satellite gravity, Time variable gravity, Spatial analysis},
year = 2025,
month = oct,
volume = {243},
number = {1},
eid = {ggaf336},
pages = {ggaf336},
abstract = "{The time-variable gravity field obtained from the Gravity Recovery and
Climate Experiment/Follow-On (GRACE/GRACE-FO) satellites has
been successfully used to detect global water mass changes over
the past two decades. However, the north{\textendash}south
striping noise in the GRACE spherical harmonic (SH) solution
limits their effectiveness. Efforts to suppress this noise and
achieve a higher signal-to-noise ratio (SNR) continue with
various product releases, but there is still a great need for
improvement. This study presents a new destriping method,
Gaussian filtering combined with bi-dimensional variational mode
decomposition (GBVMD), which employs a stepwise enhancing
framework combining Gaussian filtering with bi-dimensional
variational mode decomposition (BVMD). The methodological
breakthrough comes from two innovations: First, it employs
adaptive scale decomposition by dynamically adjusting the radius
of the Gaussian filter in conjunction with BVMD reconstruction,
effectively reducing noise across multiple scales. Second, it
features a dual-decision optimization strategy that integrates
SNR-driven mode reconstruction and iterative termination,
thereby maximizing the SNR while adapting to the specific
characteristics of the noise. In simulations, the GBVMD
outperforms the five other filters in reducing noise and keeping
signals, achieving an improvement in SNR by at least 19 per
cent, and reductions in root mean square error and mean absolute
error by at least 14 and 11 per cent, respectively. When applied
to GRACE/GRACE-FO Level-2 SH solutions, GBVMD led to a higher
SNR with an improvement of at least 12 per cent compared to
other filters. The GBVMD-filtered SH data showed strong
consistency with three Level-3 Mascon solutions across 183 river
basins. Comparable results were also found in polar regions,
validated by altimetry data. Furthermore, we effectively
corrected the leakage errors for two examples in the Caspian Sea
and the Great Lakes, demonstrating the advantages of GBVMD-
filtered SH over the Mascons for signal re-analysis. We
recommend GBVMD for further applications, especially in specific
regions such as ocean areas and other satellite missions
requiring similar destriping approaches.}",
doi = {10.1093/gji/ggaf336},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025GeoJI.243..336P},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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Mon Dec 15, F. Flechtner