Publications related to the GRACE Missions (no abstracts)

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A novel Hankel spectrum analysis filtering for reducing North-South stripes in GRACE gravity solutions

Zhou, Hao, Li, Liexing, Hu, Hanwen, Xue, Haoran, Li, Hong, Liu, Yuelong, and Luo, Zhicai, 2026. A novel Hankel spectrum analysis filtering for reducing North-South stripes in GRACE gravity solutions. Journal of Hydrology, 664:134602, doi:10.1016/j.jhydrol.2025.134602.

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@ARTICLE{2026JHyd..66434602Z,
       author = {{Zhou}, Hao and {Li}, Liexing and {Hu}, Hanwen and {Xue}, Haoran and {Li}, Hong and {Liu}, Yuelong and {Luo}, Zhicai},
        title = "{A novel Hankel spectrum analysis filtering for reducing North-South stripes in GRACE gravity solutions}",
      journal = {Journal of Hydrology},
     keywords = {Terrestrial water storage anomaly, GRACE, North-south striping error, Hankel spectrum analysis filtering, Basin analysis},
         year = 2026,
        month = jan,
       volume = {664},
          eid = {134602},
        pages = {134602},
     abstract = "{North-south striping (NSS) noise remains a significant challenge in
        spherical harmonic coefficient (SHC) solutions derived from
        Gravity Recovery and Climate Experiment (GRACE) and GRACE
        Follow-On (GRACE-FO) mission, thereby limiting their application
        in tracking terrestrial water storage variations. In this study,
        we propose a novel filtering framework, Hankel Spectrum Analysis
        Filtering (HSAF), to decompose GRACE-derived terrestrial water
        storage anomalies into orthogonal modal components. HSAF enables
        localized signal reconstruction through dual singular value
        decomposition and adaptive windowing, explicitly separating
        high-frequency NSS noise without much need for empirical
        parameter tuning, improving the accuracy of the derived water
        storage estimates. Validation using both synthetic datasets and
        real GRACE solutions demonstrates that: (1) HSAF effectively
        reduces striping artifacts while accurately preserving
        hydrological signals. (2) HSAF yields higher correlation, lower
        residual errors, and improved signal fidelity compared to
        conventional filters across a range of global and basin scale
        statistical metrics;(3) Using an expanded set of 112 global
        river basins, HSAF lowers basin-scale RMSE to an average of 1.65
        cm, delivering a mean reduction of 22 \% relative to Gaussian
        smoothing and outperforming conventional filters in 50 \% of the
        basins examined. (4) For Caspian Sea, the leakage-corrected HSAF
        series achieves an RMSE of 6.09 cm ─ 34 \% and 44 \% lower than
        Gaussian and DDK4, respectively ─ and reproduces an annual
        amplitude of 18.34 cm and a trend of {\ensuremath{-}}9.01 cm
        yr$^{{\ensuremath{-}}1}$, both closest to satellite-altimetry
        observations. The results demonstrate the effectiveness of our
        proposed HSAF in processing inherent NSS noise within GRACE-type
        SHC solutions, making it a versatile tool applicable to various
        geo-science applications.}",
          doi = {10.1016/j.jhydrol.2025.134602},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026JHyd..66434602Z},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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