Publications related to the GRACE Missions (no abstracts)

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Decomposition-based reconstruction scheme for GRACE data with irregular temporal intervals

Yuan, Ze and Chen, Xiaohong, 2025. Decomposition-based reconstruction scheme for GRACE data with irregular temporal intervals. Journal of Hydrology, 662:134011, doi:10.1016/j.jhydrol.2025.134011.

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@ARTICLE{2025JHyd..66234011Y,
       author = {{Yuan}, Ze and {Chen}, Xiaohong},
        title = "{Decomposition-based reconstruction scheme for GRACE data with irregular temporal intervals}",
      journal = {Journal of Hydrology},
     keywords = {GRACE, Irregular temporal intervals, Decomposition-based reconstruction, Daily scale lag calibration},
         year = 2025,
        month = dec,
       volume = {662},
          eid = {134011},
        pages = {134011},
     abstract = "{Irregular temporal intervals (ITI) in the Gravity Recovery and Climate
        Experiment (GRACE) data, caused by mission gaps and incomplete
        monthly sampling, introduce uncertainties into hydrological
        applications. This study introduces a decomposition-based
        reconstruction scheme specifically developed to preserve and
        leverage the ITI features of GRACE data for improved
        reconstruction performance. The scheme integrates multiple
        predictor processing techniques. It includes dynamic resampling
        to align predictor variables with the time bands of GRACE-
        derived terrestrial water storage anomaly (TWSA) products. It
        also incorporates an improved signal decomposition algorithm
        tailored for ITI series, a daily-scale lag correction to enhance
        temporal alignment, and exponential decay filtering to suppress
        high-frequency noise in precipitation inputs. Using data from 95
        Mascon grids in southern China, the proposed approach improves
        median PCC by 5 \%, NSE by 22 \%, and reduces RMSE by 12 \%
        compared to baseline schemes that disregard ITI. Reconstruction
        uncertainty is also reduced by 56 \% (trend), 178 \% (seasonal),
        and 12 \% (subseasonal) compared to baseline schemes. Further
        comparison across multiple schemes confirms the method's
        robustness. The results highlight the effectiveness and
        generalizability of ITI-aware modeling, offering a practical
        solution for GRACE-based hydrological studies under irregular
        temporal sampling conditions.}",
          doi = {10.1016/j.jhydrol.2025.134011},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2025JHyd..66234011Y},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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