Publications related to the GRACE Missions (no abstracts)

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Bridging the Terrestrial Water Storage Anomalies between the GRACE/GRACE-FO Gap Using BEAST + GMDH Algorithm

Qian, Nijia, Gao, Jingxiang, Li, Zengke, Yan, Zhaojin, Feng, Yong, Yan, Zhengwen, and Yang, Liu, 2024. Bridging the Terrestrial Water Storage Anomalies between the GRACE/GRACE-FO Gap Using BEAST + GMDH Algorithm. Remote Sensing, 16(19):3693, doi:10.3390/rs16193693.

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@ARTICLE{2024RemS...16.3693Q,
       author = {{Qian}, Nijia and {Gao}, Jingxiang and {Li}, Zengke and {Yan}, Zhaojin and {Feng}, Yong and {Yan}, Zhengwen and {Yang}, Liu},
        title = "{Bridging the Terrestrial Water Storage Anomalies between the GRACE/GRACE-FO Gap Using BEAST + GMDH Algorithm}",
      journal = {Remote Sensing},
     keywords = {GRACE, GRACE-FO, gap filling, piecewise detrending, data-driven, terrestrial water storage anomalies (TWSAs)},
         year = 2024,
        month = oct,
       volume = {16},
       number = {19},
          eid = {3693},
        pages = {3693},
     abstract = "{Regarding the terrestrial water storage anomaly (TWSA) gap between the
        Gravity Recovery and Climate Experiment (GRACE) and GRACE
        Follow-on (-FO) gravity satellite missions, a BEAST (Bayesian
        estimator of abrupt change, seasonal change and trend)+GMDH
        (group method of data handling) gap-filling scheme driven by
        hydrological and meteorological data is proposed. Considering
        these driving data usually cannot fully capture the trend
        changes of the TWSA time series, we propose first to use the
        BEAST algorithm to perform piecewise linear detrending for the
        TWSA series and then fill the gap of the detrended series using
        the GMDH algorithm. The complete gap-filling TWSAs can be
        readily obtained after adding back the previously removed
        piecewise trend. By comparing the simulated gap filled by BEAST
        + GMDH using Multiple Linear Regression and Singular Spectrum
        Analysis with reference values, the results show that the BEAST
        + GMDH scheme is superior to the latter two in terms of the
        correlation coefficient, Nash-efficiency coefficient, and root-
        mean-square error. The real GRACE/GFO gap filled by BEAST + GMDH
        is consistent with those from hydrological models, Swarm TWSAs,
        and other literature regarding spatial distribution patterns.
        The correlation coefficients there between are, respectively,
        above 0.90, 0.80, and 0.90 in most of the global river basins.}",
          doi = {10.3390/rs16193693},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2024RemS...16.3693Q},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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