@COMMENT This file was generated by bib2html_grace.pl <https://sourceforge.net/projects/bib2html/> version 0.94
@COMMENT written by Patrick Riley <https://sourceforge.net/users/patstg/>
@COMMENT This file was prepared using the NASA Astrophysics Data System (ADS)
@COMMENT https://ui.adsabs.harvard.edu/
@ARTICLE{2026HESSD..30..985S,
       author = {{Springer}, Anne and {De Lannoy}, Gabri{\"e}lle and {Rodell}, Matthew and {Ewerdwalbesloh}, Yorck and {Gerdener}, Helena and {Khaki}, Mehdi and {Li}, Bailing and {Li}, Fupeng and {Schumacher}, Maike and {Tangdamrongsub}, Natthachet and {Tourian}, Mohammad J. and {Nie}, Wanshu and {Kusche}, J{\"u}rgen},
        title = "{A review of current best practices and future directions in assimilating GRACE/-FO terrestrial water storage data into numerical models}",
      journal = {Hydrology and Earth System Sciences Discussions},
         year = 2026,
        month = feb,
       volume = {30},
       number = {4},
        pages = {985-1022},
     abstract = "{Water cycle reanalyses, generated by integrating observations into
        hydrological and land surface models, provide long-term and
        consistent estimates of key water cycle components. Reanalyses
        are essential to understand hydrological variability, extreme
        events such as droughts and floods, and to improve water
        resource management. Over the past two decades, the assimilation
        of terrestrial water storage anomaly data from the GRACE and
        GRACE Follow-On (GRACE/-FO) missions has significantly enhanced
        these reanalyses, as GRACE/-FO observations uniquely constrain
        total water storage variability across all terrestrial
        compartments. Incorporating GRACE/-FO data has led to major
        advances in representing trends in key hydrological variables,
        climate-driven changes in the water cycle, and anthropogenic
        influences such as irrigation-induced groundwater depletion ─
        factors often poorly captured in models. With processing
        pipelines now being developed for low-latency short-term data
        products from the upcoming next-generation gravity missions, we
        expect that low-latency periodically updated reanalyses and
        analyses from assimilation will become more relevant. However,
        challenges remain, particularly in resolving mismatches in
        spatial and temporal resolution between GRACE/-FO observations
        and high-resolution models, and there is no consensus yet on the
        optimal approach for assimilating GRACE/-FO data. In light of
        the upcoming launches of next-generation gravity missions and
        the development of increasingly sophisticated Earth system
        modeling frameworks, this review synthesizes insights from
        approximately 60 GRACE/-FO data assimilation studies in an
        attempt to converge to best practices. The review reveals that
        the most effective assimilation strategies leverage (robust
        modifications of) the classical ensemble Kalman filter and
        localization techniques, explicitly account for correlated
        observation errors, and address biases contained in the
        observations as well as those arising from model perturbations.
        Unmodeled processes must be carefully handled through signal
        separation, multi-source assimilation, or removal prior to
        assimilation. Future directions include developing low-latency
        products for near-real-time assimilation, integrating enhanced
        and combined satellite observations, and employing machine-
        learning approaches for downscaling and hybrid assimilation.
        Collectively, these strategies provide a pathway toward more
        accurate, physically consistent, and operationally useful water
        cycle reanalyses.}",
          doi = {10.5194/hess-30-985-2026},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026HESSD..30..985S},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}