GRACE and GRACE-FO Related Publications (no abstracts)

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SAGEA: A toolbox for comprehensive error assessment of GRACE and GRACE-FO based mass changes

Liu, Shuhao, Yang, Fan, and Forootan, Ehsan, 2025. SAGEA: A toolbox for comprehensive error assessment of GRACE and GRACE-FO based mass changes. Computers and Geosciences, 196:105825, doi:10.1016/j.cageo.2024.105825.

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@ARTICLE{2025CG....19605825L,
       author = {{Liu}, Shuhao and {Yang}, Fan and {Forootan}, Ehsan},
        title = "{SAGEA: A toolbox for comprehensive error assessment of GRACE and GRACE-FO based mass changes}",
      journal = {Computers and Geosciences},
     keywords = {GRACE, Error assessment, Post-processing, Python toolbox},
         year = 2025,
        month = feb,
       volume = {196},
          eid = {105825},
        pages = {105825},
     abstract = "{The level-2 time-variable gravity fields obtained from Gravity Recovery
        and Climate Experiment (GRACE) and its follow-on (GRACE-FO)
        mission are widely used in multi-discipline geoscience studies.
        However, the post-processing of these gravity fields to obtain a
        desired signal is rather challenging for users who are not
        familiar with the level-2 products. In addition, the error
        assessment/quantification of these derived signals, which is of
        increasing demand in science application, is still a challenging
        issue even among professional GRACE(-FO) users. In this paper,
        we review the known steps of post-processing, along with their
        implementation strategies. We also make a comprehensive
        investigation into the error of GRACE(-FO) based mass changes,
        and for the first time, we define the so-called error into three
        independent categories. This work, including the post-processing
        steps and the assessment of each error, is integrated into an
        open-source Python toolbox called SAGEA (SAtellite Gravity Error
        Assessment). With diverse options, SAGEA provides flexibility to
        generate signals along with the full error from level-2
        products. In addition, a novel in-depth optimization of our
        post-processing implementation gains a speed-up of <mml:math
        altimg=``si1.svg'' display=``inline'' id=``d1e2023''><mml:mrow><
        mml:mo>{\ensuremath{\sim}}</mml:mo><mml:mn>100</mml:mn></mml:mro
        w></mml:math> times better than traditional method. For
        verification, a number of case studies are carried out with
        SAGEA to obtain a comprehensive error assessment of GRACE(-FO)
        level-2 product at global and local scales.}",
          doi = {10.1016/j.cageo.2024.105825},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2025CG....19605825L},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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