Publications related to the GRACE Missions (no abstracts)

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Breaking the Temporal Resolution Barrier: Projected Performance of Hybrid Gravity Satellite Ensemble by the Early 2030s

Yan, Zhengwen, Ran, Jiangjun, Chen, Jianli, Lasser, Martin, Smith, Patrick, Zhang, Yu, and Massotti, Luca, 2026. Breaking the Temporal Resolution Barrier: Projected Performance of Hybrid Gravity Satellite Ensemble by the Early 2030s. Earth's Future, 14(3):e2025EF006825, doi:10.1029/2025EF006825.

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@ARTICLE{2026EaFut..1406825Y,
       author = {{Yan}, Zhengwen and {Ran}, Jiangjun and {Chen}, Jianli and {Lasser}, Martin and {Smith}, Patrick and {Zhang}, Yu and {Massotti}, Luca},
        title = "{Breaking the Temporal Resolution Barrier: Projected Performance of Hybrid Gravity Satellite Ensemble by the Early 2030s}",
      journal = {Earth's Future},
     keywords = {satellite gravimetry, GRACE, temporal gravity field, future gravity satellite missions, high temporal resolution, numerical closed-loop simulation},
         year = 2026,
        month = mar,
       volume = {14},
       number = {3},
          eid = {e2025EF006825},
        pages = {e2025EF006825},
     abstract = "{Limitations in the temporal resolution of contemporary gravity satellite
        missions hinder the precise monitoring of rapid Earth surface
        mass changes. By the early 2030s, unprecedented high-temporal
        monitoring of Earth's dynamic mass redistribution will be
        available using the temporal gravity field derived from the
        Hybrid Gravity Satellite Ensemble (referred to as the ``HGSE''
        in this study), which contains GRACE-FO, ChiGaM, TIANQIN-2,
        GRACE-C, and NGGM. This paper proposes a Hybrid-Augmented
        Resolution Dealiasing (HARD) algorithm that utilizes a sliding
        window technique to co-estimate 3-day low-degree and daily high-
        degree spherical harmonic coefficients. The HARD algorithm
        reduces temporal aliasing errors by 18.4\%─30.7\% compared to
        conventional processing strategies. Based on predefined noise
        levels for each satellite, closed-loop simulations demonstrate
        that the HGSE yields daily gravity field solutions (with a
        maximum degree and order of 60) that can effectively reduce
        noise by approximately 76.2\% in long-term trends and 39.3\% in
        annual amplitudes compared to classical monthly solutions.
        Applications in terrestrial water storage (TWS) change, glacier
        mass change, and co-seismic deformation reveal significant
        improvements: 39.4\% enhanced TWS signal recovery in large river
        basins, 21.2\% higher accuracy in monitoring Tibetan Plateau
        glacier mass variation, and 69.4\% superior co-seismic signal
        recovery for megathrust earthquakes. These findings underscore
        the potential of HGSE to advance high-frequency gravity field
        monitoring, offering critical references for the performance
        analysis of future gravity satellite missions monitoring the
        Earth's dynamic system processes on a daily scale.}",
          doi = {10.1029/2025EF006825},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026EaFut..1406825Y},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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