Publications related to the GRACE Missions (no abstracts)

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Weakening stripe noise of GRACE Level-2 spherical harmonic coefficients based on spatiotemporal joint state-space model

Feng, Yong, Chang, Guobin, Huan, Yueyang, Qian, Nijia, Cao, Yu, Tao, Yuan, Sun, Yinxiao, and Zhong, Xinying, 2025. Weakening stripe noise of GRACE Level-2 spherical harmonic coefficients based on spatiotemporal joint state-space model. Measurement Science and Technology, 36(10):106116, doi:10.1088/1361-6501/ae0a74.

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@ARTICLE{2025MeScT..36j6116F,
       author = {{Feng}, Yong and {Chang}, Guobin and {Huan}, Yueyang and {Qian}, Nijia and {Cao}, Yu and {Tao}, Yuan and {Sun}, Yinxiao and {Zhong}, Xinying},
        title = "{Weakening stripe noise of GRACE Level-2 spherical harmonic coefficients based on spatiotemporal joint state-space model}",
      journal = {Measurement Science and Technology},
     keywords = {GRACE, striping error, spatiotemporal joint state-space model, Pseudo-observation, power-law model},
         year = 2025,
        month = oct,
       volume = {36},
       number = {10},
          eid = {106116},
        pages = {106116},
     abstract = "{The paper proposes a spatiotemporal joint state-space (STSS) model,
        where the state vector contains only estimates of the true
        geophysical signals, while the striping errors and high-
        frequency noise are treated as observation noise, the covariance
        matrix reflecting the statistical information of stripe errors
        is used as the observation noise covariance matrix in the state-
        space model. The state equation is constructed by considering
        the correlation of the time-varying gravity field at adjacent
        time nodes, and a covariance matrix of process noise is
        generated using a power-law model. Based on this, spatial domain
        constraints are applied through pseudo-observation equations,
        and variance component factors are introduced to adaptively
        adjust the size of the noise covariance matrix. The parameter
        values are determined by minimizing the cost function and
        optimizing the signal-to-noise ratio. Using the gravity recovery
        and climate experiment Level-2 spherical harmonic (SH) product
        as the validation dataset, first, the model is evaluated in
        terms of the correlation between SH coefficients and mascon,
        where the STSS model shows a higher correlation compared to
        other filtered solutions. Secondly, the model's performance is
        analysed based on signal and noise levels, demonstrating
        superior performance compared to the decorrelation and denoising
        kernel (DDK) filter series and combined filters. Lastly, from
        the perspective of global and regional surface mass migration
        estimates, the STSS model shows improvements over the temporal
        state-space model, with root mean square errors comparable to
        the optimal DDK filter across various regions. When using the
        hydrological model as a reference, the STSS model achieves the
        highest correlation coefficient.}",
          doi = {10.1088/1361-6501/ae0a74},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2025MeScT..36j6116F},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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