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Impact of Different Kinematic Empirical Parameters Processing Strategies on Temporal Gravity Field Model Determination

Zhou, Hao, Luo, Zhicai, Zhou, Zebing, Li, Qiong, Zhong, Bo, Lu, Biao, and Hsu, Houze, 2018. Impact of Different Kinematic Empirical Parameters Processing Strategies on Temporal Gravity Field Model Determination. Journal of Geophysical Research (Solid Earth), 123(11):10,252–10,276, doi:10.1029/2018JB015556.

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BibTeX

@ARTICLE{2018JGRB..12310252Z,
       author = {{Zhou}, Hao and {Luo}, Zhicai and {Zhou}, Zebing and {Li}, Qiong and {Zhong}, Bo and {Lu}, Biao and {Hsu}, Houze},
        title = "{Impact of Different Kinematic Empirical Parameters Processing Strategies on Temporal Gravity Field Model Determination}",
      journal = {Journal of Geophysical Research (Solid Earth)},
         year = 2018,
        month = nov,
       volume = {123},
       number = {11},
        pages = {10,252-10,276},
     abstract = "{During temporal gravity field model determination, the kinematic
        empirical parameters are mainly designed to remove the strong
        bias, drift, and 1-cycle per revolution variations in range-
        rates. In practice, two different strategies are commonly used
        to process these empirical parameters. One is to determine the
        empirical parameters before solving spherical harmonic
        coefficients, called Pure Predetermined Strategy (PPS). The
        other is to simultaneously determine the empirical parameters
        and spherical harmonic coefficients, called Pure Simultaneous
        Strategy (PSS). In this study, apart from these two strategies,
        a novel processing strategy called Filter Predetermined Strategy
        (FPS) is also discussed. These different processing strategies
        may result in different solutions. With the Gravity Recovery and
        Climate Experiment Level 1B data spanning 2005 to 2010, the
        impacts of different kinematic empirical parameters processing
        strategies were assessed in detail. The numerical results
        indicate that (1) using three different processing strategies
        and their hybrids can determine the temporal gravity field
        model, while (2) the solutions via PPS present apparent temporal
        signal attenuation, which is approximately 15\% lower in annual
        amplitude in Amazon River Basin, and 15\% lower in yearly trend
        in Greenland, and (3) the signal-to-noise ratios of the
        solutions via PPS are generally smaller than those of the
        solutions via FPS and PSS, and (4) the performance of FPS is
        superior in terms of postfit range-rates, but compatible with
        PSS in terms of other cross comparisons. According to
        comprehensive comparison results in terms of temporal signals
        and noise, the performance of our Huazhong University of Science
        and Technology models determined via FPS is in excellent
        accordance with other representative temporal gravity field
        models, such as CSR RL05, GFZ RL05a, and JPL RL05.}",
          doi = {10.1029/2018JB015556},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2018JGRB..12310252Z},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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