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

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.