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首页> 外文期刊>TAO: Terrastrial, atmospheric, and oceanic sciences >HUST-GOGRA2018s: A new gravity field model derived from the combination of GRACE and GOCE data
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HUST-GOGRA2018s: A new gravity field model derived from the combination of GRACE and GOCE data

机译:Hust-gogra2018S:一种新的重力场模型,来自Grace和Goce数据的组合

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A new satellite-only gravity field model entitled HUST-GOGRA2018s is developed by the combination of GRACE and GOCE data in this study. The modified dynamic approach is applied for GRACE data processing, while the space-wise least square method with a cascade filter is utilized for GOCE data processing. The GRACE-only model HUST-Grace2016s and GOCE-only model HUST-GOCE2018s are then computed, respectively. Our new developed GRACE-only model HUST-Grace2016s performs better than AIUB-GRACE03S, GGM05S, Tongji-GRACE01S at higher degrees, and the quality of our GOCE-only model HUST-GOCE2018s is also better than that of GO_CONS_GCF_2_TIM_R2 and GO_CONS_GCF_2_SPW_R2. The combination is subsequently implemented by the superposition of GRACE and GOCE full normal equations. During the combination, the optimal weight is determined by the least-squares combined adjustment method with parametric covariance approach (LS-PCA) and the spectral combination method, respectively. The comparison result demonstrates that LS-PCA is more proper for the combination. As a result, the final HUST-GOGRA2018s model is developed. Validated by external gravity field models, the results demonstrate that the HUST-GOGRA2018s is dominated by GRACE data for the spherical harmonic coefficients lower than degree 60 and GOCE data for the spherical harmonic coefficients higher than degree 150, and its performance is better than that of GOCO01S.
机译:题为Hust-Gogra2018S的新卫星的重力场模型是由本研究中的恩典和衰竭数据的组合开发的。修改的动态方法适用于Grace数据处理,而具有级联滤波器的空间最小二乘法用于Goce数据处理。然后,分别计算恩惠的典型型号展开展示展示展示了展败展开型号展开硕士展示展示展示展示了普通的展位2018年。我们的新发达的恩典型号展示展示福利-RACE2016比AIUB-GRACE03S,GGM05S,同济乐队01S更高,以及我们的衰减型号的质量展开展开展示了GO_COS2018S也比Go_cons_gcf_2_tim_r2和go_cons_gcf_2_spw_r2更好。随后该组合由恩典叠加和GOCE完整正常方程来实现。在组合期间,通过分别具有参数协方差方法(LS-PCA)和光谱组合方法的最小二乘组合调整方法确定最佳权重。比较结果表明LS-PCA更适合组合。结果,开发了最终的Hust-Gogra2018S模型。由外部重力场模型验证,结果表明,Hust-Gogra2018由宽度数据为主导的球形谐波系数低于60度,并且对于高于150度的球面谐波系数的Goce数据,其性能优于Goco01s。

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