A New GRACE Filtering Approach Based on Iterative Image Convolution.

The Gravity Recovery and Climate Experiment (GRACE) mission and its successor GRACE Follow‐On (GRACE‐FO) mission provide humans with a unique perspective on mass distribution through accurate temporal gravity field models. However, these models suffer from unavoidable stripe errors in the spatial domain. A new approach based on image processing has been developed for filtering GRACE and GRACE‐FO spherical harmonic solutions. In this approach, the gravity fields are treated as noise‐contaminated images, and the stripe errors are expected to be suppressed by convolving the input with an appropriate kernel. To verify the effectiveness of the proposed approach, a closed‐loop simulation environment over the nominal mission lifetime of 5 years is designed. Image processing indicators and geophysical information evaluation results demonstrate the superior performance of the new approach in suppressing stripe errors. In the context of real GRACE data processing, our new approach still yields better results as follows: (a) The comprehensive ability of de‐striping and retaining details has slight advantages over some commonly used filters, as demonstrated through spatial distributions, amplitude spectra, and coefficient spectra. (b) The equivalent water height time series at the basin scale is comparable to the results derived from other filters or Level‐3 products. (c) The estimated signal amplitude of the Mw9.1 2004 Sumatra earthquake co‐seismic gravity change is 52.7% larger than that derived from the Gaussian 300 km filter, which is much closer to the theoretical value derived from the dislocation theory. Plain Language Summary: Mass migration inside the Earth and at its surface generates global gravitational variations. The GRACE mission pioneers a novel path of monitoring global gravitational variations from satellites. Since the raw GRACE data is highly noisy, it must be filtered before application. This study reports a new filtering approach that utilizes the method of image processing. Different from the traditional method, the new approach adopts adjustments not based on spherical harmonic coefficients. The quantitative assessments via simulation studies demonstrate the good performance of our proposed method from both the perspective of image processing and geophysical signal analysis. To illustrate the practical effect of our method, we then use it to filter the real GRACE data. The extensive comparisons also support the effectiveness of our method. In practical research, such as detecting earthquake gravity signals, we obtain more realistic results than those derived from traditional approaches. All results indicate that our method performs well in noise suppression and signal preservation. Overall, the proposed method can be considered as an important option in GRACE data filtering. Key Points: A new Gravity Recovery and Climate Experiment (GRACE) filtering approach based on the spectral features of longitudinal stripe errors is designedThe proposed approach demonstrates good performance in terms of signal preservation and suppression of stripe errorsEvaluations based on image processing analysis and geophysical information indicate the effectiveness of our method [ABSTRACT FROM AUTHOR]