SAGEA: A toolbox for comprehensive error assessment of GRACE and GRACE-FO based mass changes

The level-2 time-variable gravity fields obtained from Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) mission are widely used in multi-discipline geoscience studies. However, the post-processing of these gravity fields to obtain a desired signal is rather challenging for users who are not familiar with the level-2 products. In addition, the error assessment/quantification of these derived signals, which is of increasing demand in science application, is still a challenging issue even among professional GRACE(-FO) users. In this paper, we review the known steps of post-processing, along with their implementation strategies. We also make a comprehensive investigation into the error of GRACE(-FO) based mass changes, and for the first time, we define the so-called error into three independent categories. This work, including the post-processing steps and the assessment of each error, is integrated into an open-source Python toolbox called SAGEA (SAtellite Gravity Error Assessment). With diverse options, SAGEA provides flexibility to generate signals along with the full error from level-2 products. In addition, a novel in-depth optimization of our post-processing implementation gains a speed-up of $\sim 100$ times better than traditional method. For verification, a number of case studies are carried out with SAGEA to obtain a comprehensive error assessment of GRACE(-FO) level-2 product at global and local scales.