most citedImproving prediction of the terrestrial water storage anomalies during the GRACE and GRACE-FO gap with Bayesian convolutional neural networks

108 citations · 108 across the 1 of their papers we have counts for

collaborators

1 paper

physics.ao-ph2021★ 108 cited

Improving prediction of the terrestrial water storage anomalies during the GRACE and GRACE-FO gap with Bayesian convolutional neural networks

Shaoxing Mo, Yulong Zhong, Xiaoqing Shi +3

The Gravity Recovery and Climate Experiment (GRACE) satellite and its successor GRACE Follow-On (GRACE-FO) provide valuable and accurate observations of terrestrial water storage a…