 A deep learning model for reconstructing global climate-driven total water storage changes is presented for 1923-2022.  Our reconstruction exhibits superior consistency with GRACE observations compared to GRACE-REC.  The reconstructed datasets reveal relative reliability and challenges in humid and arid regions.