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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.
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Wang et al. (2024) studied this question.
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