Data for: ML-TWiX: A Machine Learning approach for Total Water storage anomaly eXtension back to 1980

The ML-TWiX dataset provides a globally gridded reconstruction of Total Water Storage Anomalies (TWSA) from January 1980 to December 2012. This dataset is designed to extend the GRACE satellite observations backward in time, supporting hydrological and climate-related studies that require long-term water storage information. The reconstruction was achieved using an ensemble of machine learning models - Random Forest, Gaussian Process Regression, and XGBoost - trained over the GRACE observation period (April 2002 to December 2012). Input features included monthly TWSA estimates from 13 global hydrological, land surface, and reanalysis models, applied at a 0.5° grid over global land areas (excluding Greenland and Antarctica). The dataset includes both the mean predicted TWSA and associated uncertainty, quantified through bootstrapped ensemble realizations. ML-TWiX is particularly useful for drought analysis, trend evaluation, and integration into Earth system models or water balance studies.