2026-06-26T11:26:58Zhttp://doidb.wdc-terra.org/oaip/oai

oai:doidb.wdc-terra.org:86232026-06-10T10:30:46ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.DQTO.2025.001 Uz, Metehan Metehan Uz 0000-0002-4533-7681 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Atman, Kazım Gökhan Kazım Gökhan Atman 0000-0001-8800-9736 School of Mathematical Sciences, Queen Mary University of London, London, England Akyılmaz, Orhan Orhan Akyılmaz 0000-0002-8499-2654 Dept. of Geomatics Eng., Istanbul Technical University, Istanbul, Turkey Shum, CK CK Shum 0000-0001-9378-4067 Division of Geodetic Science, School of Earth Sciences, The Ohio State University, Columbus, Ohio, USA GFZ Data Services 2025 Soft Constraint Paradigm Mass Conservation GRACE and GRACE Follow-On Gravimetry Deep Learning-aided Spatial Downscaling Terrestrial Water Storage Anomalies Earth Observation Satellites > NASA Earth System Science Pathfinder > GRACE EARTH SCIENCE > TERRESTRIAL HYDROSPHERE EARTH SCIENCE SERVICES > DATA ANALYSIS AND VISUALIZATION > STATISTICAL APPLICATIONS Uz, Metehan Metehan Uz 0000-0002-4533-7681 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Uz, Metehan Metehan Uz 0000-0002-4533-7681 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Uz, Metehan Metehan Uz 0000-0002-4533-7681 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Uz, Metehan GFZ Helmholtz Centre for Geosciences, Potsdam, Germany 2002-04-15/2022-12-15 Dataset 10.24381/cds.f17050d7 10.1029/2020GL088306 10.5194/gmd-2023-213 10.1002/2014JB011547 10.1002/2016WR019344 10.5067/TEMSC-3MJ63 10.1016/j.jhydrol.2026.135015 CC BY 4.0 This dataset provides a comprehensive, high-resolution global record of monthly Terrestrial Water Storage Anomalies (TWSA) from April 2002 to December 2022. It was generated to address the spatial resolution limitations of raw satellite gravimetry observations from the GRACE and GRACE-FO missions, offering a product suitable for regional and basin-scale hydrological analysis. The dataset was simulated using a novel deep learning framework. This model spatially downscales the low-resolution (~300 km) JPL GRACE/GRACE-FO Mascon solutions (Watkins et al., 2015; Wiese et al., 2016; Landerer et al., 2020; Wiese et al., 2023) to a high resolution of 50 km (0.5-degree grid). The core of the methodology is a dynamic soft-constrained paradigm, where the model is simultaneously guided by the observational accuracy of GRACE/GRACE-FO data and the high-resolution spatial patterns from the WaterGAP Global Hydrology Model (Müller Schmied et al., 2023) and ERA5 reanalysis data (Hersbach et al., 2023). The influence of these constraints is dynamically weighted at each training step based on the evolving correlation between the model's prediction and the high-resolution inputs, ensuring an optimal simulation of observational integrity and high-resolution detail.
Global land areas (excluding Greenland and Antarctica) and temporal coverage: April 2002 – December 2022 -179.75 179.75 -89.75 89.75