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Li, Fupeng and Kusche, Jürgen, 2026. Reproducing GRACE Total Water Storage Change at Finer Spatial Scales. Geophysical Research Letters, 53(1):e2025GL119881, doi:10.1029/2025GL119881.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026GeoRL..5319881L,
author = {{Li}, Fupeng and {Kusche}, J{\"u}rgen},
title = "{Reproducing GRACE Total Water Storage Change at Finer Spatial Scales}",
journal = {\grl},
year = 2026,
month = jan,
volume = {53},
number = {1},
eid = {e2025GL119881},
pages = {e2025GL119881},
abstract = "{The Gravity Recovery and Climate Experiment (GRACE) satellite mission
provides accurate observations of terrestrial water storage
anomalies (TWSA), but their coarse spatial resolution
({\ensuremath{\sim}}3{\textdegree}) limits sub-regional-scale
applications. Existing downscaling methods rely on high-
resolution hydrometeorological inputs, which often underestimate
the full magnitude of GRACE signals. Here, we develop a machine-
learning-based iterative downscaling method that reproduces TWSA
at 0.25{\textdegree} resolution while retaining nearly all of
the original GRACE signals, using ERA5 soil moisture,
precipitation, and temperature as inputs. We find that the
downscaled TWSA has improved agreement with in situ groundwater
levels compared to the original GRACE data, with higher
correlation at over 63\% of wells and reduced RMSE at more than
83\% globally. The downscaled TWSA also retains an average
correlation of 0.99 with original GRACE data at the basin scale,
outperforming a previously released downscaling product. The
downscaled TWSA data set is publicly available at
https://doi.org/10.5281/zenodo.17265162.}",
doi = {10.1029/2025GL119881},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026GeoRL..5319881L},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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