Fri Apr 10, F. Flechtner
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Li, Fupeng and Kusche, Jürgen, 2026. Observation–Driven Forecast of Global Terrestrial Water Storage and Evaluation for 2010–2024. Water Resources Research, 62(2):e2025WR041710, doi:10.1029/2025WR041710.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026WRR....6241710L,
author = {{Li}, Fupeng and {Kusche}, J{\"u}rgen},
title = "{Observation-Driven Forecast of Global Terrestrial Water Storage and Evaluation for 2010--2024}",
journal = {Water Resources Research},
keywords = {GRACE, total water storage, seasonal forecasting, machine learning, LSTM},
year = 2026,
month = feb,
volume = {62},
number = {2},
eid = {e2025WR041710},
pages = {e2025WR041710},
abstract = "{Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and
GRACE Follow-On (GRACE/-FO) satellite missions have provided
unprecedented measurements of terrestrial water storage changes
(TWSC). These data are essential for monitoring the global water
cycle, supporting drought and flood risk management, and
informing water-related decision-making. However, GRACE products
are typically released with a latency of several months,
limiting their utility for real-time and operational forecasting
applications. In this study, we use machine learning to forecast
GRACE-like TWSC up to 12 months ahead, relying solely on
observational and reanalysis-based inputs. The observation-
driven forecast approach is evaluated over the period 2010─2024
and benchmarked against seasonal forecasts from the European
Centre for Medium-Range Weather Forecasts (ECMWF)'s new long-
range forecasting system (SEAS5). Our results show that the
developed method offers improved accuracy and robustness
compared to the ECMWF forecasts, providing a viable data-driven
alternative for operational TWSC forecasting. We generate global
forecast data sets at 1{\textdegree} resolution, creating a
robust, publicly available resource that extends GRACE-like
insights into the near future. The study addresses the latency
of GRACE/-FO products by offering real-time TWSC forecasts to
support applications such as drought early warning, sea level
prediction, hydrological model validation, and geodetic
applications such as forecasting Earth orientation parameters
via hydrological angular momentum excitation or estimating
loading corrections in GNSS and altimetry data analysis. The
hindcast data set (2010─2024) evaluated in this study and the
regularly updated semi-operational forecast data set (from 2024
onward) are publicly available at:
https://doi.pangaea.de/10.1594/PANGAEA.973113 and
https://www.igg.uni-bonn.de/apmg/de/data-and-models/grace-fo-
forecasting.}",
doi = {10.1029/2025WR041710},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026WRR....6241710L},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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Fri Apr 10, F. Flechtner