Thu Oct 08, F. Flechtner
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Kim, Junho, Jung, Kichul, and Ahn, Kuk–Hyun, 2026. Global Terrestrial Water Storage Projections and Uncertainty Decomposition Under Multiple Warming Levels. Earth's Future, 14(7):e2025EF007835, doi:10.1029/2025EF007835.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026EaFut..1407835K,
author = {{Kim}, Junho and {Jung}, Kichul and {Ahn}, Kuk-Hyun},
title = "{Global Terrestrial Water Storage Projections and Uncertainty Decomposition Under Multiple Warming Levels}",
journal = {Earth's Future},
keywords = {global hydrologic models, climate change projection, terrestrial water storage (TWS), uncertainty decomposition},
year = 2026,
month = jul,
volume = {14},
number = {7},
eid = {e2025EF007835},
pages = {e2025EF007835},
abstract = "{Terrestrial Water Storage (TWS) is a key integrator of the global
hydrologic cycle, yet its future response to climate change
remains uncertain due to divergent climate forcings, hydrologic
model structures, and parameter choices. This study provides a
global, global-warming-level (GWL)-based assessment of future
TWS changes at 1.0{\textdegree}C, 2.0{\textdegree}C, and
3.0{\textdegree}C above pre-industrial conditions. We construct
a large ensemble that combines multiple climate scenarios, five
CMIP6 global climate models (GCMs), four global hydrologic
models (GHMs), and 50 hydrological parameter realizations per
model. Our results indicate that evaluation against Gravity
Recovery and Climate Experiment (GRACE) mascon observations
confirms that the ensemble reasonably reproduces historical
large-scale TWS variations. Projections show that TWS changes
become more widespread, stronger in magnitude, and more
consistent across models as warming intensifies. High-latitude
regions generally exhibit TWS increases linked to increased
precipitation, whereas many tropical and subtropical regions,
including the Amazon, the Sahel, and South Asia, experience TWS
declines driven by rising evaporative demand. A four-way
analysis of variance reveals that GCMs dominate global TWS
uncertainty, particularly in high-latitude and cold-climate
regions, while hydrologic-related uncertainty from GHMs and
their parameterizations becomes increasingly important in
monsoon, subtropical, and semi-arid regions. These results
underscore that developing robust, region-specific adaptation
strategies requires multi-GCM, multi-GHM, and multi-parameter
ensembles that explicitly account for both climate and
hydrologic uncertainties.}",
doi = {10.1029/2025EF007835},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026EaFut..1407835K},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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