@COMMENT This file was generated by bib2html_grace.pl <https://sourceforge.net/projects/bib2html/> version 0.94
@COMMENT written by Patrick Riley <https://sourceforge.net/users/patstg/>
@COMMENT This file was prepared using the NASA Astrophysics Data System (ADS)
@COMMENT https://ui.adsabs.harvard.edu/
@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}
}