Publications related to the GRACE Missions (no abstracts)

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Downscaling GRACE(–FO) with mass–conserving XGBoost approach reveals high–resolution patterns and drivers of hydrometeorological–induced mass changes in High Mountain Asia

Wu, Haotian, Ran, Jiangjun, and Tangdamrongsub, Natthachet, 2026. Downscaling GRACE(–FO) with mass–conserving XGBoost approach reveals high–resolution patterns and drivers of hydrometeorological–induced mass changes in High Mountain Asia. Journal of Hydrology, 671:135235, doi:10.1016/j.jhydrol.2026.135235.

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@ARTICLE{2026JHyd..67135235W,
       author = {{Wu}, Haotian and {Ran}, Jiangjun and {Tangdamrongsub}, Natthachet},
        title = "{Downscaling GRACE(-FO) with mass-conserving XGBoost approach reveals high-resolution patterns and drivers of hydrometeorological-induced mass changes in High Mountain Asia}",
      journal = {Journal of Hydrology},
     keywords = {GRACE({\ensuremath{-}}FO), Downscale, Machine learning, XGBoost, HMA},
         year = 2026,
        month = may,
       volume = {671},
          eid = {135235},
        pages = {135235},
     abstract = "{High Mountain Asia (HMA), the largest extra-polar repository of
        glaciers, critically regulates water resources for nearly two
        billion people and regional climate systems. Understanding
        climate impacts and regional water security requires quantifying
        regional mass changes at fine spatial scales, but the coarse
        resolution of GRACE({\ensuremath{-}}FO) satellite data impedes
        this quantification. To address these limitations, this study
        proposes an XGBoost downscaling method integrated with mass-
        conservation correction. After obtaining preliminary downscaling
        results with low uncertainty and RMSE using the XGBoost model,
        the weighted forward modeling approach is further applied to
        enforce mass-conservation correction, thereby enhancing physical
        consistency. This correction reduces the RMSE of the regional
        mean time series from 0.85 cm to 0.08 cm, demonstrating that
        mass conservation effectively improves the downscaled solution.
        The downscaled solution was validated against the public ASTER-
        derived global digital elevation model, yielding a mean absolute
        trend error of only 0.53 Gt/yr, and outperforms existing Mascon
        solutions. Analysis identifies a pronounced atmospheric
        oscillation over the Caspian─Black Sea region, which induces
        interannual variations in moisture transport along the northern
        branch of the westerlies. This modulation of moisture pathways
        leads to oscillatory precipitation variability across Central
        Asia, ultimately giving rise to a distinct 6─7 year interannual
        mass oscillation in the Tien Shan─Pamir region. The strong
        correlation (greater than 0.7) between this mass variability and
        detrended cumulative precipitation highlights the dominant role
        of large-scale atmospheric circulation in shaping fine-scale
        hydrometeorological-induced mass changes across HMA.}",
          doi = {10.1016/j.jhydrol.2026.135235},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026JHyd..67135235W},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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