@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{2026IJSTA..19.6780S,
       author = {{Shi}, Zhuoya and {Wang}, Zemin and {Zhang}, Baojun and {Luo}, Manman and {Wu}, Shuang and {An}, Jiachun and {Wu}, Haojian and {Zhou}, Chunxia},
        title = "{High Spatial Resolution of GRACE-Derived Ice Mass Change Reveals Glacier-Scale Mass Loss in Greenland Ice Sheet}",
      journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
     keywords = {Downscaling, geographically weighted regression (GWR), Greenland blocking (GB), Greenland ice sheet (GrIS), random forest (RF)},
         year = 2026,
        month = jan,
       volume = {19},
        pages = {6780-6791},
     abstract = "{The gravity recovery and climate experiment (GRACE) and its follower
        GRACE-Follow On (GRACE-FO) act as a reliable tool to detect the
        Earths surface mass change. However, its discontinuity between
        GRACE and GRACE-FO limits its applicability for long-term
        analysis. Its coarse spatial resolution (300 km) of GRACE and
        GRACE-FO (GRACE/GFO) hampers detailed understanding of ice mass
        change response mechanisms to climate change at spatial scales
        below 200 000 km$^{2}$. In addition, research works in
        downscaling GRACE-derived ice mass change in the Greenland ice
        sheet (GrIS) remains limited. Based on the continuous
        reconstructed GRACE/GFO data, we first compared the performance
        of geographically weighted regression (GWR) and random forest
        (RF) to downscale GRACE/GFO from 0.25 0.25 to 5 km 5 km at a
        spatial global scale (SGS) in GrIS. This study presents the
        first application of such high-resolution downscaling to the
        reconstructed GRACE/GFO results over the GrIS. Finally, the SGS-
        GWR outperformed SGS-RF in capturing reasonable and finer
        signals of ice mass change. And downscaled results from SGS-GWR
        fit well with original GRACE/GFO mascon solutions and other
        independent estimates, achieving mean correlation coefficients
        and mean root mean square error at 0.98/2.68 cm by considering
        the nonstationarity heterogeneity of variables. Based on the
        continuous and high-resolution ice mass change, glacier-scale
        analysis of climatic forcing mechanisms, such as Greenland
        Blocking through its modulation of runoff, snowfall, rainfall,
        and solid ice discharge in 2012 and 2019, represents a novel
        contribution.}",
          doi = {10.1109/JSTARS.2026.3660280},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026IJSTA..19.6780S},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}