Publications related to the GRACE Missions (no abstracts)

• Sorted by Date • Sorted by Last Name of First Author •

Improving the Spatial Resolution of GRACE-Derived Ice Sheet Mass Change in Antarctica

Shi, Zhuoya, Wang, Zemin, Zhang, Baojun, Zhang, Gangqiang, Barrand, Nicholas E., Geng, Hong, An, Jiachun, and Su, Yong, 2025. Improving the Spatial Resolution of GRACE-Derived Ice Sheet Mass Change in Antarctica. IEEE Transactions on Geoscience and Remote Sensing, 63:TGRS.2024, doi:10.1109/TGRS.2024.3511944.

Downloads

• from the NASA Astrophysics Data System  • by the DOI System  •

@ARTICLE{2025ITGRS..6311944S,
       author = {{Shi}, Zhuoya and {Wang}, Zemin and {Zhang}, Baojun and {Zhang}, Gangqiang and {Barrand}, Nicholas E. and {Geng}, Hong and {An}, Jiachun and {Su}, Yong},
        title = "{Improving the Spatial Resolution of GRACE-Derived Ice Sheet Mass Change in Antarctica}",
      journal = {IEEE Transactions on Geoscience and Remote Sensing},
     keywords = {Antarctica ice sheet (AIS), downscaling, free air gravity anomalies, gap reconstruction, gravity recovery and climate experiment (GRACE)/GRACE follow-on (GRACE-FO), ice mass changes},
         year = 2025,
        month = jan,
       volume = {63},
          eid = {TGRS.2024},
        pages = {TGRS.2024},
     abstract = "{The nominally coarse spatial resolution ( km) of gravity recovery and
        climate experiment (GRACE) and a 11-month data gap with GRACE
        follow-on (GRACE-FO) limits applications at the individual ice
        sheet drainage basin scale and complicates the evaluation of
        regional ice sheet mass changes. While numerous works have
        downscaled GRACE-estimated water storage, research on
        downscaling ice mass change in Antarctica is limited. This study
        employs joint partial least-squares regression (PSLR) and
        support vector machine (SVM) method to reconstruct GRACE-derived
        spatiotemporal data for the Antarctic ice sheet (AIS). The
        pixel-temporal downscaling (PTD) of random forest (RF) and
        pixel-spatial downscaling (PSD) of multiscale geographically
        weighted regression (MGWR) enhance spatial resolution of ice
        mass changes from 0.25{\textdegree}
        (\raisebox{-0.5ex}\textasciitilde120 km) to 1.92 km. The
        downscaled results show consistent temporal variation and
        reduced noise compared to other reconstruction methods. Both RF
        and MGWR results exhibit high consistency with original GRACE
        data, with MGWR achieving a correlation coefficient (CC) of
        0.99. The MGWR model effectively captures finer signals related
        to ice flow velocity. When compared to independent free air
        gravity anomalies, MGWR outperforms RF with improvements of
        41.51\% and 56.25\% in mean correlation for group 1 and group 2
        observation points, respectively. In addition, MGWR shows
        improvements of 16.90\%/29.69\% for flight Line A and
        11.84\%/19.72\% for flight Line B compared to RF and original
        GRACE results. The enhanced spatial resolution offers valuable
        insights into ice dynamic changes within the Western AIS and
        Eastern AIS and smaller regions such as the Antarctic Peninsula.}",
          doi = {10.1109/TGRS.2024.3511944},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2025ITGRS..6311944S},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Generated by bib2html_grace.pl (written by Patrick Riley modified for this page by Volker Klemann) on Thu Aug 14, 2025 17:55:12

---

Thu Aug 14, F. Flechtner