Publications related to the GRACE Missions (no abstracts)

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

GRACE terrestrial water storage data assimilation based on the ensemble four-dimensional variational method PODEn4DVar: Method and validation

Sun, Qin, Xie, ZhengHui, and Tian, XiangJun, 2015. GRACE terrestrial water storage data assimilation based on the ensemble four-dimensional variational method PODEn4DVar: Method and validation. Science China Earth Sciences, 58(3):371–384, doi:10.1007/s11430-014-4978-1.

Downloads

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

@ARTICLE{2015ScChD..58..371S,
       author = {{Sun}, Qin and {Xie}, ZhengHui and {Tian}, XiangJun},
        title = "{GRACE terrestrial water storage data assimilation based on the ensemble four-dimensional variational method PODEn4DVar: Method and validation}",
      journal = {Science China Earth Sciences},
     keywords = {data assimilation, land surface model, terrestrial water storage, ensemble four-dimensional variational data assimilation method},
         year = 2015,
        month = mar,
       volume = {58},
       number = {3},
        pages = {371-384},
     abstract = "{Seasonal and interannual changes in the Earth's gravity field are mainly
        due to mass exchange among the atmosphere, ocean, and
        continental water sources. The terrestrial water storage
        changes, detected as gravity changes by the Gravity Recovery and
        Climate Experiment (GRACE) satellites, are mainly caused by
        precipitation, evapotranspiration, river transportation and
        downward infiltration processes. In this study, a land data
        assimilation system LDAS-G was developed to assimilate the GRACE
        terrestrial water storage (TWS) data into the Community Land
        Model (CLM3.5) using the POD-based ensemble four-dimensional
        variational assimilation method PODEn4DVar, disaggregating the
        GRACE large-scale terrestrial water storage changes vertically
        and in time, and placing constraints on the simulation of
        vertical hydrological variables to improve land surface
        hydrological simulations. The ideal experiments conducted at a
        single point and assimilation experiments carried out over China
        by the LDAS-G data assimilation system showed that the system
        developed in this study improved the simulation of land surface
        hydrological variables, indicating the potential of GRACE data
        assimilation in large-scale land surface hydrological research
        and applications.}",
          doi = {10.1007/s11430-014-4978-1},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2015ScChD..58..371S},
      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 Mon Oct 13, 2025 16:16:50

---

Mon Oct 13, F. Flechtner