Fei et al. (2026) Assimilating GRACE Data for Improved Modeling of the Terrestrial Hydrological Cycle and Its Response to ENSO With the Noah‐MP Multi‐Physics Ensemble

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Identification

• Journal: Journal of Geophysical Research Atmospheres
• Year: 2026
• Date: 2026-08-24
• Authors: Wenli Fei, Hui Zheng, Peirong Lin, Zong‐Liang Yang, Xiangyong Lei, Kai Li, An‐Zhi Wang, Jiabing Wu, Lidu Shen, Yage Liu, Yuan Zhang, Rongping Li
• DOI: 10.1029/2026jd046517

Research Groups

• University of California, Los Angeles (UCLA) Department of Civil and Environmental Engineering
• University of Colorado Boulder Department of Atmospheric and Oceanic Sciences

Short Summary

This study investigates the impact of assimilating Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage data on hydrological simulation performance under different climatic regimes and its effect on runoff–El Niño‐Southern Oscillation (ENSO) linkages. The results show that data assimilation enhances the accuracy of simulations, particularly in regions with significant climate variability.

Objective

• Investigate the effectiveness of GRACE terrestrial water storage data assimilation on improving hydrological simulation performance under different climatic regimes.
• Examine the impact of GRACE DA on runoff–ENSO linkages in semi‐arid and arid regions.

Study Configuration

• Spatial Scale: Southern contiguous United States (CONUS)
• Temporal Scale: Daily scale

Methodology and Data

• Models used: Noah‐Multiparameterization land surface model (Noah‐MP)
• Data sources: GRACE terrestrial water storage data, Ensemble Adjustment Kalman Filter for assimilation

Main Results

• Data assimilation enhances the accuracy of terrestrial water storage anomaly simulations in regions with significant climate variability.
• Soil moisture simulations show more skill gains in the deep layer than in the surface layer.
• Snow water equivalent simulations improve in regions with deeper snow cover.
• Runoff simulations are improved in arid and semi‐arid regions, but slightly degraded in humid regions.
• Data assimilation eliminates spurious correlations between runoff and ENSO in semi‐arid and arid regions.

Contributions

This study provides new insights into the effectiveness of GRACE DA on improving hydrological simulation performance under different climatic regimes. The results demonstrate its potential for enhancing water management planning, particularly in regions with significant climate variability.

Funding

• National Science Foundation (NSF) Grant #1855406
• NASA Terrestrial Hydrology Program Grant #80NSSC18K0294

Citation

@article{Fei2026Assimilating,
  author = {Fei, Wenli and Zheng, Hui and Lin, Peirong and Yang, Zong‐Liang and Lei, Xiangyong and Li, Kai and Wang, An‐Zhi and Wu, Jiabing and Shen, Lidu and Liu, Yage and Zhang, Yuan and Li, Rongping},
  title = {Assimilating GRACE Data for Improved Modeling of the Terrestrial Hydrological Cycle and Its Response to ENSO With the Noah‐MP Multi‐Physics Ensemble},
  journal = {Journal of Geophysical Research Atmospheres},
  year = {2026},
  doi = {10.1029/2026jd046517},
  url = {https://doi.org/10.1029/2026jd046517}
}