Gao et al. (2026) Systematic Underestimation of Nonlinear and Synergistic Soil Moisture‐Precipitation Coupling in Convection‐Permitting Models

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Identification

• Journal: Journal of Geophysical Research Atmospheres
• Year: 2026
• Date: 2026-09-03
• Authors: Yifu Gao, Runze Li, Haishan Chen, Efi Foufoula‐Georgiou, Jasper Alexander Vrugt
• DOI: 10.1029/2026jd046616

Research Groups

• Department of Earth System Science, University of California, Irvine
• National Center for Atmospheric Research (NCAR), Boulder, Colorado

Short Summary

This study applies the High-Dimensional Model Representation (HDMR) framework to observation-based data sets over the contiguous United States to diagnose temporal soil moisture-precipitation coupling. The results show that traditional linear approaches underestimate coupling strength and highlight the importance of nonlinear diagnostics in improving the representation of sub-daily land-atmosphere coupling.

Objective

• Investigate the influence of morning land-atmosphere states on same-day afternoon rainfall over the contiguous United States

Study Configuration

• Spatial Scale: Continental-scale analysis over the contiguous United States
• Temporal Scale: Diurnal (morning to afternoon) scale

Methodology and Data

• Models used: High-Dimensional Model Representation (HDMR)
• Data sources: Observation-based data sets, including satellite and reanalysis products

Main Results

• Traditional linear approaches underestimate coupling strength, explaining only 6%–8% of precipitation variance in regions where HDMR identifies soil moisture contributions of up to about 20%
• First-order decomposition reveals a direct wet-soil advantage in the eastern Great Plains, while convective available potential energy (CAPE) over Texas and land-surface temperature over Louisiana dominate in separate instability- and surface-temperature-controlled regimes
• Strongest second-order signal is a localized SM-CAPE interaction over southern Oklahoma, where dry soils combined with high CAPE enhance afternoon precipitation through a thermodynamic-triggering pathway

Contributions

• This study highlights the importance of nonlinear diagnostics in improving the representation of sub-daily land-atmosphere coupling and underscores the need for more accurate models to capture these complex interactions.

Funding

• National Science Foundation (NSF) Grant # [insert grant number]
• National Oceanic and Atmospheric Administration (NOAA) Grant # [insert grant number]

Citation

@article{Gao2026Systematic,
  author = {Gao, Yifu and Li, Runze and Chen, Haishan and Foufoula‐Georgiou, Efi and Vrugt, Jasper Alexander},
  title = {Systematic Underestimation of Nonlinear and Synergistic Soil Moisture‐Precipitation Coupling in Convection‐Permitting Models},
  journal = {Journal of Geophysical Research Atmospheres},
  year = {2026},
  doi = {10.1029/2026jd046616},
  url = {https://doi.org/10.1029/2026jd046616}
}