He et al. (2026) Surface Energy Partitioning Biases in Major Reanalyses Revealed by Soil Moisture Drying Dynamics

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Journal of Geophysical Research Atmospheres
• Year: 2026
• Date: 2026-06-26
• Authors: Qing He, Huang Xin, Hui Min Lu, Kun Yang, Taikan Oki
• DOI: 10.1029/2025jd046087

Research Groups

• Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS)
• National Center for Atmospheric Research (NCAR)

Short Summary

This study evaluates the soil moisture-evaporative fraction regimes in six major reanalyses using satellite data sets over China and North America, revealing consistent overestimation of water limitation by models.

Objective

• Investigate the flux partition regimes between soil moisture and evaporative fraction in Land Surface Models (LSMs) using long-term satellite data sets.

Study Configuration

• Spatial Scale: Continental scale (China and North America)
• Temporal Scale: Long-term (multiple years)

Methodology and Data

• Models used: GLDAS-Noah, GLDAS-CLSM, MERRA2, NCEP-FNL, ERA5, JRA5
• Data sources: Satellite SM data sets (NNSM), observation-based meteorological forcing data sets

Main Results

• All models consistently overestimate the degree of water limitation at large scale.
• Model land-atmosphere coupling configurations have moderate influence on EF regimes.
• Surface soil layer thickness has minimal effect on EF regimes.

Contributions

• Advances understanding in LSMs' hydrometeorological behaviors and surface energy partitioning processes.
• Provides valuable reference for improving model parameterization on surface energy partitioning processes.

Funding

• This research was supported by the National Natural Science Foundation of China (Grant No. 41875051) and the National Center for Atmospheric Research (NCAR).

Citation

@article{He2026Surface,
  author = {He, Qing and Xin, Huang and Lu, Hui Min and Yang, Kun and Oki, Taikan},
  title = {Surface Energy Partitioning Biases in Major Reanalyses Revealed by Soil Moisture Drying Dynamics},
  journal = {Journal of Geophysical Research Atmospheres},
  year = {2026},
  doi = {10.1029/2025jd046087},
  url = {https://doi.org/10.1029/2025jd046087}
}