Sun et al. (2025) Causal pathways underlying global soil moisture–precipitation coupling

Identification

• Journal: Nature Communications
• Year: 2025
• Date: 2025-10-08
• Authors: Jing Sun, Kun Yang, Xiaogang He, Guiling Wang, Yong Wang, Yan Yu, Hui Lü
• DOI: 10.1038/s41467-025-63999-7

Research Groups

• Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Institute for Global Change Studies, Tsinghua University, Beijing, China
• State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
• Department of Civil and Environmental Engineering, National University of Singapore, Singapore, Singapore
• School of Civil and Environmental Engineering and Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT, USA
• Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China
• State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, China
• Tsinghua University (Department of Earth System Science)-Xi’an Institute of Surveying and Mapping Joint Research Center for Next-Generation Smart Mapping, Beijing, China

Short Summary

This study employs an information flow technique on satellite observations and reanalysis data to map global surface soil moisture-precipitation (SSM-P) coupling hotspots and identify the dominant sensible heat or evapotranspiration-mediated causal pathways, revealing that most CMIP6 models fail to reproduce these patterns.

Objective

• To reveal the causal pathways and underlying mechanisms of global surface soil moisture-precipitation (SSM-P) coupling.
• To identify the conditions, particularly soil moisture variability, that favor strong SSM-P coupling.
• To evaluate the ability of CMIP6 models to capture SSM-P causality and its physical pathways, and propose process-based metrics for model evaluation.

Study Configuration

• Spatial Scale: Global land (60°S–60°N), with analysis focused on eight identified hotspots. Data processed to 0.5° × 0.5° (NNsm, MSWEP) and 0.25° × 0.25° (ERA5) spatial resolutions.
• Temporal Scale: Boreal warm seasons (May–September). Daily data. NNsm and MSWEP observations from 2003–2020. ERA5 reanalysis from 1979–2021. CMIP6 simulations from 1970–2014. Lag causality analyzed up to 32 days.

Methodology and Data

• Models used:
  • Liang–Kleeman information flow technique for causality analysis.
  • 16 historical simulations from CMIP6 climate models (AWI-ESM-1-1-LR, MPI-ESM-1-2-HAM, MPI-ESM1-2-LR, MPI-ESM1-2-HR, TaiESM1, CMCC-CM2-SR5, CMCC-CM2-HR4, CMCC-ESM2, ACCESS-ESM1-5, NorESM2-MM, NorESM2-LM, BCC-CSM2-MR, BCC-ESM1, CanESM5, MIROC6, MRI-ESM2-0).
• Data sources:
  • Satellite observations: Neural Network algorithm-based satellite observations of soil moisture (NNsm, 0–5 cm surface soil moisture, 36 km spatial resolution).
  • Observational precipitation: Multi-Source Weighted Ensemble Precipitation (MSWEP version-2, 3-hourly, 0.1° spatial resolution).
  • Reanalysis data: European Center for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5, 0–7 cm surface soil moisture, precipitation, evapotranspiration, surface sensible heat flux, boundary layer height, lifting condensation level, atmospheric moisture flux convergence; hourly, 0.25° spatial resolution).

Main Results

• Strong local SSM impacts on precipitation are found across approximately 16% of global land, concentrated in eight distinct hotspots (North India, Sahel region, tropical Africa, North Brazil, Pacific coast of Mexico, western Tibetan Plateau, Iranian Plateau, and the Greater Horn of Africa).
• The sensible heat (SH)-mediated pathway (SSM→SH→P) is a crucial mechanism in most hotspots, while the evapotranspiration (ET)-mediated pathway (SSM→ET→P) dominates in the Greater Horn of Africa and tropical Africa.
• These pathway differences are linked to regional hydroclimate characteristics, specifically remote moisture availability (atmospheric moisture flux convergence) and boundary layer height variability.
• Strong SSM-P coupling preferentially occurs in regions with large SSM variability, with the SSM→SH→P pathway being particularly sensitive to changes in SSM variability magnitude.
• Most CMIP6 models (12 out of 16) fail to accurately reproduce these SSM-P coupling patterns and the variability-causality relationship, showing region-specific underestimation of sub-processes' coupling.
• Four CMIP6 models (AWI-ESM-1-1-LR, MPI-ESM1-2-LR, MPI-ESM1-2-HR, and MPI-ESM-1-2-HAM) successfully capture the ERA5-derived positive correlation between SSM variability and the probability of strong SSM-P causality.
• The influence of SSM on precipitation in these hotspots is evident at weather to sub-seasonal timescales, lasting up to 32 days with regional variations.

Contributions

• Provides novel, process-level insights into the causal pathways (sensible heat vs. evapotranspiration) underlying global surface soil moisture-precipitation coupling using an information flow technique.
• Identifies specific hydroclimate characteristics (remote moisture availability, boundary layer height variability, and soil moisture variability) that modulate the dominant coupling pathways across different regions.
• Establishes process-based metrics for evaluating climate models' representation of land-atmosphere interactions, highlighting significant deficiencies in most CMIP6 models and identifying better-performing ones.
• Offers a valuable benchmark for climate model development and improves the understanding and prediction of land-atmosphere coupling, which is critical for hydrometeorological predictions and projections.

Funding

• National Science Foundation of China Grant 42361144875 and 42405164
• China Postdoctoral Science Foundation Grant 2023TQ0168
• Postdoctoral Fellowship Program of CPSF Grant GZC20231209
• Shuimu Tsinghua Scholar Program
• Singapore Ministry of Education (MOE) Academic Research Fund Tier-1 projects Grant A-0009297-01-00 and A-8001177-00-00
• Singapore Ministry of Education (MOE) Academic Research Fund Tier-2 project Grant A-8001886-00-00
• International Partnership Program of the Chinese Academy of Sciences Grant 183311KYSB20200015

Citation

@article{Sun2025Causal,
  author = {Sun, Jing and Yang, Kun and He, Xiaogang and Wang, Guiling and Wang, Yong and Yu, Yan and Lü, Hui},
  title = {Causal pathways underlying global soil moisture–precipitation coupling},
  journal = {Nature Communications},
  year = {2025},
  doi = {10.1038/s41467-025-63999-7},
  url = {https://doi.org/10.1038/s41467-025-63999-7}
}