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Updated: Jan 15, 2026

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
Published on: June 8, 2015
Causal pathways underlying global soil moisture-precipitation coupling.
Jing Sun1, Kun Yang2,3, Xiaogang He4
1Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Institute for Global Change Studies, Tsinghua University, Beijing, China.
Surface soil moisture significantly impacts precipitation globally, mediated by sensible heat and evapotranspiration. Understanding these land-atmosphere coupling pathways is crucial for improving climate models and predictions.
Area of Science:
- Earth System Science
- Atmospheric Science
- Hydrology
Background:
- Surface soil moisture-precipitation (SSM-P) coupling is vital for climate dynamics.
- Sensible heat (SH) and evapotranspiration are key mediators, but their global mechanisms are poorly understood.
- This knowledge gap hinders accurate hydrometeorological predictions.
Purpose of the Study:
- To investigate global SSM-P coupling pathways and their underlying mechanisms.
- To identify hotspots of land-atmosphere interaction.
- To evaluate the performance of climate models in simulating these processes.
Main Methods:
- Utilized an information flow technique applied to satellite observations and reanalysis data.
- Analyzed global land areas to identify SSM impacts on precipitation.
- Investigated the roles of sensible heat and evapotranspiration in coupling pathways.
Main Results:
- Identified significant local SSM impacts on precipitation across approximately 16% of global land.
- Discovered eight coupling hotspots, with SH-mediated pathways dominant globally.
- Noted exceptions in African hotspots where evapotranspiration-mediated pathways prevail, linked to moisture and boundary layer variability.
- Found that strong coupling correlates with high SSM variability, especially for SSM-SH-P.
Conclusions:
- Most CMIP6 models inadequately represent observed SSM-P coupling patterns.
- Only a few models accurately captured the variability-causality relationship derived from ERA5 data.
- Proposed process-based metrics for enhancing climate model evaluation regarding land-atmosphere interactions.
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