Lv et al. (2026) Precipitation and soil moisture coupling constrains subseasonal predictability of a prolonged extreme heatwave

Identification

• Journal: Communications Earth & Environment
• Year: 2026
• Date: 2026-02-28
• Authors: Bingjie Lv, Shuguang Wang, Gang Greg Chen, Baoqiang Xiang
• DOI: 10.1038/s43247-026-03341-1

Research Groups

• State Key Laboratory of Severe Weather Meteorological Science and Technology, Nanjing University, Nanjing, China
• Key Laboratory of Mesoscale Severe Weather, Nanjing University, Nanjing, China
• School of Atmospheric Sciences, Nanjing University, Nanjing, China
• Dept of Atmospheric and Oceanic Sciences, University of California, Los Angeles, USA
• NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
• Cooperative Programs for the Advancement of Earth System Science, University Corporation for Atmospheric Research, Boulder, CO, USA

Short Summary

This study investigates the subseasonal predictability of the August 2022 Yangtze River Valley heatwave, finding that precipitation-soil moisture coupling is the primary factor limiting forecast accuracy due to its significant influence on surface temperature.

Objective

• To identify the fundamental processes limiting the subseasonal predictability of prolonged extreme heatwaves, specifically focusing on the August 2022 Yangtze River Valley heatwave.

Study Configuration

• Spatial Scale: Yangtze River Valley (YRV), China
• Temporal Scale: August 2022 (for the extreme heatwave event); Subseasonal to seasonal (S2S) forecast lead times.

Methodology and Data

• Models used: Real-time subseasonal to seasonal (S2S) forecast ensembles, a simple heatwave model (Z-model).
• Data sources: ERA5 reanalysis data, S2S database, MSWEP V2 precipitation data.

Main Results

• Real-time subseasonal to seasonal (S2S) forecast ensembles systematically underestimated the intensity of the August 2022 Yangtze River Valley heatwave.
• Regional precipitation effectively separates high- and low-skill forecasts of surface maximum temperature.
• Quantitative attribution analysis indicates that precipitation, rather than local high-pressure systems, explains most of the ensemble spread in surface temperature.
• Precipitation–soil moisture coupling is identified as the dominant limiting factor for the subseasonal predictability of the heatwave.
• Numerical experiments demonstrated that increased precipitation reduced surface warming by up to approximately 4 °C, while reduced precipitation amplified warming by approximately 2 °C.

Contributions

• Identifies precipitation-soil moisture coupling as a dominant and previously poorly understood limiting factor for subseasonal predictability of prolonged extreme heatwaves.
• Provides quantitative attribution of ensemble spread in surface temperature to precipitation, rather than large-scale circulation anomalies.
• Underscores the critical importance of improving the representation of precipitation processes in models to enhance heatwave predictability.

Funding

• National Natural Science Foundation of China No. 42275055
• National Key R&D Program of China, Project No. 2024YFC3013100

Citation

@article{Lv2026Precipitation,
  author = {Lv, Bingjie and Wang, Shuguang and Chen, Gang Greg and Xiang, Baoqiang},
  title = {Precipitation and soil moisture coupling constrains subseasonal predictability of a prolonged extreme heatwave},
  journal = {Communications Earth & Environment},
  year = {2026},
  doi = {10.1038/s43247-026-03341-1},
  url = {https://doi.org/10.1038/s43247-026-03341-1}
}