Choi et al. (2026) Enhanced seasonal soil moisture forecasts by integrating APCC multi-model ensemble predictions into a land surface model framework

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

Identification

• Journal: Environmental Research Letters
• Year: 2026
• Date: 2026-07-17
• Authors: Min‐Seok Kim, Jin‐Ho Yoon, Hyungjun Kim, Jee‐Hoon Jeong
• DOI: 10.1088/1748-9326/ae8c54

Research Groups

• Joint UK Land Environment Simulator (JULES) team
• National Centers for Environmental Prediction (NCEP)
• APCC Multi-Model Ensemble (MME) participating models

Short Summary

This study presents a seasonal soil moisture prediction system that integrates multi-model ensemble information into an LSM framework, yielding substantial improvements in forecast skill and extending the effective lead time for statistically significant predictions.

Objective

• Investigate the potential of integrating MME information into an LSM framework to improve seasonal soil moisture forecasting

Study Configuration

• Spatial Scale: Global scale with a focus on boreal spring–summer regions
• Temporal Scale: Seasonal timescales, specifically February-initialized hindcasts for 1991–2016

Methodology and Data

• Models used: Joint UK Land Environment Simulator (JULES) driven by NCEP CFSv2 meteorological forecasts and APCC MME temperature and precipitation forecasts
• Data sources: Reanalysis data from ERA-Interim/ERA5 (not explicitly mentioned, but implied)

Main Results

• The MME-corrected forecast (J-MME) outperforms the baseline (J-CFSv2) in predicting boreal spring–summer soil moisture with a global average coefficient of determination (R^2) increase of 0.10–0.12 at three- to four-month lead times
• Improvements driven by precipitation correction in water-limited regions and temperature correction in energy-limited high-latitude regions

Contributions

• This study demonstrates the potential of integrating MME information into an LSM framework for meaningful gains in seasonal soil moisture and drought forecasting, even with limited integration

Funding

• Not explicitly mentioned

Citation

@article{Choi2026Enhanced,
  author = {Choi, Chanhyuk and Kim, Min‐Seok and Yoon, Jin‐Ho and Kim, Hyungjun and Jeong, Jee‐Hoon},
  title = {Enhanced seasonal soil moisture forecasts by integrating APCC multi-model ensemble predictions into a land surface model framework},
  journal = {Environmental Research Letters},
  year = {2026},
  doi = {10.1088/1748-9326/ae8c54},
  url = {https://doi.org/10.1088/1748-9326/ae8c54}
}