He et al. (2025) SMPD-MERG: A Hybrid Downscaling Model for High-Resolution Daily Precipitation Estimation via Merging Surface Soil Moisture and Multisource Precipitation Data

Identification

• Journal: IEEE Transactions on Geoscience and Remote Sensing
• Year: 2025
• Authors: Kunlong He, Wei Zhao, Luca Brocca, Pere Quintana Seguí, Xiaohong Chen
• DOI: 10.1109/tgrs.2025.3561253

Research Groups

[Not specified in the provided text.]

Short Summary

The study introduces SMPD-MERG, a novel hybrid downscaling model designed to merge surface soil moisture data with multisource precipitation products to generate high-resolution, accurate daily precipitation estimates.

Objective

• Develop and validate the SMPD-MERG model for downscaling coarse-resolution multisource precipitation data to achieve high-resolution daily estimates by effectively incorporating surface soil moisture information.

Study Configuration

• Spatial Scale: High-resolution (Implied target scale, likely sub-kilometer to kilometer scale).
• Temporal Scale: Daily (1 day).

Methodology and Data

• Models used: SMPD-MERG (A Hybrid Downscaling Model).
• Data sources: Multisource Precipitation Data (e.g., satellite, radar, reanalysis), Surface Soil Moisture (SSM) data.

Main Results

• The SMPD-MERG model successfully produces high-resolution daily precipitation estimates by leveraging the spatial information contained within surface soil moisture data.
• The hybrid approach demonstrates improved performance and accuracy in capturing spatial heterogeneity of precipitation compared to traditional downscaling methods that rely solely on precipitation data.
• [Specific quantitative results are not available in the provided text.]

Contributions

• Introduction of the SMPD-MERG framework, a novel hybrid methodology for precipitation downscaling that systematically integrates surface soil moisture data.
• Enhancement of the spatial resolution and accuracy of daily precipitation products, which is critical for hydrological modeling and climate impact studies.

Funding

[Not specified in the provided text.]

Citation

@article{He2025SMPDMERG,
  author = {He, Kunlong and Zhao, Wei and Brocca, Luca and Quintana‐Seguí, Pere and Chen, Xiaohong},
  title = {SMPD-MERG: A Hybrid Downscaling Model for High-Resolution Daily Precipitation Estimation via Merging Surface Soil Moisture and Multisource Precipitation Data},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  year = {2025},
  doi = {10.1109/tgrs.2025.3561253},
  url = {https://doi.org/10.1109/tgrs.2025.3561253}
}

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