Liu et al. (2025) Global Evapotranspiration Retrieval Using Fengyun‐3D Passive Microwave Measurements With Genetic Algorithm Optimization

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

Identification

• Journal: Journal of Geophysical Research Atmospheres
• Year: 2025
• Date: 2025-08-22
• Authors: Qingyang Liu, Peng Zhang, Yipu Wang, Jiheng Hu, Rui Li
• DOI: 10.1029/2025jd043823

Research Groups

Not specified in the provided text.

Short Summary

This study developed a new global evapotranspiration product ($ET_{FY3D}$) by using a genetic algorithm to optimize a passive microwave retrieval method based on FY-3D satellite observations.

Objective

• To reduce uncertainties in global terrestrial evapotranspiration (ET) estimation and develop a new global ET product utilizing data from China's Fengyun-3D (FY-3D) satellite.

Study Configuration

• Spatial Scale: Global (0.25° resolution)
• Temporal Scale: 2020–2022

Methodology and Data

• Models used: Machine-learning Genetic Algorithm (GA) used to optimize parameters of a physical-based passive microwave (PMW) ET retrieval method.
• Data sources: FY-3D microwave radiation imager observations, reanalysis data sets, and in situ ET measurements from 207 flux towers across 13 vegetation types.

Main Results

• Improved Accuracy: Compared to the original algorithm, the optimized method reduced bias by 1.07 mm/day and root mean square error (RMSE) by 0.85 mm/day, while increasing the Kling-Gupta efficiency by 0.67.
• Cross-Product Validation: The resulting $ET_{FY3D}$ product showed consistency with established benchmark products, including MODIS, GLEAM, and PML.
• Sensitivity: Analysis indicated that vegetation and humidity parameters are the most critical factors in the retrieval process.

Contributions

• Developed the first independent global ET product based on China's FY-3D low orbit satellite.
• Demonstrated the effectiveness of using AI (Genetic Algorithms) to optimize parameters within physical-based remote sensing retrieval algorithms.

Funding

Not specified in the provided text.

Citation

@article{Liu2025Global,
  author = {Liu, Qingyang and Zhang, Peng and Wang, Yipu and Hu, Jiheng and Li, Rui},
  title = {Global Evapotranspiration Retrieval Using Fengyun‐3D Passive Microwave Measurements With Genetic Algorithm Optimization},
  journal = {Journal of Geophysical Research Atmospheres},
  year = {2025},
  doi = {10.1029/2025jd043823},
  url = {https://doi.org/10.1029/2025jd043823}
}