Pellicone et al. (2025) Assessment of Multiple Satellite Precipitation Products over Italy

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

Identification

• Journal: Remote Sensing
• Year: 2025
• Date: 2025-11-20
• Authors: Gaetano Pellicone, Tommaso Caloiero, Roberto Coscarelli, Francesco Chiaravalloti
• DOI: 10.3390/rs17223772

Research Groups

Specific research groups, labs, or departments involved in the study are not detailed in the provided text.

Short Summary

This study evaluated five satellite precipitation products (CHIRPS, GPM, HSAF, PDIRNOW, SM2RAIN) against high-resolution ground data in Italy to address rainfall estimation uncertainties. It found that no single product performs optimally across all metrics, with GPM showing the most balanced performance, and product suitability depending on the intended hydrological application.

Objective

• To assess the performance of five widely used satellite precipitation products (CHIRPS, GPM, HSAF, PDIRNOW, SM2RAIN) against the high-resolution SCIA-ISPRA ground dataset in Italy, identifying their strengths and weaknesses for various hydrological applications.

Study Configuration

• Spatial Scale: Italy, focusing on complex Mediterranean terrains. High-resolution ground data from the SCIA-ISPRA dataset was used for validation.
• Temporal Scale: Daily, seasonal, and annual.

Methodology and Data

• Models used:
  • CHIRPS (infrared–station hybrid retrieval approach)
  • GPM (microwave integration retrieval approach)
  • HSAF (geostationary blending retrieval approach)
  • PDIRNOW (neural-network infrared retrieval approach)
  • SM2RAIN (soil–moisture inversion retrieval approach)
• Data sources:
  • Satellite precipitation products: CHIRPS, GPM, HSAF, PDIRNOW, SM2RAIN.
  • Observation data: High-resolution SCIA-ISPRA ground dataset.

Main Results

• No single satellite precipitation product performs optimally across all evaluation metrics (categorical, continuous, and extreme-event indices).
• GPM demonstrated the most balanced and reliable performance overall.
• PDIRNOW and SM2RAIN showed strong detection capabilities but frequently overestimated precipitation.
• CHIRPS provided conservative estimates with a low rate of false alarms.
• HSAF exhibited less consistent performance, particularly during the winter season.
• Product suitability is application-dependent: detection-oriented products like PDIRNOW are preferable for flood forecasting, while conservative datasets like CHIRPS are better suited for drought monitoring.
• Integrating multiple products or adopting hybrid approaches is recommended to enhance precipitation assessment accuracy over complex Mediterranean terrains.

Contributions

• Provides a comprehensive, multi-metric assessment of five diverse satellite precipitation products in the challenging, complex topographical region of Italy.
• Highlights the trade-offs and application-specific suitability of different satellite precipitation retrieval approaches (infrared–station hybrid, microwave integration, geostationary blending, neural-network infrared, and soil–moisture inversion).
• Offers practical guidance for hydrologists and water resource managers on selecting appropriate satellite precipitation products for specific hydrological applications, such as flood forecasting versus drought monitoring.
• Underscores the value of multi-product integration or hybrid approaches for improving precipitation estimation accuracy in complex terrains.

Funding

Funding information is not provided in the text.

Citation

@article{Pellicone2025Assessment,
  author = {Pellicone, Gaetano and Caloiero, Tommaso and Coscarelli, Roberto and Chiaravalloti, Francesco},
  title = {Assessment of Multiple Satellite Precipitation Products over Italy},
  journal = {Remote Sensing},
  year = {2025},
  doi = {10.3390/rs17223772},
  url = {https://doi.org/10.3390/rs17223772}
}