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A Benchmark Dataset for Satellite-Based Estimation and Detection of Rain
Simon Pfreundschuh1, Malarvizhi Arulraj2, Ali Behrangi3
1Department of Atmospheric Science, Colorado State University, Fort Collins, USA. simon.pfreundschuh@colostate.edu.
Scientific Data
|January 15, 2026
Summary
A new benchmark dataset, SatRain, has been developed for artificial intelligence (AI) in satellite precipitation retrieval. This dataset enables standardized evaluation of AI models for more accurate global precipitation monitoring.
Area of Science:
- Earth Science
- Meteorology
- Artificial Intelligence
Background:
- Accurate global precipitation tracking is crucial for meteorological research and operations.
- Satellite observations are vital for consistent global precipitation monitoring.
- Lack of a standardized benchmark dataset impedes fair comparison of machine learning methods for satellite precipitation retrieval.
Purpose of the Study:
- To introduce SatRain, the first AI benchmark dataset for satellite-based precipitation detection and estimation.
- To provide a standardized evaluation protocol for machine learning approaches.
- To facilitate the development of next-generation AI models for improved global precipitation estimates.
Main Methods:
- Integration of multi-sensor satellite observations from primary remote sensing platforms.
- Inclusion of high-quality reference precipitation estimates from gauge-corrected ground-based radar composites over the conterminous United States.
- Provision of out-of-distribution testing data from Asia and Europe for robust comparisons.
Main Results:
- SatRain offers a standardized framework for evaluating AI algorithms in satellite precipitation retrieval.
- The dataset enables reproducible comparisons across different machine learning approaches.
- It supports the development of advanced AI models by incorporating diverse sensors and geostationary observations.
Conclusions:
- SatRain addresses the need for a standardized benchmark dataset in satellite precipitation research.
- The dataset is essential for advancing AI-driven precipitation estimation.
- It will contribute to more accurate and reliable global precipitation monitoring.
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