Brobst-Whitcomb et al. (2025) How Do Different Precipitation Products Perform in a Dry-Climate Region?

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

Identification

• Journal: Atmosphere
• Year: 2025
• Date: 2025-12-20
• Authors: Noelle Brobst-Whitcomb, Viviana Maggioni
• DOI: 10.3390/atmos17010005

Research Groups

Not explicitly specified in the provided text.

Short Summary

This study evaluates five satellite- and model-based precipitation products against in situ observations in Palm Desert, Southern California, a dry-climate region, to assess their performance in estimating average daily rainfall and extreme precipitation events. It found WLDAS best for precipitation magnitude estimation but poor for event detection, while IMERG and ERA5-MIN excelled at detection but were less accurate in magnitude.

Objective

• To evaluate the performance of five satellite- and model-based precipitation products (ERA5, MERRA2, WLDAS, IMERG) by comparing them against in situ rain gauge observations in a dry-climate region (Palm Desert, Southern California), focusing on average daily rainfall, extreme precipitation events, precipitation magnitude, and the accuracy of event detection.

Study Configuration

• Spatial Scale: Palm Desert, Southern California, a mountainous, arid, and urban region.
• Temporal Scale: Analysis of average daily rainfall and extreme precipitation events over an unspecified period.

Methodology and Data

• Models used: The fifth generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) (analyzing maximum and minimum precipitation rates separately), the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), the Western Land Data Assimilation System (WLDAS), and the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG).
• Data sources: Satellite- and model-based precipitation products compared against in situ rain gauge observations. Performance was assessed using statistical metrics (bias ratio, mean error, correlation coefficient) and contingency statistics (probability of detection, false alarm rate, missed precipitation fraction, false precipitation fraction).

Main Results

• WLDAS ranked highest in measuring total precipitation and extreme rainfall amounts.
• WLDAS performed the worst in detecting the occurrence of both average and extreme rainfall events.
• IMERG and ERA5-MIN demonstrated the strongest ability to detect the timing of precipitation events.
• IMERG and ERA5-MIN were less accurate in estimating the magnitude of rainfall per event.
• The study highlights a trade-off between accuracy in precipitation magnitude estimation and event detection among different products in dry regions.

Contributions

• Provides valuable insights into the reliability and limitations of various satellite- and model-based precipitation estimation products specifically for dry climate regions, where even minimal rainfall can have significant impacts.
• Addresses the critical need for accurate precipitation estimation in arid areas, which are increasingly vulnerable to intensified precipitation events due to climate change.
• Offers a comprehensive evaluation using a combination of statistical and contingency metrics for both average and extreme precipitation events.

Funding

Not specified in the provided text.

Citation

@article{BrobstWhitcomb2025How,
  author = {Brobst-Whitcomb, Noelle and Maggioni, Viviana},
  title = {How Do Different Precipitation Products Perform in a Dry-Climate Region?},
  journal = {Atmosphere},
  year = {2025},
  doi = {10.3390/atmos17010005},
  url = {https://doi.org/10.3390/atmos17010005}
}