Méndez et al. (2025) Impacts of Spatial and Temporal Station Availability on Gridded Precipitation Products in Central America

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

Identification

• Journal: Earth and Space Science
• Year: 2025
• Date: 2025-12-01
• Authors: Ana Isabel González Méndez, Diego Pons, Talia G. Anderson, Irma Ayes Rivera, Kevin J. Anchukaitis
• DOI: 10.1029/2025ea004720

Research Groups

Climate Science and Hydrology Research Groups; Regional Meteorological Service Agencies in Central America.

Short Summary

This study evaluates the performance of four gridded precipitation products (CHIRPS, GPCC, CRU, ERA5-Land) against in situ station data across Central America, finding CHIRPS to be the most accurate and highlighting the critical impact of station density on precipitation trend detection in data-sparse regions.

Objective

• To evaluate the performance of four gridded precipitation products (CHIRPS v2, GPCC Full Data Monthly Product v2022, CRU TS 4.07, and ERA5-Land reanalysis) against a network of weather stations across Central America.
• To examine how station coverage and density affect the detection of precipitation trends.

Study Configuration

• Spatial Scale: Central America
• Temporal Scale: Long-term trends (specific period not detailed in abstract)

Methodology and Data

• Models used:
  • Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) v2
  • Global Precipitation Climatology Centre (GPCC) Full Data Monthly Product v2022
  • Climatic Research Unit (CRU) TS 4.07
  • ERA5-Land (ERA5-L) reanalysis
• Data sources:
  • Network of in situ weather stations across Central America, compiled from regional meteorological service agencies.
  • Methodologies included a point (station)-to-pixel comparison and a grid-by-grid spatial decorrelation analysis.

Main Results

• CHIRPS consistently outperformed ERA5-Land, GPCC, and CRU across standard statistical metrics, including correlation coefficient, bias, and root mean square error.
• CRU exhibited the largest spatial decorrelation distances, suggesting an inflated spatial coherence likely due to interpolation in data-sparse regions.
• Disagreement was found between the spatial representation of precipitation trends derived from reanalysis-based and observation-based data sets.
• An observed regional drying trend in eastern Honduras and Nicaragua, present in GPCC and CHIRPS products, was found to potentially reflect the influence of a single station rather than a broader, spatially coherent climate signal.

Contributions

• Provides a comprehensive evaluation of major gridded precipitation products specifically for the data-sparse region of Central America.
• Quantifies the impact of spatial station density and temporal data availability on the accuracy of gridded precipitation products and the reliability of trend detection.
• Highlights the potential for misinterpretation of climate signals and trends in regions with limited in situ observations.

Funding

Not specified in the provided abstract.

Citation

@article{Méndez2025Impacts,
  author = {Méndez, Ana Isabel González and Pons, Diego and Anderson, Talia G. and Rivera, Irma Ayes and Anchukaitis, Kevin J.},
  title = {Impacts of Spatial and Temporal Station Availability on Gridded Precipitation Products in Central America},
  journal = {Earth and Space Science},
  year = {2025},
  doi = {10.1029/2025ea004720},
  url = {https://doi.org/10.1029/2025ea004720}
}