Spezza et al. (2025) Intercomparison of Gauge-Based, Reanalysis and Satellite Gridded Precipitation Datasets in High Mountain Asia: Insights from Observations and Discharge Data

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

Identification

• Journal: Climate
• Year: 2025
• Date: 2025-12-17
• Authors: Alessia Spezza, Guglielmina Diolaiuti, Davide Fugazza, Maurizio Maugeri, Veronica Manara
• DOI: 10.3390/cli13120253

Research Groups

Not explicitly provided in the paper text.

Short Summary

This study comprehensively evaluates five gridded precipitation datasets (ERA5, HARv2, GPCC, APHRODITE, PERSIANN-CDR) over High Mountain Asia from 1983–2007, finding that reanalysis products generally outperform others in capturing spatial patterns and hydrological consistency, though no single dataset is optimal for all applications.

Objective

• To provide a comprehensive evaluation of five major gridded precipitation datasets (ERA5, HARv2, GPCC, APHRODITE, and PERSIANN-CDR) across the entire High Mountain Asia domain (25–40° N, 70–100° E) over the period 1983–2007.

Study Configuration

• Spatial Scale: High Mountain Asia (25–40° N, 70–100° E).
• Temporal Scale: 1983–2007 (25 years).

Methodology and Data

• Models used: The study evaluates the performance of five gridded precipitation datasets: ERA5, HARv2, GPCC, APHRODITE, and PERSIANN-CDR. The evaluation methodology includes spatial intercomparison, validation against ground stations, and assessment against observed river discharge.
• Data sources: Gridded precipitation datasets (ERA5, HARv2, GPCC, APHRODITE, PERSIANN-CDR), ground station observations, observed river discharge data.

Main Results

• Reanalysis products (ERA5, HARv2) better capture spatial precipitation patterns, particularly along the Himalayas and Kunlun range.
• HARv2 more accurately represents elevation-dependent gradients in precipitation.
• Gauge-based (GPCC, APHRODITE) and satellite-derived (PERSIANN-CDR) datasets exhibit smoother fields and weaker orographic responses.
• In catchment-scale evaluations, reanalysis products show superior performance.
• ERA5 achieves the lowest bias, highest Kling–Gupta Efficiency, and best water-balance consistency among the evaluated datasets.
• GPCC and PERSIANN-CDR consistently underestimate river discharge.
• APHRODITE performs worst overall across the evaluation metrics.
• No single dataset is optimal for all applications; gauge-based datasets and PERSIANN-CDR are suitable for localized climatology in well-instrumented areas.
• Reanalysis products offer the best compromise between spatial realism and hydrological consistency for large-scale modeling in high-altitude regions with limited observations.

Contributions

• Provides a comprehensive, domain-wide, and long-term evaluation of multiple gridded precipitation datasets across High Mountain Asia, a region critical for water resources but challenging for precipitation estimation.
• Compares dataset performance using a multi-faceted approach, including spatial intercomparison, validation against ground stations, and assessment of hydrological consistency against observed river discharge.
• Offers practical guidance on the strengths and weaknesses of different dataset types (reanalysis, gauge-based, satellite-derived) for specific applications in data-scarce, high-altitude environments.

Funding

Not explicitly provided in the paper text.

Citation

@article{Spezza2025Intercomparison,
  author = {Spezza, Alessia and Diolaiuti, Guglielmina and Fugazza, Davide and Maugeri, Maurizio and Manara, Veronica},
  title = {Intercomparison of Gauge-Based, Reanalysis and Satellite Gridded Precipitation Datasets in High Mountain Asia: Insights from Observations and Discharge Data},
  journal = {Climate},
  year = {2025},
  doi = {10.3390/cli13120253},
  url = {https://doi.org/10.3390/cli13120253}
}