Tran et al. (2025) Evaluating reanalysis datasets as meteorological input for estimating reference evapotranspiration in Africa and Southwest Asia

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

Identification

• Journal: Hydrological Sciences Journal
• Year: 2025
• Date: 2025-12-08
• Authors: Bich Ngoc Tran, Suzan Dehati, Solomon Seyoum, Johannes van der Kwast, Graham Jewitt, R. Uijlenhoet, Marloes Mul
• DOI: 10.1080/02626667.2025.2600682

Research Groups

[Information not available in the provided text.]

Short Summary

This study evaluates the accuracy of ERA5, AgERA5, and GEOS5 reanalysis datasets for meteorological input in Africa and Southwest Asia, finding that GEOS5 is less accurate than ERA5 and AgERA5, and all datasets exhibit specific biases in meteorological variables, leading to high reference evapotranspiration (ETo) uncertainty in tropical regions.

Objective

• To evaluate the ERA5, AgERA5, and GEOS5 reanalysis datasets for meteorological input in Africa and Southwest Asia by comparing between data products and with 174 in situ sites, specifically for mapping reference evapotranspiration (ETo).

Study Configuration

• Spatial Scale: Africa and Southwest Asia (large areas).
• Temporal Scale: Recent past to near real-time.

Methodology and Data

• Models used: FAO56 ETo equation (for uncertainty propagation).
• Data sources: ERA5 reanalysis, AgERA5 reanalysis, GEOS5 reanalysis, 174 in situ observation sites.

Main Results

• Inter-comparison revealed non-stationary differences between the reanalysis datasets.
• Temporal inconsistencies were highlighted in the GEOS5 data.
• GEOS5 demonstrated lower accuracy compared with ERA5 and AgERA5 when evaluated against in situ measurements.
• All datasets accurately estimate air temperature and pressure.
• All datasets overestimate windspeed and solar radiation.
• All datasets underestimate vapour pressure.
• The propagation of uncertainty estimates of ERA5 through the FAO56 ETo equation showed particularly high uncertainty in the tropics.

Contributions

• Provides a comprehensive evaluation of three prominent reanalysis datasets (ERA5, AgERA5, GEOS5) for meteorological input in Africa and Southwest Asia, crucial for reference evapotranspiration (ETo) mapping.
• Identifies specific biases (overestimation of windspeed and solar radiation, underestimation of vapour pressure) common across the evaluated reanalysis datasets.
• Quantifies the propagation of uncertainty from reanalysis data through the FAO56 ETo equation, highlighting high uncertainty in tropical regions.
• Emphasizes the critical need for applying multiple uncertainty assessment methods, especially when using reanalysis data in data-scarce regions.

Funding

[Information not available in the provided text.]

Citation

@article{Tran2025Evaluating,
  author = {Tran, Bich Ngoc and Dehati, Suzan and Seyoum, Solomon and Kwast, Johannes van der and Jewitt, Graham and Uijlenhoet, R. and Mul, Marloes},
  title = {Evaluating reanalysis datasets as meteorological input for estimating reference evapotranspiration in Africa and Southwest Asia},
  journal = {Hydrological Sciences Journal},
  year = {2025},
  doi = {10.1080/02626667.2025.2600682},
  url = {https://doi.org/10.1080/02626667.2025.2600682}
}