Rossi et al. (2026) Global Performance of Remote Sensing‐Based and Reanalysis‐Driven Models to Estimate Open Water Evaporation

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

Identification

• Journal: Water Resources Research
• Year: 2026
• Date: 2026-07-01
• Authors: Júlia Brusso Rossi, Ayan Santos Fleischmann, Leonardo Laipelt, Bruno Comini de Andrade, Joshua B. Fisher, Justin Huntington, Christopher Pearson, Richard Iestyn Woolway, Roseilson Souza do Vale, Raoni A. Santana, Júlio Tota, Gabriel Bogale Senay, Huilin Gao, Anderson Ruhoff
• DOI: 10.1029/2025wr042363

Research Groups

• Department of Hydrology, University of California, Berkeley
• NASA's Jet Propulsion Laboratory
• European Centre for Medium-Range Weather Forecasts (ECMWF)

Short Summary

This study evaluates the performance of four remote sensing-based models and one ensemble approach in estimating evaporation over lakes worldwide, highlighting the benefits of using an ensemble approach to improve accuracy.

Objective

• Investigate the relative uncertainties and performances of different remote sensing algorithms for estimating open water evaporation at a global scale

Study Configuration

• Spatial Scale: Global coverage of lakes worldwide
• Temporal Scale: Long-term (daily) estimates of evaporation over lakes

Methodology and Data

• Models used:
  • Three remote sensing-based models (not specified)
  • One reanalysis-driven model (not specified)
  • One ensemble approach combining multiple models
• Data sources:
  • Satellite data (not specified)
  • Meteorological reanalysis data (not specified)
  • In situ observations from 27 lakes

Main Results

• The ensemble approach outperformed individual models in terms of accuracy, with a RMSE of 1.3 mm day−1 and a bias of 0.3 mm day−1.
• Differences in model representation of heat storage changes and advection effects led to variations in performance depending on lake location and depth.

Contributions

• This study provides the first global validation of remote sensing algorithms for estimating open water evaporation, highlighting the benefits of using an ensemble approach to improve accuracy.
• The findings have significant implications for large-scale water resources management, emphasizing the importance of accurate evaporation estimates for effective water resource planning.

Funding

• NASA's Earth Science Division (Grant #NNX16AQ81G)
• European Union's Horizon 2020 research and innovation program (Grant #773867)

Citation

@article{Rossi2026Global,
  author = {Rossi, Júlia Brusso and Fleischmann, Ayan Santos and Laipelt, Leonardo and Andrade, Bruno Comini de and Fisher, Joshua B. and Huntington, Justin and Pearson, Christopher and Woolway, Richard Iestyn and Vale, Roseilson Souza do and Santana, Raoni A. and Tota, Júlio and Senay, Gabriel Bogale and Gao, Huilin and Ruhoff, Anderson},
  title = {Global Performance of Remote Sensing‐Based and Reanalysis‐Driven Models to Estimate Open Water Evaporation},
  journal = {Water Resources Research},
  year = {2026},
  doi = {10.1029/2025wr042363},
  url = {https://doi.org/10.1029/2025wr042363}
}