wu et al. (2026) Evaluating surface fluxes in WRF using eddy-covariance flux measurements in the Western and Eastern U.S.

Identification

• Journal: Agricultural and Forest Meteorology
• Year: 2026
• Date: 2026-02-03
• Authors: fan wu, Kenneth J. Davis, Li Zhang, Ray G. Anderson, Jason Horne, Sarah Goslee, William Munger, Chenxia Cai, Yu Yan Cui, Zhan Zhao, Min Zhong
• DOI: 10.1016/j.agrformet.2026.111029

Research Groups

• Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, USA
• Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA, USA
• California Air Resources Board, CA, USA
• USDA - Agricultural Research Service (ARS), George E. Brown Jr. Salinity Laboratory, Agricultural Water Efficiency, and Salinity Research Unit, Riverside, CA, USA
• Department of Environmental Sciences, University of California, Riverside, CA, USA
• USDA - Agricultural Research Service (ARS), Pasture Systems & Watershed Management Research Unit, University Park, PA, USA
• Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
• Pennsylvania Department of Environmental Protection, PA, USA
• Environmental Defense Fund, Boston, MA, USA

Short Summary

This study evaluates the Weather Research and Forecasting (WRF) model's surface flux simulations, specifically using the Pleim-Xiu land surface model (PX LSM), against year-long eddy-covariance measurements from 16 sites in the San Joaquin Valley (SJV) and Multi-state Mid-Atlantic (MMA) regions, revealing significant heat flux biases in the SJV primarily linked to irrigation.

Objective

• To evaluate surface fluxes simulated by the Weather Research and Forecasting (WRF) model, using physical configurations adopted by state air quality agencies in California and Pennsylvania, against eddy-covariance flux measurements.

Study Configuration

• Spatial Scale: San Joaquin Valley (SJV) of California and the Multi-state Mid-Atlantic (MMA) region, U.S., utilizing 16 eddy-covariance flux measurement sites across these two regions.
• Temporal Scale: Year-long simulations and measurements, with specific bias analysis for daytime (10:00-16:00 LST) during spring and summer.

Methodology and Data

• Models used: Weather Research and Forecasting (WRF) model coupled with the Pleim-Xiu land surface model (PX LSM).
• Data sources: Year-long eddy-covariance flux measurements from 16 sites.

Main Results

• The Pleim-Xiu land surface model (PX LSM) exhibits substantial heat flux biases in the San Joaquin Valley (SJV) but lacks systematic biases in the Multi-state Mid-Atlantic (MMA).
• In the SJV, the model overestimates daytime (10:00-16:00 LST) sensible heat flux (H) by 260 W m⁻² (274%) and underestimates latent heat flux (LE) by 200 W m⁻² (68%) at irrigated croplands and orchards during spring and summer.
• In the MMA, PX LSM moderately overestimates both H and LE, with stronger partitioning into H over urban surfaces and into LE over vegetation.
• Daytime momentum fluxes are overestimated in both regions, while nighttime biases are inconsistent.
• Heat flux biases in the SJV are strongly associated with irrigation during the growing season.
• In the MMA, model-data residuals are limited to modest errors in the Bowen ratio and depend on land cover.

Contributions

• Provides a comprehensive evaluation of WRF model surface flux simulations, using configurations relevant to state air quality agencies, against extensive year-long eddy-covariance measurements across two distinct and complex U.S. regions.
• Identifies significant, quantitatively large biases in heat fluxes in the San Joaquin Valley, directly linking them to the model's inadequate representation of irrigation during the growing season.
• Highlights the need for improved representation of irrigation and land use in WRF, potentially through satellite remote sensing, to enhance the accuracy of surface flux simulations crucial for air quality modeling.

Funding

No specific funding projects, programs, or reference codes were explicitly listed in the provided paper text.

Citation

@article{wu2026Evaluating,
  author = {wu, fan and Davis, Kenneth J. and Zhang, Li and Anderson, Ray G. and Horne, Jason and Goslee, Sarah and Munger, William and Cai, Chenxia and Cui, Yu Yan and Zhao, Zhan and Zhong, Min},
  title = {Evaluating surface fluxes in WRF using eddy-covariance flux measurements in the Western and Eastern U.S.},
  journal = {Agricultural and Forest Meteorology},
  year = {2026},
  doi = {10.1016/j.agrformet.2026.111029},
  url = {https://doi.org/10.1016/j.agrformet.2026.111029}
}