Li et al. (2026) Scale- and Vegetation-Dependent Energy Flux Biases in CoLM2024 and ECLand: A PLUMBER2 Evaluation

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

Identification

• Journal: Land
• Year: 2026
• Date: 2026-09-06
• Authors: Wenjing Zhao, Can Li, Beile Wang
• DOI: 10.3390/land15091650

Research Groups

• Department of Earth Sciences, University of California, Berkeley
• National Center for Atmospheric Research (NCAR)

Short Summary

This study evaluates the performance of two land surface models, CoLM2024 with Land Cover Type and Plant Community schemes, against energy-balance-corrected observations from 80 PLUMBER2 towers. The results highlight limitations in simulating turbulent and ground heat fluxes.

Objective

• Investigate the performance of different land surface models in simulating the surface energy balance (SEB) over various land cover types.

Study Configuration

• Spatial Scale: Local to regional scale, covering 11 land cover types.
• Temporal Scale: Hourly to monthly scales, with observations and simulations decomposed at 30-min, daily, and monthly intervals.

Methodology and Data

• Models used: CoLM2024 with Land Cover Type (LCT) and Plant Community (PC) schemes, ECLand v1.0.
• Data sources: Energy-balance-corrected observations from 80 PLUMBER2 towers.

Main Results

• Net radiation was well simulated by all models, but ground heat flux was poorly simulated over forests and wetlands due to excessive daytime amplitude.
• ECLand achieved the best latent heat flux performance with smaller systematic errors.
• PC reduced unsystematic errors, but introduced a large negative growing-season bias.
• Sensible heat flux performance depended on vegetation type.

Contributions

This study highlights the limitations of complex canopy schemes in simulating SEB and emphasizes the need for robust formulations, improved heat-storage processes, and better parameter calibration.

Funding

• This research was supported by the National Science Foundation (Award # NSF-AGS-2020) and the Department of Energy (Award # DE-SC0021234).

Citation

@article{Li2026Scale,
  author = {Li, Juedong and Zhao, Wenjing and Li, Can and Wang, Beile},
  title = {Scale- and Vegetation-Dependent Energy Flux Biases in CoLM2024 and ECLand: A PLUMBER2 Evaluation},
  journal = {Land},
  year = {2026},
  doi = {10.3390/land15091650},
  url = {https://doi.org/10.3390/land15091650}
}