Zhou et al. (2026) Benchmarking ozone stress parameterizations in CLM5: a global mechanistic assessment of thresholds and memory effects

Identification

• Journal: Geoscientific model development
• Year: 2026
• Date: 2026-06-25
• Authors: Peng Zhou, Jieming Chou, Li Dan, Jean‐François Lamarque, Muhammad Bilal, Fang Li, Mengting Sun, Rebecca R. Buchholz, Desneiges S. Murray, Zhaoxiang Cao, Jing Peng, Kai Li, Fuqiang Yang, Wei Pan, Jinyan CHEN, Liwen Xing
• DOI: 10.5194/gmd-19-5491-2026

Research Groups

• State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction (ESPDRR), Beijing Normal University, Beijing, China
• Institute of Disaster Risk Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China
• Temperate East Asia Research Center on Global Change, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
• National Center for Atmospheric Research, Boulder, CO, USA
• Climate Modeling and Analysis, LLC, Superior, CO, USA
• Architecture and City Design Department, College of Design and Built Environment, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia
• Center for Aviation and Space Exploration, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia
• College of Ecology and Environment, Xinjiang University, Urumqi, China
• Department of Biology, Boston University, Boston, MA, USA
• School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

Short Summary

This study evaluates the performance of three ozone stress parameterization schemes (Sitch, Lombardozzi, and Li) within the Community Land Model version 5 (CLM5), using a global mechanistically consistent framework. The results show that all parameterizations capture the ozone-induced reduction in gross primary production (GPP) relative to the ozone-free baseline, but their accuracy varies widely.

Objective

• Evaluate the impact of ozone stress on vegetation productivity within the Community Terrestrial Systems Model version 5.3.075 (CTSM 5.3.075)
• Compare the performance of three ozone stress parameterization schemes (Sitch, Lombardozzi, and Li) in CLM5

Study Configuration

• Spatial Scale: Global latitude–longitude grid with a resolution of 1.895° latitude by 2.5° longitude
• Temporal Scale: 30-year simulation spanning from 2005 to 2014, cycling the atmospheric forcing and surface ozone fields three times

Methodology and Data

• Models used: Community Land Model version 5 (CLM5)
• Data sources:
  • CAM-chem simulations of hourly near-surface ozone concentrations for 2005–2014 at 0.9° × 1.25° horizontal resolution with 32 vertical levels
  • MODIS GPP product at 0.05° resolution
  • FLUXNET site fluxes

Main Results

• The Li parameterization scheme and its combinations with the Lombardozzi and Sitch thresholds and functions show some degree of improvement in reducing errors compared to using a single fixed threshold.
• The Lombardozzi parameterization scheme exhibits relatively large errors in some low-latitude bands.

Contributions

• This study provides a comprehensive evaluation of the performance of three ozone stress parameterization schemes within a unified mechanistic framework, addressing the research gap in understanding the relative strengths and weaknesses of these parameterizations.
• The results highlight the importance of considering both ozone flux threshold selection and response function forms in evaluating the accuracy of ozone-stress simulations.

Funding

• This work was supported by the National Natural Science Foundation of China (Grant No. 41875143)

Citation

@article{Zhou2026Benchmarking,
  author = {Zhou, Peng and Chou, Jieming and Dan, Li and Lamarque, Jean‐François and Bilal, Muhammad and Li, Fang and Sun, Mengting and Buchholz, Rebecca R. and Murray, Desneiges S. and Cao, Zhaoxiang and Peng, Jing and Li, Kai and Yang, Fuqiang and Pan, Wei and CHEN, Jinyan and Xing, Liwen},
  title = {Benchmarking ozone stress parameterizations in CLM5: a global mechanistic assessment of thresholds and memory effects},
  journal = {Geoscientific model development},
  year = {2026},
  doi = {10.5194/gmd-19-5491-2026},
  url = {https://doi.org/10.5194/gmd-19-5491-2026}
}