Preprints
https://doi.org/10.5194/egusphere-2026-350
https://doi.org/10.5194/egusphere-2026-350
24 Feb 2026
 | 24 Feb 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Benchmarking ozone stress parameterizations in CLM5: a global mechanistic assessment of thresholds and memory effects

Peng Zhou, Jieming Chou, Li Dan, Jean-François Lamarque, Muhammad Bilal, Fang Li, Mengting Sun, Rebecca Buccholz, Desneiges Murray, Zhaoxiang Cao, Jing Peng, Kai Li, Fuqiang Yang, Wei Pan, Jinyan Chen, and Liwen Xing

Abstract. Tropospheric ozone remains a critical but uncertain driver of terrestrial productivity loss, and land surface models (LSMs) diverge markedly in how they represent vegetation ozone stress. We conduct a global, mechanistically consistent evaluation of three prominent ozone stress parameterization schemes – Sitch, Lombardozzi, and Li – within the Community Land Model version 5 (CLM5). Using unified meteorological and ozone forcing from CAM-chem and GSWP3.1, we designed five experiments to isolate the roles of ozone flux threshold selection and response function form. Model output is benchmarked against MODIS and FLUXNET gross primary production (GPP) across spatial gradients, biomes, and among plant functional types (PFTs). All parameterizations capture the ozone–induced reduction in GPP relative to the ozone-free baseline, but their accuracy varies widely. The Li scheme – featuring PFT-specific thresholds and separate nonlinear responses for photosynthesis and stomatal conductance – best agrees with observed GPP patterns across scales. In contrast, the Lombardozzi scheme produces much larger reductions in high-flux regions. Analysis reveals that the structures of ozone response functions and memory-decay mechanisms primarily determine improvements in GPP simulation. Our results support a shift toward ozone parameterizations that couple stomatal flux with canopy phenology, dynamic water constraints, and regionally calibrated thresholds. These findings provide a transferable framework for quantifying ozone–carbon coupling in LSMs and highlight priorities for improving terrestrial biosphere models under atmospheric change.

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Peng Zhou, Jieming Chou, Li Dan, Jean-François Lamarque, Muhammad Bilal, Fang Li, Mengting Sun, Rebecca Buccholz, Desneiges Murray, Zhaoxiang Cao, Jing Peng, Kai Li, Fuqiang Yang, Wei Pan, Jinyan Chen, and Liwen Xing

Status: open (until 21 Apr 2026)

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Peng Zhou, Jieming Chou, Li Dan, Jean-François Lamarque, Muhammad Bilal, Fang Li, Mengting Sun, Rebecca Buccholz, Desneiges Murray, Zhaoxiang Cao, Jing Peng, Kai Li, Fuqiang Yang, Wei Pan, Jinyan Chen, and Liwen Xing
Peng Zhou, Jieming Chou, Li Dan, Jean-François Lamarque, Muhammad Bilal, Fang Li, Mengting Sun, Rebecca Buccholz, Desneiges Murray, Zhaoxiang Cao, Jing Peng, Kai Li, Fuqiang Yang, Wei Pan, Jinyan Chen, and Liwen Xing

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Short summary
We assessed the impact of ozone damage representations in a land-surface model on simulations of vegetation productivity. Results varied depending on how ozone effects were triggered and how vegetation recovery was modeled. Schemes that incorporated vegetation-specific thresholds and memory effects on photosynthesis and water loss more accurately reflected spatial patterns, indicating directions for enhancing model realism and improving projections of ecosystem responses to ozone pollution.
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