the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 Mar 2025
A first calibration of the JULES-crop version 7.4 for rice using the novel O3-FACE experiment in China
Abstract. Ozone (O3) pollution poses an escalating threat to rice production and food security in China, with concentrations projected to rise under future climate scenarios. Accurately quantifying O3 impacts on rice is thus crucial for informed agricultural planning. This study is the first to utilise Free Air Concentration Enrichment (FACE) observations specific to rice for calibrating a crop model (JULES-crop) and assessing the impacts of O3. FACE experiments, which involve growing crops under natural field conditions while exposing them to elevated O3 levels, provide an ideal approach for studying the effects of O3 on crops. Utilising data from the only O3-FACE facility dedicated to rice, we calibrated physiological and O3-response parameters in JULES-crop and evaluated the model against additional independent FACE observations. The calibration establishes this as the first crop model refined with ideal open-air field observations, significantly enhancing its capability to simulate rice growth processes and O3-induced yield losses, surpassing the performance of simulations based on the default parameters in JULES-crop. With this newly calibrated model, JULES-crop is now equipped to assess the impacts of O3 on agriculture, offering a valuable tool to inform mitigation strategies.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-4077', Anonymous Referee #1, 08 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2024-4077/egusphere-2024-4077-RC1-supplement.pdf
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RC2: 'Comment on egusphere-2024-4077', Anonymous Referee #2, 29 May 2025
General Comments:
This manuscript presents a novel calibration of the JULES-crop model for rice, incorporating data from a new Free Air Concentration Enrichment (FACE) experiment with elevated ozone (O₃). The use of field-based O₃-FACE data to tune crop-model parameters is timely and important, given increasing O₃ stress on agriculture. The authors outline clear objectives and proceed through logical calibration steps (leaf-photosynthesis, phenology, carbon partitioning, growth, and O₃ response), followed by an evaluation on independent field data. In general, the conclusions—that calibrated parameters improve simulated crop growth and O₃ impacts relative to defaults—are supported by the results. The writing is clear, and the figures convey the key points, but there are some issues that should be addressed.
The authors leverage unique O₃-FACE observations, which is a major strength. The calibration includes tuning of two O₃-response parameters using three planting densities. It would be useful to explain how “high” and “low” sensitivity bounds were chosen (e.g. to bracket the observed RY range) and whether a single “best” set was identified. In the Abstract and Introduction, the authors claim to calibrate “O₃-response parameters”, but the manuscript might clarify that only those two parameters were tuned. More discussion of uncertainties in these parameters and how they affect model outputs would be valuable.
Overall, I find the work to be worthy of publication after revision. The study tackles an important problem (modelling O₃ effects on rice) and makes a valuable contribution. My detailed, section-specific suggestions below should help improve clarity, completeness, and rigour.
Specific Comments:
- In introduction, the motivation is well explained. One phrase could be improved: “Rice is the primary energy source for over half of the world’s population…”. Rice is typically called a staple food or calorie source rather than “energy source.”
- Section 2.1, since JULES-crop’s O₃ damage scheme is central, I suggest briefly summarizing it here or adding a forward reference to Sect.3.1.4. For readers not familiar with JULES-crop, clarify how O₃ effects are implemented (e.g. via reduced assimilation tied to stomatal O₃ flux).
- In Section 2.2, You might add the actual O₃ concentration levels (ambient vs elevated) to quantify “25% higher.”
- The default values of ratio of stem/root nitrogen concentration to leaf nitrogen concentration and calibrated values indicate leaf has more N than stem/root – is this consistent with literature?
- The figures are relevant, but some captions and labelling need improvement. For example, Figure 12’s caption contains a typo (“verses day of year” should be “versus”). Several figure captions should clearly define all symbols, line colours, and panels. The axes and units should be legible. In Fig.12 and 13, the color-coding is explained, but ensure consistency (e.g. in Fig.13 caption “low” and “high” O₃ sensitivity should specify which line is which colour).
- Spelling is inconsistent (e.g. “ozone” vs “O₃”).
- Minor grammatical fixes (e.g. “As green leaves begin to turn yellow…” instead of “As green begin to turn yellow”) would improve readability.
- Ensure all acronyms (LAI, FACE, POD, AOT40, etc.) are defined at first use.
- The section heading “Result” should be plural (Results).
- In Sect.3.1.4, the term “O₃ related parameters were applied” (p.18) could be rephrased more clearly (e.g. “The calibrated O₃-damage parameters were applied”).
In summary, I find this manuscript to be a valuable contribution on calibrating a crop model with novel O₃ data. Addressing the above points will significantly enhance the paper. After revision, it should be suitable for publication in Geoscientific Model Development.
Citation: https://doi.org/10.5194/egusphere-2024-4077-RC2 - AC1: 'Comment on egusphere-2024-4077', Beiyao Xu, 04 Jul 2025
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