the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 May 2026
Consideration of radiation absorption by stems in forests for microclimate modeling
Abstract. Forest canopy models are used to simulate biosphere–atmosphere coupling in global climate models, as well as the microclimate influences of forests at the stand scale. It has recently been shown that wood structures store significant heat following radiation absorption and impact air temperature diurnal patterns inside canopies. Yet, radiation absorption by woody stems is not fully considered in current models. Here we modify the radiative transfer component of the CanVeg2 multilayer canopy model to include radiation absorption by woody stems. We evaluate the model modifications by comparing estimates against a validated 3D ray tracing radiative transfer model parametrized using ground lidar measurements, and against tower observations of albedo in four broadleaf forests. We found a very good agreement between the 1D and 3D models, and a good agreement between models and observations. Our approach provides a tractable and computationally efficient implementation of radiation absorption by woody stems to calculate biomass heat storage in canopy models.
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Status: open (until 03 Jul 2026)
- RC1: 'Comment on egusphere-2026-2201', Anonymous Referee #1, 16 May 2026 reply
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RC2: 'Comment on egusphere-2026-2201', Run Zhong, 06 Jun 2026
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This manuscript presents a potentially useful development for canopy radiative transfer and forest microclimate modelling by modifying the Norman radiative transfer model to explicitly include radiation absorption by woody structures. The topic is relevant to GMD and the problem is important: most canopy and land surface models do not explicitly partition absorbed shortwave radiation between foliage and woody biomass. The proposed development could therefore be valuable for modelling canopy energy balance, biomass heat storage, and within-canopy microclimate.
However, in its current form, I do not think the manuscript yet provides a sufficiently rigorous evaluation of the proposed model development. I therefore recommend acceptance subject to major revisions.
My main concern is that the central process introduced in the paper, namely radiation absorption by woody structures, is not directly validated. The evaluation relies primarily on comparison with the FLiESvox 3D ray-tracing model and on tower-based broadband albedo observations. The comparison with FLiESvox is useful as a model benchmark, but it is not an independent observational validation. Similarly, canopy albedo is an integrated quantity and cannot uniquely constrain the partitioning of absorbed radiation among leaves, wood, and soil. Different combinations of leaf optical properties, bark optical properties, clumping assumptions, and multiple-scattering treatments could potentially produce similar albedo values. Therefore, the current evaluation does not demonstrate that the simulated wood absorption is correct. The authors should substantially revise the wording throughout the manuscript to distinguish model benchmarking from observational validation, and they should explicitly acknowledge that wood absorption is only indirectly evaluated in the present study.
A second major concern is the treatment of the wood clumping index. The manuscript adopts a single value of Omega_w = 0.75, derived from leaf-off light transmission measurements at one temperate deciduous forest, and applies it to all four study sites, including the tropical Pasoh forest. This is a strong assumption. Woody element distribution is likely to vary with forest type, species composition, stand age, crown architecture, branch size distribution, and height within the canopy. A constant, vertically invariant Omega_w is therefore not well justified. At minimum, the manuscript should include a sensitivity analysis showing how the main results change for a plausible range of Omega_w values. Without such an analysis, it is difficult to assess whether the reported agreement with FLiESvox and the improvement in albedo are robust or partly the result of parameter tuning.
Third, the extension of recollision probability theory to broadleaf canopies is insufficiently justified. The implementation appears to have a substantial influence on NIR scattering and albedo, yet the physical basis for applying this treatment to broadleaf foliage is not convincingly established. The manuscript should either provide stronger theoretical and empirical support for this assumption or clearly frame it as an uncertain parameterization. A sensitivity test with and without this treatment, or with alternative strengths of the recollision effect, would be important for determining how much the conclusions depend on this assumption.
The manuscript sometimes presents the agreement between the modified Norman model and FLiESvox too strongly. Since both models use related structural inputs and some shared assumptions, agreement between them should not be interpreted as independent proof of physical correctness. The manuscript should avoid overstatements such as “validated” or “accurately reproduces” unless these claims are clearly limited to the model intercomparison framework. Terms such as “benchmark comparison” or “consistency with the 3D model” would be more appropriate.
The generality of the proposed method remains uncertain. All evaluation sites are broadleaf or broadleaf-dominated forests. The performance of the method in needleleaf forests, mixed forests, sparse canopies, savannas, boreal forests, and leaf-off conditions is not adequately demonstrated. The conclusions and implications for land surface models should therefore be toned down. The method may be promising, but its applicability across plant functional types remains to be tested.
Finally, the reproducibility of the model development should be improved. The manuscript states that data inputs and outputs are available, but the code availability statement appears incomplete, with a GitHub link to be inserted upon acceptance. For a GMD development paper, the model code, documentation, and example configuration should be available during review or at least provided in a clearly accessible archived form. I recommend that the authors provide the modified Norman model code, input files, and scripts necessary to reproduce the key figures before acceptance.
In summary, the manuscript addresses an important problem and proposes a potentially valuable model development. However, the current version relies too heavily on model-to-model comparison, lacks direct or sufficiently constraining observational validation of wood absorption, uses a weakly justified constant wood clumping parameter, and does not adequately explore the sensitivity of the results to key structural parameters. I therefore recommend acceptance subject to major revisions. The paper could become publishable if the authors add key sensitivity analyses, clarify the limits of their validation, improve reproducibility, and substantially moderate their claims.
Citation: https://doi.org/10.5194/egusphere-2026-2201-RC2
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General Comments: Béland et al. developed the CanVeg2 model, which explicitly incorporates within-canopy woody structures and their storage effects on the forest microclimate. By correcting sub-canopy light and heat conditions, this model holds great potential for improving the predictive capabilities of Land Surface Models (LSMs). While the core scientific question is highly relevant, I believe the current version of the manuscript exhibits two major deficiencies that should be addressed before publication.
Major Concerns:
#1.Context-Specific Efficacy and Model Boundary Conditions: Although this study utilizes four distinct sites to demonstrate the superiority of CanVeg2 in simulating microclimate dynamics, the manuscript fails to clarify when and where the inclusion of woody structures is most critical. The authors should explicitly define the environmental or structural thresholds under which CanVeg2 provides the greatest improvement. For instance, if a site is characterized by a high leaf area index (LAI) but a low wood area index (WAI) or low woody biomass density, does CanVeg2 still outperform traditional models? This implies that CanVeg2's advantages may not be universal, but rather highly dependent on the relative dominance of woody structures in regulating the microclimate. A clearer justification of its contextual applicability is needed.
#2.Impact on Carbon-Water Coupling Processes: The authors should conduct sensitivity experiments or diagnostic simulations to evaluate how the inclusion of woody structure parameters alters carbon and water coupling processes within CanVeg2. Specifically, under conditions of high woody biomass density, what is the quantitative difference in gross primary productivity (GPP) and evapotranspiration (ET) when accounting for stem-level radiation absorption versus ignoring it? Investigating these cascading effects on downstream ecohydrological fluxes would substantially strengthen the physical mechanism and value of the model.
Minor comments:
In summary, additional discussions and results regarding the improvement of model performance should be included in the paper to better demonstrate the advancement and superiority of the proposed model.