the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Mar 2026
Improving Permafrost Soil Representation in a Dynamic Global Vegetation Model Enhances Predictions of Boreal Forest Carbon Dynamics and Vegetation Structure
Abstract. Boreal forests constitute a major component of the global terrestrial carbon sink, yet how climate-driven permafrost degradation alters their ecosystem carbon dynamics remains poorly constrained. Despite their importance, the persistence of this carbon sink remains highly uncertain, partly due to limitations in Earth system model projections of future carbon dynamics in permafrost-affected regions. Here, we improve the soil module of the LPJ-GUESS model by implementing a deep soil profile (3 m) with refined vertical discretization (30 layers) and explicit ice-impedance effects. The enhanced model (LPJ-GUESS-Cryo) is then used to simulate carbon and hydrothermal dynamics in the climate-sensitive boreal forests of Northeast China. Model evaluation shows that LPJ-GUESS-Cryo substantially improves the simulation of soil hydrothermal dynamics relative to the default configuration. The correlation coefficient for deep soil temperature (1 m) increases from 0.818 to 0.894, while the systematic overestimation of soil water content is effectively corrected, with the bias at 1 m reduced from 0.321 to -0.006. These process-level improvements lead to a more realistic simulation of vegetation composition. The dominance of needleleaf forests is corrected from near-complete saturation to 24.1 %, consistent with observed vegetation patterns. Consequently, biases in carbon estimates are reduced, with simulated net primary productivity decreasing from 583.5 to 560.1 g C m-2 yr-1 and aboveground biomass from 112.9 to 99.0 t ha-1, resulting in better agreement with estimates from satellite-based observations. Model sensitivity analysis indicates that vegetation composition is highly sensitive to changes in soil hydrothermal conditions relative to the control simulation. Pronounced shifts in vegetation composition occur when soil temperature increases exceed 0.6 °C and soil water deficits exceed 0.6 m3 m-3 compared to the default model configuration. Overall, this study highlights that accurately representing permafrost processes in dynamic global vegetation models is critical for reducing uncertainties in high-latitude climate-carbon feedbacks.
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RC1: 'Comment on egusphere-2026-870', Anonymous Referee #1, 13 Apr 2026
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General commentsYang et al. present modifications to the LPJ-GUESS model by introducing a deeper and more discretized soil column and accounting for the influence of soil ice content on water percolation. The model is evaluated at a limited number of sites within a small region. I appreciate the effort involved in modifying and testing a land surface model, and I recognize the challenges associated with implementing new processes and conducting validation.However, I have several concerns regarding the scope, robustness, and physical interpretation of the proposed developments.First, the extent of the model development appears relatively limited. While incorporating the effect of soil ice on percolation is a useful step, it does not fully justify the designation of a “Cryo” version of LPJ-GUESS. Freeze–thaw processes typically influence multiple aspects of land surface dynamics, including soil thermal properties, hydraulic conductivity, and carbon transport. In its current form, the model seems to account for only a subset of these processes, and the representation of freeze–thaw impacts on coupled water–heat dynamics remains incomplete.Second, the evaluation is conducted over a relatively small region with a limited number of observational sites. This raises questions about the robustness and general applicability of the proposed modifications. It would be important to demonstrate whether the model improvements hold across a broader range of environmental conditions.Third, the manuscript lacks a sufficiently detailed physical interpretation of the results. For instance, the impact of increased soil layering and freeze–thaw processes on hydrological and thermal dynamics, as well as their implications for vegetation, are not fully explained. Given the relatively modest model modifications, it is unclear whether the model is capable of supporting such mechanistic interpretations.Specific comments1. The relative contributions of increased soil vertical resolution (e.g., 2 layers vs. 30 layers) and freeze–thaw processes are not clearly separated. It would be useful to quantify their individual and combined effects on soil thermal and hydrological dynamics.2. The functional relationship used to represent ice inhibition of percolation should be illustrated (e.g., with a curve or schematic), to better understand its behavior.3. The manuscript provides detailed information for the Huzhong flux tower site, but much less for the other four sites. A clearer description and comparison of all sites would improve the transparency of the evaluation.4. The simulation protocol is not sufficiently described. For example, what is the simulation length, and were the simulations spun up to equilibrium?5. At L225 and Fig. A1, the simulated soil temperature at 1 m depth at the Huzhong site appears to deviate substantially from observations. This discrepancy seems larger than what could be attributed to observational uncertainty alone and deserves further discussion.6. L242: repeated sentences.7. Fig. 2 suggests that the model modifications reduce soil moisture in the upper layers while increasing it in deeper layers. This redistribution should be discussed and physically interpreted.8. Section 4.1 would benefit from a more mechanistic discussion, including:* the impact of increased soil layering on water and heat transport;* the influence of freeze–thaw processes on these dynamics;* the relative and interactive effects of these two model developments.Given the model setup, such sensitivity analyses should be feasible.9. Fig. A1: The legend appears to have reversed colors for “Observation” and “LPJ-GUESS.” In addition, the impact of the Cryo modification on simulated soil temperature appears limited. Could the authors clarify this point? Also, please clarify what the two lines in panel (d) represent.10. Fig. A4 suggests that the modifications have limited impact on soil temperature but a substantial effect on soil moisture. Are frozen and unfrozen soil water distinguished in this analysis?11. Table B2: From LPJ-GUESS 2L to LPJ-GUESS-Cryo 30L, the correlation coefficient (R) decreases, while RMSD, bias, and MAE improve. This inconsistency should be explained.ReplyCitation: https://doi.org/
10.5194/egusphere-2026-870-RC1 -
RC2: 'Comment on egusphere-2026-870', Anonymous Referee #2, 13 Apr 2026
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Review of “Improving Permafrost Soil Representation in a Dynamic Global Vegetation Model Enhances Predictions of Boreal Forest Carbon Dynamics and Vegetation Structure” by Yang et al.
General comments
In this manuscript, the authors present a refined vertical soil structure in the LPJ-GUESS-Cryo model, which improves the simulation of aboveground biomass and NPP compared to remote sensing estimates within the study region. The paper falls within the journal's scope and addresses a relevant topic: the representation of permafrost-related processes in global vegetation models.
However, the manuscript would benefit from a more detailed discussion on the choice of development approach. While the model improvements are clearly described and shown to enhance performance, the rationale behind methodological choices remains insufficiently explored.
In addition, the analysis did not address potential impacts on soil carbon storage and permafrost carbon emissions from changes in soil hydrothermal dynamics. Providing a more thorough analysis of the methodological choices and their implications - also for belowground processes and on a regional scale - would substantially strengthen the manuscript.
Specific comments
Title: The authors could consider specifying their study region (e.g. boreal forests of Northeast China) to mark that their developments have been tested on a site scale
Figure 1. Please edit the caption, so that it is self-explanatory, e.g. Study area location in Heilongjiang Province and the Inner Mongolia Autonomous Region (left) and land use classification based on X (right).
Table B1-B2. Please add the abbreviations (e.g. MAE) in the table header.
L50: Consider elaborating on (1) why simplified representations are commonly used in DGVMs, and (2) which specific processes limit their ability to simulate cold-region soil hydrothermal dynamics realistically.
L55: Please clarify what is meant by “high climate sensitivity” and “extensive forest cover,” and explain why these characteristics make the study region particularly suitable.
L76: rephrase: the regions has high vegetation cover…
L90. Permafrost and wetland-related processes had been implemented in LPJ-GUESS based on Wania et al 2009a, 2009b (https://doi.org/10.1029/2008GB003412, https://doi.org/10.1029/2008GB003413).
L214. Please rephrase for clarity. e.g. Larger Δ value indicated larger differences between LPJ-GUESS and LPJ-GUESS-Cryo.
L217. What do you mean by “joint hydrothermal perturbations”?
L380. Regarding study limitations: In addition to their impact on soil thermohydrodynamics, it would be interesting to at least mention how these developments affect simulated carbon balance in these permafrost-underlain areas. It would be important to emphasize that although improving the vertical thermodynamics is important, models in general still lack other processes (e.g. vertical soil carbon storage) that challenge the accuracy of simulated vegetation dynamics and carbon fluxes in permafrost underlain regions.
Additionally, the developments would still need to be tested on a broad regional scale (e.g. Pan-Arctic), to ensure the robustness of improvement in soil temperature and carbon balance estimates.
L420. While the authors correctly highlight the importance of improving soil hydrothermal processes, it would be helpful to clarify that the presented developments represent a step forward rather than a comprehensive solution.
Technical corrections
L7: rephrase: e.g. Our model evaluation shows…
L63: Materials and Methods
L64: Study area
L184. Structural changes
L187: made to the model
L241: repeated sentence
L310: “conditions(Gert”
Citation: https://doi.org/10.5194/egusphere-2026-870-RC2
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