Forest and bioenergy expansion amplifies climate warming by accelerating regional cloud loss
Abstract. Land use and land cover change (LUCC) can exacerbate cloud-mediated climate warming. However, the long-term response of cloud cover to LUCC remains underexplored, particularly regarding differences between idealized and realistic forest expansion scenarios, as well as between forest and bioenergy expansion. Here, using simulations from the fully coupled Community Earth System Model (CESM), we demonstrate that large-scale idealized afforestation and bioenergy expansion accelerate the loss of low- and mid-level clouds while enhancing high-level clouds, thereby amplifying regional warming hotspots through intensified positive shortwave cloud radiative forcing. In contrast, realistic afforestation yields a net cooling effect. Idealized afforestation drives a pronounced decline in low-level cloud cover (1.14 times globally, 1.52 times over land), followed by bioenergy expansion (1.03 times globally and 1.23 times over land), primarily driven by reduced total precipitable water and relative humidity, as revealed by an interpretable machine learning framework, which identifies biophysical warming of the boundary layer due to albedo-driven surface heating and enhanced sensible heat flux as the dominant mechanism. Forest darkening reduces surface albedo, which increases absorbed solar radiation and elevates sensible heat, thereby drying the boundary layer and suppressing cloud formation. Conversely, realistic afforestation mitigates the loss of low- and mid-level clouds and suppresses boreal warming. Our findings indicate that more forest expansion does not always generate greater climate benefits; the climatic outcome largely depends on the type of land conversion and specific latitude bands, and highlights the critical importance of carefully selecting afforestation areas in the future to achieve positive climate benefits.
Review of “Forest and bioenergy expansion amplifies climate warming by accelerating regional cloud loss” by Liu et al.
This study uses the CESM coupled model to simulate long-term changes in cloud cover and associated climate feedback under scenarios of forest and bioenergy expansion. The topic is relevant, and the ongoing debate on whether afforestation necessarily leads to climate cooling has attracted considerable attention. The manuscript suggests that large-scale afforestation may enhance regional warming by accelerating low-cloud reduction, a finding that is to some extent interesting. It highlights the importance of cloud feedback in land-use decision-making. Overall, I have the following comments.
Major comments:
The interpretation of cloud reduction due to afforestation seems simplified and does not account for several competing land-atmosphere processes associated with afforestation. Forest expansion typically alters not only surface albedo, but also aerodynamic roughness, evapotranspiration, boundary-layer turbulence, and moisture recycling. Increased evapotranspiration may enhance local atmospheric moisture supply, while increased roughness can strengthen turbulent mixing and modify planetary boundary-layer structure. These processes may either promote or suppress low-level cloud maintenance depending on the regional background climate and circulation regime.
Cloud responses may involve substantial non-local influences, including large-scale circulation adjustments, changes in moisture transport pathways, downwind moisture recycling, and land-ocean thermal contrasts. However, the current mechanism explanations remain largely qualitative and focused primarily on local thermodynamic effects, without sufficiently disentangling the relative contributions of competing local and remote processes.
The study points out that the idealized forest expansion leads to a reduction in low-level clouds and an enhancement in high-level clouds. Some papers the authors cited, such as Teuling et al., 2017 and Duveiller et al., 2021, show an enhancement of low-level clouds due to afforestation. It is recommended that the authors discuss the discrepancies. Here, studies reported that deforestation increases cloud cover may be a good option to discuss, such as Xu et al., 2022 and Leung et al., 2024. The authors should also clarify more precisely: is the observed reduction in cloud cover driven by a local biophysical process, or is it dominated by changes in large-scale atmospheric circulation?
The reported increase in high clouds requires a more careful physical explanation, as high clouds are generally considered weakly coupled with local surface perturbations and are primarily controlled by large-scale dynamical and thermodynamic conditions in the upper troposphere. In this context, the manuscript does not sufficiently clarify the pathway through which afforestation can systematically influence high-level cloud fraction. If the simulated high-level cloud response is robust, it likely reflects indirect mechanisms rather than local surface forcing.
This study relies on CESM simulations; however, cloud representation remains one of the largest sources of uncertainty in contemporary climate models. It would be valuable to acknowledge that uncertainties in cloud parameterizations may affect both the magnitude and even the sign of simulated cloud feedback.
Specific comments:
Lines 88-93: It is recommended to discuss recent studies, for example, Tom and Graham, 2026 and Luo et al., 2024, that quantify the relationship between forest loss and changes in cloud albedo, as these are directly relevant to the current study.
Line 227: A wording issue here. Only the CRE in the atmosphere evaluates the influence of clouds on the atmosphere. TOA CRE measures the influence on the Earth-atmosphere system, while surface CRE measures the influence only on the surface.
Line 230: Change “LwCRE” to “lwCRE”.
Line 231: Change “SwCRE” to “swCRE”.
Line 272: Change “LW” to “LW↓”. Change “from the surface” to “at the surface”.
Line 302: 1037 should be 0.1037.
Line 303: BE50 and CTL have the same decline trend for CLDTOT.
Line 314: Does “downward response” refer to a “decreasing trend”?
Fig. S23: Could the authors show the differences between the experiments and the original data? It is currently difficult to identify the tree-cover changes from the maps. In particular, it is unclear whether the REAL and AF50 experiments exhibit distinct changes across different latitudes. Since afforestation at different latitudes can lead to substantially different albedo and surface energy responses, a clearer comparison would help readers better interpret the results.