Changes in the land surface can drive large responses in the atmosphere on local, regional, and global scales. Surface properties control the partitioning of energy within the surface energy budget to fluxes of shortwave and longwave radiation, sensible and latent heat, and ground heat storage. Changes in surface energy fluxes can impact the atmosphere across scales through changes in temperature, cloud cover, and large-scale atmospheric circulation. We test the sensitivity of the atmosphere to global changes in three land surface properties: albedo, evaporative resistance, and surface roughness. We show the impact of changing these surface properties differs drastically between simulations run with an offline land model, compared to coupled land–atmosphere simulations that allow for atmospheric feedbacks associated with land–atmosphere coupling. Atmospheric feedbacks play a critical role in defining the temperature response to changes in albedo and evaporative resistance, particularly in the extratropics. More than 50% of the surface temperature response to changing albedo comes from atmospheric feedbacks in over 80% of land areas. In some regions, cloud feedbacks in response to increased evaporative resistance result in nearly 1 K of additional surface warming. In contrast, the magnitude of surface temperature responses to changes in vegetation height are comparable between offline and coupled simulations. We improve our fundamental understanding of how and why changes in vegetation cover drive responses in the atmosphere, and develop understanding of the role of individual land surface properties in controlling climate across spatial scales—critical to understanding the effects of land-use change on Earth’s climate.

Abstract. Changes in forest cover have a strong effect on climate through the alteration of surface biogeophysical and biogeochemical properties that affect energy, water and carbon exchange with the atmosphere. To quantify biogeophysical and biogeochemical effects of deforestation in a consistent setup, nine Earth system models (ESMs) carried out an idealized experiment in the framework of the Coupled Model Intercomparison Project, phase 6 (CMIP6). Starting from their pre-industrial state, models linearly replace 20×106 km2 of forest area in densely forested regions with grasslands over a period of 50 years followed by a stabilization period of 30 years. Most of the deforested area is in the tropics, with a secondary peak in the boreal region. The effect on global annual near-surface temperature ranges from no significant change to a cooling by 0.55 ∘C, with a multi-model mean of -0.22±0.21 ∘C. Five models simulate a temperature increase over deforested land in the tropics and a cooling over deforested boreal land. In these models, the latitude at which the temperature response changes sign ranges from 11 to 43∘ N, with a multi-model mean of 23∘ N. A multi-ensemble analysis reveals that the detection of near-surface temperature changes even under such a strong deforestation scenario may take decades and thus longer than current policy horizons. The observed changes emerge first in the centre of deforestation in tropical regions and propagate edges, indicating the influence of non-local effects. The biogeochemical effect of deforestation are land carbon losses of 259±80 PgC that emerge already within the first decade. Based on the transient climate response to cumulative emissions (TCRE) this would yield a warming by 0.46 ± 0.22 ∘C, suggesting a net warming effect of deforestation. Lastly, this study introduces the “forest sensitivity” (as a measure of climate or carbon change per fraction or area of deforestation), which has the potential to provide lookup tables for deforestation–climate emulators in the absence of strong non-local climate feedbacks. While there is general agreement across models in their response to deforestation in terms of change in global temperatures and land carbon pools, the underlying changes in energy and carbon fluxes diverge substantially across models and geographical regions. Future analyses of the global deforestation experiments could further explore the effect on changes in seasonality of the climate response as well as large-scale circulation changes to advance our understanding and quantification of deforestation effects in the ESM frameworks.

Vegetation influences the atmosphere in complex and nonlinear ways, such that large-scale changes in vegetation cover can drive changes in climate on both local and global scales. Large-scale land surface changes have been shown to introduce excess energy to one hemisphere, causing a shift in atmospheric circulation on a global scale. However, past work has not quantified how the climate response scales with the area of vegetation. Here, the response of climate to linearly increasing the area of forest cover in the northern midlatitudes is systematically evaluated. This study shows that the magnitude of afforestation of the northern midlatitudes determines the local climate response in a nonlinear fashion, and the authors identify a threshold in vegetation-induced cloud feedbacks—a concept not previously addressed by large-scale vegetation manipulation experiments. Small increases in tree cover drive compensating cloud feedbacks, while latent heat fluxes reach a threshold after sufficiently large increases in tree cover, causing the troposphere to warm and dry, subsequently reducing cloud cover. Increased absorption of solar radiation at the surface is driven by both surface albedo changes and cloud feedbacks. This study shows how atmospheric cross-equatorial energy transport changes as the area of afforestation is incrementally increased. The results highlight the importance of considering both local and remote climate effects of large-scale vegetation change and explore the scaling relationship between changes in vegetation cover and resulting climate impacts.

Regional-scale tree die-off events driven by drought and warming and associated pests and pathogens have occurred recently on all forested continents and are projected to increase in frequency and extent with future warming. Within areas where tree mortality has occurred, ecological, hydrological and meteorological consequences are increasingly being documented. However, the potential for tree die-off to impact vegetation processes and related carbon dynamics in areas remote to where die-off occurs has rarely been systematically evaluated, particularly for multiple distinct regions within a given continent. Such remote impacts can occur when climate effects of local vegetation change are propagated by atmospheric circulation-the phenomena of 'ecoclimate teleconnections'. We simulated tree die-off events in the 13 most densely forested US regions (selected from the 20 US National Ecological Observatory Network [NEON] domains) and found that tree die-off even for smaller regions has potential to affect climate and hence Gross Primary Productivity (GPP) in disparate regions (NEON domains), either positively or negatively. Some regions exhibited strong teleconnections to several others, and some regions were relatively sensitive to tree loss regardless of what other region the tree loss occurred in. For the US as a whole, loss of trees in the Pacific Southwest-an area undergoing rapid tree die-off-had the largest negative impact on remote US GPP whereas loss of trees in the Mid-Atlantic had the largest positive impact. This research lays a foundation for hypotheses that identify how the effects of tree die-off (or other types of tree loss such as deforestation) can ricochet across regions by revealing hot-spots of forcing and response. Such modes of connectivity have direct applicability for improving models of climate change impacts and for developing more informed and coordinated carbon accounting across regions.

Variations in the reflective properties of the bulk material that comprises the surface of landdominated planets will affect the planetary energy balance by interacting differently with incident radiation from the host star. Furthermore, low-mass cool stars, such as nearby M8V dwarf TRAPPIST-1, emit a significant fraction of their flux in longer wavelengths relative to the Sun in regions where terrestrial materials may exhibit additional variability in albedo. Using the Community Earth System Model (CESM) we investigate the effect of the composition of the land surface and its albedo on planetary climate in the context of spatially homogeneous, entirely land-covered planets with dry atmospheres at the orbital separation of TRAPPIST-1d, TRAPPIST-1e, and TRAPPIST-1f. We use empirically derived spectra of four terrestrial compositional endmembers (granite, calcite, aridisol, and dune sand) and a composite spectrum of TRAPPIST-1 for these simulations and compare these model output to an aquaplanet and several Sol-spectrum control cases. We report a difference of approximately 50 K in global mean surface temperature, variations in atmospheric rotational features, and a reduction in cross-equatorial heat transport between scenarios in which materials with higher albedo in the infrared (calcite and dune sand) were used and those with more absorptive crustal material, such as granite or dry soils. An aquaplanet TRAPPIST-1d scenario results in an unstable runaway greenhouse regime. Therefore, we demonstrate that determining the composition and albedo of continental landmasses is crucial for making accurate determinations of the climate of terrestrial exoplanets.

Increasing concentrations of CO2 in the atmosphere not only influence climate through CO2’s effect as a greenhouse gas but also through its impact on plants. Plants respond to atmospheric CO2 concentrations in several ways that can alter surface energy and water fluxes and thus surface climate, including changes in stomatal conductance, water use, and canopy leaf area. These plant physiological responses are already embedded in most Earth System models, and a robust literature demonstrates that they can affect global-scale temperature. However, the physiological contribution to transient warming has yet to be assessed systematically in Earth System models. Here this gap is addressed using carbon cycle simulations from the 5th and 6th phases of the Coupled Model Intercomparison Project (CMIP) to isolate the radiative and physiological contributions to the transient climate response (TCR), which is defined as the change in globally averaged near-surface air temperature during the 20-year window centered on the time of CO2 doubling relative to pre-industrial CO2 concentrations. In CMIP6 models, the physiological effect contributes 0.12°C (σ: 0.09°C; range: 0.02 - 0.29°C) of warming to the TCR, corresponding to 6.1% of the full TCR (σ: 3.8%; range: 1.4 - 13.9%). Moreover, variation in the physiological contribution to the TCR across models contributes disproportionately more to the inter-model spread of TCR estimates than it does to the mean. The largest contribution of plant physiology to CO2-forced warming – and the inter-model spread in warming – occurs over land, especially in forested regions.

Macrosystems are integrated human-natural systems, in recognition of the fact that virtually every natural system on Earth influences and is influenced by human activities, even over long distances. It is therefore crucial to incorporate inherent properties of broad-scale systems, such as human-nature connectivity and feedbacks at multi-scales, into macrosystems biology studies. Here, we propose the "metacoupling" framework as a macrosystems biology approach. This framework incorporates the study of ecological and socioeconomic dimensions and their interactions within, between, and among adjacent and distant locations. We present examples highlighting that (1) human activities are increasing multi-scale interactions; (2) the increase in frequency and intensity of distant interactions reduces the importance of proximity as a dominant factor connecting systems; and (3) metacoupling generates both ecological and socioeconomic feedbacks, with profound impacts. The metacoupling framework discussed here can advance macrosystems biology, create opportunities for innovative scientific discoveries, and address global challenges.

Changes in land surface albedo and land surface evaporation modulate the atmospheric energy budget by changing temperatures, water vapor, clouds, snow and ice cover, and the partitioning of surface energy fluxes. Here idealized perturbations to land surface properties are imposed in a global model to understand how such forcings drive shifts in zonal mean atmospheric energy transport and zonal mean tropical precipitation. For a uniform decrease in global land albedo, the albedo forcing and a positive water vapor feedback contribute roughly equally to increased energy absorption at the top of the atmosphere (TOA), while radiative changes due to the temperature and cloud cover response provide a negative feedback and energy loss at TOA. Decreasing land albedo causes a northwards shift in the zonal mean intertropical convergence zone (ITCZ). The combined effects on ITCZ location of all atmospheric feedbacks roughly cancel for the albedo forcing; the total ITCZ shift is comparable to that predicted for the albedo forcing alone. For an imposed increase in evaporative resistance that reduces land evaporation, low cloud cover decreases in the northern mid-latitudes and more energy is absorbed at TOA there; longwave loss due to warming provides a negative feedback on the TOA energy balance and ITCZ shift. Imposed changes in land albedo and evaporative resistance modulate fundamentally different aspects of the surface energy budget. However, the pattern of TOA radiation changes due to the water vapor and air temperature responses are highly correlated for these two forcings because both forcings lead to near-surface warming.