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Emission budgets are defined as the cumulative amount of anthropogenic CO2 emission compatible with a global temperature-change target. The simplicity of the concept has made it attractive to policy-makers, yet it relies on a linear approximation of the global carbon–climate system’s response to anthropogenic CO2 emissions. Here we investigate how emission budgets are impacted by the inclusion of CO2 and CH4 emissions caused by permafrost thaw, a non-linear and tipping process of the Earth system. We use the compact Earth system model OSCAR v2.2.1, in which parameterizations of permafrost thaw, soil organic matter decomposition and CO2 and CH4 emission were introduced based on four complex land surface models that specifically represent high-latitude processes. We found that permafrost carbon release makes emission budgets path dependent (that is, budgets also depend on the pathway followed to reach the target). The median remaining budget for the 2 °C target reduces by 8% (1–25%) if the target is avoided and net negative emissions prove feasible, by 13% (2–34%) if they do not prove feasible, by 16% (3–44%) if the target is overshot by 0.5 °C and by 25% (5–63%) if it is overshot by 1 °C. (Uncertainties are the minimum-to-maximum range across the permafrost models and scenarios.) For the 1.5 °C target, reductions in the median remaining budget range from ~10% to more than 100%. We conclude that the world is closer to exceeding the budget for the long-term target of the Paris Climate Agreement than previously thought.

Substantial deposits of peat have accumulated since the last glacial. Since peat accumulation rates are rather low, this process was previously neglected in carbon cycle models. For assessments of the global carbon cycle on millennial or even longer timescales, though, the carbon storage in peat cannot be neglected any more. We have therefore developed a dynamic model of wetland extent and peat accumulation in order to assess the influence of peat accumulation on the global carbon cycle. The model is based on the dynamic global vegetation model LPJ and consists of a wetland module and routines describing the accumulation and decay of peat. The wetland module, based on the TOPMODEL approach, dynamically determines inundated area and water table, which change depending on climate. Not all temporarily inundated areas accumulate peat, though, but peat accumulates in permanently inundated areas with rather stable water table position. Peatland area therefore is highly uncertain, and we perform sensitivity experiments to cover the uncertainty range for peatland extent. The peat module describes oxic and anoxic decomposition of organic matter in the acrotelm, i.e., the part of the peat column above the permanent water table, as well as anoxic decomposition in the catotelm, the peat below the summer minimum water table. We apply the model to the period of the last 8000 years, during which the model accumulates 330 PgC as catotelm peat in the peatland areas north of 40° N, with an uncertainty range from 240 PgC to 490 PgC. This falls well within the range of published estimates for the total peat storage in high northern latitudes, considering the fact that these usually cover the total carbon accumulated, not just the last 8000 years we considered in our model experiments. In the model, peat primarily accumulates in Scandinavia and eastern Canada, though eastern Europe and north-western Russia also show substantial accumulation. Modelled wetland distribution is biased towards Eurasia, where inundated area is overestimated, while it is underestimated in North America. Latitudinal sums compare favourably to measurements, though, implying that total areas, as well as climatic conditions in these areas, are captured reasonably, though the exact positions of peatlands are not modelled well. Since modelling the initiation of peatland growth requires a knowledge of topography below peat deposits, the temporal development of peatlands is not modelled explicitly, therefore overestimating peatland extent during the earlier part of our experiments. Overall our results highlight the substantial amounts of carbon taken up by peatlands during the last 8000 years. This uptake would have substantial impacts on the global carbon cycle and therefore cannot be neglected.

The responses of carbon dioxide (CO2) and other climate variables to an emission pulse of CO2 into the atmosphere are often used to compute the Global Warming Potential (GWP) and Global Temperature change Potential (GTP), to characterize the response timescales of Earth System models, and to build reduced-form models. In this carbon cycle-climate model intercomparison project, which spans the full model hierarchy, we quantify responses to emission pulses of different magnitudes injected under different conditions. The CO2 response shows the known rapid decline in the first few decades followed by a millennium-scale tail. For a 100 Gt-C emission pulse added to a constant CO2 concentration of 389 ppm, 25 ± 9% is still found in the atmosphere after 1000 yr; the ocean has absorbed 59 ± 12% and the land the remainder (16 ± 14%). The response in global mean surface air temperature is an increase by 0.20 ± 0.12 °C within the first twenty years; thereafter and until year 1000, temperature decreases only slightly, whereas ocean heat content and sea level continue to rise. Our best estimate for the Absolute Global Warming Potential, given by the time-integrated response in CO2 at year 100 multiplied by its radiative efficiency, is 92.5 × 10−15 yr W m−2 per kg-CO2. This value very likely (5 to 95% confidence) lies within the range of (68 to 117) × 10−15 yr W m−2 per kg-CO2. Estimates for time-integrated response in CO2 published in the IPCC First, Second, and Fourth Assessment and our multi-model best estimate all agree within 15% during the first 100 yr. The integrated CO2 response, normalized by the pulse size, is lower for pre-industrial conditions, compared to present day, and lower for smaller pulses than larger pulses. In contrast, the response in temperature, sea level and ocean heat content is less sensitive to these choices. Although, choices in pulse size, background concentration, and model lead to uncertainties, the most important and subjective choice to determine AGWP of CO2 and GWP is the time horizon.

The end of the African Humid Period about 6,000 years ago was associated with vegetation change and decreased precipitation. Conceptual modelling suggests that the nature of the feedback between climate and vegetation is dependent on vegetation type and diversity. The end of the African Humid Period between 6,000 and 4,000 years ago was associated with large changes in precipitation and vegetation cover. Sediment records from Lake Yoa, Chad, show a gradual decline in precipitation and fluctuation in vegetation over this interval, and have been suggested to demonstrate a weak interaction between climate and vegetation 1 , 2 , 3 . However, interpretation of these data has neglected the potential effects of plant diversity on the stability of the climate–vegetation system. Here we use a conceptual model that represents plant diversity in terms of moisture requirement. Some of the plant types simulated are sensitive to changes in precipitation, which alone would lead to an unstable system with the possibility of abrupt changes. Other plants are more resilient, resulting in a stable system that changes gradually. We demonstrate that plant diversity tends to attenuate the instability of the interaction between climate and sensitive plant types, whereas it reduces the stability of the interaction between climate and less-sensitive plant types. Hence, despite large sensitivities of individual plant types to precipitation, a gradual decline in precipitation and shift in mean vegetation cover can occur. However, we suggest that the system could become unstable if some plant types were removed or introduced, leading to an abrupt regime shift.

Cold‐season methane (CH4) emissions may be poorly constrained in wetland models. We examined cold‐season CH4 emissions simulated by 16 models participating in the Global Carbon Project model intercomparison and analyzed temporal and spatial patterns in simulation results using prescribed inundation data for 2000–2020. Estimated annual CH4 emissions from northern (>60°N) wetlands averaged 10.0 ± 5.5 Tg CH4 yr−1. While summer CH4 emissions were well simulated compared to in‐situ flux measurement observations, the models underestimated CH4 during September to May relative to annual total (27 ± 9%, compared to 45% in observations) and substantially in the months with subzero air temperatures (5 ± 5%, compared to 27% in observations). Because of winter warming, nevertheless, the contribution of cold‐season emissions was simulated to increase at 0.4 ± 0.8% decade−1. Different parameterizations of processes, for example, freezing–thawing and snow insulation, caused conspicuous variability among models, implying the necessity of model refinement. Plain Language Summary Wetlands in the northern high latitudes are a major source of methane (CH4) to the atmosphere, mainly during the warm season. Previously, models have assumed that cold‐season CH4 emissions are low, but recent observations suggest high‐latitude wetlands can be substantial sources even in winter. We compared CH4 emissions simulated by 16 state‐of‐the‐art wetland models, participating in a model intercomparison project with a focus on the cold‐season in northern wetlands. The model simulations indicated that nearly one third of annual emissions were simulated to occur from September to May, and CH4 emissions to the atmosphere were not negligible even under freezing air temperatures, although the results differed greatly among the models. However, field studies suggest cold‐season emissions account for an even larger fraction of annual emissions. These results highlight the contribution of cold‐season emissions to the annual CH4 budget, which future climatic warming is expected to affect severely, and they also show that simulations of cold‐season CH4 emissions from wetlands need to be improved. Key Points Cold‐season methane (CH4) emissions simulated by 16 Global Carbon Project‐CH4 wetland models were analyzed Most models underestimate the cold‐season emissions in comparison with observational data Further model improvement by including cold‐season processes is required to reduce the model bias and uncertainty

The carbon balance of peatlands is predicted to shift from a sink to a source this century. However, peatland ecosystems are still omitted from the main Earth system models that are used for future climate change projections, and they are not considered in integrated assessment models that are used in impact and mitigation studies. By using evidence synthesized from the literature and an expert elicitation, we define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future. We also identify uncertainties and knowledge gaps in the scientific community and provide insight towards better integration of peatlands into modelling frameworks. Given the importance of the contribution by peatlands to the global carbon cycle, this study shows that peatland science is a critical research area and that we still have a long way to go to fully understand the peatland–carbon–climate nexus.Peatlands are impacted by climate and land-use changes, with feedback to warming by acting as either sources or sinks of carbon. Expert elicitation combined with literature review reveals key drivers of change that alter peatland carbon dynamics, with implications for improving models.

Boreal and subarctic peatlands are an important dynamical component of the earth system. They are sensitive to climate change and could either continue to serve as a carbon sink or become a carbon source. Climatic thresholds for switching peatlands from sink to source are not well defined and therefore, incorporating peatlands into Earth system models is a challenging task. Here we introduce a climatic index, warm precipitation excess, to delineate the potential geographic distribution of boreal peatlands for a given climate and landscape morphology. This allows us to explain the present-day distribution of peatlands in Western Siberia, their absence during the Last Glacial Maximum, their expansion during the mid-Holocene and to form a working hypothesis about the trend to peatland degradation in the southern taiga belt of Western Siberia under an RCP 8.5 scenario for the projected climate in year 2100.

Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations. Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the performance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH4 emissions, simulated wetland areas, and CH4 fluxes per unit wetland area and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 ± 0.54 Tg CH4 yr−1), inversions (6.06 ± 1.22 Tg CH4 yr−1), and in situ observations (3.91 ± 1.29 Tg CH4 yr−1) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH4 emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmental driver (inundation or air temperature), unlike those of inversions and more sophisticated forward models; (d) differences in biogeochemical schemes across models had relatively smaller influence over performance; and (e) multiyear or multidecade observational records are crucial for evaluating models' responses to long-term climate change.

Trends in the atmospheric concentration of CO2 during three recent interglacials – the Holocene, the Eemian and Marine Isotope Stage (MIS) 11 – are investigated using an earth system model of intermediate complexity, which we extended with process-based modules to consider two slow carbon cycle processes – peat accumulation and shallow-water CaCO3 sedimentation (coral reef formation). For all three interglacials, model simulations considering peat accumulation and shallow-water CaCO3 sedimentation substantially improve the agreement between model results and ice core CO2 reconstructions in comparison to a carbon cycle set-up neglecting these processes. This enables us to model the trends in atmospheric CO2, with modelled trends similar to the ice core data, forcing the model only with orbital and sea level changes. During the Holocene, anthropogenic CO2 emissions are required to match the observed rise in atmospheric CO2 after 3 ka BP but are not relevant before this time. Our model experiments show a considerable improvement in the modelled CO2 trends by the inclusion of the slow carbon cycle processes, allowing us to explain the CO2 evolution during the Holocene and two recent interglacials consistently using an identical model set-up.

Small-scale surface heterogeneities can influence land-atmosphere fluxes and therefore carbon, water and energy budgets on a larger scale. This effect is of particular relevance for high-latitude ecosystems, because of the great amount of carbon stored in their soils. We introduce a novel micro-topographic model, the Hummock-Hollow (HH) model, which explicitly represents small-scale surface elevation changes. By computing the water table at the small scale, and by coupling the model with a process-based model for soil methane processes, we are able to model the effects of micro-topography on hydrology and methane emissions in a typical boreal peatland. In order to assess the effect of micro-topography on water the balance and methane emissions of the peatland we compare two versions of the model, one with a representation of micro-topography and a classical single-bucket model version, and show that the temporal variability in the model version with micro-topography performs better if compared with local data. Accounting for micro-topography almost triples the cumulative methane flux over the simulated time-slice. We found that the single-bucket model underestimates methane emissions because of its poor performance in representing hydrological dynamics. The HH model with micro-topography captures the spatial dynamics of water and methane fluxes, being able to identify the hotspots for methane emissions. The model also identifies a critical scale (0.01 km2) which marks the minimal resolution for the explicit representation of micro-topography in larger-scale models.