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Carbon cycle feedbacks represent large uncertainties in climate change projections, and the response of soil carbon to climate change contributes the greatest uncertainty to this. Future changes in soil carbon depend on changes in litter and root inputs from plants and especially on reductions in the turnover time of soil carbon (τs) with warming. An approximation to the latter term for the top one metre of soil (ΔCs,τ) can be diagnosed from projections made with the CMIP6 and CMIP5 Earth System Models (ESMs), and is found to span a large range even at 2 °C of global warming (-196 ± 117 PgC). Here, we present a constraint on ΔCs,τ, which makes use of current heterotrophic respiration and the spatial variability of τs inferred from observations. This spatial emergent constraint allows us to halve the uncertainty in ΔCs,τ at 2 °C to -232 ± 52 PgC.

In the version of this Article originally published, a parallelization coding problem, which meant that a subset of model grid cells were subjected to erroneous updating of atmospheric gas concentrations, resulted in incorrect calculation of atmospheric CO2 for these grid cells, and therefore underestimation of the carbon uptake by land through vegetation growth and eventual increases to soil carbon stocks. Having re-run the simulations using the corrected code, the authors found that the original estimates of the impact of the natural wetland methane feedback were overestimated. The permafrost and natural wetland methane feedback requires lower permissible emissions of 9–15% to achieve climate stabilization at 1.5 °C, compared with the original published estimate of 17–23%. The Article text, Table 1 and Fig. 3 have been updated online to reflect the revised numerical estimates. The Supplementary Information file has also been amended, with Supplementary Figs 6, 7, 8 and 9 replaced with revised versions produced using the corrected model output. As the strength of feedbacks remain significant, still require inclusion in climate policy and are nonlinear with global warming, the overall conclusions of the Article remain unchanged.

Scenarios that limit global warming to below 2 °C by 2100 assume significant land-use change to support large-scale carbon dioxide (CO2) removal from the atmosphere by afforestation/reforestation, avoided deforestation, and Biomass Energy with Carbon Capture and Storage (BECCS). The more ambitious mitigation scenarios require even greater land area for mitigation and/or earlier adoption of CO2 removal strategies. Here we show that additional land-use change to meet a 1.5 °C climate change target could result in net losses of carbon from the land. The effectiveness of BECCS strongly depends on several assumptions related to the choice of biomass, the fate of initial above ground biomass, and the fossil-fuel emissions offset in the energy system. Depending on these factors, carbon removed from the atmosphere through BECCS could easily be offset by losses due to land-use change. If BECCS involves replacing high-carbon content ecosystems with crops, then forest-based mitigation could be more efficient for atmospheric CO2 removal than BECCS.

Global methane emissions from natural wetlands and carbon release from permafrost thaw have a positive feedback on climate, yet are not represented in most state-of-the-art climate models. Furthermore, a fraction of the thawed permafrost carbon is released as methane, enhancing the combined feedback strength. We present simulations with an inverted intermediate complexity climate model, which follows prescribed global warming pathways to stabilization at 1.5 or 2.0 °C above pre-industrial levels by the year 2100, and which incorporates a state-of-the-art global land surface model with updated descriptions of wetland and permafrost carbon release. We demonstrate that the climate feedbacks from those two processes are substantial. Specifically, permissible anthropogenic fossil fuel CO2 emission budgets are reduced by 17–23% (47–56 GtC) for stabilization at 1.5 °C, and 9–13% (52–57 GtC) for 2.0 °C stabilization. In our simulations these feedback processes respond more quickly at temperatures below 1.5 °C, and the differences between the 1.5 and 2 °C targets are disproportionately small. This key finding holds for transient emission pathways to 2100 and does not account for longer-term implications of these feedback processes. We conclude that natural feedback processes from wetlands and permafrost must be considered in assessments of transient emission pathways to limit global warming.

To understand the importance of methane on the levels of carbon emission reductions required to achieve temperature goals, a processed-based approach is necessary rather than reliance on the transient climate response to emissions. We show that plausible levels of methane (CH4) mitigation can make a substantial difference to the feasibility of achieving the Paris climate targets through increasing the allowable carbon emissions. This benefit is enhanced by the indirect effects of CH4 on ozone (O3). Here the differing effects of CH4 and CO2 on land carbon storage, including the effects of surface O3, lead to an additional increase in the allowable carbon emissions with CH4 mitigation. We find a simple robust relationship between the change in the 2100 CH4 concentration and the extra allowable cumulative carbon emissions between now and 2100 (0.27 ± 0.05 GtC per ppb CH4). This relationship is independent of modelled climate sensitivity and precise temperature target, although later mitigation of CH4 reduces its value and thus methane reduction effectiveness. Up to 12% of this increase in allowable emissions is due to the effect of surface ozone. We conclude early mitigation of CH4 emissions would significantly increase the feasibility of stabilising global warming below 1.5 °C, alongside having co-benefits for human and ecosystem health.

Achieving climate targets requires mitigation against climate change but also understanding of the response of land and ocean carbon systems. In this context, global soil carbon stocks and their response to environmental changes are key. This paper quantifies the global soil carbon feedbacks due to changes in atmospheric CO 2 , and the associated climate changes, for Earth system models (ESMs) in CMIP6. A standard approach is used to calculate carbon cycle feedbacks, defined here as soil carbon-concentration (βs) and carbon-climate (γs) feedback parameters, which are also broken down into processes which drive soil carbon change. The sensitivity to CO 2 is shown to dominate soil carbon changes at least up to a doubling of atmospheric CO 2. However, the sensitivity of soil carbon to climate change is found to become an increasingly important source of uncertainty under higher atmospheric CO 2 concentrations. [ABSTRACT FROM AUTHOR]

Achieving climate targets requires mitigation against climate change, but also understanding of the response of land and ocean carbon systems. In this context, global soil carbon stocks and its response to environmental changes is key. This paper quantifies the global soil carbon feedback to changes in atmospheric CO2, and associated climate changes, for Earth system models (ESMs) in CMIP6. A standard approach is used to calculate carbon cycle feedbacks, defined here as soil specific carbon-concentration (βs) and carbon-climate (γs) feedback parameters. The sensitivity to CO2 is shown to dominate soil carbon changes at least up to a doubling of atmospheric CO2. However, the sensitivity of soil carbon to climate change is found to become an increasingly important source of uncertainty under higher atmospheric CO2 concentrations. [ABSTRACT FROM AUTHOR]

Reliable estimates of soil carbon change are required to determine the carbon budgets consistent with the Paris Agreement climate targets. This study evaluates projections of soil carbon during the 21st century in Coupled Model Intercomparison Project Phase 6 (CMIP6) Earth system models (ESMs) under a range of atmospheric composition scenarios. In general, we find a reduced spread of changes in global soil carbon (ΔCs) in CMIP6 compared to the previous CMIP5 model generation. However, similar reductions were not seen in the derived contributions to ΔCs due to both increases in plant net primary productivity (NPP, named ΔCs,NPP) and reductions in the effective soil carbon turnover time (τs , named ΔCs,τ). Instead, we find a strong relationship across the CMIP6 models between these NPP and τs components of ΔCs , with more positive values of ΔCs,NPP being correlated with more negative values of ΔCs,τ. We show that the concept of "false priming" is likely to be contributing to this emergent relationship, which leads to a decrease in the effective soil carbon turnover time as a direct result of NPP increase and occurs when the rate of increase in NPP is relatively fast compared to the slower timescales of a multi-pool soil carbon model. This finding suggests that the structure of soil carbon models within ESMs in CMIP6 has likely contributed towards the reduction in the overall model spread in future soil carbon projections since CMIP5. [ABSTRACT FROM AUTHOR]

Reliable estimates of soil carbon change are required to determine the carbon budgets consistent with the Paris climate targets. This study evaluates projections of soil carbon during the 21st century in CMIP6 Earth System Models (ESMs) under a range of atmospheric composition scenarios. In general, we find a reduced spread of changes in global soil carbon (Δ Cs) in CMIP6 compared to the previous CMIP5 model generation. However, similar reductions were not seen in the derived contributions to Δ Cs due to both increases in plant Net Primary Productivity (NPP, named Δ Cs , NPP) and reductions in the effective soil carbon turnover time (τ s , named Δ Cs,τ). Instead, we find a strong relationship across the CMIP6 models between these NPP and τ s components of Δ Cs , with more positive values of Δ Cs , NPP being correlated with more negative values of Δ Cs,τ. We show that this emergent relationship is the result of 'false priming', which leads to a decrease in the effective soil carbon turnover time as a direct result of NPP increase and occurs when the rate of increase of NPP is relatively fast compared to the slower timescales of a multipool soil carbon model. The inclusion of more soil carbon models with multiple pools in CMIP6 compared to CMIP5, therefore seems to have contributed towards the reduction in the overall model spread in future soil carbon projections. [ABSTRACT FROM AUTHOR]

Northern peatland stores a large amount of organic soil carbon and is considered to be one of the most significant CH4 sources among wetlands. The default wetland CH4 emission scheme in JULES (land surface model of the UK Earth System model) only takes into account the CH4 emissions from inundated areas in a simple way. However, it is known that the processes for peatland CH4 emission are complex. In this work, we coupled the process-based peatland CH4 emission model HIMMELI (HelsinkI Model of MEthane buiLd-up and emIssion for peatlands) with JULES (JULES-HIMMELI) by taking the HIMMELI input data from JULES simulations. Firstly, the soil temperature, water table depth (WTD) and soil carbon simulated by JULES, as well as the prescribed maximum leaf area index (LAI) in JULES were evaluated against available datasets at the studied northern wetland sites. Then, the simulated CH4 emissions from JULES and JULES-HIMMELI simulations were compared against the observed CH4 emissions at these sites. Moreover, sensitivities of CH4 emissions to the rate of anoxic soil respiration (anoxic Rs), surface soil temperature and WTD were investigated. Results show that JULES can well represent the magnitude and seasonality of surface (5–10 cm) and relatively deep (34–50 cm) soil temperatures, whereas the simulated WTD and soil carbon density profiles show large deviations from the site observations. The prescribed maximum LAI in JULES was within one standard deviation of the maximum LAIs derived from the Sentinel-2 satellite data for Siikaneva, Kopytkowo and Degerö sites, but lower for the other three sites. The simulated CH4 emissions by JULES have much smaller inter-annual variability than the observations. However, no specific simulation setup of the coupled model can lead to consistent improvements in the simulated CH4 emissions for all the sites. When using observed WTD or modified soil decomposition rate, there were only improvements in simulated CH4 fluxes at certain sites or years. Both simulated and observed CH4 emissions at sites strongly depend on the rate of anoxic Rs, which is the basis of CH4 emission estimates in HIMMELI. By excluding the effect from the rate of anoxic Rs on CH4 emissions, it is found that the Rs-log-normalized CH4 emissions (log normalization of the ratio of CH4 emission to anoxic Rs rate) show similar increasing trends with increased surface soil temperature from both observations and simulations, but different trends with raised WTD which may due to the uncertainty in simulated O2 concentration in HIMMELI. In general, we consider the JULES-HIMMELI model is more appropriate in simulating the wetland CH4 emissions than the default wetland CH4 emission scheme in JULES. Nevertheless, in order to improve the accuracy of simulated wetland CH4 emissions with the JULES-HIMMELI model, it is still necessary to better represent the peat soil carbon and hydrologic processes in JULES and the CH4 production and transportation processes in HIMMELI, such as plant transportation of gases, seasonality of parameters controlling oxidation and production, and adding microbial activities. [ABSTRACT FROM AUTHOR]

Most Land Surface Models (LSMs), the land components of Earth system models (ESMs), include representation of N limitation on ecosystem productivity. However only few of these models have incorporated phosphorus (P) cycling. In tropical ecosystems, this is likely to be particularly important as N tends to be abundant but the availability of rock-derived elements, such as P, can be very low. Thus, without a representation of P cycling, tropical forest response in areas such as Amazonia to rising atmospheric CO2 conditions remains highly uncertain. In this study, we introduced P dynamics and its interactions with the N and carbon (C) cycles into the Joint UK Land Environment Simulator (JULES). The new model (JULES-CNP) includes the representation of P stocks in vegetation and soil pools, as well as key processes controlling fluxes between these pools. We evaluate JULES-CNP at the Amazon nutrient fertilization experiment (AFEX), a low fertility site, representative of about 60 % of Amazon soils. We apply the model under ambient CO2 and elevated CO2. The model is able to reproduce the observed plant and soil P pools and fluxes under ambient CO2. We estimate P to limit net primary productivity (NPP) by 24 % under current CO2 and by 46 % under elevated CO2. Under elevated CO2, biomass in simulations accounting for CNP increase by 10 % relative to at contemporary CO2, although it is 5 % lower compared with CN and C-only simulations. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low fertility soils. [ABSTRACT FROM AUTHOR]

Microtopography can be a key driver of heterogeneity in the ground thermal and hydrological regime of permafrost landscapes. In turn, this heterogeneity can influence plant communities, methane fluxes and the initiation of abrupt thaw processes. Here we have implemented a two-tile representation of microtopography in JULES (the Joint UK Land Environment Simulator), where tiles are representative of repeating patterns of elevation difference. We evaluate the model against available spatially resolved observations at four sites, gauge the importance of explicitly representing microtopography for modelling methane emissions and quantify the relative importance of model processes and the model's sensitivity its parameters. Tiles are coupled by lateral flows of water, heat and redistribution of snow. A surface water store is added to represent ponding. The model is parametrised using characteristic dimensions of landscape features at sites. Simulations are performed of two Siberian polygon sites, Samoylov and Kytalyk, and two Scandinavian palsa sites, Stordalen and Iškoras. The model represents the observed differences between greater snow depth in hollows vs raised areas well. The model also improves soil moisture for hollows vs the non-tiled configuration (‘standard JULES') though the raised tile remains drier than observed. For the two palsa sites, it is found that drainage needs to be impeded from the lower tile, representing the non-permafrost mire, to achieve the observed soil saturation. This demonstrates the need for the landscape-scale drainage to be correctly modelled. Causes of moisture heterogeneity between tiles are decreased runoff from the low tile, differences in snowmelt, and high to low-tile water flow. Unsaturated flows between tiles are negligible, suggesting the adequacy of simpler water-table based models of lateral flow in wetland environments. The modelled differences in snow depths and soil moistures between tiles result in the lower tile soil temperatures being warmer for palsa sites. When comparing the soil temperatures for July at 20 cm depth, the difference in temperature between tiles, or ‘temperature splitting', is smaller than observed (3.2 vs 5.5 °C). The mean temperature of the two tiles remains approximately unchanged (+0.4 °C) vs standard JULES, and lower than observations. Polygons display small (0.2 °C) to zero temperature splitting, in agreement with observations. Consequently, methane fluxes are near identical (+0 to 9 %) to those for standard JULES for polygons, though can be greater than standard JULES for palsa sites (+10 to 49 %). Through a sensitivity analysis we identify the parameters resulting in the greatest uncertainty in modelled temperature. We find that at the sites tested, varying the parameters can result in the modelled July temperature splitting being at most 0.9 or 3 °C larger than observed for palsa or polygon sites respectively. Varying the palsa elevation between 0.5 and 3 m has little effect on modelled soil temperatures, showing that having only two tiles can still be a valid representation of sites with a large variability of palsa elevations. Lateral conductive fluxes, while small, reduce the temperature splitting by ~1 °C, and correspond to the order of observed lateral degradation rates in peat plateau regions, indicating possible application in an area-based thaw model. [ABSTRACT FROM AUTHOR]

Peatlands have often been neglected in Earth System Models (ESMs). Where they are included, they are usually represented via a separate, prescribed grid cell fraction that is given the physical characteristics of a peat (highly organic) soil. However, in reality soils vary on a spectrum between purely mineral soil (no organic material), and purely organic soil, typically with an organic layer of variable thickness overlying mineral soil below. They are also dynamic, with organic layer thickness and its properties changing over time. Neither the spectrum of soil types nor their dynamic nature can be captured by current ESMs. Here we present a new version of an ESM land surface scheme (Joint UK Land Environment Simulator, JULES) where soil organic matter accumulation - and thus peatland formation, degradation and stability - is integrated in the vertically-resolved soil carbon scheme. We also introduce the capacity to track soil carbon age as a function of depth in JULES, and compare this to measured peat age-depth profiles. This scheme simulates dynamic feedbacks between the soil organic material and its thermal and hydraulic characteristics. We show that draining the peatlands can lead to significant carbon loss along with soil compaction and changes in peat properties. However, negative feedbacks can lead to the potential for peatlands to rewet themselves following drainage. These ecohydrological feedbacks can also lead to peatlands maintaining themselves in climates where peat formation would not otherwise initiate in the model, i.e. displaying some degree of resilience. The new model produces similar results to the original model for mineral soils, and realistic profiles of soil organic carbon for peatlands. In particular the best performing configurations had root mean squared error (RMSE) in carbon density for peat sites of 7.7-16.7 kgC m−3 depending on climate zone, when compared against typical peat profiles based on 216 sites from a global dataset of peat cores. This error is considerably smaller than the soil carbon itself (around 30-60 kgC m−3) and reduced by 35-80 % compared with standard JULES. The RMSE at mineral soil sites is also smaller in JULES-Peat than JULES itself (reduced by ~30-50 %). Thus JULES-Peat can be used as a complete scheme that simulates both organic and mineral soils. It does not require any additional input data and introduces minimal additional variables to the model. This provides a new approach for improving the simulation of organic and peatland soils, and associated carbon-cycle feedbacks in ESMs, which other land surface models could follow. [ABSTRACT FROM AUTHOR]

Understanding future changes in the terrestrial carbon cycle is important for reliable projections of climate change and impacts on ecosystems. It is known that nitrogen could limit plants' response to increased atmospheric carbon dioxide and is therefore important to include in Earth System Models. Here we present the implementation of the terrestrial nitrogen cycle in the JULES land surface model (JULES-CN). Two versions are discussed - the one implemented within the UK Earth System Model (UKESM1) which has a bulk soil biogeochemical model and a development version which resolves the soil biogeochemistry with depth. The nitrogen cycle is based on the existing carbon cycle in the model. It represents all the key terrestrial nitrogen processes in an efficient way. Biological fixation and nitrogen deposition are external inputs, and loss occurs via leaching and a bulk gas loss parameterisation. Nutrient limitation reduces carbon-use efficiency (CUE - ratio of net to gross primary productivity) and can slow soil decomposition. We show that ecosystem level limitation of net primary productivity by nitrogen is consistent with observational estimates and that simulated carbon and nitrogen pools and fluxes are comparable to the limited available observations. The impact of N limitation is most pronounced in northern mid-latitudes. The introduction of a nitrogen cycle improves the representation of interannual variability of global net ecosystem exchange which was much too pronounced in the carbon cycle only versions of JULES (JULES-C). It also reduces the CUE and alters its response over the twentieth century and limits the CO2-fertilisation effect, such that the simulated current day land carbon sink is reduced by about 0.5 Pg C yr-1. The inclusion of a prognostic land nitrogen scheme marks a step forward in functionality and realism for the JULES and UKESM models. [ABSTRACT FROM AUTHOR]

Scenarios avoiding global warming greater than 1.5 or 2 °C, as stipulated in the Paris Agreement, may require the combined mitigation of anthropogenic greenhouse gas emissions alongside enhancing negative emissions through approaches such as afforestation/reforestation (AR) and biomass energy with carbon capture and storage (BECCS). We use the JULES land-surface model coupled to an inverted form of the IMOGEN climate emulator to investigate mitigation scenarios that achieve the 1.5 or 2 °C warming targets of the Paris Agreement. Specifically, we characterise the global and regional effectiveness of land-based (BECCS and/or AR) and anthropogenic methane (CH4) emission mitigation, separately and in combination, on the anthropogenic fossil fuel carbon dioxide emission budgets (AFFEBs) to 2100, using consistent data and socio-economic assumptions from the IMAGE integrated assessment model. The analysis includes the effects of the methane and carbon-climate feedbacks from wetlands and permafrost thaw, which we have shown previously to be significant constraints on the AFFEBs. Globally, mitigation of anthropogenic CH4 emissions has large impacts on the anthropogenic fossil fuel emission budgets, potentially offsetting (i.e. allowing extra) carbon dioxide emissions of 188-212 GtC. Methane mitigation is beneficial everywhere, particularly for the major CH4-emitting regions of India, USA and China. Land-based mitigation has the potential to offset 51-100 GtC globally, but both the effectiveness and the preferred land-management strategy (i.e., AR or BECCS) have strong regional dependencies. Additional analysis shows extensive BECCS could adversely affect water security for several regions. Our results highlight the extra potential CO2 emissions that can occur, while still keeping global warming below key warming thresholds, by investment in regionally appropriate mitigation strategies. [ABSTRACT FROM AUTHOR]