Abstract. The permafrost region stores ∼1300 PgC, and its response to warming is a significant uncertainty in future climate projections. We assess how the treatment of vegetation dynamics and CO2 fertilisation influences the permafrost carbon feedback (PCF) by performing experiments with the land-surface model ICON-Land. A vertically explicit implementation of the YASSO soil-carbon scheme resolves depth-dependent carbon pools, as well as temperature and moisture controls on decomposition, while a newly introduced cold-adapted shrub plant-functional type (PFT) enables a more realistic description of Arctic vegetation. Using CMIP5-derived climate forcing, we performed nine offline experiments from the year 2020 to 2299 CE under RCP 2.6, 4.5 and 8.5. The experiments isolate the effects of (a) climate warming with fixed 2019 CO2 and vegetation, (b) rising CO2 with constant vegetation cover, and (c) the effects of both rising CO2 and a fully dynamic vegetation. All simulations start from a data-constrained pre-industrial permafrost soil carbon inventory. When vegetation is held static, strong warming (RCP 8.5) alone drives a loss of ∼650 PgC by 2300 CE, turning the permafrost region from a modest sink of carbon into a strong source. Allowing CO2 fertilisation but no vegetation change reduces the loss to ∼250 PgC because enhanced NPP increases litter inputs. In the fully dynamic experiments, shrubification and northward tree expansion dramatically increase aboveground biomass (of up to 199 PgC) and litterfall, limiting soil-C loss to only ~70 PgC. Consequently, total permafrost-region carbon declines by < 100 PgC under RCP 8.5 and even shows a net gain under the low-emission pathways (RCPs 2.6 and 4.5). These results demonstrate that the sign and magnitude of the PCF are highly sensitive to the representation of vegetation dynamics. Dynamic competition among PFTs, CO2-driven NPP enhancement, and the resulting shifts in carbon accumulation together can offset most of the carbon released by thawing soils. Incorporating realistic Arctic vegetation, especially cold-tolerant shrubs, is therefore decisive for reliable projections of the permafrost carbon feedback and its impact on the global carbon cycle.

Wetlands are the largest natural source of atmospheric methane (CH4), yet comprehensive global budgets are typically delayed by years, preventing a timely understanding of CH4 sources, sinks, and trends. To reduce this delay, we present a model emulator-driven framework and accompanying workflow that enable timely, continuous emission updates using a machine-learning emulator to reconstruct spatially explicit monthly emission fields at 1 degrees & times; 1 degrees resolution. We apply this framework to a global dataset of natural vegetated wetland CH4 emissions to extend the most recent Global Methane Budget (GMB; Saunois et al., 2025) record that covers the 2000-2020 emissions through 2025. In the test data (similar to 30 % of the total dataset), the emulator achieved a global R-2 of 0.65 +/- 0.003 (mean +/- 95 % CI, hereafter) and an RMSE of 5.49 +/- 0.12 & times; 10(-3) Tg CH4 yr(-1). The emulator is trained on 35 GMB model estimates, including 22 process-based models and 13 atmospheric inversions, paired with 10 ensemble realizations of 11 gridded climate predictor variables from atmospheric reanalyses. Our results show that the global mean predicted wetland CH4 emissions for 2021-2025 (157.8 +/- 2.4 Tg CH4 yr(-1)) are not significantly higher (similar to 0.05 Tg CH4 yr(-1)) than the 2000-2020 baseline. However, this stability masks a significant hemispheric redistribution of emissions. We detect an increase in Northern Hemisphere (NH) emissions in 2021-2025, with mid- and high-latitudes increasing by 0.76 +/- 0.07 and 0.35 +/- 0.03 Tg CH4 yr(-1), respectively, while the tropics and Southern Hemisphere (SH) extratropics show offsetting negative trends (-0.95 +/- 0.19 and -0.11 +/- 0.02 Tg CH4 yr(-1), respectively). The predicted emissions are able to capture the low emissions in 2023 in South America linked to El Ni & ntilde;o-related drought, as reported by recent studies (Ciais et al., 2026; Quinn et al., 2025). Furthermore, we identify a distinct seasonal amplification of global emission trends that peaks in late boreal summer. This new modeled dataset and operational framework bridge the gap between the latest updated budgets and low-latency monitoring, providing a scalable capacity to frequently update global emission estimates and critical early warnings of regional wetland feedback loops. The data are publicly available at https://doi.org/10.5281/zenodo.18870108 (Li et al., 2026).

Workshop on the Arctic Land-Ocean Carbon Cycle and Its Role in the Remaining What: An international and interdisciplinary workshop brought together about 40 researchers and representatives from policy and the science-policy interface to discuss the Arctic land-ocean carbon cycle and its significance for the remaining global carbon budget. Through keynote presentations and interactive panel discussions, participants assessed the current state of knowledge, identified key research gaps, and formulated concrete recommendations and priorities for future research and policy dialogue.

Over the last 20 000 years, Northern Hemisphere vegetation underwent major shifts in response to orbital changes, rising CO2, and ice sheet retreat. Using the large-scale pollen-based tree cover reconstruction by Schild et al. (2025), we evaluate the performance of the MPI-ESM Earth System Model in simulating tree cover dynamics from the Last Glacial Maximum to the present. Although the model reproduces the broad increase in tree cover during deglaciation and decrease throughout the Holocene, it fails to simulate the mid-Holocene maximum observed in the reconstructions. The model does capture the shift from energy-limited conditions during deglaciation to water-limited conditions in the early to mid-Holocene, and then back to energy-limited conditions in the late Holocene, but regional discrepancies remain substantial. MPI-ESM simulates too much forest in sparsely forested areas and too little forest in densely forested areas, particularly in mid- and high-latitude regions. Statistical analyses indicate that summer temperature dominates simulated high-latitude forests, while precipitation is critical in most other regions, contrasting with reconstructions that highlight cold-season temperature in temperate and boreal forests. Areas of model-data agreement show largely linear responses to climate drivers, whereas regions of disagreement exhibit non-linear dynamics to the temperature of the warmest month and over-sensitivity of the plant-physiological CO2 response. Employing an emulator with a bias-corrected climate reduces the mismatch in the forest steppe transition zones, but does not lead to an overall improvement of the model-data agreement. In particular, the mismatch in the boreal region remains unresolved, suggesting structural limitations in the model. Improving dynamic vegetation models for simulating climatic transitions in both, past and future contexts, requires integrating realistic soil and permafrost processes, dynamic biome thresholds and disturbance regimes. Trait-based approaches could lead to better representation of the vegetation response to climate changes.

The permafrost soils in the northern high latitudes contain about twice as much carbon as the atmosphere. This organic soil matter has accumulated over many thousands of years and is now exposed to anthropogenic warming, which is amplified by a factor of three to four in the Arctic compared to global warming. The thawed organic matter is mineralized and released into the atmosphere as CO2 or CH4, which amplifies ongoing warming (permafrost carbon feedback). In addition, the thawing of permafrost soils leads to changes in land surface hydrology and potential drainage, which could also amplify global warming due to the decrease in summer cloud cover (permafrost cloud feedback). The permafrost changes impact other regions and Earth tipping elements, including tropical forests.Are permafrost feedbacks nonlinear, is there a threshold for global warming above which the feedbacks lead to disproportional increase in carbon thaw? Future projections using Earth system and land surface models suggest a rather linear permafrost response to global warming, but they are mostly based on gradual thawing processes and do not take into account abrupt thawing and extreme events. Numerous processes that lead to abrupt thawing at the local level, such as thermokarst, lake formation and drainage, or surface subsidence, have been neglected in large-scale models to date. We will present the results of model experiments and discuss the potential impact of these missing processes on the nonlinear response, as well as indicators of multistability of carbon and hydrology at different scales. We will also discuss irreversibility of permafrost changes and their response timescales as supported by paleo evidence.

Under changing climatic conditions, the Arctic is undergoing massive changes. Due to Arctic amplification, the Arctic is warming faster than any other region on Earth. The combination of warming and CO2 fertilization leads to increases in productivity and changes in vegetation composition, with shrubs invading the Tundra, and trees also shifting northwards. At the same time, permafrost thaws, adding previously frozen carbon deposits to the active carbon cycle. The net carbon balance resulting from all of these coupled processes is less clear than one might think and requires an integrated modelling approach.We use ICON-Land, the land surface model of the ICON Earth System Model, to investigate changes in the carbon cycle of the permafrost region. We have extended the soil carbon model YASSO by introducing a vertical dimension in order to consider carbon storages in deeper frozen soil layers. Furthermore, we are considering Arctic-specific shrub PFTs in our dynamic vegetation scheme in order to represent the changes in vegetation composition expected in a changing climate, thus allowing a complete assessment of carbon cycle changes.We initialise the soil C pools for the preindustrial climate state from the Northern Circumpolar Soil Carbon Database to insure initial C pool sizes close to measurements. We then determine changes in vegetation composition and soil C storage in transient model experiments following historical and future climate changes under RCPs 2.6, 4.5, and 8.5. Based on these experiments, we quantify the greenhouse gas balance under future climatic conditions. While the permafrost soils lose carbon in all scenarios, productivity increases, especially if the vegetation can adapt to the changed climatic conditions, leading to lower carbon release.

Abstract. Wetlands are the largest natural source of atmospheric methane (CH4), yet comprehensive global budgets are typically delayed by several years, preventing a timely understanding of CH4 sources, sinks, and their trends. To reduce this delay, we present a model emulator-driven framework and accompanying workflow that enable timely, continuous emission updates and applying the framework to a global dataset of natural vegetated wetland CH4 emissions to extend the most recent Global Methane Budget (GMB; Saunois et al., 2025) record through 2025 at monthly 1°x1° resolution. We developed a machine-learning emulator to reconstruct spatially explicit monthly emission fields (global R2 =0.65 ± 0.003 (mean ± 95 % CI, hereafter) and RMSE=5.49 ± 0.12 ×10-3 Tg CH4/year in test data which is ~30 % of the total data). The emulator is trained on 35 GMB model estimates (22 process-based model estimates and 13 atmospheric inversion estimates) paired with 10 ensemble realizations of 11 gridded climate predictor variables from atmospheric reanalyses. While the global mean predicted wetland CH4 emissions for 2021–2025 (157.83 ± 2.38 Tg CH4/year) are only marginally higher (~0.05 Tg CH4/year) than the 2000–2020 baseline, this stability masks a significant hemispheric redistribution of emissions. We detect a surge in Northern Hemisphere emissions in 2021–2025, with mid- and high-latitudes increasing by 0.76 ± 0.07 (z-score: 2.21) and 0.35 ± 0.03 Tg/year (z-score:1.01), respectively, while the tropics and Southern Hemisphere extratropics show offsetting negative trends (-0.95 ± 0.19 and -0.11 ± 0.02 Tg/year with z-scores of -2.81 and -0.34, respectively). The predicted emissions capture the low emissions in 2023 in South America linked to El Niño-related drought, as reported by recent studies (Ciais et al., 2026; Quinn et al., 2025). Post-2020 growth rates of emission anomalies are a magnitude higher than that in 2000–2025, suggesting an intensification of emission variability. Furthermore, we identify a distinct seasonal amplification of global emission growth peaking in late boreal summer. This new dataset and operational framework bridge the gap between latest updated budgets and low-latency monitoring, providing a scalable capacity to frequently update global emission estimates and critical early warnings of regional wetland feedback loops. The data are publicly available at https://doi.org/10.5281/zenodo.18870108 (Li et al., 2026).

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. CH4 is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2), and both emissions and atmospheric concentrations of CH4 have continued to increase since 2007 after a temporary pause. The relative importance of CH4 emissions compared to those of CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH4 yr−1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr−1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr−1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr−1 or ∼ 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr−1 or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr−1 (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH4 yr−1 (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr−1) larger global emissions (669 Tg CH4 yr−1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr−1 in Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH4 yr−1 based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty (∼ 25 %). The total sink of CH4 is estimated at 633 [507–796] Tg CH4 yr−1 by the bottom-up approaches and at 554 [550–567] Tg CH4 yr−1 by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified. For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH4 yr−1 in the top-down budget and 211 [195–231] Tg CH4 yr−1 in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH4 yr−1 in the top-down budget and 120 [117–125] Tg CH4 yr−1 in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH4 yr−1 in the top-down budget and 28 [21–39] Tg CH4 yr−1 in the bottom-up budget. We identify five major priorities for improving the CH4 budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH4 observations at local (e.g. FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024).

Methane is a potent greenhouse gas which has substantially contributed to climate change since the pre-industrial era, second only in importance to carbon dioxide. Due to its short atmospheric lifetime and high global warming potential, methane emissions have disproportionately large impacts on near-term climate change. Beyond its direct role as a greenhouse gas, methane also has other important implications for climate, human health, air quality and vegetation, largely due to its impact on tropospheric ozone. Thus, reducing methane emissions has been identified as a key policy lever for delaying the worst impacts of near-term climate change with expected co-benefits for health and air quality. The most notable of these efforts is the Global Methane Pledge which aims to achieve a 30% reduction in global anthropogenic methane emissions by 2030 as compared to 2020. And yet, in many respects, methane mitigation has been overlooked relative to other climate mitigation strategies. Existing modelling evidence for the estimating the potential climate benefits of methane mitigation rely extensively on idealised climate emulators or comprehensive modelling studies based on a limited number of models and ensemble members. Both approaches have important limitations. Hence, there is a pressing need for a co-ordinated intermodel comparison project which uses state-of-the-art ESMs in which all modelling groups prescribe identical reductions in methane concentrations or emissions, all modelling groups use the same baseline scenario, and sufficient ensemble members are simulated to investigate the broader climate and health impacts of methane mitigation. MethaneMIP has been envisioned to undertake these tasks.In this talk I will introduce the MethaneMIP protocol and the two new methane reduction scenarios ‘Technical Measures’ and ‘Ambitious’, which are both branched from SSP2-4.5 and cover the period 2020-2050. The overarching aim of MethaneMIP is to provide a policy-relevant state-of-the-art estimate of the climate and health impacts of methane mitigation, and a robust quantification of the uncertainties, as well as furthering our understanding of methane’s role in the climate system. Over ten modelling centres from across the world are participating in MethaneMIP, with simulations for the core MethaneMIP experiments currently underway. For the first time, I will present the preliminary results of MethaneMIP as pertaining to the research questions it was set up to address, including: What are the best estimates of the expected climate and health benefits of plausible methane mitigation by mid-century? Which near-term climate events projected to occur may be delayed or avoided by curbing methane emissions? What are potential impacts of successful implementation of the Global Methane Pledge? When should we expect the climate or health signal from reduced methane to be detectable in the presence of internal variability? I will finish by discussing the implications of MethaneMIP for climate policy, as well as introducing the flagship emissions-driven MethaneMIP simulations which will be performed later this year.

Pollen records are the most widespread archive for past climate and vegetation changes, offering valuable insights into Earth’s environmental history. These records provide a unique opportunity to evaluate Earth System Models. In recent years, the availability of quantitative plant cover reconstructions on a continental scale has increased, exemplified by the consistent dataset of REVEALS-based reconstructions provided by Schild et al. (2024) for the entire Northern Hemisphere.We use this data set for comparison with the changes in tree cover simulated by the Max Planck Institute Earth System Model (MPI-ESM) for the last 20,000 years. While the overall agreement between model and data is promising, there are significant regional discrepancies. Notable differences emerge in boreal regions such as Alaska/Western Canada and Siberia, where the model predicts a delayed and weaker tree cover increase during the deglaciation. Conversely, in temperate forest-steppe transition zones, the model shows an earlier and stronger tree cover expansion, balancing out the Northern Hemispheric mean change.However, systematic biases complicate the interpretation of this comparison. For instance, the model tends to simulate excessively cold conditions in boreal latitudes, while the reconstructions likely overestimate tree cover in these regions. As a result, the agreement in vegetation history remains uncertain leaving the comparison of absolute values between reconstructions and model results questionable. An EOF analysis highlights common modes of vegetation changes over the last 20,000 years in MPI-ESM and reconstructions, deepening our understanding despite these uncertainties.References: Schild, L., Ewald, P., Li, C., Hébert, R., Laepple, T., and Herzschuh, U.: LegacyVegetation 1.0: Global reconstruction of vegetation composition and forest cover from pollen archives of the last 50 ka, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-486, in review, 2024

When considering high latitude regions, one of the striking characteristics is the abundance of surface water in comparison to lower latitudes. This difference is not just limited to the total area covered by surface water, but it also extends to the size distribution of water bodies: While surface water in lower latitudes most often occurs in the form of larger lakes or rivers, high latitude regions often display a wide variety of surface water features, ranging from small puddles to huge lakes. Considering the climatic and carbon cycle consequences of lower latitude large water bodies in land models is relatively straightforward – they can be considered static, be prescribed from observations, and described using dedicated submodels. However, considering surface water in the high latitudes comprehensively is substantially more challenging, as a much larger range of sizes needs to be considered, parts of which will not be available from observations. Furthermore, due to the dynamics of permafrost, these cannot be considered static any more and need to be treated dynamically. To better represent high latitude regions in the ICON-Land land surface model, part of the ICON-ESM Earth System Modelling framework, we are developing a representation of multiple scales of water bodies, ranging from large lakes to small puddles, as well as areas of water-saturated soil. The smaller-scale features are of particular interest, as they do not just affect the exchange of water and energy between surface and atmosphere, but also have large impacts on the carbon cycle and methane emissions. To do this, we employ a statistical distribution function of water body sizes, allowing us to obtain energy, water, carbon and methane fluxes for water features of all sizes. We will present our novel modelling framework and show first results covering selected Arctic locations.

Removing carbon dioxide (CO2) from the atmosphere is required for mitigating climate change. Large-scale direct air capture combined with injecting CO2 into geological formations could retain carbon long-term, but demands a substantial amount of energy, pipeline infrastructure, and suitable sites for gaseous storage. Here, we study Earth system impacts of modular, sun-powered process chains, which combine direct air capture with (electro)chemical conversion of the captured CO2 into liquid or solid sink products and subsequent product storage (sDACCCS). Drawing on a novel explicit representation of CO2 removal in a state-of-the-art Earth system model, we find that these process chains can be renewably powered and have minimal implications for the climate and carbon cycle. However, to stabilize the planetary temperature two degrees above pre-industrial levels, CO2 capturing, conversion, and associated energy harvest demand up to 0.46% of the global land area in a high-efficiency scenario. This global land footprint increases to 2.82% when assuming present-day technology and pushing to the bounds of removal. Mitigating historical emission burdens within individual countries in this high-removal scenario requires converting an area equivalent to 40% of the European Union's agricultural land. Scenarios assuming successful technological development could halve this environmental burden, but it is uncertain to what degree they could materialize. Therefore, ambitious decarbonization is vital to reduce the risk of land use conflicts if efficiencies remain lower than expected.

Over the last hundreds of millennia, natural rhythms in Earth's astronomical motions triggered large-scale climate changes and led periodically to humid conditions in much of northern Africa. Known as African Humid Periods (AHPs), such times sustained vast river networks, vegetation, wildlife, and prehistoric settlements. The mechanisms, extent, and timing of the changes remain poorly constrained. Although AHPs along glacial cycles are recognizable in marine sediment records, the related land cover changes are difficult to reconstruct due to the scarcity of proxy data over the continent. Moreover, most available information covers only the latest AHP during the Holocene. Here we use a comprehensive Earth system model to look at additional, much earlier, possible cases of AHPs. We simulate the full last glacial cycle, aiming to reproduce the last four AHPs as seen in available proxies. The simulated AHPs seem in broad agreement with geological records, especially in terms of timing and relative strength. We focus on the simulated vegetation coverage in northern Africa, and we detect a dominant change pattern that seems to scale linearly with known climate forcing variables. We use such scaling to approximate northern African vegetation fractions over the last eight glacial cycles. Although the simple linear estimation is based on a single mode of vegetation variability (that explains about 70 % of the variance), it helps to discuss some broad-scale spatial features that had only been considered for the Holocene AHP. Extending the climate simulation several millennia into the future reveals that such (palaeo-based) pattern scaling breaks when greenhouse gases (GHGs) become a stronger climate change driver.

The continually evolving large ice sheets present in the Northern Hemisphere during the last glacial cycle caused significant changes to drainage pathways both through directly blocking rivers and through glacial isostatic adjustment. These changing drainage pathways drove the formation, evolution and (sometimes catastrophic) drainage of large glacial lakes such as Lake Agassiz. Studies have shown this changing hydrology had a significant impact on the ocean circulation through changing the pattern of freshwater discharge into the oceans. A coupled Earth system model simulation of the last glacial cycle thus requires a lake model that uses a set of river pathways and lakes that evolve with Earth's changing orography. Here, we present a method for dynamically modelling lakes (building on previous work on dynamically modelling rivers) by applying predefined corrections to an evolving fine-scale orography (accounting for the changing ice sheets and isostatic rebound) each time the river directions and lakes basins are recalculated. The lakes are delineated from this corrected fine scale orography and water level within each lake is modelled within the JSBACH land surface model. Lake inflow and outflow are linked to the existing river flow model within JSBACH while evaporation from the lake surface is linked to the ECHAM atmospheric general circulation model.

To meet the Paris Agreement temperature goal, allowable carbon emissions in the future are tightly limited. It is very likely that the 1.5°C temperature limit will be at least temporarily exceeded (overshoot) under an emission pathway following current climate policies and actions. Peatlands store large amounts of soil carbon, the destabilization of which could potentially cause large amplifying feedback on global warming. Using the reduced-complexity Earth system model OSCAR v3.1.2 and a new peat carbon module, we assessed whether carbon emissions from northern peatlands triggered by climate change will increase the chance and intensity of temperature overshoot. We found that, although northern peatlands continue to accumulate carbon, they represent positive feedback under climate change through their high CH4 emissions. For a 1°C increase in peak temperature anomaly, emissions from peatlands further contribute to the peak temperature by 0.02 (0.01-0.02) °C. Considering northern peatlands would lead to a reduction in the carbon budget by about 40 (16-60) GtCO2, or 8.6% for 1.5°C, and a reduction of about 105 (45-166) GtCO2 reduction (or 4.2% relative decrease) for 2.5°C. Our findings highlight the importance of properly accounting for northern peatland emissions for estimating climate feedbacks, especially under overshoot scenarios.

Due to ongoing climate change, methane (CH4) emissions from vegetated wetlands are projected to increase during the 21st century, challenging climate mitigation efforts aimed at limiting global warming. However, despite reports of rising emission trends, a comprehensive evaluation and attribution of recent changes remains limited. Here we assessed global wetland CH4 emissions from 2000–2020 based on an ensemble of 16 process-based wetland models. Our results estimated global average wetland CH4 emissions at 158 ± 24 (mean ± 1σ) Tg CH4 yr−1 over a total annual average wetland area of 8.0 ± 2.0×106 km2 for the period 2010–2020, with an average increase of 6–7 Tg CH4 yr−1 in 2010–2019 compared to the average for 2000–2009. The increases in the four latitudinal bands of 90–30° S, 30° S–30° N, 30–60° N, and 60–90° N were 0.1–0.2, 3.6–3.7, 1.8–2.4, and 0.6–0.8 Tg CH4 yr−1, respectively, over the 2 decades. The modeled CH4 sensitivities to temperature show reasonable consistency with eddy-covariance-based measurements from 34 sites. Rising temperature was the primary driver of the increase, while precipitation and rising atmospheric CO2 concentrations played secondary roles with high levels of uncertainty. These modeled results suggest that climate change is driving increased wetland CH4 emissions and that direct and sustained measurements are needed to monitor developments.

High-latitude frozen soils contain a vast store of organic matter, a potential source of greenhouse gases due to permafrost thaw. Understanding natural carbon cycle responses to climate change is crucial for emission reduction strategies. We use the Max Planck Institute Earth System Model, driven by the Adaptive Emission Reduction Approach (AERA), to assess emission pathways for limiting global warming to 2 degrees C and 3 degrees C relative to preindustrial levels, while accounting for frozen soil carbon (FSC). We found that thawing FSC makes 122 PgC under 2 degrees C and 229 PgC under 3 degrees C warming, available for decomposition with about 75% reaching the atmosphere as carbon-dioxide by 2298. Emission pathways that include the release of FSC diverge from their respective reference simulations without permafrost between the middle (2 degrees C) and end (3 degrees C) of the current century. By 2298, remaining carbon budgets are reduced by similar to 13% (115 PgC) for 2 degrees C and similar to 11% (156 PgC) for 3 degrees C stabilization levels. Annual permafrost emissions average similar to 0.7 PgC/yr for 3 degrees C and similar to 0.3 PgC/yr for 2 degrees C during the simulation period (2025-2298). However, temporary emission peaks reaching half of present-day annual fossil fuel emissions (similar to 5 PgC) are possible. Surprisingly, while negative emissions are required for both reference simulations, only the simulation for the 3 degrees C warming, accounting for FSC, requires negative fossil fuel emissions. This occurs because the FSC release causes an earlier initiation of emission reduction by AERA, resulting in a smoother emission curve. These findings underscore the importance of factoring in carbon released from permafrost thaw in mitigation action.

Abstract. Biochar has been proposed as a promising soil amendment for climate change mitigation, owing to its capacity to sequester carbon and alter soil physical properties. This study investigates the potential influence of biochar-induced changes in soil hydrological and thermal properties on future climate, with a focus on extreme climate events. We implemented a series of biochar addition scenarios (ranging from 5 to 150 t/ha) into the Max Planck Institute Earth System Model (MPI-ESM), modifying eight soil physical variables via pedo-transfer functions to investigate their impacts on climate in the near future (2040–2049) under the CMIP6 framework. Our results show that while biochar-induced soil property changes produced minimal global effects on temperature and precipitation, they led to more structured and consistent responses in climate extremes over land. In particular, the addition of biochar reduced temperature extremes – especially nighttime minimum temperatures (TNn) – across cold regions such as Eastern Europe, the Russian Arctic, and West Siberia. Contrary to our initial hypothesis, these effects were not driven by enhanced latent heat flux but rather by increased humidity and cloud cover that altered surface energy balance via sensible heat redistribution. Precipitation extremes also responded to biochar addition, with a consistent decrease in extreme rainfall (Rx1day) over land. However, changes in consecutive dry days (CDD) were more region-specific, with increases observed in arid and coastal regions such as the Arabian Peninsula and Central Australia, indicating heightened drought risks in already vulnerable zones. These findings suggest that although biochar’s direct modifications are localized, its indirect effects on climate extremes can extend across sensitive regions through land-atmosphere interactions. Our study highlights the importance of integrating both biogeophysical and biogeochemical pathways in Earth system models to better evaluate biochar's climate mitigation potential.