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Understanding climate variability from millennial to glacial-interglacial timescales remains challenging due to the complex and non-linear feedbacks between ice, ocean, and atmosphere. Although the ever-increasing number of reconstructions has helped to form compelling hypotheses for the evolution of ocean and atmosphere circulation or ice sheet extent over the last glacial cycle, climate models, required for systematically testing these hypotheses, struggle to dynamically and comprehensively simulate such long time periods as a result of the large computational costs. Here, we therefore coupled a dynamical ice sheet model to the Bern3D Earth system model of intermediate complexity, that allows for simulating multiple glacial-interglacial cycles in reasonable time. To test the fully-coupled model, we explore the climate evolution over the entire last glacial cycle in a transient simulation forced by the orbital configuration and greenhouse gas and aerosol concentrations. We are able to simulate Global Mean Surface Temperature (GMST) in fair agreement with reconstructions exhibiting a gradual cooling trend since the last interglacial that is interrupted by two more rapid cooling events during the early Marine Isotope Stage (MIS) 4 and Last Glacial Maximum (LGM). The glacial-interglacial GMST and mean ocean temperature differences are 5 °C and 1.6 °C, respectively. Ice volume shows pronounced variability on orbital timescales mirroring northern hemispheric summer insolation. From early MIS3 to the LGM ice volume roughly doubles in good agreement with recent sea-level reconstructions. The Atlantic overturning circulation shows larger variability during the relatively warm MIS5 than during the cooler MIS3, however we note that Dansgaard-Oeschger events are not intrinsically simulated in our setup. At the LGM the Atlantic overturning has a strength of about 14 Sv, which is a reduction by about one quarter compared to the pre-industrial. We thus demonstrate that the new coupled model is able to realistically simulate glacial-interglacial cycles, which allows as to systematically investigate the sensitivities to parameters such as equilibrium climate sensitivity or aerosol radiative forcing during the last glacial cycle.

Climate policies such as the Paris Agreement are framed in terms of global warming levels. Based on past warming and past CO2 emissions, the amount of future cumulative CO2 emissions allowed to keep global warming at or below a global warming level can be estimated. Yet, global warming scenarios in the successive Coupled Model Intercomparison Projects are framed in terms of prescribed atmospheric CO2 concentration or emissions, yielding a wide range of warming levels per CO2 pathway in response to the different transient climate responses to cumulative emissions in the coupled climate models. Based on these scenarios and the latest model projections, the IPCC Sixth Assessment Report assessed climatic impacts of different warming levels. These impacts are thus evaluated in simulations where the warming targets are passed transiently, at different points in time, and not stabilized, as opposed to how climate agreements are framed.Here, we propose a new Model Intercomparison Project AERA-MIP building on an adaptive approach - the Adaptive Emissions Reduction Approach - that successively calculates the compatible emissions to stabilize global warming at the required temperature target. Earth System Models (ESMs) are run forward in emission-driven mode, with prescribed, model-specific emissions successively calculated every five years, so that all models reach the same warming target and thereafter stabilize at this warming level. The warming uncertainty is thus side-stepped, while different emissions pathways emerge out of the variety of participating ESMs. The approach is based on the TCRE framework and successively adapting for any changes in the Earth System that might affect global mean surface temperature, including the zero emissions commitment as emissions approach zero.Simulations of the first participating modelling centers already reveal a panel of emissions pathways that successfully stabilize global warming at 1.5ºC and 2ºC. This includes the decline rate from peak emissions, the timing of having to reach net-zero emissions, and the magnitude of negative emissions needed to stabilize the climate. These different emissions pathways result in a range of atmospheric CO2 concentration evolution (350 to 450 ppm at year 2100 in the 1.5°C stabilization scenario) and distribution of anthropogenic carbon in the Earth System components. Unlike concentration-driven projections, these AERA simulations provide an uncertainty range for impacts that are directly affected by atmospheric CO2 concentration such as ocean acidification. The project also includes temporary temperature overshoot simulations using the AERA approach.

Nitrous oxide (N2O) is a greenhouse gas that causes both global warming and ozone depletion in the stratosphere. Global N2O fluxes are likely to change rapidly with global environmental changes (increasing CO2, warming and changes in soil moisture) and are also influenced by nitrogen (N) fertilizer use in agriculture and managed grasslands, atmospheric N deposition, and soil organic carbon (SOC) levels. Environmental dependencies of N2O emissions have been investigated through both field measurements and experimental studies, but disparate results have been obtained. A confrontation of model-simulated N2O emissions against a diversity of observations, from flux measurements and experiments, has not yet been performed.We compiled data on annual total N2O emissions from published field (n = 214 sites, 835 observations) and experimental (n = 55 sites, 142 observations) studies, and used these data to develop statistical models to model the responses of N2O emission to local N fertilization, climate variables, green vegetation cover and SOC. Using field measurements, we found that N2O emissions from forest soils increase with growth temperature (Tg) and observed soil moisture, likely reflecting higher nitrification and denitrification rates in warmer and wetter soils. In grasslands, we found that N2O emissions increase with N fertilization, and with the seasonal minimum value of fraction of absorbed photosynthetically active radiation (min fAPAR). Lower min fAPAR is associated with grasslands in dry or cold climates that constrain both productivity and the rate of organic matter turnover. In croplands, N2O increases with N fertilization, temperature, and humidity, consistent with the above, but also increases with SOC, and with total incident photosynthetic photon flux density over the growing season (total PPFD) and max fAPAR – two important controls of total annual primary production. The partial response of cropland N2O emission to min fAPAR however is negative, likely reflecting enhanced N2O emission from soil during periods when the crop cover is absent.In the experimental database, N2O response to elevated CO2 (eCO2) varies strongly across experiments, with log response ratios ranging from ­–2.2 to 1.8. Overall, N2O tends to decrease with eCO2, which is likely due to mineralized N being taken up by more rapidly by faster-growing plants. Response ratios also increase with N fertilization and total PPFD. In warming experiments, response ratios increase with SOC and temperature, consistent with what we found in field measurements.We have constructed data-driven models that shows significant responses of N2O emission to climate, N fertilization and SOC. We plan to use these as benchmarks for the evaluation of emergent N2O responses to global environmental changes in Earth System models. We will use LPX-Bern, and other models participating in the Global N2O Model Intercomparison Project (NMIP), to compare simulated environmental dependencies of N2O emission with our data-driven models. The data-driven models will also allow us to independently quantify N2O emission factors in croplands, and to compare global N2O-climate and N2O-CO2 feedbacks with previously published values.

We implement the Wet Bulb Globe Temperature (WBGT), a standardized heat stress metric, into the Community Land Model (CLM5), the land surface component of the Community Earth System Model (CESM2). This includes the notoriously difficult calculation related to measuring human heat stress: radiation. Following the International Organization for Standardization (ISO) 7243, physical representations of the instruments, a globe thermometer and natural wet bulb thermometer, simulate where humans work and live in non-urban environments. By using ISO 7243 within CLM5, we create a common framework within Earth system models to calculate the impact of radiation on temperature-moisture covariance. We demonstrate the capabilities of the WBGT using a default configuration of CLM5. We output 4x daily temporal resolutions globally, showing the advantage of simulating the WBGT within each environment. The WBGT outdoor and indoor calibration is simulated in an averaged grid cell, above the vegetation canopy, below the vegetation canopy, and bare ground environments. We examine the 1995 Chicago Heatwave, specifically the rural regions impacted by the heatwave, and demonstrate that the grid cell average calculated at the CLM5 30-minute time step is a poor representation of human environments and can differ by multiple degrees. In high heat stress environments following ISO 7243, a 0.5C change in WBGT can lead to a >10% reduction in labor capacity. This difference in temperature and labor capacity shows that assumptions about calculating a non-linear algorithm — even utilizing high temporal frequency grid cell averages that drive non-linear labor capacity impact models — is a flawed approach that can grossly over or underestimate the impact of heat stress on future climate change projections. To accurately assess the direct exposure, risk, and damage of climate change on people, it is critical to implement diagnostics directly into Earth system models.

Nitrous oxide (N2O) is a greenhouse gas and ozone-depleting agent that is predominately emitted from the land biosphere, linking to the yet only poorly understood carbon-nitrogen cycle. The seasonal cycle of the tropospheric N2O mixing ratio (aN2O), measured at globally distributed air sampling sites, offers an observational model constraint. Recent studies attribute the aN2O seasonality to exchange with N2O-depleted stratospheric air. Yet, how land biosphere N2O fluxes contribute to the seasonal amplitude, phasing, and amplitude growth of aN2O has not been well understood at global scales.Here we apply surface-atmosphere fluxes from global simulations of the Nitrogen/N2O Model Inter-comparison Project (NMIP) and the Bern3D ocean model to atmospheric transport matrices to simulate aN2O at air sampling sites. Land N2O fluxes from eight NMIP models show broad agreement on seasonal phasing. In contrast, seasonal amplitudes of regionally averaged fluxes differ severalfold across models. For example, seasonal amplitudes range from 2.2 to 5.4 TgN yr­-1 (median: 3.7) for 20oN-40oN and from 1.1 to 4.5 TgN yr­-1 (2.3) for 40oN-60oN during 2001 to 2020. The amplitudes for these two regions increased on average by 155% and 84%, respectively, over the industrial period. The increase predominantly results from anthropogenic activities, e.g, fertilizer application. The seasonal amplitude of regional ocean-atmosphere fluxes (0.2 to 1.1 TgN yr-1) and their changes are comparably small.The NMIP land fluxes result in seasonal amplitudes of aN2O on average ranging from 0.27 to 0.84 ppb (observed: 0.23 to 0.91 ppb) at six selected stations (Alert and Barrow, Ascension Island, Ragged Point, and Samoa, and Cape Grim). The model spread in aN2O amplitude is up to 0.55 ppb and, thus, large in comparison with observations. The contributions from Bern3D ocean fluxes to aN2O seasonality at the six stations (0.13 to 0.26 ppb) are generally smaller than from land. Substantial data-model mismatches in aN2O seasonal amplitudes and phasing are likely due to neglecting stratospheric fluxes in our models.Our results demonstrate significant contributions of land biosphere N2O emissions to aN2O seasonality. Model uncertainties in land biosphere fluxes translate into large uncertainties in aN2O seasonality, calling for land biosphere model improvements. In situ aN2O observations, in combination with atmospheric transport and chemistry models, potentially provide a novel top-down constraint for global land biosphere models towards improved projections of C-N coupling, the land carbon sink, and atmospheric CO2 and N2O.

Radiocarbon is a tracer that provides unique insights into the ocean’s ability to sequester CO2 from the atmosphere. While spatial patterns of radiocarbon in the ocean interior can indicate the vectors and timescales for carbon transport through the ocean, estimates of the global average ocean-atmosphere radiocarbon age offset (B-Atm) place constraints on the closure of the global carbon cycle. Here, we apply a Bayesian interpolation method to compiled B-Atm data to generate global interpolated fields and mean ocean B-Atm estimates for a suite of time-slices across the last deglaciation. The compiled data and interpolations confirm a stepwise and spatially heterogeneous ‘rejuvenation’ of the ocean, suggesting that carbon was released to the atmosphere through two swings of a ‘ventilation seesaw’ operating between the North Atlantic and the Southern Ocean/North Pacific. Sensitivity tests using the Bern3D model of intermediate complexity demonstrate that a portion of the reconstructed deglacial B-Atm changes may reflect ‘phase-attenuation’ biases that are unrelated to ocean ventilation, and that could arise from independent atmospheric radiocarbon dynamics instead. However, when correcting for such biases, the sensitivity tests further demonstrate that evolving ocean-atmosphere exchange could still account for at least one third of deglacial atmospheric CO2 rise. Approximately half of the contribution to CO2 rise appears to have been associated with the Bølling-Allerød, while the rest was linked mainly to Heinrich Stadial 1 and the Younger Dryas. Our global average B-Atm estimates place further new constraints on the long-standing mystery of global radiocarbon budget closure across the last deglaciation and suggest that glacial radiocarbon production levels are likely underestimated on average by existing reconstructions.

Terrestrial carbon (C) sequestration is limited by nitrogen (N), a constraint that could intensify under CO2 fertilisation and future global change. The terrestrial C sink is estimated to currently sequester approximately a third of annual anthropogenic CO2 emissions based on an ensemble of terrestrial biosphere models, which have been evaluated in their ability to reproduce observations of the C, water, and energy cycles. However, their ability to reproduce observations of N cycling and thus the regulation of terrestrial C sequestration by N has been largely unexplored. Here, we evaluate an ensemble of terrestrial biosphere models with coupled C-N cycling and their performance at simulating N cycling, outlining a framework for evaluating N cycling that can be applied across terrestrial biosphere models. We find that models exhibit significant variability across N pools and fluxes, simulating different magnitudes and trends over the historical period, despite their ability to generally reproduce the historical terrestrial C sink. This suggests that the underlying N processes that regulate terrestrial C sequestration operate differently across models and may not be fully captured. Furthermore, models tended to overestimate tropical biological N fixation, vegetation C:N ratio, and soil C:N ratio but underestimate temperate biological N fixation relative to observations. However, there is significant uncertainty associated with measurements of N cycling processes given their scarcity (especially relative to those of C cycling processes) and their high spatiotemporal variability. Overall, our results suggest that terrestrial biosphere models that represent coupled C-N cycling (let alone those without a representation of N cycling) could be overestimating C storage per unit N, which could lead to biases in projections of the future terrestrial C sink under CO2 fertilisation and future global change. More extensive observations of N cycling processes are crucial to evaluate N cycling and its impact on C cycling as well as guide its development in terrestrial biosphere models.

Vegetation gross primary production (GPP) is the largest terrestrial carbon flux and plays an important role in regulating the carbon sink. Current terrestrial ecosystem models (TEMs) are indispensable tools for evaluating and predicting GPP. However, to which degree the TEMs can capture the interannual variability (IAV) of GPP remains unclear. With large data sets of remote sensing, in situ observations, and predictions of TEMs at a global scale, this study found that the current TEMs substantially underestimate the GPP IAV in comparison to observations at global flux towers. Our results also showed the larger underestimations of IAV in GPP at nonforest ecosystem types than forest types, especially in arid and semiarid grassland and shrubland. One cause of the underestimation is that the IAV in GPP predicted by models is strongly dependent on canopy structure, that is, leaf area index (LAI), and the models underestimate the changes of canopy physiology responding to climate change. On the other hand, the simulated interannual variations of LAI are much less than the observed. Our results highlight the importance of improving TEMs by precisely characterizing the contribution of canopy physiological changes on the IAV in GPP and of clarifying the reason for the underestimated IAV in LAI. With these efforts, it may be possible to accurately predict the IAV in GPP and the stability of the global carbon sink in the context of global climate change. Vegetation gross primary production (GPP) is the largest terrestrial carbon flux and plays an important role in regulating the carbon sink. Current terrestrial ecosystem models (TEMs) are indispensable tools for evaluating and predicting GPP. However, to which degree the TEMs can capture the interannual variability (IAV) of GPP remains unclear. With large data sets of remote sensing, in situ observations, and predictions of TEMs at a global scale, this study found that the current TEMs substantially underestimate the GPP IAV in comparison to observations at global flux towers. Our results also showed the larger underestimations of IAV in GPP at nonforest ecosystem types than forest types, especially in arid and semiarid grassland and shrubland. One cause of the underestimation is that the IAV in GPP predicted by models is strongly dependent on canopy structure, that is, leaf area index (LAI), and the models underestimate the changes of canopy physiology responding to climate change. On the other hand, the simulated interannual variations of LAI are much less than the observed. Our results highlight the importance of improving TEMs by precisely characterizing the contribution of canopy physiological changes on the IAV in GPP and of clarifying the reason for the underestimated IAV in LAI. With these efforts, it may be possible to accurately predict the IAV in GPP and the stability of the global carbon sink in the context of global climate change.

Future ocean acidification mainly depends on the continuous ocean uptake of CO2 from the atmosphere. The trajectory of future atmospheric CO2 is prescribed in traditional climate projections with Earth system models, leading to a small model spread and apparently low uncertainties for projected acidification, but a large spread in global warming. However, climate policies such as the Paris Agreement define climate targets in terms of global warming levels and as traditional simulations do not converge to a given warming level, they cannot be used to assess uncertainties in projected acidification. Here, we perform climate simulations that converge to given temperature levels using the Adaptive Emission Reduction Algorithm (AERA) with the Earth system model Bern3D-LPX at different setups with different Transient Climate Response to cumulative carbon Emissions (TCRE) and choices between reductions in CO2 and non-CO2 forcing agents. With these simulations, we demonstrate that uncertainties in surface ocean acidification are an order of magnitude larger than the usually reported inter-model uncertainties from simulations with prescribed atmospheric CO2. Uncertainties in acidification at a given stabilized temperature are dominated by TCRE and the choice of emission reductions of non-CO2 greenhouse gases (GHGs). High TCRE and relatively low reductions of non-CO2 GHGs, for example, necessitate relatively strong reductions in CO2 emissions and lead to relatively little ocean acidification at a given temperature level. The results suggest that choices between reducing emissions of CO2 versus non-CO2 agents should consider the economic costs and ecosystem damage of ocean acidification.

The last time in Earth's history when high latitudes were warmer than during pre-industrial times was the last interglacial period (LIG, 129–116 ka BP). Since the LIG is the most recent and best documented interglacial, it can provide insights into climate processes in a warmer world. However, some key features of the LIG are not well constrained, notably the oceanic circulation and the global carbon cycle. Here, we use a new database of LIG benthic δ13C to investigate these two aspects. We find that the oceanic mean δ13C was ∼ 0.2 ‰ lower during the LIG (here defined as 125–120 ka BP) when compared to the Holocene (7–2 ka BP). A lower terrestrial carbon content at the LIG than during the Holocene could have led to both lower oceanic δ13C and atmospheric δ13CO2 as observed in paleo-records. However, given the multi-millennial timescale, the lower oceanic δ13C most likely reflects a long-term imbalance between weathering and burial of carbon. The δ13C distribution in the Atlantic Ocean suggests no significant difference in the latitudinal and depth extent of North Atlantic Deep Water (NADW) between the LIG and the Holocene. Furthermore, the data suggest that the multi-millennial mean NADW transport was similar between these two time periods.

The parties of the Paris Agreement agreed to keep global warming well below 2°C and assess the necessary greenhouse gas emissions reductions every five years during the global stocktake. Globally, the necessary reductions in greenhouse gases are often derived using the remaining emissions budget concept. However, estimations of this budget vary by a factor of two to three and may hamper efforts to establish ambitions emissions reductions. Here, we propose an adaptive approach that side-step these uncertainties to quantify these global emissions reductions during the successive global stocktake solely based on regularly updated observations of past temperatures, radiative forcing, and emissions statistics. The approach consists of three main steps repeated every five years: (1) determining the anthropogenic warming to date and hence the remaining warming allowed, (2) estimating the remaining CO2 forcing equivalent (CO2-fe) emission budget, and (3) proposing a CO2-fe or CO2 emission trajectory for the next 5 years. We test this approach using the Bern3D-LPX Earth System Model of Intermediate Complexity and demonstrate that the temperature targets 1.5°C and 2°C can be reached following a smooth emissions pathway. The adaptive nature makes the approach robust against inherent uncertainties in the observational records, climate sensitivity to emissions, and effectiveness of emissions reduction implementations. The approach thus allows developing an emissions trajectory that would iteratively adapt to ultimately meet the agreed temperature goal. The approach also provides a strong alternative to the often-used pre-defined emissions or concentration pathways (such as SSPs), which can result in very different end-of-century temperatures for the same emission or concentration trajectories. Some of these pathways are developed to be consistent with a given warming level (e.g., SSP1-1.9 for 1.5°C), not knowing the actual response of the Earth system to emissions. As opposed to these simulations, simulations from different models using the adaptive approach we propose here would be directly comparable in terms of warming and broader climate impacts but would differ in terms of required emissions. Our approach would hence guide a valuable and highly policy-relevant complementary set of simulations for the next generation of CMIP models resulting in a range of future emission trajectories compatible with a given global warming target.

The frequency and severity of droughts and heatwaves are projected to increase under global warming. However, their impacts on the terrestrial biosphere and the anthropogenic CO2 sink remain poorly understood. Here we analyse the effects of six hypothetical climate scenarios with stationary climate but differing drought-heat signatures on vegetation distribution and land carbon dynamics, as modelled by seven state-of-the-art dynamic global vegetation models. The six forcing scenarios are sampled from a long climate model simulation and consist of a control scenario representing a natural climate, a scenario with no hot and dry extremes, one with no compound hot and dry extremes but univariate extremes are possible, one with only hot extremes, one with only dry extremes, and one with both hot and dry extremes. Models show substantial differences in their vegetation coverage response to the different scenarios. While in some models, climate with no droughts and heatwaves favours tree growth, this is not the case for other models, where grasses benefit. Similarly, climates with frequent droughts promote grasses in some models and reduce forest growth in others. Models tend to agree that a climate with frequent concurrent droughts and heatwaves leads to reduced tree cover and increased grass cover. The changes in coverage are mirrored by changes in gross and net carbon fluxes. The stark differences among model responses illustrate the different modelling processes dealing with heat and drought stress and how they are differently affected by the extremes. Overall, this comparison helps quantify model uncertainties and process differences that are important for how vegetation behaves under extreme climate events.Our study illustrates how factorial model experiments can be employed to disentangle the impacts from single and compound extremes. The findings from this model comparison may also help to identify sources of uncertainty in carbon cycle projections.

The Atlantic overturning circulation plays a critical role in inter-hemispheric transport of heat, carbon, and nutrients, and its potential collapse under anthropogenic forcing is thought to be a major tipping point in the climate system. As such, painstaking efforts have been dedicated to a better understanding of the Atlantic circulation’s past variability and mean-state under different boundary conditions. Yet, despite decades of research many uncertainties remain regarding the state of the ocean circulation over the past 20,000 years, during which Earth’s climate was propelled out of the last ice age. Here, we employed the Bern3D intermediate complexity model, which is equipped with all major water mass tracers (Δ14C, δ13C, δ18O, εNd, Pa/Th, nutrients, and temperature), to search for converging constraints on the often conflicting interpretations of paleo-reconstructions from individual proxies focusing on the Last Glacial Maximum (LGM). By varying formation rates of northern- and southern-sourced waters we explore a wide range of circulation states and test their ability to reproduce the spatial patterns of newly compiled proxy data of the LGM. Generally, we find that late-Holocene to LGM anomalies give more consistent pictures of proxy distributions than absolute values, since systematic biases, that plague some of the proxies, cancel out. This has the additional advantage that also systematic model biases are minimized. Considering this, we find that the previously opposing neodymium and stable carbon isotope-based interpretations of the glacial water mass structure can be reconciled when non-conservative effects are appropriately taken into account. Furthermore, combining the information from all proxies indicates some shoaling of glacial northern-sourced water, yet not to the same extent as previous studies suggested.

Bursts of carbon dioxide, released into the atmosphere and occurring on centennial time scales, were seen during the cold periods of the last glacial cycle but not in older or warmer conditions. Nehrbass-Ahles et al. present a record of atmospheric carbon dioxide concentrations retrieved from the European Project for Ice Coring in Antarctica Dome C ice core showing that these carbon dioxide jumps occurred during both cold and warm periods between 330,000 and 450,000 years ago. They relate these pulses to disruptions of the Atlantic meridional overturning circulation caused by freshwater discharge from ice sheets. Such rapid carbon dioxide increases could occur in the future if global warming also disrupts this ocean circulation pattern.Science, this issue p. 1000Pulse-like carbon dioxide release to the atmosphere on centennial time scales has only been identified for the most recent glacial and deglacial periods and is thought to be absent during warmer climate conditions. Here, we present a high-resolution carbon dioxide record from 330,000 to 450,000 years before present, revealing pronounced carbon dioxide jumps (CDJ) under cold and warm climate conditions. CDJ come in two varieties that we attribute to invigoration or weakening of the Atlantic meridional overturning circulation (AMOC) and associated northward and southward shifts of the intertropical convergence zone, respectively. We find that CDJ are pervasive features of the carbon cycle that can occur during interglacial climate conditions if land ice masses are sufficiently extended to be able to disturb the AMOC by freshwater input.

Large amounts of the carbon-isotope 14C, entering Earth's carbon cycle, were produced in the atmosphere by atomic bomb tests in the 1950s and 1960s. Here, we forced the ocean and land components of the Community Earth System Model with atmospheric 14CO2 over the historical period to constrain overturning time scales and fluxes. The uptake of bomb 14C by the land model is lower than observation-based estimates. This mismatch is likely linked to too-low 14C uptake by vegetation as the model overestimates 14C/C ratios of modern soils. This suggests model biases in forest productivity or wood carbon allocation and turnover, and, in turn, a bias in the forest sink of anthropogenic carbon. The ocean model matches the observation-based global bomb 14C inventories when applying the quadratic relationship between gas transfer piston velocity and wind speed of Wanninkhof (2014), https://doi.org/10.4319/lom.2014.12.351 and the wind products from Large and Yeager or the Japanese Reanalysis Project. Simulated natural radiocarbon ages in the deep ocean are many centuries older than data-based estimates, indicating too slow deep ocean ventilation. The sluggish circulation causes large biases in biogeochemical tracers and implies a delayed deep ocean uptake of heat and carbon in global warming projections. Our study suggests that 14C observations are key to constrain carbon fluxes and transport timescales for improved representations of land and ocean biogeochemical cycles and Earth system model projections.

The parties of the Paris Agreement agreed to keep global warming well below 2°C and pursue efforts to limit it to 1.5°C. A global stocktake is instituted to assess the necessary emissions reductions every 5 years. Here we present an adaptive approach to successively quantify global emissions reductions that allow reaching a temperature target within ±0.2°C, solely based on regularly updated observations of past temperatures, radiative forcing and emissions statistics, and not on climate model projections. Testing this approach using an Earth system model of intermediate complexity demonstrates that defined targets can be reached following a smooth emissions pathway. Its adaptive nature makes the approach robust against inherent uncertainties in observational records, climate sensitivity, effectiveness of emissions reduction implementations and the metric to estimate CO2 equivalent emissions. This approach allows developing emission trajectories for CO2, CH4, N2O and other agents that iteratively adapt to meet a chosen temperature target.

The frequency and severity of droughts and heatwaves are projected to increase under global warming. However, the differential impacts of climate extremes on the terrestrial biosphere and anthropogenic CO2 sink remain poorly understood. In this study, we analyse the effects of six hypothetical climate scenarios with differing drought-heat signatures, sampled from a long stationary climate model simulation, on vegetation distribution and land carbon dynamics, as modelled by a dynamic global vegetation model (LPX-Bern v1.4). The six forcing scenarios consist of a Control scenario representing a natural climate, a Noextremes scenario featuring few droughts and heatwaves, a Nocompound scenario which allows univariate hot or dry extremes but no co-occurring extremes, a Hot scenario with frequent heatwaves, a Dry scenario with frequent droughts, and a Hotdry scenario featuring frequent concurrent hot and dry extremes. We find that a climate with no extreme events increases tree coverage by up to 10 % compared to the Control scenario and also increases ecosystem productivity as well as the terrestrial carbon pools. A climate with many heatwaves leads to an overall increase in tree coverage primarily in higher latitudes, while the ecosystem productivity remains similar to the Control scenario. In the Dry and even more so in the Hotdry scenario, tree cover and ecosystem productivity are reduced by up to −4 % compared to the Control scenario. Regionally, this value can be much larger, for example up to −80 % in mid-western USA or up to −50 % in mid-Eurasia for Hotdry tree ecosystem productivity. Depending on the vegetation type, the effects of the Hotdry scenario are stronger than the effects of the Hot and Dry scenarios combined, illustrating the importance of correctly simulating compound extremes for future impact assessment. Overall, our study illustrates how factorial model experiments can be employed to disentangle the effects of single and compound extremes.

Peatlands are diverse wetland ecosystems distributed mostly over the northern latitudes and tropics. Globally they store a large portion of the global soil organic carbon and provide important ecosystem services. The future of these systems under continued anthropogenic warming and direct human disturbance has potentially large impacts on atmospheric CO2 and climate. We performed global long term projections of peatland area and carbon over the next 5000 years using a dynamic global vegetation model forced with climate anomalies from ten models of the Coupled Model Intercomparison Project (CMIP6) and three scenarios. These projections are continued from a transient simulation from the Last Glacial Maximum to the present to account for the full transient history. Our results suggest short to long term net losses of global peatland area and carbon, with higher losses under higher emission scenarios. Large parts of today's active northern peatlands are at risk. Conditions for peatlands in the tropics and, in case of mitigation, eastern Asia and western north America improve. Factorial simulations reveal committed historical changes and future rising temperature as the main driver of future peatland loss and increasing precipitations as driver for regional peatland expansion. Additional simulations forced with two CMIP6 scenarios extended transiently beyond 2100, show qualitatively similar results to the standard scenarios, but highlight the importance of extended future scenarios for long term carbon cycle projections. The spread between simulations forced with different climate model anomalies suggests a large uncertainty in projected peatland variables due to uncertain climate forcing. Our study highlights the importance of quantifying the future peatland feedback to the climate system and its inclusion into future earth system model projections.

The Southern Ocean south of 30°S, occupying about a third of global surface ocean area, accounts for approximately 40% of the past anthropogenic carbon uptake and about 75% of excess heat uptake by the ocean. However, Earth system models have large difficulties in reproducing the Southern Ocean circulation, and therefore its historical and future anthropogenic carbon and excess heat uptake. In the first part of the talk, we show that there exists a tight relation across two Earth system model ensembles (CMIP5 and CMIP6) between present-day sea surface salinity in the subtropical-polar frontal zone, the formation region of mode and intermediate waters, and the past and future anthropogenic carbon uptake in the Southern Ocean. By using observations and Earth system model results, we constrain the projected cumulative Southern Ocean anthropogenic carbon uptake over 1850-2100 by the CMIP6 model ensemble to 158 ± 6 Pg C under the low-emissions scenario SSP1-2.6 and to 279 ± 14 Pg C under the high emissions scenario SSP5-8.5. Our results suggest that the Southern Ocean anthropogenic carbon sink is 14-18% larger and 46-54% less uncertain than estimated by the unconstrained CMIP6 Earth system model results. The identified constraint demonstrated the importance of the freshwater cycle for the Southern Ocean circulation and carbon cycle. In the second part of the talk, potential emergent constraints for the Southern Ocean excess heat uptake will be discussed.

Droughts and heatwaves have large impacts on the terrestrial carbon cycle. They lead to reductions in gross and net carbon uptake or anomalous carbon emissions by the vegetation to the atmosphere because of responses such as stomatal closure, hydraulic failure and vegetation mortality. The impacts are particularly strong when drought and heat occur at the same time. Climate model simulations diverge in their occurrence frequency of compound hot and dry events, and so far it is unclear how these differences affect carbon dynamics. Furthermore, it is unknown whether a higher frequency of droughts and heatwaves leads to long-term changes in carbon dynamics, and how such an increase might affect vegetation composition.To study the immediate and long-term effects of varying signatures of droughts and heatwaves on carbon dynamics and vegetation composition, we employ the state-of-the-art dynamic global vegetation model LPX-Bern (v1.4) under different drought-heat scenarios. We constructed six 100-yr long scenarios with different drought-heat signatures: a “control”, “no extremes”, “no compound extremes”, “heat only”, “drought only”, and “compound drought and heat” scenario. This was done by sampling daily climate variables from a 2000-year stationary simulation of a General Circulation Model (EC-Earth) for present-day climate conditions. Such a sampling ensures physically-consistent co-variability between climate variables in the climate forcing.The scenarios differ little in their mean climate conditions (global mean land temperature differences of around 0.3°C and global mean land precipitation differences smaller than 7%), but vary strongly in the occurrence frequency of extremes such as droughts, heatwaves, and compound drought and heatwaves (up to five times more compound extremes in the “hotdry “scenario than in the “control”), allowing us to study the effects of the extremes on vegetation. Combined hot and dry extremes reduce all tree types and promotes grassland, while only hot extremes favours trees, especially in higher latitudes. No extremes are preferred by all tree types in LPX. Net Ecosystem Production (NEP) is expected to increase in most regions for the “noextremes” scenario, while the “hotdry” scenario is likely to reduce NEP.Our results provide a better understanding of the links between hot and dry conditions and vegetation dynamics as well as carbon dynamics. These analyses may help to reduce uncertainties in carbon cycle projections, which is important for constraining carbon cycle-climate feedbacks. The presented scenarios can be used for a variety of purposes such as studying the effects of differing drought-heat signatures on crop yield or the occurrence of fire besides others.

Observed sea surface salinity constrains past and future anthropogenic carbon uptake in the Southern Ocean., The ocean attenuates global warming by taking up about one quarter of global anthropogenic carbon emissions. Around 40% of this carbon sink is located in the Southern Ocean. However, Earth system models struggle to reproduce the Southern Ocean circulation and carbon fluxes. We identify a tight relationship across two multimodel ensembles between present-day sea surface salinity in the subtropical-polar frontal zone and the anthropogenic carbon sink in the Southern Ocean. Observations and model results constrain the cumulative Southern Ocean sink over 1850-2100 to 158 ± 6 petagrams of carbon under the low-emissions scenario Shared Socioeconomic Pathway 1-2.6 (SSP1-2.6) and to 279 ± 14 petagrams of carbon under the high-emissions scenario SSP5-8.5. The constrained anthropogenic carbon sink is 14 to 18% larger and 46 to 54% less uncertain than estimated by the unconstrained estimates. The identified constraint demonstrates the importance of the freshwater cycle for the Southern Ocean circulation and carbon cycle.

International audience; We synthesized N2O emissions over North America using 17 bottom-up (BU) estimates from 1980–2016 and five top-down (TD) estimates from 1998 to 2016. The BU-based total emission shows a slight increase owing to U.S. agriculture, while no consistent trend is shown in TD estimates. During 2007–2016, North American N2O emissions are estimated at 1.7 (1.0–3.0) Tg N yr−1 (BU) and 1.3 (0.9–1.5) Tg N yr−1 (TD). Anthropogenic emissions were twice as large as natural fluxes from soil and water. Direct agricultural and industrial activities accounted for 68% of total anthropogenic emissions, 71% of which was contributed by the U.S. Our estimates of U.S. agricultural emissions are comparable to the EPA greenhouse gas (GHG) inventory, which includes estimates from IPCC tier 1 (emission factor) and tier 3 (process-based modeling) approaches. Conversely, our estimated agricultural emissions for Canada and Mexico are twice as large as the respective national GHG inventories.Nitrous oxide (N2O) is the third most important greenhouse gase (GHG) after CO2 and CH4 causing global warming. Among world regions, North America (defined herein as U.S., Canada, and Mexico) is the second largest source of N2O emissions globally, and previous source estimates for this region vary widely. This study aims to provide a comprehensive N2O assessment over North America including all available estimates based on a number of approaches. We report total emissions, and emissions from four anthropogenic source sectors, over the past four decades. Agriculture and industry are two major N2O sources in North America. Our results show a minor increase in the total N2O emission due to agricultural trends in the U.S. Our bottom-up estimate of U.S. agricultural N2O emissions are close to those in the EPA national GHG inventory that includes both empirical and model results. The high consistency suggests the need to take process-based modeling results into account for future national GHG inventories.

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. 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.

Anthropogenic climate change profoundly alters the ocean’s environmental conditions, which, in turn, impact marine ecosystems. Some of these changes are happening fast and may be difficult to reverse. The identification and monitoring of such changes, which also includes tipping points, is an ongoing and emerging research effort. Prevention of negative impacts requires mitigation efforts based on feasible research-based pathways. Climate-induced tipping points are traditionally associated with singular catastrophic events (relative to natural variations) of dramatic negative impact. High-probability high-impact ocean tipping points due to warming, ocean acidification, and deoxygenation may be more fragmented both regionally and in time but add up to global dimensions. These tipping points in combination with gradual changes need to be addressed as seriously as singular catastrophic events in order to prevent the cumulative and often compounding negative societal and Earth system impacts.There are no data underlying this work.

Deglaciations are characterized by the largest natural changes in methane (CH4) and nitrous oxide (N2O) concentrations of the past 800 thousand years. Reconstructions of millennial to centennial-scale variability within these periods are mostly restricted to the last deglaciation. In this study, we present composite records of CH4 and N2O concentrations from the EPICA Dome C ice core covering the penultimate deglaciation at temporal resolutions of about ~ 100 years. Our data permit the identification of centennial-scale fluctuations standing out of the overall transition to interglacial levels. These features occurred in concert with reinvigorations of the Atlantic Meridional Overturning Circulation (AMOC) and northward shifts of the Intertropical Convergence Zone. The abrupt CH4 and N2O rises at about ~ 134 and ~ 128 thousand of years before present (hereafter ka BP) are assimilated to the fluctuations accompanying the Dansgaard–Oeschger events of the last glacial period, while rising N2O levels at ~ 130.5 ka BP are assimilated to a pattern of increasing N2O concentrations that characterized the end of Heinrich stadials. We suggest the 130.5-ka event to be driven by a partial reinvigoration of the AMOC. Overall, the CH4 and N2O fluctuations during the penultimate deglaciation exhibit modes of variability that are also found during the last deglaciation. However, trace gas responses may differ for similar type of climatic events, as exemplified by the reduced amplitude and duration of the 134-ka event compared to the fluctuations of the Bølling–Allerød during the last deglaciation.

The last time in Earth’s history when the high latitudes were warmer than during pre-industrial times was the last interglacial (LIG, 129–116 ka BP). Since the LIG is the most recent and best documented warm time period, it can provide insights into climate processes in a warmer world. However, some key features of the LIG are not well constrained, notably the oceanic circulation and the global carbon cycle. Here, we use a new database of LIG benthic 𝛿13C to investigate these two aspects. We find that the oceanic mean 𝛿13C was ~ 0.2 ‰ lower during the LIG (here defined as 125–120 ka BP) when compared to the mid-Holocene (7–4 ka BP). As the LIG was slightly warmer than the Holocene, it is possible that terrestrial carbon was lower, which would have led to both a lower oceanic 𝛿13C and atmospheric 𝛿13CO2 as observed in paleo-records. However, given the multi-millennial timescale, the lower oceanic 𝛿13C most likely reflects a long-term imbalance between weathering and burial of carbon. The 𝛿13C distribution in the Atlantic Ocean suggests no significant difference in the latitudinal and depth extent of North Atlantic Deep Water (NADW) between the LIG and the mid-Holocene. Furthermore, the data suggests that the multi-millennial mean NADW transport was similar between these two time periods.