Explore the vast range of titles available.

Global warming drives changes in Earth’s cloud cover, which, in turn, may amplify or dampen climate change. This “cloud feedback” is the single most important cause of uncertainty in Equilibrium Climate Sensitivity (ECS)—the equilibrium global warming following a doubling of atmospheric carbon dioxide. Using data from Earth observations and climate model simulations, we here develop a statistical learning analysis of how clouds respond to changes in the environment. We show that global cloud feedback is dominated by the sensitivity of clouds to surface temperature and tropospheric stability. Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 ± 0.35 W·m−2·K−1 (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K. We thus anticipate that our approach will enable tighter constraints on climate change projections, including its manifold socioeconomic and ecological impacts.

Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1 % yr−1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm−1) and ocean (0.79 ± 0.07 PgC ppm−1), while the carbon–climate feedback over land (−45.1 ± 50.6 PgC ∘C−1) is about 3 times larger than over ocean (−17.2 ± 5.0 PgC ∘C−1). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 ∘C EgC−1 and is similar to that found in CMIP5 models (1.63 ± 0.48 ∘C EgC−1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

This paper documents the biogeochemistry configuration of the Energy Exascale Earth System Model (E3SM), E3SMv1.1‐BGC. The model simulates historical carbon cycle dynamics, including carbon losses predicted in response to land use and land cover change, and the responses of the carbon cycle to changes in climate. In addition, we introduce several innovations in the treatment of soil nutrient limitation mechanisms, including explicit dependence on phosphorus availability. The suite of simulations described here includes E3SM contributions to the Coupled Climate‐Carbon Cycle Model Intercomparison Project and other projects, as well as simulations to explore the impacts of structural uncertainty in representations of nitrogen and phosphorus limitation. We describe the model spin‐up and evaluation procedures, provide an overview of results from the simulation campaign, and highlight key features of the simulations. Cumulative warming over the twentieth century is similar to observations, with a midcentury cold bias offset by stronger warming in recent decades. Ocean biomass production and carbon uptake are underpredicted, likely due to biases in ocean transport leading to widespread anoxia and undersupply of nutrients to surface waters. The inclusion of nutrient limitations in the land biogeochemistry results in weaker carbon fertilization and carbon‐climate feedbacks than exhibited by other Earth System Models that exclude those limitations. Finally, we compare with an alternative representation of terrestrial biogeochemistry, which differs in structure and in initialization of soil phosphorus. While both configurations agree well with observational benchmarks, they differ significantly in their distribution of carbon among different pools and in the strength of nutrient limitations. Plain Language Summary A new state‐of‐the‐art Earth System Model has been funded by the United States Department of Energy (DOE) to explore questions relevant to DOE's mission. The Energy Exascale Earth System Model version 1.1 (E3SMv1.1) represents nitrogen and phosphorous controls on the carbon cycle and extends the recently released E3SMv1 to include active biogeochemistry in the land, ocean, and ice components. E3SMv1.1 also includes an alternative representation of terrestrial carbon and nutrient cycles that is used to explore model structural uncertainties. E3SMv1.1's capabilities are demonstrated through a set of experiments described by the Coupled Climate‐Carbon Cycle Model Intercomparison Project, aimed at understanding the influence of changes in climate and CO2 on the carbon cycle. Simulations of the land surface properties and terrestrial carbon cycle compare well with observations, as does the simulated global and regional climate. Nutrient limitations result in less land carbon uptake compared to models that exclude these limitations. However, variations in model structure and initialization influence the magnitude of those limitations and carbon cycle dynamics. The ocean biogeochemistry in E3SMv1.1 simulates less biomass and slightly lower anthropogenic carbon uptake than is observed. Future efforts will aim to reduce model biases as well as to include additional aspects of global carbon cycle dynamics. Key Points Introduces the U.S. DOE's Energy Exascale Earth System Model‐Biogeochemistry version, E3SMv1.1‐BGC, is introduced Ecosystem‐climate responses are characterized in a standard set of C4MIP‐type simulations The impacts of terrestrial nitrogen and phosphorus limitations and their structural uncertainties are explored

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C • C −1 on a 100 year time scale. For CH 4 emissions, our approach assumes a fixed saturated area and that increases in CH 4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH 4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.

Oceanic absorption of atmospheric carbon dioxide (CO2) is expected to slow down under increasing anthropogenic emissions; however, the driving mechanisms and rates of change remain uncertain, limiting our ability to project long‐term changes in climate. Using an Earth system simulation, we show that the uptake of anthropogenic carbon will slow in the next three centuries via reductions in surface alkalinity. Warming and associated changes in precipitation and evaporation intensify density stratification of the upper ocean, inhibiting the transport of alkaline water from the deep. The effect of these changes is amplified threefold by reduced carbonate buffering, making alkalinity a dominant control on CO2 uptake on multi‐century timescales. Our simulation reveals a previously unknown alkalinity‐climate feedback loop, amplifying multi‐century warming under high emission trajectories. Plain Language Summary Over the past century, humans have been burning fossil fuels and adding extra carbon dioxide to the atmosphere. The ocean has been doing us a big favor by absorbing some of this carbon dioxide, lowering the amount of global warming that occurs. Our study shows that the ocean will begin to lose its ability to absorb carbon dioxide beyond the year 2100, leaving more fossil‐derived carbon in the atmosphere and leading to additional global warming. Our study describes a previously undiscovered mechanism for the slowdown in ocean carbon absorption, where changes in rainfall and warming affect ocean currents that, in turn, change the chemistry of the ocean surface. Key Points Oceanic uptake of carbon could slow in upcoming centuries through previously unidentified alkalinity‐climate feedback Reduced upwelling and carbonate buffer enhance the influence of alkalinity on the increase in surface ocean carbon dioxide Reductions in surface alkalinity will reduce the rate of carbon uptake on multi‐century timescales

Both higher temperatures and increased CO2 concentrations are (separately) expected to increase the emissions of biogenic volatile organic compounds (BVOCs). This has been proposed to initiate negative climate feedback mechanisms through increased formation of secondary organic aerosol (SOA). More SOA can make the clouds more reflective, which can provide a cooling. Furthermore, the increase in SOA formation has also been proposed to lead to increased aerosol scattering, resulting in an increase in diffuse radiation. This could boost gross primary production (GPP) and further increase BVOC emissions. In this study, we have used the Norwegian Earth System Model (NorESM) to investigate both these feedback mechanisms. Three sets of experiments were set up to quantify the feedback with respect to (1) doubling the CO2, (2) increasing temperatures corresponding to a doubling of CO2 and (3) the combined effect of both doubling CO2 and a warmer climate. For each of these experiments, we ran two simulations, with identical setups, except for the BVOC emissions. One simulation was run with interactive BVOC emissions, allowing the BVOC emissions to respond to changes in CO2 and/or climate. In the other simulation, the BVOC emissions were fixed at present-day conditions, essentially turning the feedback off. The comparison of these two simulations enables us to investigate each step along the feedback as well as estimate their overall relevance for the future climate. We find that the BVOC feedback can have a significant impact on the climate. The annual global BVOC emissions are up to 63 % higher when the feedback is turned on compared to when the feedback is turned off, with the largest response when both CO2 and climate are changed. The higher BVOC levels lead to the formation of more SOA mass (max 53 %) and result in more particles through increased new particle formation as well as larger particles through increased condensation. The corresponding changes in the cloud properties lead to a −0.43 W m−2 stronger net cloud forcing. This effect becomes about 50 % stronger when the model is run with reduced anthropogenic aerosol emissions, indicating that the feedback will become even more important as we decrease aerosol and precursor emissions. We do not find a boost in GPP due to increased aerosol scattering on a global scale. Instead, the fate of the GPP seems to be controlled by the BVOC effects on the clouds. However, the higher aerosol scattering associated with the higher BVOC emissions is found to also contribute with a potentially important enhanced negative direct forcing (−0.06 W m−2). The global total aerosol forcing associated with the feedback is −0.49 W m−2, indicating that it has the potential to offset about 13 % of the forcing associated with a doubling of CO2.

Soil organic carbon (SOC) regulates terrestrial ecosystem functioning, provides diverse energy sources for soil microorganisms, governs soil structure, and regulates the availability of organically bound nutrients. Investigators in increasingly diverse disciplines recognize how quantifying SOC attributes can provide insight about ecological states and processes. Today, multiple research networks collect and provide SOC data, and robust, new technologies are available for managing, sharing, and analyzing large data sets. We advocate that the scientific community capitalize on these developments to augment SOC data sets via standardized protocols. We describe why such efforts are important and the breadth of disciplines for which it will be helpful, and outline a tiered approach for standardized sampling of SOC and ancillary variables that ranges from simple to more complex. We target scientists ranging from those with little to no background in soil science to those with more soil-related expertise, and offer examples of the ways in which the resulting data can be organized, shared, and discoverable.

This study estimates short-term climate feedbacks by using a new set of radiative kernels applied to observations and the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations. The new kernels are generated based on multiyear satellite observations, and they can well reproduce the top-of-atmosphere (TOA) radiation budget. The choice of radiative kernels influences the feedback estimation, especially the surface albedo feedback and cloud feedback in the Arctic and the Southern Ocean. Observational estimates show that tropospheric water vapor feedback makes the largest contribution to global warming, while lapse rate feedback is the largest contributor to local warming over East Asia. Compared to the observations, biases occur but differ when simulating global and East Asian local climate feedbacks. CMIP6 models overestimate global mean Planck, lapse rate, stratospheric temperature and water vapor, and cloud feedbacks, but underestimate global mean tropospheric water vapor and surface albedo feedbacks. Over East Asia, local Planck and lapse rate feedbacks are underestimated, while tropospheric water vapor, stratospheric temperature, and cloud feedbacks are overestimated. The simulation biases in local longwave (LW) and shortwave (SW) cloud feedbacks over East Asia are considerable, probably due to the failure in simulating cloud fraction response of marine cirrostratus, deep convective cloud, and stratus. The intermodel spread of cloud feedback is the largest for both global and East Asian local feedback processes. Our results suggest that contemporary climate models are still difficult to accurately simulate global and local climate feedback processes.

The land surface models JULES (Joint UK Land Environment Simulator, two versions) and ORCHIDEE-MICT (Organizing Carbon and Hydrology in Dynamic Ecosystems), each with a revised representation of permafrost carbon, were coupled to the Integrated Model Of Global Effects of climatic aNomalies (IMOGEN) intermediate-complexity climate and ocean carbon uptake model. IMOGEN calculates atmospheric carbon dioxide (CO2) and local monthly surface climate for a given emission scenario with the land–atmosphere CO2 flux exchange from either JULES or ORCHIDEE-MICT. These simulations include feedbacks associated with permafrost carbon changes in a warming world. Both IMOGEN–JULES and IMOGEN–ORCHIDEE-MICT were forced by historical and three alternative future-CO2-emission scenarios. Those simulations were performed for different climate sensitivities and regional climate change patterns based on 22 different Earth system models (ESMs) used for CMIP3 (phase 3 of the Coupled Model Intercomparison Project), allowing us to explore climate uncertainties in the context of permafrost carbon–climate feedbacks. Three future emission scenarios consistent with three representative concentration pathways were used: RCP2.6, RCP4.5 and RCP8.5. Paired simulations with and without frozen carbon processes were required to quantify the impact of the permafrost carbon feedback on climate change. The additional warming from the permafrost carbon feedback is between 0.2 and 12 % of the change in the global mean temperature (ΔT) by the year 2100 and 0.5 and 17 % of ΔT by 2300, with these ranges reflecting differences in land surface models, climate models and emissions pathway. As a percentage of ΔT, the permafrost carbon feedback has a greater impact on the low-emissions scenario (RCP2.6) than on the higher-emissions scenarios, suggesting that permafrost carbon should be taken into account when evaluating scenarios of heavy mitigation and stabilization. Structural differences between the land surface models (particularly the representation of the soil carbon decomposition) are found to be a larger source of uncertainties than differences in the climate response. Inertia in the permafrost carbon system means that the permafrost carbon response depends on the temporal trajectory of warming as well as the absolute amount of warming. We propose a new policy-relevant metric – the frozen carbon residence time (FCRt) in years – that can be derived from these complex land surface models and used to quantify the permafrost carbon response given any pathway of global temperature change.

The Antarctic Ice Sheet will play a crucial role in the evolution of global mean sea level as the climate warms. An interactively coupled climate and ice sheet model is needed to understand the impacts of ice–climate feedbacks during this evolution. Here we use a two-way coupling between the UK Earth System Model and the BISICLES (Berkeley Ice Sheet Initiative for Climate at Extreme Scales) dynamic ice sheet model to investigate Antarctic ice–climate interactions under two climate change scenarios. We perform ensembles of SSP1–1.9 and SSP5–8.5 (Shared Socioeconomic Pathway) scenario simulations to 2100, which we believe are the first such simulations with a climate model that include two-way coupling of atmosphere and ocean models to dynamic models of the Greenland and Antarctic ice sheets. We focus our analysis on the latter. In SSP1–1.9 simulations, ice shelf basal melting and grounded ice mass loss from the Antarctic Ice Sheet are generally lower than present rates during the entire simulation period. In contrast, the responses to SSP5–8.5 forcing are strong. By the end of the 21st century, these simulations feature order-of-magnitude increases in basal melting of the Ross and Filchner–Ronne ice shelves, caused by intrusions of masses of warm ocean water. Due to the slow response of ice sheet drawdown, this strong melting does not cause a substantial increase in ice discharge during the simulations. The surface mass balance in SSP5–8.5 simulations shows a pattern of strong decrease on ice shelves, caused by increased melting, and strong increase on grounded ice, caused by increased snowfall. Despite strong surface and basal melting of the ice shelves, increased snowfall dominates the mass budget of the grounded ice, leading to an ensemble mean Antarctic contribution to global mean sea level of a fall of 22 mm by 2100 in the SSP5–8.5 scenario. We hypothesise that this signal would revert to sea-level rise on longer timescales, caused by the ice sheet dynamic response to ice shelf thinning. These results demonstrate the need for fully coupled ice–climate models in reducing the substantial uncertainty in sea-level rise from the Antarctic Ice Sheet.