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The additional water from the Antarctic ice sheet and ice shelves due to climate‐induced melt can impact ocean circulation and global climate. However, the major processes driving melt are not adequately represented in Coupled Model Intercomparison Project phase 6 (CMIP6) models. Here, we analyze a novel multi‐model ensemble of CMIP6 models with consistent meltwater addition to examine the robustness of the modeled response to meltwater, which has not been possible in previous single‐model studies. Antarctic meltwater addition induces a substantial weakening of open‐ocean deep convection. Additionally, Antarctic Bottom Water warms, its volume contracts, and the sea surface cools. However, the magnitude of the reduction varies greatly across models, with differing anomalies correlated with their respective mean‐state climatology, indicating the state‐dependency of the climate response to meltwater. A better representation of the Southern Ocean mean state is necessary for narrowing the inter‐model spread of response to Antarctic meltwater. Plain Language Summary: The melting of the Antarctic ice sheet and ice shelves can have significant impacts on ocean circulation and thermal structure, but current climate models do not fully capture these effects. In this study, we analyze seven climate models to understand how they respond to the addition of meltwater from Antarctica. We find that the presence of Antarctic meltwater leads to a significant weakening of deep convection in the open ocean. The meltwater also causes Antarctic Bottom Water to warm and its volume to decrease, while the sea surface cools and sea ice expands. However, the magnitude of the response to meltwater varies across models, suggesting that the mean‐state conditions of the Southern Ocean play a role. A better representation of the mean state and the inclusion of Antarctic meltwater in climate models will help reduce uncertainties and improve our understanding of the impact of Antarctic meltwater on climate. Key Points: Antarctic meltwater substantially reduces the strength of simulated Southern Ocean deep convection in climate modelsThe additional meltwater induces Antarctic Bottom Water warming and contraction, with dense water classes converting to lighter onesDifferences in the magnitude of these responses between models can be partly attributed to their different base states [ABSTRACT FROM AUTHOR]

As the climate warms, the grounded ice sheet and floating ice shelves surrounding Antarctica are melting and releasing additional freshwater into the Southern Ocean. Nonetheless, almost all existing coupled climate models have fixed ice sheets and lack the physics required to represent the dominant sources of Antarctic melt. These missing ice dynamics represent a key uncertainty that is typically unaccounted for in current global climate change projections. Previous modelling studies that have imposed additional Antarctic meltwater have demonstrated regional impacts on Southern Ocean stratification, circulation, and sea ice, as well as remote changes in atmospheric circulation, tropical precipitation, and global temperature. However, these previous studies have used widely varying rates of freshwater forcing, have been conducted using different climate models and configurations, and have reached differing conclusions on the magnitude of meltwater–climate feedbacks. The Southern Ocean Freshwater Input from Antarctica (SOFIA) initiative brings together a team of scientists to quantify the climate system response to Antarctic meltwater input along with key aspects of the uncertainty. In this paper, we summarize the state of knowledge on meltwater discharge from the Antarctic ice sheet and ice shelves to the Southern Ocean and explain the scientific objectives of our initiative. We propose a series of coupled and ocean–sea ice model experiments, including idealized meltwater experiments, historical experiments with observationally consistent meltwater input, and future scenarios driven by meltwater inputs derived from stand-alone ice sheet models. Through coordinating a multi-model ensemble of simulations using a common experimental design, open data archiving, and facilitating scientific collaboration, SOFIA aims to move the community toward better constraining our understanding of the climate system response to Antarctic melt. [ABSTRACT FROM AUTHOR]

As a major sink for anthropogenic carbon, the oceans slow the increase in carbon dioxide in the atmosphere and regulate climate change. Future changes in the ocean carbon sink, and its uncertainty at a global and regional scale, are key to understanding the future evolution of the climate. Here we report on the changes and uncertainties in the historical and future ocean carbon sink using output from the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble and compare to an observation-based product. We show that future changes in the ocean carbon sink are concentrated in highly active regions – 70 % of the total sink occurs in less than 40 % of the global ocean. High pattern correlations between the historical uptake and projected future changes in the carbon sink indicate that future uptake will largely continue to occur in historically important regions. We conduct a detailed breakdown of the sources of uncertainty in the future carbon sink by region. Consistent with CMIP5 models, scenario uncertainty dominates at the global scale, followed by model uncertainty and then internal variability. We demonstrate how the importance of internal variability increases moving to smaller spatial scales and go on to show how the breakdown between scenario, model, and internal variability changes between different ocean regions, governed by different processes. Using the CanESM5 large ensemble we show that internal variability changes with time based on the scenario, breaking the widely employed assumption of stationarity. As with the mean sink, we show that uncertainty in the future ocean carbon sink is also concentrated in the known regions of historical uptake. Patterns in the signal-to-noise ratio have implications for observational detectability and time of emergence, which we show to vary both in space and with scenario. We show that the largest variations in emergence time across scenarios occur in regions where the ocean sink is less sensitive to forcing – outside of the highly active regions. In agreement with CMIP5 studies, our results suggest that for a better chance of early detection of changes in the ocean carbon sink and to efficiently reduce uncertainty in future carbon uptake, highly active regions, including the northwestern Atlantic and the Southern Ocean, should receive additional focus for modeling and observational efforts. [ABSTRACT FROM AUTHOR]

Observations show that since the 1950s, the subsurface Southern Ocean has been rapidly warming in the south and cooling in the north. However, what drives these opposing latitudinal patterns of change is not well understood. By analyzing the outputs of atmosphere–ocean general circulation models, we examine and quantify the processes controlling the temperature change in the Southern Ocean. We find that subsurface cooling in the north results from the combined effect of weak warming driven by greenhouse gases and cooling forced by aerosols. Contrary to previous work, we find that the influence of stratospheric ozone forcing is small and unnecessary to explain the observed patterns. Analysis of heat budget diagnostics shows that ocean heat content change between 400 and 1200 m in the Southern Ocean is primarily driven by slight imbalances between the large and opposing changes in residual mean advection and isopycnal diffusion. We show that while surface heat flux anomalies are the main contributor to the warming in the Southern Ocean, changes in wind stress are also required to produce the observed pattern of temperature change. These results highlight the importance of ocean dynamics in subsurface ocean heat content change. The counterbalancing effects of aerosols and greenhouse gases on ocean heat content change in the Southern Ocean will change with aerosols declining in the future, while our results suggest that changes in stratospheric ozone forcing will have only a minor effect on future patterns of Southern Ocean thermohaline structure. [ABSTRACT FROM AUTHOR]

As a major sink for anthropogenic carbon, the oceans slow the increase of carbon dioxide in the atmosphere and regulate climate change. Future changes in the ocean carbon sink, and its uncertainty at a global and regional scale, are key to understanding the future evolution of the climate. Here, we conduct a multimodel analysis of the changes and uncertainties in the historical and future ocean carbon sink using output data from the latest phase of the Coupled Model Intercomparison Project: CMIP6, and observations. We show that the ocean carbon sink is concentrated in highly active regions - 70 percent of the total sink occurs in less than 40 percent of the global ocean. High pattern correlations between the historical and projected future carbon sink indicate that future uptake will largely continue to occur in historically important regions. We conduct a detailed breakdown of the sources of uncertainty in the future carbon sink by region. Scenario uncertainty dominates at the global scale, followed by model uncertainty, and then internal variability. We demonstrate how the importance of internal variability increases moving to smaller spatial scales and go on to show how the breakdown between scenario, model, and internal variability changes between different ocean basins, governed by different processes. Moreover, we show that internal variability changes with time based on the scenario. As with the mean sink, we show that uncertainty in the future ocean carbon sink is also concentrated in the known regions of historical uptake. The resulting patterns in the signal-to-noise ratio have strong implications for observational detectability and time of emergence, which varies both in space and with scenario. Our results suggest that to detect human influence on the ocean carbon sink as early as possible and to efficiently reduce uncertainty in future carbon uptake, modeling and observational efforts should be focused in the known regions of high historical uptake, including the Northwest Atlantic and the Southern Ocean. [ABSTRACT FROM AUTHOR]

The decline in global emissions of carbon dioxide due to the COVID‐19 pandemic provides a unique opportunity to investigate the sensitivity of the global carbon cycle and climate system to emissions reductions. Recent efforts to study the response to these emissions declines has not addressed their impact on the ocean, yet ocean carbon absorption is particularly susceptible to changing atmospheric carbon concentrations. Here, we use ensembles of simulations conducted with an Earth system model to explore the potential detection of COVID‐related emissions reductions in the partial pressure difference in carbon dioxide between the surface ocean and overlying atmosphere (ΔpCO2), a quantity that is regularly measured. We find a unique fingerprint in global‐scale ΔpCO2 that is attributable to COVID, though the fingerprint is difficult to detect in individual model realizations unless we force the model with a scenario that has four times the observed emissions reduction. Plain Language Summary: The COVID‐19 pandemic is slowing the rate of fossil fuel use, and thus impacting the carbon dioxide concentration in the atmosphere. Here we explore what this change in fossil fuel use does to carbon in the ocean. We use a climate model to estimate the change in ocean‐atmosphere carbon exchange and ocean acidity. Since we don't yet know how much we will slow our fossil fuel use due to COVID, we make several informed guesses and see how our model ocean responds to each. We use the model to investigate whether the change that we model would be detectable in real world observations. We find that it is nearly impossible to detect a COVID‐related change in ocean acidity with observations. It might be possible to detect a COVID‐related change in ocean‐atmosphere carbon exchange, but only if we use the most extreme guess, and only if we have enough observation stations in place to record it. Key Points: COVID‐related emissions reductions will be imperceptible in surface ocean pH observationsThe CanESM5 COVID ensemble predicts a unique fingerprint of COVID‐related emissions reductions in global mean ΔpCO2 (pCO2oc ‐ pCO2atm)The fingerprint is potentially detectable in global‐scale observations of ΔpCO2, but only with large emissions reductions [ABSTRACT FROM AUTHOR]

The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial-scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and their coupling, as well as various aspects of model development, including tuning, optimization, and a reproducibility strategy. We also document the stability of the model using a long control simulation, quantify the model's ability to reproduce large-scale features of the historical climate, and evaluate the response of the model to external forcing. CanESM5 is comprised of three-dimensional atmosphere (T63 spectral resolution equivalent roughly to 2.8 ∘) and ocean (nominally 1 ∘) general circulation models, a sea-ice model, a land surface scheme, and explicit land and ocean carbon cycle models. The model features relatively coarse resolution and high throughput, which facilitates the production of large ensembles. CanESM5 has a notably higher equilibrium climate sensitivity (5.6 K) than its predecessor, CanESM2 (3.7 K), which we briefly discuss, along with simulated changes over the historical period. CanESM5 simulations contribute to the Coupled Model Intercomparison Project phase 6 (CMIP6) and will be employed for climate science and service applications in Canada. [ABSTRACT FROM AUTHOR]

The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and their coupling, as well as various aspects of model development, including tuning, optimization and a reproducibility strategy. We also document the stability of the model using a long control simulation, quantify the model's ability to reproduce large scale features of the historical climate, and evaluate the response of the model to external forcing. CanESM5 is comprised of three dimensional atmosphere (T63 spectral resolution/2.8°) and ocean (nominally 1°) general circulation models, a sea ice model, a land surface scheme, and explicit land and ocean carbon cycle models. The model features relatively coarse resolution and high throughput, which facilitates the production of large ensembles. CanESM5 has a notably higher equilibrium climate sensitivity (5.7 K) than its predecessor CanESM2 (3.8 K), which we briefly discuss, along with simulated changes over the historical period. CanESM5 simulations are contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6), and will be employed for climate science and service applications in Canada. [ABSTRACT FROM AUTHOR]

An emergent property of most Earth system models is a near-linear relationship between cumulative emission of CO2 and change in global near-surface temperature. This relationship, which has been named the transient climate response to cumulative CO2 emissions (TCRE), implies a finite budget of fossil fuel carbon that can be burnt over all time consistent with a chosen temperature change target. Carbon budgets are inversely proportional to the value of TCRE and are therefore sensitive to the uncertainty in TCRE. Here the authors have used a perturbed physics approach with an Earth system model of intermediate complexity to assess the uncertainty in the TCRE that arises from uncertainty in the rate of transient temperature change and the effect of this uncertainty on carbon cycle feedbacks. The experiments are conducted using an idealized 1% yr-1 increase in CO2 concentration. Additionally, the authors have emulated the temperature output of 23 models from phase 5 of the Climate Model Intercomparison Project (CMIP5). The experiment yields a mean value for TCRE of 1.72 K EgC-1 with a 5th to 95th percentile range of 0.88 to 2.52 K EgC-1. This range of uncertainty is consistent with the likely range from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (0.8 to 2.5 K EgC-1) but by construction underestimates the total uncertainty range of TCRE, as the authors' experiments cannot account for the uncertainty from their models imperfect representation of the global carbon cycle. Transient temperature change uncertainty induces a 5th to 95th percentile range in the airborne fraction at the time of doubled atmospheric CO, of 0.50 to 0.58. Overall the uncertainty in the value of TCRE remains considerable. [ABSTRACT FROM AUTHOR]

This paper examines trends in the southern annular mode (SAM) and the strength, position, and width of the Southern Hemisphere surface westerly wind jet in observations, reanalyses, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). First the period over 1951-2011 is considered, and it is shown that there are differences in the SAM and jet trends between the CMIP5 models, the Hadley Centre gridded SLP (HadSLP2r) dataset, and the Twentieth Century Reanalysis. The relationships between these trends demonstrate that the SAM index cannot be used to directly infer changes in any one kinematic property of the jet. The spatial structure of the observed trends in SLP and zonal winds is shown to be largest, but also most uncertain, in the southeastern Pacific. To constrain this uncertainty six reanalyses are included and compared with station-based observations of SLP. The CMIP5 mean SLP trends generally agree well with the direct observations, despite some climatological biases, while some reanalyses exhibit spuriously large SLP trends. Similarly, over the more reliable satellite era the spatial pattern of CMIP5 SLP trends is in excellent agreement with HadSLP2r, whereas several reanalyses are not. Then surface winds are compared with a satellite-based product, and it is shown that the CMIP5 mean trend is similar to observations in the core region of the westerlies, but that several reanalyses overestimate recent trends. The authors caution that studies examining the impact of wind changes on the Southern Ocean could be biased by these spuriously large trends in reanalysis products. [ABSTRACT FROM AUTHOR]

We assess the detectability of COVID‐like emissions reductions in global atmospheric CO2 concentrations using a suite of large ensembles conducted with an Earth system model. We find a unique fingerprint of COVID in the simulated growth rate of CO2 sampled at the locations of surface measurement sites. Negative anomalies in growth rates persist from January 2020 through December 2021, reaching a maximum in February 2021. However, this fingerprint is not formally detectable unless we force the model with unrealistically large emissions reductions (2 or 4 times the observed reductions). Internal variability and carbon‐concentration feedbacks obscure the detectability of short‐term emission reductions in atmospheric CO2. COVID‐driven changes in the simulated, column‐averaged dry air mole fractions of CO2 are eclipsed by large internal variability. Carbon‐concentration feedbacks begin to operate almost immediately after the emissions reduction; these feedbacks reduce the emissions‐driven signal in the atmosphere carbon reservoir and further confound signal detection. Plain Language Summary: COVID pandemic lockdowns suddenly slowed the rate at which we burned fossil fuels and released carbon dioxide into the atmosphere, yet we cannot find any significant reductions in the growth of carbon dioxide in the atmosphere from our measurements. Here we provide some reasons to explain this conundrum. We use a climate model to mimic the changes in atmospheric carbon that would occur with different amounts of reductions in fossil fuel burning. We find that it is hard to see the change in fossil fuel burning in atmospheric carbon dioxide or its growth because of a large background component of natural variability. In addition, once we reduce our fossil fuel burning and the amount of carbon dioxide in the atmosphere decreases, the ocean and land also stop taking up as much carbon as normal. As we will soon lower our fossil fuel burning on purpose to slow climate change, our findings forewarn of the difficulties of detecting the effects of this in measurements of atmospheric carbon dioxide. Key Points: Climate model simulations suggest a lagged response in the global growth rate of atmospheric CO2 due to COVID‐19 emissions reductionsDetection of this reduction in observations is hampered by internal variability combined with reduced ocean and land uptake of CO2Our results foreshadow the challenges of detecting the effects of CO2 mitigation efforts to meet the Paris climate agreement [ABSTRACT FROM AUTHOR]

The Canadian Earth System Model version 5.0 (CanESM5.0), the most recent major version of the global climate model developed at the Canadian Centre for Climate Modelling and Analysis (CCCma) at Environment and Climate Change Canada (ECCC), has been used extensively in climate research and for providing future climate projections in the context of climate services. Previous studies have shown that CanESM5.0 performs well compared to other models and have revealed several model biases. To address these biases, the CCCma has recently initiated the "Analysis for Development" (A4D) activity, a coordinated analysis activity in support of CanESM development. Here we describe the goals and organization of this effort and introduce two variants ("p1" and "p2") of a new CanESM version, CanESM5.1, which features important improvements as a result of the A4D activity. These improvements include the elimination of spurious stratospheric temperature spikes and an improved simulation of tropospheric dust. Other climate aspects of the p1 variant of CanESM5.1 are similar to those of CanESM5.0, while the p2 variant of CanESM5.1 features reduced equilibrium climate sensitivity and improved El Niño–Southern Oscillation (ENSO) variability as a result of intentional tuning of the atmospheric component. The A4D activity has also led to the improved understanding of other notable CanESM5.0 and CanESM5.1 biases, including the overestimation of North Atlantic sea ice, a cold bias over sea ice, biases in the stratospheric circulation and a cold bias over the Himalayas. It provides a potential framework for the broader climate community to contribute to CanESM development, which will facilitate further model improvements and ultimately lead to improved climate change information. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) have been widely used to project terrestrial species' responses to climate change and are increasingly being used for similar objectives in the marine realm. These projections are critically needed to develop strategies for resource management and the conservation of marine ecosystems. SDMs are a powerful and necessary tool; however, they are subject to many sources of uncertainty, both quantifiable and unquantifiable. To ensure that SDM projections are informative for management and conservation decisions, sources of uncertainty must be considered and properly addressed. Here we provide ten overarching guidelines that will aid researchers to identify, minimize, and account for uncertainty through the entire model development process, from the formation of a study question to the presentation of results. These guidelines focus on correlative models and were developed at an international workshop attended by over 50 researchers and practitioners. Although our guidelines are broadly applicable across biological realms, we provide particular focus to the challenges and uncertainties associated with projecting the impacts of climate change on marine species and ecosystems. [ABSTRACT FROM AUTHOR]

The Canadian Earth System Model version 5.0 (CanESM5.0), the most recent major version of the global climate model developed at the Canadian Centre for Climate Modelling and Analysis (CCCma) at Environment and Climate Change Canada (ECCC), has been used extensively in climate research and for providing future climate projections in the context of climate services. Previous studies have shown that CanESM5.0 performs well compared to other models and have revealed several model biases. To address these biases, CCCma has recently initiated the 'Analysis for Development' (A4D) activity, a coordinated analysis activity in support of CanESM development. Here we describe the goals and organization of this effort and introduce two variants ("p1" and "p2") of a new CanESM version, CanESM5.1, which features substantial improvements as a result of the A4D activity. These improvements include the elimination of spurious stratospheric temperature spikes and an improved simulation of tropospheric dust. Other climate aspects of the p1 variant of CanESM5.1 are similar to those of CanESM5.0, while the p2 variant of CanESM5.1 features reduced equilibrium climate sensitivity and improved ENSO variability as a result of intentional tuning of the atmospheric component. The A4D activity has also led to the improved understanding of other notable CanESM5.0/5.1 biases, including the overestimation of North Atlantic sea ice, a cold bias over sea ice, biases in the stratospheric circulation and a cold bias over the Himalayas. It provides a potential framework for the broader climate community to contribute to CanESM development, which will facilitate further model improvements and ultimately lead to improved climate change information. [ABSTRACT FROM AUTHOR]

Using an Earth System Model and observations we analyze the sequence of events connecting episodes of trade wind strengthening (or weakening) to global mean surface temperature (GMST) cooling (or warming), with tropical ocean wave dynamics partially setting the time scale. In this sequence tropical west Pacific wind stress signals lead equatorial east Pacific thermocline depth signals which lead tropical east Pacific sea surface temperature (SST) signals which lead GMST signals. Using the anthropogenic, natural and tropical wind signals extracted from our simulations in a multivariate linear regression with observed GMST makes clear the balance that exists between anthropogenic warming and tropical wind-induced cooling during the recent warming slowdown, and between volcanic cooling and tropical wind-induced warming during the El Chichón and Pinatubo eruptions. Finally, we find an anticorrelation between global-mean temperatures in the near-surface (upper $$\sim $$ 100 m) and subsurface ( $$\sim $$ 100-300 m) ocean layers, linked to wind-driven interannual to decadal variations in the strength of the subtropical cell overturning in the upper Pacific Ocean. [ABSTRACT FROM AUTHOR]

Future climate projections from Earth system models (ESMs) typically focus on the timescale of this century. We use a set of five ESMs and one Earth system model of intermediate complexity (EMIC) to explore the dynamics of the Earth's climate and carbon cycles under contrasting emissions trajectories beyond this century to the year 2300. The trajectories include a very-high-emissions, unmitigated fossil-fuel-driven scenario, as well as a mitigation scenario that diverges from the first scenario after 2040 and features an "overshoot", followed by a decrease in atmospheric CO 2 concentrations by means of large net negative CO 2 emissions. In both scenarios and for all models considered here, the terrestrial system switches from being a net sink to either a neutral state or a net source of carbon, though for different reasons and centered in different geographic regions, depending on both the model and the scenario. The ocean carbon system remains a sink, albeit weakened by carbon cycle feedbacks, in all models under the high-emissions scenario and switches from sink to source in the overshoot scenario. The global mean temperature anomaly is generally proportional to cumulative carbon emissions, with a deviation from proportionality in the overshoot scenario that is governed by the zero emissions commitment. Additionally, 23rd century warming continues after the cessation of carbon emissions in several models in the high-emissions scenario and in one model in the overshoot scenario. While ocean carbon cycle responses qualitatively agree in both globally integrated and zonal mean dynamics in both scenarios, the land models qualitatively disagree in zonal mean dynamics, in the relative roles of vegetation and soil in driving C fluxes, in the response of the sink to CO 2 , and in the timing of the sink–source transition, particularly in the high-emissions scenario. The lack of agreement among land models on the mechanisms and geographic patterns of carbon cycle feedbacks, alongside the potential for lagged physical climate dynamics to cause warming long after CO 2 concentrations have stabilized, points to the possibility of surprises in the climate system beyond the 21st century time horizon, even under relatively mitigated global warming scenarios, which should be taken into consideration when setting global climate policy. [ABSTRACT FROM AUTHOR]

Ice algae play a fundamental role in shaping sea-ice-associated ecosystems and biogeochemistry. This role can be investigated by field observations; however the influence of ice algae at the regional and global scales remains unclear due to limited spatial and temporal coverage of observations and because ice algae are typically not included in current Earth system models. To address this knowledge gap, we introduce a new model intercomparison project (MIP), referred to here as the Ice Algae Model Intercomparison Project phase 2 (IAMIP2). IAMIP2 is built upon the experience from its previous phase and expands its scope to global coverage (both Arctic and Antarctic) and centennial timescales (spanning the mid-20th century to the end of the 21st century). Participating models are three-dimensional regional and global coupled sea-ice–ocean models that incorporate sea-ice ecosystem components. These models are driven by the same initial conditions and atmospheric forcing datasets by incorporating and expanding the protocols of the Ocean Model Intercomparison Project, an endorsed MIP of the Coupled Model Intercomparison Project phase 6 (CMIP6). Doing so provides more robust estimates of model bias and uncertainty and consequently advances the science of polar marine ecosystems and biogeochemistry. A diagnostic protocol is designed to enhance the reusability of the model data products of IAMIP2. Lastly, the limitations and strengths of IAMIP2 are discussed in the context of prospective research outcomes. [ABSTRACT FROM AUTHOR]

The ocean biogeochemistry components of the Canadian Earth System Model v. 5 are presented and compared to observations and other models. CanESM5 employs the same biogeochemistry module as CanESM2 whereas CanESM5-CanOE ("Canadian Ocean Ecosystem model") is a new, more complex biogeochemistry module developed for Sixth Coupled Model Intercomparison Project (CMIP6), with multiple food chains, flexible phytoplankton elemental ratios, and a prognostic iron cycle. This new model is described in detail and the outputs compared to CanESM5 and CanESM2, as well as to observations and other CMIP6 models. Both CanESM5 models show gains in skill relative to CanESM2, which are attributed primarily to improvements in ocean circulation. CanESM5-CanOE shows improved skill relative to CanESM5 in some areas. CanESM5-CanOE includes a prognostic iron cycle, and maintains high nutrient / low chlorophyll conditions in the expected regions (in CanESM2 and CanESM5, iron limitation is specified as a temporally static 'mask'). Surface nitrate concentrations are biased low in the subarctic Pacific and equatorial Pacific, and high in the Southern Ocean. Export production in CanESM5-CanOE is among the lowest for CMIP6 models; in CanESM5 it is among the highest, but shows the most rapid decline after about 1980. CanESM5-CanOE has relatively low concentrations of zooplankton and detritus relative to phytoplankton, and a high and relatively constant living phytoplankton fraction of total particulate organic matter. In most regions, large and small phytoplankton show decoupled seasonal cycles with greater abundance of large phytoplankton in the productive seasons. Cumulative ocean uptake of anthropogenic carbon dioxide through 2014 is lower in both CanESM5 models than in observation-based estimates or the model ensemble mean, and is lower in CanESM5-CanOE (122PgC) than in CanESM5 (132PgC). [ABSTRACT FROM AUTHOR]

Future climate projections from Earth system models (ESMs) typically focus on the timescale of this century. We use a set of four ESMs and one Earth system model of intermediate complexity (EMIC) to explore the dynamics of the Earth's climate and carbon cycles under contrasting emissions trajectories beyond this century, to the year 2300. The trajectories include a very high emissions, unmitigated fossil-fuel driven scenario, as well as a second mitigation scenario that diverges from the first scenario after 2040 and features an "overshoot", followed by stabilization of atmospheric CO2 concentrations by means of large net-negative CO2 emissions. In both scenarios, and for all models considered here, the terrestrial system switches from being a net sink to either a neutral state or a net source of carbon, though for different reasons and centered in different geographic regions, depending on both the model and the scenario. The ocean carbon system remains a sink, albeit weakened by climate-carbon feedbacks, in all models under the high emissions scenario, and switches from sink to source in the overshoot scenario. The global mean temperature anomaly generally follows the trajectories of cumulative carbon emissions, except that 23rd-century warming continues after the cessation of carbon emissions in several models, both in the high emissions scenario and in one model in the overshoot scenario. While ocean carbon cycle responses qualitatively agree both in globally integrated and zonal-mean dynamics in both scenarios, the land models qualitatively disagree in zonal-mean dynamics, in the relative roles of vegetation and soil in driving C fluxes, in the response of the sink to CO2, and in the timing of the sink-source transition, particularly in the high emissions scenario. The lack of agreement among land models on the mechanisms and geographic patterns of carbon cycle feedbacks, alongside the potential for lagged physical climate dynamics to cause warming long after CO2 concentrations have stabilized, point to the possibility of surprises in the climate system beyond the 21st century time horizon, even under relatively mitigated global warming scenarios, which should be taken into consideration when setting global climate policy. [ABSTRACT FROM AUTHOR]

We compare the mass budget of the Arctic sea ice for 15 models submitted to the latest Coupled Model Intercomparison Project (CMIP6), using new diagnostics that have not been available for previous model inter-comparisons. These diagnostics allow us to look beyond the standard metrics of ice cover and thickness to compare the processes of sea ice growth and loss in climate models in a more detailed way than has previously been possible. For the 1960–1989 multi-model mean, the dominant processes causing annual ice growth are basal growth and frazil ice formation, which both occur during the winter. The main processes by which ice is lost are basal melting, top melting and advection of ice out of the Arctic. The first two processes occur in summer, while the latter process is present all year. The sea ice budgets for individual models are strikingly similar overall in terms of the major processes causing ice growth and loss and in terms of the time of year during which each process is important. However, there are also some key differences between the models, and we have found a number of relationships between model formulation and components of the ice budget that hold for all or most of the CMIP6 models considered here. The relative amounts of frazil and basal ice formation vary between the models, and the amount of frazil ice formation is strongly dependent on the value chosen for the minimum frazil ice thickness. There are also differences in the relative amounts of top and basal melting, potentially dependent on how much shortwave radiation can penetrate through the sea ice into the ocean. For models with prognostic melt ponds, the choice of scheme may affect the amount of basal growth, basal melt and top melt, and the choice of thermodynamic scheme is important in determining the amount of basal growth and top melt. As the ice cover and mass decline during the 21st century, we see a shift in the timing of the top and basal melting in the multi-model mean, with more melt occurring earlier in the year and less melt later in the summer. The amount of basal growth reduces in the autumn, but it increases in the winter due to thinner sea ice over the course of the 21st century. Overall, extra ice loss in May–June and reduced ice growth in October–November are partially offset by reduced ice melt in August and increased ice growth in January–February. For the individual models, changes in the budget components vary considerably in terms of magnitude and timing of change. However, when the evolving budget terms are considered as a function of the changing ice state itself, behaviours common to all the models emerge, suggesting that the sea ice components of the models are fundamentally responding in a broadly consistent way to the warming climate. It is possible that this similarity in the model budgets may represent a lack of diversity in the model physics of the CMIP6 models considered here. The development of new observational datasets for validating the budget terms would help to clarify this. [ABSTRACT FROM AUTHOR]

Ice algae play a fundamental role in shaping polar marine ecosystems and biogeochemistry. This role can be investigated by field observations, however the influence of ice algae at the regional and global scales remains unclear due to limited spatial and temporal coverage of observations, and because ice algae are typically not included in current Earth System Models. To address this knowledge gap, we introduce a new model intercomparison project (MIP), referred to here as the Ice Algae Model Intercomparison Project phase 2 (IAMIP2). IAMIP2 is built upon the experience from its previous phase, and expands its scope to global coverage (both Arctic and Antarctic) and centennial timescales (spanning the mid-twentieth century to the end of the twenty-first century). Participating models are three-dimensional regional and global coupled sea ice–ocean models that incorporate sea-ice ecosystem components. These models are driven by the same initial conditions and atmospheric forcing datasets by incorporating and expanding the protocols of the Ocean Model Intercomparison Project, an endorsed MIP of the Coupled Model Intercomparison Project phase 6 (CMIP6). Doing so provides more robust estimates of model bias and uncertainty, and consequently advances the science of polar marine ecosystems and biogeochemistry. A diagnostic protocol is designed to enhance the reusability of the model data products of IAMIP2. Lastly, the limitations and strengths of IAMIP2 are discussed in the context of prospective research outcomes. [ABSTRACT FROM AUTHOR]

The ocean biogeochemistry components of two new versions of the Canadian Earth System Model (CanESM) are presented and compared to observations and other models. CanESM5 employs the same ocean biology model as CanESM2, whereas CanESM5-CanOE (Canadian Ocean Ecosystem model) is a new, more complex model developed for CMIP6, with multiple food chains, flexible phytoplankton elemental ratios, and a prognostic iron cycle. This new model is described in detail and the outputs (distributions of major tracers such as oxygen, dissolved inorganic carbon, and alkalinity, the iron and nitrogen cycles, plankton biomass, and historical trends in CO 2 uptake and export production) compared to CanESM5 and CanESM2, as well as to observations and other CMIP6 models. Both CanESM5 models show gains in skill relative to CanESM2, which are attributed primarily to improvements in ocean circulation. CanESM5-CanOE shows improved skill relative to CanESM5 for most major tracers at most depths. CanESM5-CanOE includes a prognostic iron cycle, and maintains high-nutrient/low-chlorophyll conditions in the expected regions (in CanESM2 and CanESM5, iron limitation is specified as a temporally static "mask"). Surface nitrate concentrations are biased low in the subarctic Pacific and equatorial Pacific, and high in the Southern Ocean, in both CanESM5 and CanESM5-CanOE. Export production in CanESM5-CanOE is among the lowest for CMIP6 models; in CanESM5, it is among the highest, but shows the most rapid decline after about 1980. CanESM5-CanOE shows some ability to simulate aspects of plankton community structure that a single-species model can not (e.g. seasonal dominance of large cells) but is biased towards low concentrations of zooplankton and detritus relative to phytoplankton. Cumulative ocean uptake of anthropogenic carbon dioxide through 2014 is lower in both CanESM5-CanOE (122 PgC) and CanESM5 (132 PgC) than in observation-based estimates (145 PgC) or the model ensemble mean (144 PgC). [ABSTRACT FROM AUTHOR]