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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 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.

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1% per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.

The strength of feedbacks between a changing climate and future CO2 concentrations is uncertain and difficult to predict using Earth System Models (ESMs). We analyzed emission-driven simulations—in which atmospheric CO2levels were computed prognostically—for historical (1850–2005) and future periods (Representative Concentration Pathway (RCP) 8.5 for 2006–2100) produced by 15 ESMs for the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Comparison of ESM prognostic atmospheric CO2 over the historical period with observations indicated that ESMs, on average, had a small positive bias in predictions of contemporary atmospheric CO2. Weak ocean carbon uptake in many ESMs contributed to this bias, based on comparisons with observations of ocean and atmospheric anthropogenic carbon inventories. We found a significant linear relationship between contemporary atmospheric CO2 biases and future CO2levels for the multimodel ensemble. We used this relationship to create a contemporary CO2 tuned model (CCTM) estimate of the atmospheric CO2 trajectory for the 21st century. The CCTM yielded CO2estimates of 600±14 ppm at 2060 and 947±35 ppm at 2100, which were 21 ppm and 32 ppm below the multimodel mean during these two time periods. Using this emergent constraint approach, the likely ranges of future atmospheric CO2, CO2-induced radiative forcing, and CO2-induced temperature increases for the RCP 8.5 scenario were considerably narrowed compared to estimates from the full ESM ensemble. Our analysis provided evidence that much of the model-to-model variation in projected CO2 during the 21st century was tied to biases that existed during the observational era and that model differences in the representation of concentration-carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability. By improving models to more closely match the long-term time series of CO2from Mauna Loa, our analysis suggests that uncertainties in future climate projections can be reduced.

This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. MostEMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6-6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO2 emissions after 2300 results in slowly decreasing atmospheric CO2 concentrations. At year 3000 atmospheric CO2 is still at more than half its year-2300 level in all EMICs forRCPs 4.5-8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination ofCO2 emissions in allEMICs.Restoration of atmosphericCO2 fromRCPto preindustrial levels over 100-1000 years requires large artificial removal of CO2 from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO2. © 2013 American Meteorological Society.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.dsr.2004.12.008 Byline: E. Machu (a), A. Biastoch (b), A. Oschlies (b), M. Kawamiya (b), J.R.E. Lutjeharms (c), V. Garcon (a) Abstract: The greater Agulhas Current system has several components with high mesoscale turbulence. The phytoplankton distribution in the southwest Indian Ocean reflects this activity. We have used a regional eddy-permitting, coupled physical-biological model to study the physical-biological interactions and to address the main processes responsible for phytoplankton distribution in three different biogeochemical provinces: the southwest Subtropical Indian Gyre (SWSIG), the subtropical convergence zone (SCZ) and the subantarctic waters (SAW) south of South Africa. The biological model with four compartments (Nitrate-Phytoplankton-Zooplankton-Detritus) adequately reproduces the observed field of chlorophyll a. The phase of the strong modelled seasonality in the SWSIG is opposite to that of the SCZ that forms the southern boundary of the subtropical gyre. Phytoplankton concentrations are governed by the source-minus-sink terms, which are one order of magnitude greater than the dynamical diffusion and advection terms. North of 35[degrees]S, in the SWSIG, phytoplankton growth is limited by nutrients supply throughout the year. However, deeper stratification, enhanced cross-frontal transport and higher detritus remineralization explain the simulated higher concentrations of phytoplankton found in winter in the SWSIG. The region between 35[degrees] and 40[degrees]S constitutes a transition zone between the SCZ and the oligotrophic subtropical province. Horizontal advection is the main process bringing nutrients for phytoplankton growth. The front at 34[degrees]S represents a dynamical barrier to an extension further to the north of this advection of nutrients. Within the SCZ, primary production is high during spring and summer. This high productivity depletes the nutrient standing stock built up during winter time. In winter, nutrients supply in the convergence zone is indeed large, but the deep mixing removes phytoplankton from the euphotic zone and inhibits photosynthesis, yielding lower surface chlorophyll a concentrations. Waters south of the Subantarctic Front have a summer biomass close to that of frontal waters and higher than for subtropical waters. However, these simulated concentrations are slightly higher than the observed ones suggesting that limitation by iron and/or silica may play a role. Author Affiliation: (a) Laboratoire d'Etudes en Geophysique et Oceanographie Spatiales, CNRS, UMR5566, 18, Avenue E. Belin, 31401 Toulouse cedex 9, France (b) Institut fur Meereskunde an der Universitat Kiel, Dusternbrooker Weg 20, 24105, Kiel, Germany (c) Department of Oceanography, University of Cape Town, 7700 Rondebosch, South Africa

Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes seem to be underestimated. It is possible that recent modelled climate trends or climate-carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2x and 4x CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate-carbon feedbacks. The values from EMICs generally fall within the range given by General Circulation Models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows considerable synergy between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from paleoclimate reconstructions. This in turn could be a result of errors in the reconstructions of volcanic and/or solar radiative forcing used to drive the models or the incomplete representation of certain processes or variability within the models. Given the datasets used in this study, the models calculate significant land-use emissions over the pre-industrial. This implies that land-use emissions might need to be taken into account, when making estimates of climate-carbon feedbacks from paleoclimate reconstructions. [ABSTRACT FROM AUTHOR]

The importance of evaluating models using paleoclimate simulations is becoming more recognized in efforts to improve climate projection. To evaluate an integrated Earth System Model, MIROC-ESM, we performed simulations in time-slice experiments for the mid-Holocene (6000 yr before present, 6 ka) and preindustrial (1850 AD) times under the protocol of the Coupled Model Intercomparison Project 5/Paleoclimate Modeling Intercomparison Project 3. We first overview the simulated global climates by comparing with simulations using a previous version of the MIROC model (MIROC3), which is an atmosphere-ocean coupled general circulation model, and then comprehensively discuss various aspects of climate change with 6 ka forcing. We also discuss the 6 ka African monsoon activity. The 6 ka precipitation change over northern Africa according to MIROC-ESM does not differ dramatically from that obtained with MIROC3, which means that newly developed components such as dynamic vegetation and improvements in the atmospheric processes do not have significant impacts on representing the 6 ka monsoon change suggested by proxy records. Although there is no drastic difference in the African monsoon representation between the two models, there are small but significant differences in the precipitation enhancement in MIROC-ESM, which can be related to the representation of the sea surface temperature rather than the vegetation coupling, at least in MIROC-ESM. [ABSTRACT FROM AUTHOR]

The largest pH decline and widespread undersaturation with respect to aragonite in this century due to uptake of anthropogenic carbon dioxide in the Arctic Ocean have been projected. The reductions in pH and aragonite saturation state have been caused primarily by an increase in the concentration of atmospheric carbon dioxide. However, in a previous study, simulations with and without warming showed that these reductions in the Arctic Ocean also advances due to the melting of sea ice caused by global warming. Therefore, future projections of pH and aragonite saturation in the Arctic Ocean will be affected by how rapidly the reduction in sea ice occurs. In this study, the impact of sea-ice reduction rate on projected pH and aragonite saturation state in the Arctic surface waters was investigated. Reductions in pH and aragonite saturation were calculated from the outputs of two versions of an earth system model (ESM) with different sea-ice reduction rates under similar CO2 emission scenarios. The newer model version projects that Arctic summer ice-free condition will be achieved by the year 2040, and the older version predicts ice-free condition by 2090. The Arctic surface water was projected to be undersaturated with respect to aragonite in the annual mean when atmospheric CO2 concentration reached 480 (550) ppm in year 2040 (2048) in new (old) version. At an atmospheric CO2 concentration of 520 ppm, the maximum differences in pH and aragonite saturation state between the two versions were 0.08 and 0.15, respectively. The analysis showed that the decreases in pH and aragonite saturation state due to rapid sea-ice reduction were caused by increases in both CO2 uptake and freshwater input. Thus, the reductions in pH and aragonite saturation state in the Arctic surface waters are significantly affected by the difference in future projections for sea-ice reduction rate. The critical CO2 concentration, at which the Arctic surface waters become undersaturated with respect to aragonite on annual mean bias, would be lower by 70 ppm in the version with the rapid sea-ice reduction. [ABSTRACT FROM AUTHOR]

The article describes the earth system model MIROC-ESM in relation to each model component and their interactions. It presents the findings for the Coupled Model Intercomparison Project phase 5 (CMIP5) to illustrate the performance of the model from different perspectives including atmospheric chemistry, terrestrial biogeochemistry and aerosols. Also discussed is the reasonable simulation of the global distribution of column ozone in the model.

Eleven coupled climate–carbon cycle models used a common protocol to study the coupling between climate change and the carbon cycle. The models were forced by historical emissions and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 anthropogenic emissions of CO2 for the 1850–2100 time period. For each model, two simulations were performed in order to isolate the impact of climate change on the land and ocean carbon cycle, and therefore the climate feedback on the atmospheric CO2 concentration growth rate. There was unanimous agreement among the models that future climate change will reduce the efficiency of the earth system to absorb the anthropogenic carbon perturbation. A larger fraction of anthropogenic CO2 will stay airborne if climate change is accounted for. By the end of the twenty-first century, this additional CO2 varied between 20 and 200 ppm for the two extreme models, the majority of the models lying between 50 and 100 ppm. The higher CO2 levels led to an additional climate warming ranging between 0.1° and 1.5°C. All models simulated a negative sensitivity for both the land and the ocean carbon cycle to future climate. However, there was still a large uncertainty on the magnitude of these sensitivities. Eight models attributed most of the changes to the land, while three attributed it to the ocean. Also, a majority of the models located the reduction of land carbon uptake in the Tropics. However, the attribution of the land sensitivity to changes in net primary productivity versus changes in respiration is still subject to debate; no consensus emerged among the models. [ABSTRACT FROM AUTHOR]

Abstract Background Climate variability modifies both oceanic and terrestrial surface CO2 flux. Using observed/assimilated data sets, earlier studies have shown that tropical oceanic climate variability has strong impacts on the land surface temperature and soil moisture, and that there is a negative correlation between the oceanic and terrestrial CO2 fluxes. However, these data sets only cover less than the most recent 20 years and are insufficient for identifying decadal and longer periodic variabilities. To investigate possible impacts of interannual to interdecadal climate variability on CO2 flux exchange, the last 125 years of an earth system model (ESM) control run are examined. Results Global integration of the terrestrial CO2 flux anomaly shows variation much greater in amplitude and longer in periodic timescale than the oceanic flux. The terrestrial CO2 flux anomaly correlates negatively with the oceanic flux in some periods, but positively in others, as the periodic timescale is different between the two variables. To determine the spatial pattern of the variability, a series of composite analyses are performed. The results show that the oceanic CO2 flux variability peaks when the eastern tropical Pacific has a large sea surface temperature anomaly (SSTA). By contrast, the terrestrial CO2 flux variability peaks when the SSTA appears in the central tropical Pacific. The former pattern of variability resembles the ENSO-mode and the latter the ENSO-modoki1. Conclusions Our results imply that the oceanic and terrestrial CO2 flux anomalies may correlate either positively or negatively depending on the relative phase of these two modes in the tropical Pacific.

Nutrient inputs from the atmosphere and rivers to the ocean are increased substantially by human activities. However, the effects of increased nutrient inputs are not included in the widely used CMIP5 Earth system models, which introduce bias into model simulations of ocean biogeochemistry. Here, using historical simulations by an Earth system model with perturbed atmospheric and riverine nutrient inputs, we show that the contribution of anthropogenic nutrient inputs to past global changes in ocean biogeochemistry is of similar magnitude to the effect of climate change. Anthropogenic nutrient inputs increase oceanic productivity and carbon uptake, offsetting climate-induced decrease and accelerating climate-driven deoxygenation in the upper ocean. Moreover, accounting for anthropogenic nutrient inputs improves the known carbon budget imbalance and model underestimation of the observed decrease in the global oxygen inventory. Considering the effects of both nutrient inputs and climate change is crucial in assessing anthropogenic impacts on ocean biogeochemistry.

Many nations responded to the corona virus disease-2019 (COVID-19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO 2 , other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial-condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near-surface temperature or rainfall during 2020-2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID-19-related emission reductions on near-term climate., (© 2021. Crown Copyright. © 2021. Her Majesty the Queen in Right of Canada. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland. Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA.)

Recent climate modeling studies have concluded that cumulative carbon emissions determine temperature increase, regardless of emission pathways. Accordingly, the optimal emission pathway can be determined from a socioeconomic standpoint. To access the path dependence of socioeconomic impacts for cumulative carbon emissions, we used a computable general equilibrium model to analyze impacts on major socioeconomic indicators on a global scale for 30-50 pathways with different emission reduction starting years, different subsequent emission pathways, and three different cumulative 2100 emission scenarios (emissions that meet the 2 °C target, the 2 °C target emissions plus 10 %, and emissions producing radiative forcing of 4.5 W/m 2 ). The results show that even with identical cumulative emission figures, the resulting socioeconomic impacts vary by the pathway realized. For the United Nations 2 °C target, for example, (a) the 95 % confidence interval of cumulative global gross domestic product (GDP) is 1355-1363 trillion US dollars (2010-2100, discount rate = 5 %), (b) the cumulative GDP of pathways with later emission reduction starting years grows weaker (5 % significance level), and (c) emissions in 2100 have a moderate negative correlation with cumulative GDP. These results suggest that GDP loss is minimized with pathways with earlier emission reduction followed by more moderate reduction rates to achieve lower emission levels. Consequently, we suggest an early emission peak to meet the stringent target. In our model setting, it is desirable for emissions to peak by 2020 to reduce mitigation cost and by 2030 at the latest to meet the 2 °C target.

Global warming effects on seaweed beds are already perceptible. Their geographical distributions greatly depend on water temperatures. To predict future geographical distributions of brown alga, Sargassum horneri, forming large beds in the northwestern Pacific, we referred to future monthly surface water temperatures at about 1.1° of longitude and 0.6° of latitude in February and August in 2050 and 2100 simulated by 12 organizations under an A2 scenario of global warming. The southern limit of S. horneri distribution is expected to keep moving northward such that it may broadly disappear from Honshu Island, the Chinese coast, and Korean Peninsula in 2100, when tropical Sargassum species such as Sargassum tenuifolium may not completely replace S. horneri. Thus, their forests in 2100 do not substitute those of S. horneri in 2000. Fishes using the beds and seaweed rafts consisting of S. horneri in East China Sea suffer these disappearances., (Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Climate variability modifies both oceanic and terrestrial surface CO2 flux. Using observed/assimilated data sets, earlier studies have shown that tropical oceanic climate variability has strong impacts on the land surface temperature and soil moisture, and that there is a negative correlation between the oceanic and terrestrial CO2 fluxes. However, these data sets only cover less than the most recent 20 years and are insufficient for identifying decadal and longer periodic variabilities. To investigate possible impacts of interannual to interdecadal climate variability on CO2 flux exchange, the last 125 years of an earth system model (ESM) control run are examined., Results: Global integration of the terrestrial CO2 flux anomaly shows variation much greater in amplitude and longer in periodic timescale than the oceanic flux. The terrestrial CO2 flux anomaly correlates negatively with the oceanic flux in some periods, but positively in others, as the periodic timescale is different between the two variables. To determine the spatial pattern of the variability, a series of composite analyses are performed. The results show that the oceanic CO2 flux variability peaks when the eastern tropical Pacific has a large sea surface temperature anomaly (SSTA). By contrast, the terrestrial CO2 flux variability peaks when the SSTA appears in the central tropical Pacific. The former pattern of variability resembles the ENSO-mode and the latter the ENSO-modoki1., Conclusions: Our results imply that the oceanic and terrestrial CO2 flux anomalies may correlate either positively or negatively depending on the relative phase of these two modes in the tropical Pacific.