scholarly journals Compiled records of carbon isotopes in atmospheric CO<sub>2</sub> for historical simulations in CMIP6

2017 ◽  
Author(s):  
Heather Graven ◽  
Colin E. Allison ◽  
David M. Etheridge ◽  
Samuel Hammer ◽  
Ralph F. Keeling ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Carbon Isotopes ◽  
Coupled Model ◽  
Atmospheric Co2 ◽  
Historical Period ◽  
Terrestrial Biosphere ◽  
Climate Simulations ◽  
Intercomparison Project ◽  
Natural Carbon ◽  
Carbon Cycle Modelling

Abstract. The isotopic composition of carbon (Δ14C and δ13C) in atmospheric CO2 and in oceanic and terrestrial carbon reservoirs is influenced by anthropogenic emissions and by natural carbon exchanges, which can respond to and drive changes in climate. Simulations of 14C and 13C in the ocean and terrestrial components of Earth System Models (ESMs) present opportunities for model evaluation and for investigation of carbon cycling, including anthropogenic CO2 emissions and uptake. The use of carbon isotopes in novel evaluation of the ESMs' component ocean and terrestrial biosphere models and in new analyses of historical changes may improve predictions of future changes in the carbon cycle and climate system. We compile existing data to produce records of Δ14C and δ13C in atmospheric CO2 for the historical period 1850–2015. The primary motivation for this compilation is to provide the atmospheric boundary condition for historical simulations in the Coupled Model Intercomparison Project 6 (CMIP6) for models simulating carbon isotopes in their ocean or terrestrial biosphere models. The data may also be useful for other carbon cycle modelling activities.

scholarly journals Compiled records of carbon isotopes in atmospheric CO<sub>2</sub> for historical simulations in CMIP6

2017 ◽  
Vol 10 (12) ◽  
pp. 4405-4417 ◽  
Author(s):  
Heather Graven ◽  
Colin E. Allison ◽  
David M. Etheridge ◽  
Samuel Hammer ◽  
Ralph F. Keeling ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Carbon Isotopes ◽  
Coupled Model ◽  
Atmospheric Co2 ◽  
Historical Period ◽  
Terrestrial Biosphere ◽  
Climate Simulations ◽  
Intercomparison Project ◽  
Natural Carbon ◽  
Carbon Cycle Modelling

Abstract. The isotopic composition of carbon (Δ14C and δ13C) in atmospheric CO2 and in oceanic and terrestrial carbon reservoirs is influenced by anthropogenic emissions and by natural carbon exchanges, which can respond to and drive changes in climate. Simulations of 14C and 13C in the ocean and terrestrial components of Earth system models (ESMs) present opportunities for model evaluation and for investigation of carbon cycling, including anthropogenic CO2 emissions and uptake. The use of carbon isotopes in novel evaluation of the ESMs' component ocean and terrestrial biosphere models and in new analyses of historical changes may improve predictions of future changes in the carbon cycle and climate system. We compile existing data to produce records of Δ14C and δ13C in atmospheric CO2 for the historical period 1850–2015. The primary motivation for this compilation is to provide the atmospheric boundary condition for historical simulations in the Coupled Model Intercomparison Project 6 (CMIP6) for models simulating carbon isotopes in the ocean or terrestrial biosphere. The data may also be useful for other carbon cycle modelling activities.

scholarly journals Constraining a land surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System

2016 ◽  
Author(s):  
G. J. Schürmann ◽  
T. Kaminski ◽  
C. Köstler ◽  
N. Carvalhais ◽  
M. Voßbeck ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Land Surface ◽  
Data Stream ◽  
Atmospheric Co2 ◽  
Surface Model ◽  
Terrestrial Biosphere ◽  
Multiple Observations ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS) built around the tangent-linear version of the land surface scheme of the MPI-Earth System Model v1 (JSBACH). The simulated terrestrial biosphere processes (phenology and carbon balance) were constrained by observations of the fraction of photosynthetically active radiation (TIP-FAPAR product) and by observations of atmospheric CO2 at a global set of monitoring stations for the years 2005–2009. The system successfully, and computationally efficiently, improved average foliar area and northern extra-tropical seasonality of foliar area when constrained by TIP-FAPAR. Global net and gross carbon fluxes were improved when constrained by atmospheric CO2, although the system tended to underestimate tropical productivity. Assimilating both data streams jointly allowed the MPI-CCDAS to match both observations (TIP-FAPAR and atmospheric CO2) equally well as the single data stream assimilation cases, therefore overall increasing the appropriateness of the resultant parameter values and biosphere dynamics. Our study thus highlights the role of the TIP-FAPAR product in stabilising the underdetermined atmospheric inversion problem and demonstrates the value of multiple-data stream assimilation for the simulation of terrestrial biosphere dynamics. The constraint on regional gross and net CO2 flux patterns is limited through the parametrisation of the biosphere model. We expect improvement on that aspect through a refined initialisation strategy and inclusion of further biosphere observations as constraints.

scholarly journals Deglacial carbon cycle changes observed in a compilation of 127 benthic <i>δ</i><sup>13</sup>C time series (20–6 ka)

2018 ◽  
Vol 14 (8) ◽  
pp. 1229-1252 ◽  
Author(s):  
Carlye D. Peterson ◽  
Lorraine E. Lisiecki
Keyword(s):  
Time Series ◽  
Carbon Cycle ◽  
Carbon Storage ◽  
Large Scale ◽  
Deep Ocean ◽  
Atmospheric Co2 ◽  
Last Deglaciation ◽  
Terrestrial Biosphere ◽  
Spatial Coverage ◽  
Ocean Carbon

Abstract. We present a compilation of 127 time series δ13C records from Cibicides wuellerstorfi spanning the last deglaciation (20–6 ka) which is well-suited for reconstructing large-scale carbon cycle changes, especially for comparison with isotope-enabled carbon cycle models. The age models for the δ13C records are derived from regional planktic radiocarbon compilations (Stern and Lisiecki, 2014). The δ13C records were stacked in nine different regions and then combined using volume-weighted averages to create intermediate, deep, and global δ13C stacks. These benthic δ13C stacks are used to reconstruct changes in the size of the terrestrial biosphere and deep ocean carbon storage. The timing of change in global mean δ13C is interpreted to indicate terrestrial biosphere expansion from 19–6 ka. The δ13C gradient between the intermediate and deep ocean, which we interpret as a proxy for deep ocean carbon storage, matches the pattern of atmospheric CO2 change observed in ice core records. The presence of signals associated with the terrestrial biosphere and atmospheric CO2 indicates that the compiled δ13C records have sufficient spatial coverage and time resolution to accurately reconstruct large-scale carbon cycle changes during the glacial termination.

scholarly journals Quantifying Carbon Cycle Feedbacks

2009 ◽  
Vol 22 (19) ◽  
pp. 5232-5250 ◽  
Author(s):  
J. M. Gregory ◽  
C. D. Jones ◽  
P. Cadule ◽  
P. Friedlingstein
Keyword(s):  
Carbon Cycle ◽  
Co2 Emissions ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Climate Feedback ◽  
Climate Response ◽  
Carbon Cycle Model ◽  
Atmospheric Co2 Concentration ◽  
Intercomparison Project ◽  
Earth System Models

Abstract Perturbations to the carbon cycle could constitute large feedbacks on future changes in atmospheric CO2 concentration and climate. This paper demonstrates how carbon cycle feedback can be expressed in formally similar ways to climate feedback, and thus compares their magnitudes. The carbon cycle gives rise to two climate feedback terms: the concentration–carbon feedback, resulting from the uptake of carbon by land and ocean as a biogeochemical response to the atmospheric CO2 concentration, and the climate–carbon feedback, resulting from the effect of climate change on carbon fluxes. In the earth system models of the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP), climate–carbon feedback on warming is positive and of a similar size to the cloud feedback. The concentration–carbon feedback is negative; it has generally received less attention in the literature, but in magnitude it is 4 times larger than the climate–carbon feedback and more uncertain. The concentration–carbon feedback is the dominant uncertainty in the allowable CO2 emissions that are consistent with a given CO2 concentration scenario. In modeling the climate response to a scenario of CO2 emissions, the net carbon cycle feedback is of comparable size and uncertainty to the noncarbon–climate response. To quantify simulated carbon cycle feedbacks satisfactorily, a radiatively coupled experiment is needed, in addition to the fully coupled and biogeochemically coupled experiments, which are referred to as coupled and uncoupled in C4MIP. The concentration–carbon and climate–carbon feedbacks do not combine linearly, and the concentration–carbon feedback is dependent on scenario and time.

scholarly journals AerChemMIP: quantifying the effects of chemistry and aerosols in CMIP6

2017 ◽  
Vol 10 (2) ◽  
pp. 585-607 ◽  
Author(s):  
William J. Collins ◽  
Jean-François Lamarque ◽  
Michael Schulz ◽  
Olivier Boucher ◽  
Veronika Eyring ◽  
...  
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Climate Impacts ◽  
Atmospheric Composition ◽  
Historical Period ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and their climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. Specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.

PMIP-carbon: towards a multi-models comparison of climate-carbon interactions at the Last Glacial Maximum

2020 ◽  
Author(s):  
Nathaelle Bouttes ◽  
Ruza Ivanovic ◽  
Ayako Abe-Ouchi ◽  
Hidetaka Kobayashi ◽  
Laurie Menviel ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Carbon Isotopes ◽  
Last Glacial Maximum ◽  
Ocean Circulation ◽  
Ice Cores ◽  
Glacial Maximum ◽  
Last Glacial ◽  
Intercomparison Project ◽  
The Last Glacial Maximum ◽  
The Last Glacial

&lt;p&gt;More and more climate models now include the carbon cycle, but multi-models studies of climate-carbon simulations within the Climate Model Intercomparison Project (CMIP) are limited to present and future time periods. In addition, the carbon cycle is not considered in the simulations of past periods analysed within the Paleoclimate Modelling Intercomparison Project (PMIP). Yet, climate-carbon interactions are crucial to anticipate future atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentrations and their impact on climate. Such interactions can change depending on the background climate, it is thus necessary to compare model results among themselves and to data for past periods with different climates such as the Last Glacial Maximum (LGM).&lt;/p&gt;&lt;p&gt;The Last Glacial Maximum, around 21,000 years ago, was about 4&amp;#176;C colder than the pre-industrial, and associated with large ice sheets on the American and Eurasian continents. It is one of the best documented periods thanks to numerous paleoclimate archives such as marine sediment cores and ice cores. Despite this period having been studied for years, no consensus on the causes of the lower atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration at the time (around 180 ppm) has been reached and models still struggle to simulate these low CO&lt;sub&gt;2&lt;/sub&gt; values. The ocean, which contains around 40 times more carbon than the atmosphere, likely plays a key role, but models tend to simulate ocean circulation changes in disagreement with proxy data, such as carbon isotopes.&lt;/p&gt;&lt;p&gt;This new project aims at comparing, for the first time, the carbon cycle representation at the Last Glacial Maximum from general circulation models and intermediate complexity models. We will explain the protocol and present first results in terms of carbon storage in the main reservoirs (atmosphere, land and ocean) and their link to key climate variables such as temperature, sea ice and ocean circulation. The use of coupled climate-carbon models will not only allow to compare changes in the carbon cycle in models and analyse their causes, but it will also enable us to better compare to indirect data related to the carbon cycle such as carbon isotopes.&lt;/p&gt;

scholarly journals Description of the MIROC-ES2L Earth system model and evaluation of its climate–biogeochemical processes and feedbacks

2019 ◽  
Author(s):  
Tomohiro Hajima ◽  
Michio Watanabe ◽  
Akitomo Yamamoto ◽  
Hiroaki Tatebe ◽  
Maki A. Noguchi ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Nitrogen Cycle ◽  
Carbon Sink ◽  
Coupled Model ◽  
System Model ◽  
Climate Response ◽  
Earth System ◽  
Model Intercomparison ◽  
Transient Climate Response ◽  
Intercomparison Project

Abstract. This study developed a new Model for Interdisciplinary Research on Climate, Earth System version2 for Long-term simulations (MIROC-ES2L) Earth system model (ESM) using a state-of-the-art climate model as the physical core. This model embeds a terrestrial biogeochemical component with explicit carbon–nitrogen interaction to account for soil nutrient control on plant growth and the land carbon sink. The model’s ocean biogeochemical component is largely updated to simulate biogeochemical cycles of carbon, nitrogen, phosphorus, iron, and oxygen such that oceanic primary productivity can be controlled by multiple nutrient limitations. The ocean nitrogen cycle is coupled with the land component via river discharge processes, and external inputs of iron from pyrogenic and lithogenic sources are considered. Comparison of a historical simulation with observation studies showed the model could reproduce reasonable historical changes in climate, the carbon cycle, and other biogeochemical variables together with reasonable spatial patterns of distribution of the present-day condition. The model demonstrated historical human perturbation of the nitrogen cycle through land use and agriculture, and it simulated the resultant impact on the terrestrial carbon cycle. Sensitivity analyses in preindustrial conditions revealed modeled ocean biogeochemistry could be changed regionally (but substantially) by nutrient inputs from the atmosphere and rivers. Through an idealized experiment of a 1 %CO2 increase scenario, we found the transient climate response (TCR) in the model is 1.5 K, i.e., approximately 70 % that of our previous model. The cumulative airborne fraction (AF) is also reduced by 15 % because of the intensified land carbon sink, resulting in an AF close to the multimodel mean of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs. The transient climate response to cumulative carbon emission (TCRE) is 1.3 K EgC−1, i.e., slightly smaller than the average of the CMIP5 ESMs, suggesting optimistic model performance in future climate projections. This model and the simulation results are contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). The ESM could help further understanding of climate–biogeochemical interaction mechanisms, projections of future environmental changes, and exploration of our future options regarding sustainable development by evolving the processes of climate, biogeochemistry, and human activities in a holistic and interactive manner.

scholarly journals Recurrence Spectra of European Temperature in Historical Climate Simulations

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 166 ◽  
Author(s):  
M. Alvarez-Castro ◽  
Davide Faranda ◽  
Thomas Noël ◽  
Pascal Yiou
Keyword(s):  
Coupled Model ◽  
Temperature Extremes ◽  
Model Intercomparison ◽  
Model Ensemble ◽  
Climate Simulations ◽  
Ensemble Mean ◽  
Order Of Magnitude ◽  
Intercomparison Project ◽  
European Temperature Extremes ◽  
Cold Extremes

We analyse and quantify the recurrences of European temperature extremes using 32 historical simulations (1900–1999) of the fifth Coupled Model Intercomparison Project (CMIP5) and 8 historical simulations (1971–2005) from the EUROCORDEX experiment. We compare the former simulations to the 20th Century Reanalysis (20CRv2c) dataset to compute recurrence spectra of temperature in Europe. We find that, (1) the spectra obtained by the model ensemble mean are generally consistent with those of 20CR; (2) spectra biases have a strong regional dependence; (3) the resolution does not change the order of magnitude of spectral biases between models and reanalysis, (4) the spread in recurrence biases is larger for cold extremes. Our analysis of biases provides a new way of selecting a subset of the CMIP5 ensemble to obtain an optimal estimate of temperature recurrences for a range of time-scales.

Showcasing the compact Earth system model OSCAR v3.1 with CMIP6 simulations

2021 ◽  
Author(s):  
Yann Quilcaille ◽  
Thomas Gasser
Keyword(s):  
Carbon Cycle ◽  
Atmospheric Chemistry ◽  
Coupled Model ◽  
Climate Feedback ◽  
Large Set ◽  
Earth System ◽  
Ocean Carbon Cycle ◽  
Intercomparison Project ◽  
Reduced Complexity ◽  
Ocean Carbon

&lt;p&gt;While Earth system models (ESM) provide spatially detailed process-based outputs, they present heavy computational costs. Reduced complexity models such as OSCAR are calibrated on those complex models and provide an alternative with faster calculations but lower resolutions. Yet, reduced-complexity models need to be evaluated and validated. We diagnose the newest version of OSCAR (v3.1) using observations and results from ESMs and the current Coupled Model Intercomparison Project 6. A total of 99 experiments are selected for simulation with OSCAR v3.1 in a probabilistic framework, reaching a total of 567,700,000 simulated years. Here, we showcase these results. A first highlight of this exercise is the unstability of the model for high-warming scenarios, which we attribute to the ocean carbon cycle module. The diverging runs caused by this unstability were discarded in the post-processing. The ensuing main results were further obtained by weighting each physical parametrizations based on their performance to replicate a set of observations. Overall, OSCAR v3.1 qualitively behaves like complex ESMs, for all aspects of the Earth system, although we observe a number of quantitative differences with state-of-the-art models. Some specific features of OSCAR contribute in these differences, such as its fully interactive atmospheric chemistry and endogenous calculations of biomass burning, wetlands and permafrost emissions. Nevertheless, the low sensitivity of the land carbon cycle to climate change, the unstability of the ocean carbon cycle, the seemingly over-constrained climate module, and the strong climate feedback over short-lived species, all call for an improvement of these aspects in OSCAR. Beyond providing a key diagnosis of the model in the context of the reduced-complexity models intercomparison project (RCMIP), this work is also meant to help with the upcoming calibration of OSCAR on CMIP6 results, and to provide a large set of CMIP6 simulations all run consistently with a probalistic model.&lt;/p&gt;

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