scholarly journals Mineralogical constraints on Neoproterozoic pCO2 and marine carbonate chemistry

Geology ◽  
2020 ◽  
Vol 48 (6) ◽  
pp. 599-603
Author(s):  
Justin V. Strauss ◽  
Nicholas J. Tosca
Keyword(s):  
Carbon Cycle ◽  
System Change ◽  
Global Carbon Cycle ◽  
Earth System ◽  
Precipitation Kinetics ◽  
Secular Changes ◽  
Marine Carbonate ◽  
Ocean Atmosphere ◽  
Global Carbon ◽  
Early Neoproterozoic

Abstract Numerous investigators have sought to identify the perturbations to the global carbon cycle that fueled Earth system change during the Neoproterozoic Era. Nevertheless, a lack of constraints on ocean-atmosphere carbon chemistry has precluded efforts to link biology, climate, and the lithosphere. We combined field and petrographic observations with experimental and theoretical geochemistry to show that early Neoproterozoic seawater featured elevated alkalinity in the presence of high atmospheric pCO2, which sustained remarkable marine CaCO3 supersaturation (Ωcalcite). Without pelagic calcification, Neoproterozoic marine Ωcalcite and pCO2 would have been mediated principally by CaCO3 precipitation kinetics; thus, secular changes in kinetic inhibitors to CaCO3 nucleation may have destabilized the global carbon cycle.

Representing Arctic coastal erosion in the Max Planck Institute Earth System Model (MPI-ESM)

2020 ◽  
Author(s):  
David Marcolino Nielsen ◽  
Johanna Baehr ◽  
Victor Brovkin ◽  
Mikhail Dobrynin
Keyword(s):  
Carbon Cycle ◽  
Sea Ice ◽  
Coastal Erosion ◽  
Global Carbon Cycle ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Max Planck ◽  
Erosion Rates ◽  
Global Carbon

<p>The Arctic has warmed twice as fast as the globe and sea-ice extent has decreased, causing permafrost to thaw and the duration of the open-water period to extend. This combined effect increases the vulnerability of the Arctic coast to erosion, which in turn releases substantial amounts of carbon to both the ocean and the atmosphere, potentially contributing to further warming due to a positive climate-carbon cycle feedback. Therefore, Arctic coastal erosion is an important process of the global carbon cycle.</p><p>Comprehensive modelling studies exploring Arctic coastal erosion within the Earth system are still in their infancy. Here, we describe the development of a semi-empirical Arctic coastal erosion model and its coupling with the Max Planck Institute Earth System Model (MPI-ESM). We also present preliminary results for historical and future climate projections of coastal erosion rates in the Arctic. The coupling consists on the exchange of a combination of driving forcings from the atmosphere and the ocean, such as surface air temperature, winds and sea-ice concentration, which result in annual coastal erosion rates. In a further setp, organic matter from the eroded permafrost is provided to the ocean biogeochemistry model and, consequently, to the global carbon cycle including atmospheric CO<sub>2</sub>.</p>

Modelling the global carbon cycle for the past and future evolution of the earth system

1999 ◽  
Vol 159 (1-4) ◽  
pp. 305-317 ◽  
Author(s):  
Siegfried Franck ◽  
Konrad Kossacki ◽  
Christine Bounama
Keyword(s):  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Earth System ◽  
Future Evolution ◽  
The Past ◽  
The Earth ◽  
Global Carbon

scholarly journals Calcium isotope compositions as a means to trace carbonate recycling

2021 ◽  
Author(s):  
Shichun Huang ◽  
Stein B Jacobsen
Keyword(s):  
Carbon Cycle ◽  
Subduction Zones ◽  
Global Carbon Cycle ◽  
Calcium Isotope ◽  
Marine Carbonate ◽  
Deep Interior ◽  
Marine Carbonates ◽  
Pros And Cons ◽  
Global Carbon

Marine carbonate, an important CO2 reservoir, is continuously sent to the Earth's deep interior at subduction zones, forming an essential part of the global carbon cycle. The pros and cons of using calcium isotope compositions to trace marine carbonates recycled into the mantle are discussed in this Perspective.

Reconstructions and predictions of the global carbon cycle with an emission-driven Earth System Model

2021 ◽  
Author(s):  
Hongmei Li ◽  
Tatiana Ilyina ◽  
Tammas Loughran ◽  
Julia Pongratz
Keyword(s):  
Growth Rate ◽  
Carbon Cycle ◽  
Carbon Budget ◽  
Global Carbon Cycle ◽  
System Model ◽  
Earth System ◽  
Global Carbon Budget ◽  
Predictive Skill ◽  
Atmospheric Carbon ◽  
Global Carbon

<p>The global carbon budget including CO<sub>2</sub> fluxes among different reservoirs and atmospheric carbon growth rate vary substantially in interannual to decadal time-scales. Reconstructing and predicting the variable global carbon cycle is of essential value of tracing the fate of carbon and the corresponding climate and ecosystem changes. For the first time, we extend our prediction system based on the Max Planck Institute Earth system model (MPI-ESM) from concentration-driven to emission-driven taking into account the interactive carbon cycle and hence enabling prognostic atmospheric carbon increment. </p><p>By assimilating atmospheric and oceanic observational data products into MPI-ESM decadal prediction system, we can reproduce the observed variations of the historical global carbon cycle globally. The reconstruction from the fully coupled model enables quantification of global carbon budget within a close Earth system and therefore avoids the budget imbalance term of budgeting the carbon with standalone models. Our reconstructions of carbon budget provide a novel approach for supporting global carbon budget and understanding the dominating processes. Retrospective predictions based on the  emission-driven hindcasts, which are initiated from the reconstructions, show predictive skill in the atmospheric carbon growth rate, air-sea CO<sub>2</sub> fluxes, and air-land CO<sub>2</sub> fluxes. The air-sea CO<sub>2</sub> fluxes have higher predictive skill up to 5 years, and the air-land CO<sub>2</sub> fluxes and atmospheric carbon growth rate show predictive skill of 2 years. Our results also suggest predictions based on Earth system models enable reproducing and further predicting the evolution of atmospheric CO<sub>2</sub> concentration changes. The earth system predictions will provide valuable inputs for understanding the global carbon cycle and supporting climate relevant policy development. </p>

scholarly journals Development of a system emulating the global carbon cycle in Earth system models

2010 ◽  
Vol 3 (2) ◽  
pp. 365-376 ◽  
Author(s):  
K. Tachiiri ◽  
J. C. Hargreaves ◽  
J. D. Annan ◽  
A. Oka ◽  
A. Abe-Ouchi ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Climate Sensitivity ◽  
State Of The Art ◽  
Global Carbon Cycle ◽  
Transient Simulation ◽  
Earth System ◽  
Vegetation Model ◽  
Equilibrium Climate Sensitivity ◽  
Earth System Models ◽  
Global Carbon

Abstract. Recent studies have indicated that the uncertainty in the global carbon cycle may have a significant impact on the climate. Since state of the art models are too computationally expensive for it to be possible to explore their parametric uncertainty in anything approaching a comprehensive fashion, we have developed a simplified system for investigating this problem. By combining the strong points of general circulation models (GCMs), which contain detailed and complex processes, and Earth system models of intermediate complexity (EMICs), which are quick and capable of large ensembles, we have developed a loosely coupled model (LCM) which can represent the outputs of a GCM-based Earth system model, using much smaller computational resources. We address the problem of relatively poor representation of precipitation within our EMIC, which prevents us from directly coupling it to a vegetation model, by coupling it to a precomputed transient simulation using a full GCM. The LCM consists of three components: an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon cycle (an NPZD-type marine ecosystem model); a state of the art vegetation model (Sim-CYCLE); and a database of daily temperature, precipitation, and other necessary climatic fields to drive Sim-CYCLE from a precomputed transient simulation from a state of the art AOGCM. The transient warming of the climate system is calculated from MIROC-lite, with the global temperature anomaly used to select the most appropriate annual climatic field from the pre-computed AOGCM simulation which, in this case, is a 1% pa increasing CO2 concentration scenario. By adjusting the effective climate sensitivity (equivalent to the equilibrium climate sensitivity for an energy balance model) of MIROC-lite, the transient warming of the LCM could be adjusted to closely follow the low sensitivity (with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By tuning of the physical and biogeochemical parameters it was possible to reasonably reproduce the bulk physical and biogeochemical properties of previously published CO2 stabilisation scenarios for that model. As an example of an application of the LCM, the behavior of the high sensitivity version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also demonstrated. Given the highly adjustable nature of the model, we believe that the LCM should be a very useful tool for studying uncertainty in global climate change, and we have named the model, JUMP-LCM, after the name of our research group (Japan Uncertainty Modelling Project).

scholarly journals The global carbon cycle in the Canadian Earth system model (CanESM1): Preindustrial control simulation

2010 ◽  
Vol 115 (G3) ◽  
Author(s):  
J. R. Christian ◽  
V. K. Arora ◽  
G. J. Boer ◽  
C. L. Curry ◽  
K. Zahariev ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Control Simulation ◽  
Global Carbon

scholarly journals On constraining the strength of the terrestrial CO<sub>2</sub> fertilization effect in an Earth system model

2016 ◽  
Author(s):  
V. K. Arora ◽  
J. F. Scinocca
Keyword(s):  
Carbon Cycle ◽  
Carbon Budget ◽  
Co2 Flux ◽  
Global Carbon Cycle ◽  
System Model ◽  
Historical Period ◽  
Earth System ◽  
Co2 Fertilization ◽  
Fertilization Effect ◽  
Global Carbon

Abstract. Earth system models (ESMs) explicitly simulate the interactions between the physical climate system components and biogeochemical cycles. Physical and biogeochemical aspects of ESMs are routinely compared against their observation-based counterparts to assess model performance and to evaluate how this performance is affected by ongoing model development. Here, we assess the performance of version 4.2 of the Canadian Earth system model against four, land carbon cycle focused, observation-based determinants of the global carbon cycle and the historical global carbon budget over the 1850–2005 period. Our objective is to constrain the strength of the terrestrial CO2 fertilization effect which is known to be the most uncertain of all carbon cycle feedbacks. The observation-based determinants include (1) globally-averaged atmospheric CO2 concentration, (2) cumulative atmosphere–land CO2 flux, (3) atmosphere–land CO2 flux for the decades of 1960s, 1970s, 1980s, 1990s and 2000s and (4) the amplitude of the globally-averaged annual CO2 cycle and its increase over the 1980 to 2005 period. The optimal simulation that satisfies constraints imposed by the first three determinants yields a net primary productivity (NPP) increase from ~ 58 Pg C yr−1 in 1850 to about ~ 74 Pg C yr−1 in 2005; an increase of ~ 27 % over the 1850–2005 period. The simulated loss in the global soil carbon amount due to anthropogenic land use change over the historical period is also broadly consistent with empirical estimates. Yet, it remains possible that these determinants of the global carbon cycle are insufficient to adequately constrain the historical carbon budget, and consequently the strength of terrestrial CO2 fertilization effect as it is represented in the model, given the large uncertainty associated with LUC emissions over the historical period.

scholarly journals Constraining the strength of the terrestrial CO<sub>2</sub> fertilization effect in the Canadian Earth system model version 4.2 (CanESM4.2)

2016 ◽  
Vol 9 (7) ◽  
pp. 2357-2376 ◽  
Author(s):  
Vivek K. Arora ◽  
John F. Scinocca
Keyword(s):  
Carbon Cycle ◽  
Carbon Budget ◽  
Co2 Flux ◽  
Global Carbon Cycle ◽  
System Model ◽  
Historical Period ◽  
Earth System ◽  
Co2 Fertilization ◽  
Fertilization Effect ◽  
Global Carbon

Abstract. Earth system models (ESMs) explicitly simulate the interactions between the physical climate system components and biogeochemical cycles. Physical and biogeochemical aspects of ESMs are routinely compared against their observation-based counterparts to assess model performance and to evaluate how this performance is affected by ongoing model development. Here, we assess the performance of version 4.2 of the Canadian Earth system model against four land carbon-cycle-focused, observation-based determinants of the global carbon cycle and the historical global carbon budget over the 1850–2005 period. Our objective is to constrain the strength of the terrestrial CO2 fertilization effect, which is known to be the most uncertain of all carbon-cycle feedbacks. The observation-based determinants include (1) globally averaged atmospheric CO2 concentration, (2) cumulative atmosphere–land CO2 flux, (3) atmosphere–land CO2 flux for the decades of 1960s, 1970s, 1980s, 1990s, and 2000s, and (4) the amplitude of the globally averaged annual CO2 cycle and its increase over the 1980 to 2005 period. The optimal simulation that satisfies constraints imposed by the first three determinants yields a net primary productivity (NPP) increase from  ∼  58 Pg C year−1 in 1850 to about  ∼  74 Pg C year−1 in 2005; an increase of  ∼  27 % over the 1850–2005 period. The simulated loss in the global soil carbon amount due to anthropogenic land use change (LUC) over the historical period is also broadly consistent with empirical estimates. Yet, it remains possible that these determinants of the global carbon cycle are insufficient to adequately constrain the historical carbon budget, and consequently the strength of terrestrial CO2 fertilization effect as it is represented in the model, given the large uncertainty associated with LUC emissions over the historical period.

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