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

2021 ◽  
Author(s):  
Hongmei Li ◽  
Tatiana Ilyina ◽  
Tammas Francis Loughran ◽  
Julia Pongratz
Author(s):  
J. R. Christian ◽  
V. K. Arora ◽  
G. J. Boer ◽  
C. L. Curry ◽  
K. Zahariev ◽  
...  

2020 ◽  
Author(s):  
David Marcolino Nielsen ◽  
Johanna Baehr ◽  
Victor Brovkin ◽  
Mikhail Dobrynin

<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>


2021 ◽  
Author(s):  
Hongmei Li ◽  
Tatiana Ilyina ◽  
Tammas Loughran ◽  
Julia Pongratz

<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>


2016 ◽  
Author(s):  
V. K. Arora ◽  
J. F. Scinocca

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.


2016 ◽  
Vol 9 (7) ◽  
pp. 2357-2376 ◽  
Author(s):  
Vivek K. Arora ◽  
John F. Scinocca

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.


2018 ◽  
Author(s):  
Chuncheng Guo ◽  
Mats Bentsen ◽  
Ingo Bethke ◽  
Mehmet Ilicak ◽  
Jerry Tjiputra ◽  
...  

Abstract. A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g. 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multi-millennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speedup is primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean-sea ice horizontal grid configuration that allows an increase of the ocean-sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasises model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F in general agree well with observational estimates, and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain.


2019 ◽  
Vol 12 (1) ◽  
pp. 343-362 ◽  
Author(s):  
Chuncheng Guo ◽  
Mats Bentsen ◽  
Ingo Bethke ◽  
Mehmet Ilicak ◽  
Jerry Tjiputra ◽  
...  

Abstract. A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g., 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multimillennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speed-up is primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean–sea ice horizontal grid configuration that allows an increase of the ocean–sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasizes model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F in general agree well with observational estimates and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain.


2010 ◽  
Vol 3 (1) ◽  
pp. 123-141 ◽  
Author(s):  
J. F. Tjiputra ◽  
K. Assmann ◽  
M. Bentsen ◽  
I. Bethke ◽  
O. H. Otterå ◽  
...  

Abstract. We developed a complex Earth system model by coupling terrestrial and oceanic carbon cycle components into the Bergen Climate Model. For this study, we have generated two model simulations (one with climate change inclusions and the other without) to study the large scale climate and carbon cycle variability as well as its feedback for the period 1850–2100. The simulations are performed based on historical and future IPCC CO2 emission scenarios. Globally, a pronounced positive climate-carbon cycle feedback is simulated by the terrestrial carbon cycle model, but smaller signals are shown by the oceanic counterpart. Over land, the regional climate-carbon cycle feedback is highlighted by increased soil respiration, which exceeds the enhanced production due to the atmospheric CO2 fertilization effect, in the equatorial and northern hemisphere mid-latitude regions. For the ocean, our analysis indicates that there are substantial temporal and spatial variations in climate impact on the air-sea CO2 fluxes. This implies feedback mechanisms act inhomogeneously in different ocean regions. In the North Atlantic subpolar gyre, the simulated future cooling of SST improves the CO2 gas solubility in seawater and, hence, reduces the strength of positive climate carbon cycle feedback in this region. In most ocean regions, the changes in the Revelle factor is dominated by changes in surface pCO2, and not by the warming of SST. Therefore, the solubility-associated positive feedback is more prominent than the buffer capacity feedback. In our climate change simulation, the retreat of Southern Ocean sea ice due to melting allows an additional ~20 Pg C uptake as compared to the simulation without climate change.


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