scholarly journals Uncertainty of Concentration–Terrestrial Carbon Feedback in Earth System Models*

2014 ◽  
Vol 27 (9) ◽  
pp. 3425-3445 ◽  
Author(s):  
Tomohiro Hajima ◽  
Kaoru Tachiiri ◽  
Akihiko Ito ◽  
Michio Kawamiya

Abstract Carbon uptake by land and ocean as a biogeochemical response to increasing atmospheric CO2 concentration is called concentration–carbon feedback and is one of the carbon cycle feedbacks of the global climate. This feedback can have a major impact on climate projections with an uncertain magnitude. This paper focuses on the concentration–carbon feedback in terrestrial ecosystems, analyzing the mechanisms and strength of the feedback reproduced by Earth system models (ESMs) participating in phase 5 of the Coupled Model Intercomparison Project. It is confirmed that multiple ESMs driven by a common scenario show a large spread of concentration–carbon feedback strength among models. Examining the behavior of the carbon fluxes and pools of the models showed that the sensitivity of plant productivity to elevated CO2 is likely the key to reduce the spread, although increasing CO2 stimulates other carbon cycle processes. Simulations with a single ESM driven by different CO2 pathways demonstrated that carbon accumulation increases in scenarios with slower CO2 increase rates. Using both numerical and analytical approaches, the study showed that the difference among CO2 scenarios is a time lag of terrestrial carbon pools in response to atmospheric CO2 increase—a high rate of CO2 increase results in smaller carbon accumulations than that in an equilibrium state of a given CO2 concentration. These results demonstrate that the current quantities for concentration–carbon feedback are incapable of capturing the feedback dependency on the carbon storage state and suggest that the concentration feedback can be larger for future scenarios where the CO2 growth rate is reduced.

2014 ◽  
Vol 27 (2) ◽  
pp. 511-526 ◽  
Author(s):  
Pierre Friedlingstein ◽  
Malte Meinshausen ◽  
Vivek K. Arora ◽  
Chris D. Jones ◽  
Alessandro Anav ◽  
...  

Abstract In the context of phase 5 of the Coupled Model Intercomparison Project, most climate simulations use prescribed atmospheric CO2 concentration and therefore do not interactively include the effect of carbon cycle feedbacks. However, the representative concentration pathway 8.5 (RCP8.5) scenario has additionally been run by earth system models with prescribed CO2 emissions. This paper analyzes the climate projections of 11 earth system models (ESMs) that performed both emission-driven and concentration-driven RCP8.5 simulations. When forced by RCP8.5 CO2 emissions, models simulate a large spread in atmospheric CO2; the simulated 2100 concentrations range between 795 and 1145 ppm. Seven out of the 11 ESMs simulate a larger CO2 (on average by 44 ppm, 985 ± 97 ppm by 2100) and hence higher radiative forcing (by 0.25 W m−2) when driven by CO2 emissions than for the concentration-driven scenarios (941 ppm). However, most of these models already overestimate the present-day CO2, with the present-day biases reasonably well correlated with future atmospheric concentrations’ departure from the prescribed concentration. The uncertainty in CO2 projections is mainly attributable to uncertainties in the response of the land carbon cycle. As a result of simulated higher CO2 concentrations than in the concentration-driven simulations, temperature projections are generally higher when ESMs are driven with CO2 emissions. Global surface temperature change by 2100 (relative to present day) increased by 3.9° ± 0.9°C for the emission-driven simulations compared to 3.7° ± 0.7°C in the concentration-driven simulations. Although the lower ends are comparable in both sets of simulations, the highest climate projections are significantly warmer in the emission-driven simulations because of stronger carbon cycle feedbacks.


2016 ◽  
Author(s):  
Dongmin Kim ◽  
Myong-In Lee ◽  
Su-Jong Jeong ◽  
Jungho Im ◽  
Dong Hyun Cha ◽  
...  

Abstract. This study compares historical simulations of the terrestrial carbon cycle produced by 10 Earth System Models (ESMs) that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Using MODIS satellite estimates, this study validates the simulation of gross primary production (GPP), net primary production (NPP), and carbon use efficiency (CUE), which depend on plant function types (PFTs). The models show noticeable deficiencies compared to the MODIS data in the simulation of the spatial patterns of GPP and NPP and large differences among the simulations, although the multi-model ensemble (MME) mean provides a realistic global mean value and spatial distributions. The larger model spreads in GPP and NPP compared to those of surface temperature and precipitation suggest that the differences among simulations in terms of the terrestrial carbon cycle are largely due to uncertainties in the parameterization of terrestrial carbon fluxes by vegetation. The models also exhibit large spatial differences in their simulated CUE values and at locations where the dominant PFT changes, primarily due to differences in the parameterizations. While the MME-simulated CUE values show a strong dependence on surface temperatures, the observed CUE values from MODIS show greater complexity, as well as non-linear sensitivity. This leads to the overall underestimation of CUE using most of the PFTs incorporated into current ESMs. The results of this comparison suggest that more careful and extensive validation is needed to improve the terrestrial carbon cycle in terms of ecosystem-level processes.


2013 ◽  
Vol 26 (18) ◽  
pp. 6801-6843 ◽  
Author(s):  
A. Anav ◽  
P. Friedlingstein ◽  
M. Kidston ◽  
L. Bopp ◽  
P. Ciais ◽  
...  

Abstract The authors assess the ability of 18 Earth system models to simulate the land and ocean carbon cycle for the present climate. These models will be used in the next Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) for climate projections, and such evaluation allows identification of the strengths and weaknesses of individual coupled carbon–climate models as well as identification of systematic biases of the models. Results show that models correctly reproduce the main climatic variables controlling the spatial and temporal characteristics of the carbon cycle. The seasonal evolution of the variables under examination is well captured. However, weaknesses appear when reproducing specific fields: in particular, considering the land carbon cycle, a general overestimation of photosynthesis and leaf area index is found for most of the models, while the ocean evaluation shows that quite a few models underestimate the primary production.The authors also propose climate and carbon cycle performance metrics in order to assess whether there is a set of consistently better models for reproducing the carbon cycle. Averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles and PDFs from different observed datasets. Although the metrics used in this study allow identification of some models as better or worse than the average, the ranking of this study is partially subjective because of the choice of the variables under examination and also can be sensitive to the choice of reference data. In addition, it was found that the model performances show significant regional variations.


2018 ◽  
Vol 9 (2) ◽  
pp. 507-523 ◽  
Author(s):  
Steven J. Lade ◽  
Jonathan F. Donges ◽  
Ingo Fetzer ◽  
John M. Anderies ◽  
Christian Beer ◽  
...  

Abstract. Changes to climate–carbon cycle feedbacks may significantly affect the Earth system's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth system models. Here, we construct a stylised global climate–carbon cycle model, test its output against comprehensive Earth system models, and investigate the strengths of its climate–carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon cycle feedbacks and the operation of the carbon cycle. Specific results include that different feedback formalisms measure fundamentally the same climate–carbon cycle processes; temperature dependence of the solubility pump, biological pump, and CO2 solubility all contribute approximately equally to the ocean climate–carbon feedback; and concentration–carbon feedbacks may be more sensitive to future climate change than climate–carbon feedbacks. Simple models such as that developed here also provide workbenches for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the planetary boundaries, that are currently too uncertain to be included in comprehensive Earth system models.


2009 ◽  
Vol 22 (19) ◽  
pp. 5232-5250 ◽  
Author(s):  
J. M. Gregory ◽  
C. D. Jones ◽  
P. Cadule ◽  
P. Friedlingstein

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.


2021 ◽  
Author(s):  
Alexander J. Winkler ◽  
Ranga B. Myneni ◽  
Markus Reichstein ◽  
Victor Brovkin

<div> <div> <div> <p>The prevailing understanding of the carbon-cycle response to anthropogenic CO<sub>2 </sub>emissions suggests that it depends only on the magnitude of this forcing, not on its timing. However, a recent study (Winkler <em>et al</em>., <em>Earth System Dynamics</em>, 2019) demonstrated that the same magnitude of CO<sub>2 </sub>forcing causes considerably different responses in various Earth system models when realized following different temporal trajectories. Because the modeling community focuses on concentration-driven runs that do not represent a fully-coupled carbon-cycle-climate continuum, and the experimental setups are mainly limited to exponential forcing timelines, the effect of different temporal trajectories of CO<sub>2 </sub>emissions in the system is under-explored. Together, this could lead to an incomplete notion of the carbon-cycle response to anthropogenic CO<sub>2 </sub>emissions.</p> <p>We use the latest CMIP6 version of the Max-Planck-Institute Earth System Model (MPI-ESM1.2) with a fully-coupled carbon cycle to investigate the effect of emission timing in form of four drastically different pathways. All pathways emit an identical total of 1200 Pg C over 200 years, which is about the IPCC estimate to stay below 2 °K of warming, and the approximate amount needed to double the atmospheric CO<sub>2 </sub>concentration. The four pathways differ only in their CO<sub>2 </sub>emission rates, which include a constant, a negative parabolic (ramp-up/ramp-down), a linearly decreasing, and an exponentially increasing emission trajectory. These experiments are idealized, but designed not to exceed the observed maximum emission rates, and thus can be placed in the context of the observed system.</p> <p>We find that the resulting atmospheric CO<sub>2 </sub>concentration, after all the carbon has been emitted, can vary as much as 100 ppm between the different pathways. The simulations show that for pathways, where the system is exposed to higher rates of CO<sub>2 </sub>emissions early in the forcing timeline, there is considerably less excess CO<sub>2 </sub>in the atmosphere at the end. These pathways also show an airborne fraction approaching zero in the final decades of the simulation. At this point, the carbon sinks have reached a strength that removes more carbon from the atmosphere than is emitted. In contrast, the exponentially increasing pathway with high CO<sub>2 </sub>emission rates in the last decades of the simulation, the pathway usually studied, shows a fairly stable airborne fraction. We propose a new general framework to estimate the atmospheric growth rate of CO<sub>2 </sub>not only as a function of the emission rate, but also include the aspect of time the system has been exposed to excess CO<sub>2 </sub>in the atmosphere. As a result, the transient temperature response is a function not only of the cumulative CO<sub>2 </sub>emissions, but also of the time the system was exposed to the excess CO<sub>2</sub>. We also apply this framework to other Earth system models and observational records of CO<sub>2 </sub>concentration and emissions.</p> </div> </div> </div><div> <div> <div> <p>The Earth system is currently in a phase of increasing, nearly exponential CO<sub>2 </sub>forcing. The impact of excess CO<sub>2 </sub>exposure time could become apparent as we approach the point of maximum CO<sub>2 </sub>emission rate, affecting the achievability of the climate targets.</p> </div> </div> </div>


2012 ◽  
Vol 3 (1) ◽  
pp. 63-78 ◽  
Author(s):  
H. Schmidt ◽  
K. Alterskjær ◽  
D. Bou Karam ◽  
O. Boucher ◽  
A. Jones ◽  
...  

Abstract. In this study we compare the response of four state-of-the-art Earth system models to climate engineering under scenario G1 of two model intercomparison projects: GeoMIP (Geoengineering Model Intercomparison Project) and IMPLICC (EU project "Implications and risks of engineering solar radiation to limit climate change"). In G1, the radiative forcing from an instantaneous quadrupling of the CO2 concentration, starting from the preindustrial level, is balanced by a reduction of the solar constant. Model responses to the two counteracting forcings in G1 are compared to the preindustrial climate in terms of global means and regional patterns and their robustness. While the global mean surface air temperature in G1 remains almost unchanged compared to the control simulation, the meridional temperature gradient is reduced in all models. Another robust response is the global reduction of precipitation with strong effects in particular over North and South America and northern Eurasia. In comparison to the climate response to a quadrupling of CO2 alone, the temperature responses are small in experiment G1. Precipitation responses are, however, in many regions of comparable magnitude but globally of opposite sign.


2015 ◽  
Vol 12 (9) ◽  
pp. 2655-2694 ◽  
Author(s):  
E. S. Weng ◽  
S. Malyshev ◽  
J. W. Lichstein ◽  
C. E. Farrior ◽  
R. Dybzinski ◽  
...  

Abstract. The long-term and large-scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water, and nutrients. Woody biomass, a pool of carbon (C) larger than 50% of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth system models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition for light, competition for water, and explicit scaling from individuals to ecosystems into the land model version 3 (LM3) currently used in the Earth system models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the perfect plasticity approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water, and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3-PPA model is able to include a large number of phenomena across a range of spatial and temporal scales and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy – the strategy that can competitively exclude all others – shifts as a function of the atmospheric CO2 concentration. This strategy is referred to as an evolutionarily stable strategy (ESS) in the ecological literature and is typically not the same as a productivity- or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values.


2016 ◽  
Vol 121 (3) ◽  
pp. 903-918 ◽  
Author(s):  
Yongwen Liu ◽  
Tao Wang ◽  
Mengtian Huang ◽  
Yitong Yao ◽  
Philippe Ciais ◽  
...  

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