scholarly journals Quantifying the global carbon cycle response to volcanic stratospheric aerosol radiative forcing using Earth System Models

2014 ◽  
Vol 119 (1) ◽  
pp. 101-111 ◽  
Author(s):  
A. M. Foley ◽  
M. Willeit ◽  
V. Brovkin ◽  
G. Feulner ◽  
A. D. Friend
Keyword(s):  
Carbon Cycle ◽  
Radiative Forcing ◽  
Global Carbon Cycle ◽  
Stratospheric Aerosol ◽  
Earth System ◽  
Aerosol Radiative Forcing ◽  
System Models ◽  
Earth System Models ◽  
Global Carbon ◽  
Aerosol Radiative

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 Uncertainties in CMIP5 Climate Projections due to Carbon Cycle Feedbacks

2014 ◽  
Vol 27 (2) ◽  
pp. 511-526 ◽  
Author(s):  
Pierre Friedlingstein ◽  
Malte Meinshausen ◽  
Vivek K. Arora ◽  
Chris D. Jones ◽  
Alessandro Anav ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Co2 Emissions ◽  
Radiative Forcing ◽  
Coupled Model ◽  
Atmospheric Co2 ◽  
Climate Projections ◽  
Earth System ◽  
Surface Temperature Change ◽  
System Models ◽  
Earth System Models

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.

Time-scale dependence of climate-carbon cycle feedbacks for weak perturbations in CMIP5 models

2021 ◽  
Author(s):  
Guilherme Torres Mendonça ◽  
Julia Pongratz ◽  
Christian Reick
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Time Scales ◽  
Radiative Forcing ◽  
Global Carbon Cycle ◽  
Atmospheric Co2 ◽  
Ice Age ◽  
Cmip5 Models ◽  
Global Carbon ◽  
Different Time Scales

<p>The increase in atmospheric CO2 driven by anthropogenic emissions is the main radiative forcing causing climate change. But this increase is not only a result from emissions, but also from changes in the global carbon cycle. These changes arise from feedbacks between climate and the carbon cycle that drive CO2 into or out of the atmosphere in addition to the emissions, thereby either accelerating or buffering climate change. Therefore, understanding the contribution of these feedbacks to the global response of the carbon cycle is crucial in advancing climate research. Currently, this contribution is quantified by the α-β-γ framework (Friedlingstein et al., 2003). But this quantification is only valid for a particular perturbation scenario and time period. In contrast, a recently proposed generalization (Rubino et al., 2016) of this framework for weak perturbations quantifies this contribution for all scenarios and at different time scales. </p><p>Thereby, this generalization provides a systematic framework to investigate the response of the global carbon cycle in terms of the climate-carbon cycle feedbacks. In the present work we employ this framework to study these feedbacks and the airborne fraction in different CMIP5 models. We demonstrate (1) that this generalization of the α-β-γ framework consistently describes the linear dynamics of the carbon cycle in the MPI-ESM; and (2) how by this framework the climate-carbon cycle feedbacks and airborne fraction are quantified at different time scales in CMIP5 models. Our analysis shows that, independently of the perturbation scenario, (1) the net climate-carbon cycle feedback is negative at all time scales; (2) the airborne fraction generally decreases for increasing time scales; and (3) the land biogeochemical feedback dominates the model spread in the airborne fraction at all time scales. This last result therefore emphasizes the need to improve our understanding of this particular feedback.</p><p><strong>References:</strong></p><p>P. Friedlingstein, J.-L. Dufresne, P. Cox, and P. Rayner. How positive is the feedback between climate change and the carbon cycle? Tellus B, 55(2):692–700, 2003.</p><p>M. Rubino, D. Etheridge, C. Trudinger, C. Allison, P. Rayner, I. Enting, R. Mulvaney, L. Steele, R. Langenfelds, W. Sturges, et al. Low atmospheric CO2 levels during the Little Ice Age due to cooling-induced terrestrial uptake. Nature Geoscience, 9(9):691–694, 2016.</p>

scholarly journals Analytically tractable climate–carbon cycle feedbacks under 21st century anthropogenic forcing

2018 ◽  
Vol 9 (2) ◽  
pp. 507-523 ◽  
Author(s):  
Steven J. Lade ◽  
Jonathan F. Donges ◽  
Ingo Fetzer ◽  
John M. Anderies ◽  
Christian Beer ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Global Climate ◽  
Future Climate Change ◽  
Earth System ◽  
Co2 Solubility ◽  
Carbon Cycle Model ◽  
Ocean Climate ◽  
System Models ◽  
Analytical Expressions ◽  
Earth System Models

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.

scholarly journals Stratospheric aerosol radiative forcing simulated by the chemistry climate model EMAC using Aerosol CCI satellite data

2018 ◽  
Vol 18 (17) ◽  
pp. 12845-12857 ◽  
Author(s):  
Christoph Brühl ◽  
Jennifer Schallock ◽  
Klaus Klingmüller ◽  
Charles Robert ◽  
Christine Bingen ◽  
...  
Keyword(s):  
Optical Depth ◽  
Radiative Forcing ◽  
Volcanic Eruptions ◽  
Stratospheric Aerosol ◽  
Radiative Heating ◽  
Aerosol Radiative Forcing ◽  
Tropospheric Aerosol ◽  
Model Aerosol ◽  
Atmospheric Sounding ◽  
Aerosol Radiative

Abstract. This paper presents decadal simulations of stratospheric and tropospheric aerosol and its radiative effects by the chemistry general circulation model EMAC constrained with satellite observations in the framework of the ESA Aerosol CCI project such as GOMOS (Global Ozone Monitoring by Occultation of Stars) and (A)ATSR ((Advanced) Along Track Scanning Radiometer) on the ENVISAT (European Environmental Satellite), IASI (Infrared Atmospheric Sounding Interferometer) on MetOp (Meteorological Operational Satellite), and, additionally, OSIRIS (Optical Spectrograph and InfraRed Imaging System). In contrast to most other studies, the extinctions and optical depths from the model are compared to the observations at the original wavelengths of the satellite instruments covering the range from the UV (ultraviolet) to terrestrial IR (infrared). This avoids conversion artifacts and provides additional constraints for model aerosol and interpretation of the observations. MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) SO2 limb measurements are used to identify plumes of more than 200 volcanic eruptions. These three-dimensional SO2 plumes are added to the model SO2 at the eruption times. The interannual variability in aerosol extinction in the lower stratosphere, and of stratospheric aerosol radiative forcing at the tropopause, is dominated by the volcanoes. To explain the seasonal cycle of the GOMOS and OSIRIS observations, desert dust simulated by a new approach and transported to the lowermost stratosphere by the Asian summer monsoon and tropical convection turns out to be essential. This also applies to the radiative heating by aerosol in the lowermost stratosphere. The existence of wet dust aerosol in the lowermost stratosphere is indicated by the patterns of the wavelength dependence of extinction in observations and simulations. Additional comparison with (A)ATSR total aerosol optical depth at different wavelengths and IASI dust optical depth demonstrates that the model is able to represent stratospheric as well as tropospheric aerosol consistently.

scholarly journals Sensitivity of Global Warming to Carbon Emissions: Effects of Heat and Carbon Uptake in a Suite of Earth System Models

2017 ◽  
Vol 30 (23) ◽  
pp. 9343-9363 ◽  
Author(s):  
Richard G. Williams ◽  
Vassil Roussenov ◽  
Philip Goodwin ◽  
Laure Resplandy ◽  
Laurent Bopp
Keyword(s):  
Climate Sensitivity ◽  
Carbon Emissions ◽  
Radiative Forcing ◽  
Carbon Uptake ◽  
Earth System ◽  
Ocean Heat Uptake ◽  
Surface Warming ◽  
System Models ◽  
Heat Uptake ◽  
Earth System Models

Climate projections reveal global-mean surface warming increasing nearly linearly with cumulative carbon emissions. The sensitivity of surface warming to carbon emissions is interpreted in terms of a product of three terms: the dependence of surface warming on radiative forcing, the fractional radiative forcing from CO2, and the dependence of radiative forcing from CO2 on carbon emissions. Mechanistically each term varies, respectively, with climate sensitivity and ocean heat uptake, radiative forcing contributions, and ocean and terrestrial carbon uptake. The sensitivity of surface warming to fossil-fuel carbon emissions is examined using an ensemble of Earth system models, forced either by an annual increase in atmospheric CO2 or by RCPs until year 2100. The sensitivity of surface warming to carbon emissions is controlled by a temporal decrease in the dependence of radiative forcing from CO2 on carbon emissions, which is partly offset by a temporal increase in the dependence of surface warming on radiative forcing. The decrease in the dependence of radiative forcing from CO2 is due to a decline in the ratio of the global ocean carbon undersaturation to carbon emissions, while the increase in the dependence of surface warming is due to a decline in the ratio of ocean heat uptake to radiative forcing. At the present time, there are large intermodel differences in the sensitivity in surface warming to carbon emissions, which are mainly due to uncertainties in the climate sensitivity and ocean heat uptake. These uncertainties undermine the ability to predict how much carbon may be emitted before reaching a warming target.

The Transient Response of the Carbon-Cycle-Climate Continuum to CO2 Emissions is Pathway Dependent 

2021 ◽  
Author(s):  
Alexander J. Winkler ◽  
Ranga B. Myneni ◽  
Markus Reichstein ◽  
Victor Brovkin
Keyword(s):  
Carbon Cycle ◽  
Emission Rate ◽  
Transient Temperature ◽  
Emission Rates ◽  
Earth System ◽  
Max Planck ◽  
System Models ◽  
The Impact ◽  
Fully Coupled ◽  
Earth System Models

<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>

scholarly journals A map of global peatland distribution created using machine learning for use in terrestrial ecosystem and earth system models

2017 ◽  
Author(s):  
Yuanqiao Wu ◽  
Ed Chan ◽  
Joe R. Melton ◽  
Diana L. Verseghy
Keyword(s):  
Machine Learning ◽  
Statistical Model ◽  
Machine Learning Method ◽  
Learning Method ◽  
Earth System ◽  
Geophysical Field ◽  
Fractional Coverage ◽  
System Models ◽  
Earth System Models ◽  
Global Carbon

Abstract. Peatlands store large amounts of soil carbon and constitute an important component of the global carbon cycle. Accurate information on the global extent and distribution of peatlands is presently lacking but it important for earth system models (ESMs) to be able to simulate the effects of climate change on the global carbon balance. The most comprehensive peatland map produced to date is a qualitative presence/absence product. Here, we present a spatially continuous global map of peatland fractional coverage using the extremely randomized tree machine learning method suitable for use as a prescribed geophysical field in an ESM. Inputs to our statistical model include spatially distributed climate data, soil data and topographical slopes. Available maps of peatland fractional coverage for Canada and West Siberia were used along with a proxy for non-peatland areas to train and test the statistical model. Regions where the peatland fraction is expected to be zero were estimated from a map of topsoil organic carbon content below a threshold value of 13 kg/m2. The modelled coverage of peatlands yields a root mean square error of 4 % and a coefficient of determination of 0.91 for the 10,978 tested 0.5 degree grid cells. We then generated a complete global peatland fractional coverage map. In comparison with earlier qualitative estimates, our global modelled peatland map is able to reproduce peatland distributions in places remote from the training areas and capture peatland hot spots in both boreal and tropical regions, as well as in the southern hemisphere. Additionally we demonstrate that our machine-learning method has greater skill than solely setting peatland areas based on histosols from a soil database.

scholarly journals Solar irradiance reduction to counteract radiative forcing from a quadrupling of CO<sub>2</sub>: climate responses simulated by four earth system models

2012 ◽  
Vol 3 (1) ◽  
pp. 63-78 ◽  
Author(s):  
H. Schmidt ◽  
K. Alterskjær ◽  
D. Bou Karam ◽  
O. Boucher ◽  
A. Jones ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Surface Air Temperature ◽  
Co2 Concentration ◽  
Northern Eurasia ◽  
Earth System ◽  
Model Intercomparison ◽  
Regional Patterns ◽  
System Models ◽  
Eu Project ◽  
Earth System Models

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.

scholarly journals A new energy-balance approach to linear filtering for estimating effective radiative forcing from temperature time series

2020 ◽  
Vol 6 (2) ◽  
pp. 91-102
Author(s):  
Donald P. Cummins ◽  
David B. Stephenson ◽  
Peter A. Stott
Keyword(s):  
Time Series ◽  
Energy Balance ◽  
Surface Temperature ◽  
Radiative Forcing ◽  
Earth System ◽  
Linear Filtering ◽  
Past Climate ◽  
System Models ◽  
Effective Radiative Forcing ◽  
Earth System Models

Abstract. Reliable estimates of historical effective radiative forcing (ERF) are important for understanding the causes of past climate change and for constraining predictions of future warming. This study proposes a new linear-filtering method for estimating historical radiative forcing from time series of global mean surface temperature (GMST), using energy-balance models (EBMs) fitted to GMST from CO2-quadrupling general circulation model (GCM) experiments. We show that the response of any k-box EBM can be represented as an ARMA(k, k−1) (autoregressive moving-average) filter. We show how, by inverting an EBM's ARMA filter representation, time series of surface temperature may be converted into radiative forcing. The method is illustrated using three-box EBM fits to two recent Earth system models from CMIP5 and CMIP6 (Coupled Model Intercomparison Project). A comparison with published results obtained using the established ERF_trans method, a purely GCM-based approach, shows that our new method gives an ERF time series that closely matches the GCM-based series (correlation of 0.83). Time series of estimated historical ERF are obtained by applying the method to a dataset of historical temperature observations. The results show that there is clear evidence of a significant increase over the historical period with an estimated forcing in 2018 of 1.45±0.504 W m−2 when derived using the two Earth system models. This method could be used in the future to attribute past climate changes to anthropogenic and natural factors and to help constrain estimates of climate sensitivity.

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