Compatible Fossil Fuel CO2 emissions in the CMIP6 Earth System Models’ Historical and Shared Socioeconomic Pathway experiments of the 21st Century

2020 ◽  
pp. 1-72
Author(s):  
Spencer K. Liddicoat ◽  
Andy J. Wiltshire ◽  
Chris D. Jones ◽  
Vivek K. Arora ◽  
Victor Brovkin ◽  
...  

AbstractWe present the compatible CO2 emissions from fossil fuel burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth System Models (ESMs) participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The multi-model mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (392±63 GtC vs 400±20 GtC respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs’ diagnosed FF emission rates are consistent with those generated by the Integrated Assessment Models (IAMs) from which the SSPs’ CO2 concentration pathways were constructed; the simpler IAMs’ emissions lie within the ESMs’ spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs’ FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4 and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models’ ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land use and land cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two.

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>


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.


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.


2021 ◽  
Author(s):  
Kine Onsum Moseid

<p>The Earth’s surface energy balance is heavily affected by incoming solar radiation and how it propagates through our atmosphere. How the sunlight propagates towards the surface depends on the atmospheric presence of aerosols, gases, and clouds. </p><p>Surface temperature evolution according to earth system models (ESMs) in the historical experiment from the coupled model intercomparison project phase 6 (CMIP6) suggests that models may be overly sensitive to aerosol forcing. Other studies have found that ESMs do not recreate observed decadal patterns in surface shortwave radiation - suggesting the models inaccurately underestimate the shortwave impact of atmospheric aerosols. These contradictory results act as a basis for our study.<br>Our study decomposes what determines both all sky and clear sky downwelling shortwave radiation at the surface in ESMs, using different experiments of CMIP6. We try to determine the respective role of aerosols, clouds and gases in the shortwave energy balance at the surface, and assess the effect of seasonality and regional differences.</p>


2021 ◽  
Author(s):  
Bertrand Guenet ◽  
Jérémie Orliac ◽  
Lauric Cécillon ◽  
Olivier Torres ◽  
Laurent Bopp

<p>Earth system models (ESMs) are numerical representations of the Earth system aiming at representing the climate dynamic including feedbacks between climate and carbon cycle. CO<sub>2</sub> flux due to soil respiration including heterotrophic respiration coming from the soil organic matter (SOM) microbial decomposition and autotrophic respiration coming from the roots respiration is one of the most important flux between the surface and the atmosphere. Thus, even small changes in this flux may impact drastically the climate dynamic. It is therefore essential that ESMs reliably reproduce soil respiration. Until recently, such an evaluation at global scale of the ESMs was not straightforward because of the absence of observation-derived product to evaluate heterotrophic respiration fluxes from ESMs at global scale. Recently, several gridded products were published opening a new research avenue on climate-carbon feedbacks. In this study, we used simulations from 13 ESMs performed within the sixth coupled model intercomparison project (CMIP6) and we evaluate their capacities to reproduce the heterotrophic respiration flux using three gridded observation-based products. We first evaluate the total heterotrophic respiration flux for each model as well as the spatial patterns. We observed that most of the models are able to reproduce the total heterotrophic respiration flux but the spatial analysis underlined that this was partially due to some bias compensation between regions overestimating the flux and regions underestimating the flux. To better identify the causes of the identified bias in predicting the total heterotrophic respiration flux, we analysed the residues of ESMs using linear mixed effect models and we observed that lithology and climate were the most important drivers of the ESMs residues. Our results suggest that the response of SOM microbial decomposition to soil moisture and temperature must be improved in the next ESMs generation and that the effect of lithology should be better taken into account.</p>


Author(s):  
Roland Séférian ◽  
Sarah Berthet ◽  
Andrew Yool ◽  
Julien Palmiéri ◽  
Laurent Bopp ◽  
...  

Abstract Purpose of Review The changes or updates in ocean biogeochemistry component have been mapped between CMIP5 and CMIP6 model versions, and an assessment made of how far these have led to improvements in the simulated mean state of marine biogeochemical models within the current generation of Earth system models (ESMs). Recent Findings The representation of marine biogeochemistry has progressed within the current generation of Earth system models. However, it remains difficult to identify which model updates are responsible for a given improvement. In addition, the full potential of marine biogeochemistry in terms of Earth system interactions and climate feedback remains poorly examined in the current generation of Earth system models. Summary Increasing availability of ocean biogeochemical data, as well as an improved understanding of the underlying processes, allows advances in the marine biogeochemical components of the current generation of ESMs. The present study scrutinizes the extent to which marine biogeochemistry components of ESMs have progressed between the 5th and the 6th phases of the Coupled Model Intercomparison Project (CMIP).


2020 ◽  
Vol 33 (19) ◽  
pp. 8561-8578
Author(s):  
Claire M. Zarakas ◽  
Abigail L. S. Swann ◽  
Marysa M. Laguë ◽  
Kyle C. Armour ◽  
James T. Randerson

AbstractIncreasing concentrations of CO2 in the atmosphere influence climate both through CO2’s role as a greenhouse gas and through its impact on plants. Plants respond to atmospheric CO2 concentrations in several ways that can alter surface energy and water fluxes and thus surface climate, including changes in stomatal conductance, water use, and canopy leaf area. These plant physiological responses are already embedded in most Earth system models, and a robust literature demonstrates that they can affect global-scale temperature. However, the physiological contribution to transient warming has yet to be assessed systematically in Earth system models. Here this gap is addressed using carbon cycle simulations from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP) to isolate the radiative and physiological contributions to the transient climate response (TCR), which is defined as the change in globally averaged near-surface air temperature during the 20-yr window centered on the time of CO2 doubling relative to preindustrial CO2 concentrations. In CMIP6 models, the physiological effect contributes 0.12°C (σ: 0.09°C; range: 0.02°–0.29°C) of warming to the TCR, corresponding to 6.1% of the full TCR (σ: 3.8%; range: 1.4%–13.9%). Moreover, variation in the physiological contribution to the TCR across models contributes disproportionately more to the intermodel spread of TCR estimates than it does to the mean. The largest contribution of plant physiology to CO2-forced warming—and the intermodel spread in warming—occurs over land, especially in forested regions.


2020 ◽  
Author(s):  
Bouwe Andela ◽  
Lisa Bock ◽  
Björn Brötz ◽  
Faruk Diblen ◽  
Laura Dreyer ◽  
...  

<p>The Earth System Model Evaluation Tool (ESMValTool) is a free and open-source community diagnostic and performance metrics tool for the evaluation of Earth system models participating in the Coupled Model Intercomparison Project (CMIP). Version 2 of the tool (Righi et al. 2019, www.esmvaltool.org) features a brand new design, consisting of ESMValCore (https://github.com/esmvalgroup/esmvalcore), a package for working with CMIP data and ESMValTool (https://github.com/esmvalgroup/esmvaltool), a package containing the scientific analysis scripts. This new version has been specifically developed to handle the increased data volume of CMIP Phase 6 (CMIP6) and the related challenges posed by the analysis and the evaluation of output from multiple high-resolution or complex Earth system models. The tool also supports CMIP5 and CMIP3 datasets, as well as a large number of re-analysis and observational datasets that can be formatted according to the same standards (CMOR) on-the-fly or through scripts currently included in the ESMValTool package.</p><p>At the heart of this new version is the ESMValCore software package, which provides a configurable framework for finding CMIP files using a “data reference syntax”, applying commonly used pre-processing functions to them, running analysis scripts, and recording provenance. Numerous pre-processing functions, e.g. for data selection, regridding, and statistics are readily available and the modular design makes it easy to add more. The ESMValCore package is easy to install with relatively few dependencies, written in Python 3, based on state-of-the-art open-source libraries such as Iris and Dask, and widely used standards such as YAML, NetCDF, CF-Conventions, and W3C PROV. An extensive set of automated tests and code quality checks ensure the reliability of the package. Documentation is available at https://esmvaltool.readthedocs.io.</p><p>The ESMValCore package uses human-readable recipes to define which variables and datasets to use, how to pre-process that data, and what scientific analysis scripts to run. The package provides convenient interfaces, based on the YAML and NetCDF/CF-convention file formats, for running diagnostic scripts written in any programming language. Because the ESMValCore framework takes care of running the workflow defined in the recipe in parallel, most analyses run much faster, with no additional programming effort required from the authors of the analysis scripts. For example, benchmarks show a factor of 30 speedup with respect to version 1 of the tool for a representative recipe on a 24 core machine. A large collection of standard recipes and associated analysis scripts is available in the ESMValTool package for reproducing selected peer-reviewed analyses. The ESMValCore package can also be used with any other script that implements it’s easy to use interface. All pre-processing functions of the ESMValCore can also be used directly from any Python program. These features allow for use by a wide community of scientific users and developers with different levels of programming skills and experience.</p><p>Future plans involve extending the public Python API (application programming interface) from just preprocessor functions to include all functionality, including finding the data and running diagnostic scripts. This would make ESMValCore suitable for interactive data exploration from a Jupyter Notebook.</p>


2020 ◽  
Author(s):  
Gitta Lasslop ◽  
Stijn Hantson ◽  
Victor Brovkin ◽  
Fang Li ◽  
David Lawrence ◽  
...  

<p>Fires are an important component in Earth system models (ESMs), they impact vegetation carbon storage, vegetation distribution, atmospheric composition and cloud formation. The representation of fires in ESMs contributing to CMIP phase 5 was still very simplified. Several Earth system models updated their representation of fires in the meantime. Using the latest simulations of CMIP6 we investigate how fire regimes change in the future for different scenarios and how land use, climate and atmospheric CO<sub>2</sub> concentration contribute to the fire regimes changes. We quantify changes in fire danger, burned area and carbon emissions on an annual and seasonal basis. Factorial model simulations allow to quantify the influence of land use, climate and atmospheric CO<sub>2</sub> on fire regimes.</p><p>We complement the information on fire regime change supplied by ESMs that include a fire module with a statistical modelling approach for burned area. This will use information from simulated changes in climate, vegetation and socioeconomic changes (population density and land use) provided for a set of different future scenarios. This allows the integration of information provided by global satellite products on burned area with the process-based simulations of climate and vegetation changes and information from socioeconomic scenarios.</p><p> </p>


2021 ◽  
Author(s):  
Bettina K. Gier ◽  
Michael Buchwitz ◽  
Maximilian Reuter ◽  
Peter M. Cox ◽  
Pierre Friedlingstein ◽  
...  

<p>Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) showed large uncertainties in simulating atmospheric CO<sub>2</sub> concentrations. We utilize the Earth System Model Evaluation Tool (ESMValTool) to evaluate emission-driven CMIP5 and CMIP6 simulations with satellite data of column-average CO<sub>2</sub> mole fractions (XCO<sub>2</sub>). XCO<sub>2</sub> time series show a large spread among the model ensembles both in CMIP5 and CMIP6. Using the satellite observations as reference, the CMIP6 models have a <span>l</span>ower bias in the the multi-model mean than CMIP5, but the spread remains large. The satellite data are a combined data product covering the period 2003–2014 based on the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat (2003–2012) and Thermal And Near infrared Sensor for carbon Observation Fourier transform spectrometer/Greenhouse Gases Observing Satellite (TANSO-FTS/GOSAT) (2009–2014) instruments. While the combined satellite product shows a strong negative trend of decreasing <span>seasonal cycle amplitude (SCA)</span> with increasing XCO<sub>2</sub> in the northern midlatitudes, both CMIP ensembles instead show a non-significant positive trend in the multi-model mean. The negative trend is reproduced by the models when sampling them as the observations, attributing it to sampling characteristics. Applying a mask of the mean data coverage of each satellite to the models, the SCA is higher for the SCIAMACHY/Envisat mask than when using the TANSO-FTS/GOSAT mask. This induces an artificial negative trend when using observational sampling over the full period, as SCIAMACHY/Envisat covers the early period until 2012, with TANSO-FTS/GOSAT measurements starting in 2009. Overall, the CMIP6 ensemble shows better agreement with the satellite data than the CMIP5 ensemble in all considered quantities (mean XCO<sub>2</sub>, growth rate, SCA and trend in SCA). This study shows that the availability of column-integral CO<sub>2</sub> from satellite provides a promising new way to evaluate the performance of Earth system models on a global scale, complementing existing studies that are based on in situ measurements from single ground-based stations.</p>


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