Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models

Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1 % yr−1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean± standard deviation= 0.97± 0.40 PgC ppm−1) and ocean (0.79± 0.07 PgC ppm−1), while the carbon–climate feedback over land (−45.1± 50.6 PgC ◦C−1) is about 3 times larger than over ocean (−17.2± 5.0 PgC ◦C−1). The strength of both feedbacks is an order of magnitude more Published by Copernicus Publications on behalf of the European Geosciences Union. 4174 V. K. Arora et al.: Carbon–concentration and carbon–climate feedbacks uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77± 0.37 C EgC−1 and is similar to that found in CMIP5 models (1.63± 0.48 C EgC−1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models. Copyright statement. The works published in this journal are distributed under the Creative Commons Attribution 3.0 License. This license does not affect the Crown copyright work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 3.0 License and the OGL are interoperable and do not conflict with, reduce or limit each other. © Crown copyright 2020

[1]  Joachim Segschneider,et al.  The HAMburg Ocean Carbon Cycle Model HAMOCC5.1 - Technical Description Release 1.1 , 2005 .

[2]  T. Ziehn,et al.  The Australian Earth System Model: ACCESS-ESM1.5 , 2020 .

[3]  M. Maqueda,et al.  Sensitivity of a global sea ice model to the treatment of ice thermodynamics and dynamics , 1997 .

[4]  Shian‐Jiann Lin A “Vertically Lagrangian” Finite-Volume Dynamical Core for Global Models , 2004 .

[5]  Kumiko Takata,et al.  Development of the minimal advanced treatments of surface interaction and runoff , 2003 .

[6]  J. Kattge,et al.  Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems. , 2014, Annals of botany.

[7]  C. Jones,et al.  The HadGEM2 family of Met Office Unified Model climate configurations , 2011 .

[8]  E. Kowalczyk,et al.  The ACCESS coupled model: description, control climate and evaluation , 2013 .

[9]  R. Schnur,et al.  Climate-carbon cycle feedback analysis: Results from the C , 2006 .

[10]  J. A. Pyle,et al.  Geoscientific Model Development Evaluation of the new UKCA climate-composition model – Part 1 : The stratosphere , 2009 .

[11]  C. Delire,et al.  The Global Land Carbon Cycle Simulated With ISBA‐CTRIP: Improvements Over the Last Decade , 2020, Journal of Advances in Modeling Earth Systems.

[12]  P. Friedlingstein,et al.  Emission budgets and pathways consistent with limiting warming to 1.5 °C , 2017 .

[13]  F. Hourdin,et al.  Resolved versus parametrized boundary-layer plumes , 2009 .

[14]  V. Brovkin,et al.  Representation of natural and anthropogenic land cover change in MPI‐ESM , 2013 .

[15]  J. Berry,et al.  A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species , 1980, Planta.

[16]  F. Chéruy,et al.  LMDZ6A: The Atmospheric Component of the IPSL Climate Model With Improved and Better Tuned Physics , 2020, Journal of Advances in Modeling Earth Systems.

[17]  Bo Qiu,et al.  Development of Land Surface Model BCC_AVIM2.0 and Its Preliminary Performance in LS3MIP/CMIP6 , 2019, Journal of Meteorological Research.

[18]  V. Arora,et al.  An assessment of natural methane fluxes simulated by the CLASS-CTEM model , 2017, Biogeosciences.

[19]  C. Heinze,et al.  Nonlinearity of Ocean Carbon Cycle Feedbacks in CMIP5 Earth System Models , 2014 .

[20]  K.,et al.  Carbon–Concentration and Carbon–Climate Feedbacks in CMIP5 Earth System Models , 2012 .

[21]  K. Denman,et al.  Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases , 2011 .

[22]  Thierry Penduff,et al.  Impact of partial steps and momentum advection schemes in a global ocean circulation model at eddy-permitting resolution , 2006 .

[23]  F. Chéruy,et al.  A Density Current Parameterization Coupled with Emanuel’s Convection Scheme. Part II: 1D Simulations , 2010 .

[24]  S. Valcke,et al.  The OASIS3 coupler: a European climate modelling community software , 2012 .

[25]  F. Hourdin,et al.  Resolved Versus Parametrized Boundary-Layer Plumes. Part II: Continuous Formulations of Mixing Rates for Mass-Flux Schemes , 2010 .

[26]  Myles R. Allen,et al.  Constraining the Ratio of Global Warming to Cumulative CO2 Emissions Using CMIP5 Simulations , 2013 .

[27]  D. N. Walters,et al.  The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations , 2017 .

[28]  Mohamed Zerroukat,et al.  The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations , 2011, Geoscientific Model Development.

[29]  Shian-Jiann Lin,et al.  Structure and Performance of GFDL's CM4.0 Climate Model , 2019, Journal of Advances in Modeling Earth Systems.

[30]  Ramaswamy,et al.  The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3 , 2011 .

[31]  J. Sarmiento,et al.  Response of the Ocean Natural Carbon Storage to Projected Twenty-First-Century Climate Change , 2014 .

[32]  Vivek K. Arora,et al.  A parameterization of leaf phenology for the terrestrial ecosystem component of climate models , 2005 .

[33]  Peter R. Oke,et al.  Evaluation of a near-global eddy-resolving ocean model , 2012 .

[34]  Nathan Collier,et al.  The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty , 2019, Journal of Advances in Modeling Earth Systems.

[35]  B. Choudhury Carbon use efficiency, and net primary productivity of terrestrial vegetation , 2000 .

[36]  Hongmei Li,et al.  Global ocean biogeochemistry model HAMOCC: Model architecture and performance as component of the MPI‐Earth system model in different CMIP5 experimental realizations , 2013 .

[37]  Dai Yamazaki,et al.  Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6 , 2018, Geoscientific Model Development.

[38]  Thierry Penduff,et al.  Impact of partial steps and momentum advection schemes in a global ocean circulation model at eddy-permitting resolution , 2009 .

[39]  Rachel M. Law,et al.  A global model of carbon, nitrogen and phosphorus cycles for the terrestrial biosphere , 2009 .

[40]  Julia C. Hargreaves,et al.  Long-term climate commitments projected with climate-carbon cycle models , 2008 .

[41]  P. Cox,et al.  JULES-CN: a coupled terrestrial Carbon-Nitrogen Scheme (JULES vn5.1) , 2020 .

[42]  T. Ilyina,et al.  Incorporating a prognostic representation of marine nitrogen fixers into the global ocean biogeochemical model HAMOCC , 2017 .

[43]  Deliang Chen,et al.  The Beijing Climate Center atmospheric general circulation model: description and its performance for the present-day climate , 2008 .

[44]  S. Malyshev,et al.  A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1 , 2017 .

[45]  F. Hourdin,et al.  A Thermal Plume Model for the Convective Boundary Layer : Representation of Cumulus Clouds , 2008 .

[46]  I. C. Prentice,et al.  A dynamic global vegetation model for studies of the coupled atmosphere‐biosphere system , 2005 .

[47]  A. Weaver,et al.  Nonlinearity of Carbon Cycle Feedbacks , 2010 .

[48]  X. Yin Responses of leaf nitrogen concentration and specific leaf area to atmospheric CO2 enrichment: a retrospective synthesis across 62 species , 2002 .

[49]  Tetsuji Yamada,et al.  Simulations of Nocturnal Drainage Flows by a q2l Turbulence Closure Model , 1983 .

[50]  A. MacDougall The Transient Response to Cumulative CO2 Emissions: a Review , 2016, Current Climate Change Reports.

[51]  Richard G. Williams,et al.  Reconciling Atmospheric and Oceanic Views of the Transient Climate Response to Emissions , 2018, Geophysical Research Letters.

[52]  J. R. Wilson,et al.  The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs , 2018 .

[53]  Michael J. Follows,et al.  Preformed phosphate, soft tissue pump and atmospheric CO 2 , 2005 .

[54]  D. Lawrence,et al.  Parametric Controls on Vegetation Responses to Biogeochemical Forcing in the CLM5 , 2019, Journal of Advances in Modeling Earth Systems.

[55]  Andrea Stenke,et al.  Review of the global models used within phase 1 of the Chemistry–Climate Model Initiative (CCMI) , 2017 .

[56]  Thomas R. Anderson,et al.  MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies , 2013 .

[57]  Vivek K. Arora,et al.  Uncertainties in the 20th century carbon budget associated with land use change , 2010 .

[58]  David M. Karl,et al.  VERTEX: carbon cycling in the northeast Pacific , 1987 .

[59]  Peter M. Cox,et al.  Description of the "TRIFFID" Dynamic Global Vegetation Model , 2001 .

[60]  Jessica Y. Luo,et al.  Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6 , 2020, Current Climate Change Reports.

[61]  Ronald,et al.  GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models. Part I: Physical Formulation and Baseline Simulation Characteristics , 2012 .

[62]  G. J. Collatz,et al.  Comparison of Radiative and Physiological Effects of Doubled Atmospheric CO2 on Climate , 1996, Science.

[63]  Y. Wanga,et al.  A two-leaf model for canopy conductance , photosynthesis and partitioning of available energy I : Model description and comparison with a multi-layered model , 1998 .

[64]  Thomas M. Smith,et al.  Plant functional types : their relevance to ecosystem properties and global change , 1998 .

[65]  E. Hawkins,et al.  The Potential to Narrow Uncertainty in Regional Climate Predictions , 2009 .

[66]  R. Waldman,et al.  Evaluation of CNRM Earth System Model, CNRM‐ESM2‐1: Role of Earth System Processes in Present‐Day and Future Climate , 2019, Journal of Advances in Modeling Earth Systems.

[67]  J. Dunne,et al.  Drivers of trophic amplification of ocean productivity trends in a changing climate , 2014 .

[68]  John P. Dunne,et al.  Global-scale carbon and energy flows through the marine planktonic food web: An analysis with a coupled physical–biological model , 2014 .

[69]  Ken Caldeira,et al.  Importance of carbon dioxide physiological forcing to future climate change , 2010, Proceedings of the National Academy of Sciences.

[70]  W. Cramer,et al.  A global biome model based on plant physiology and dominance, soil properties and climate , 1992 .

[71]  S. Malyshev,et al.  The underpinnings of land‐use history: three centuries of global gridded land‐use transitions, wood‐harvest activity, and resulting secondary lands , 2006 .

[72]  Rik Wanninkhof,et al.  Relationship between wind speed and gas exchange over the ocean revisited , 2014 .

[73]  C. Stock,et al.  Temperature and oxygen dependence of the remineralization of organic matter , 2017 .

[74]  Motoko Inatomi,et al.  Water-Use Efficiency of the Terrestrial Biosphere: A Model Analysis Focusing on Interactions between the Global Carbon and Water Cycles , 2012 .

[75]  S. Malyshev,et al.  Diverse Mycorrhizal Associations Enhance Terrestrial C Storage in a Global Model , 2019, Global Biogeochemical Cycles.

[76]  H. Douville,et al.  Development and evaluation of CNRM Earth system model – CNRM-ESM1 , 2015 .

[77]  Edward W. Blockley,et al.  The sea ice model component of HadGEM3-GC3.1 , 2017 .

[78]  S. Malyshev,et al.  Scaling from individual trees to forests in an Earth system modeling framework using a mathematically tractable model of height-structured competition , 2015 .

[79]  Gurvan Madec,et al.  Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6 , 2017 .

[80]  F. Hourdin,et al.  Parameterization of the Dry Convective Boundary Layer Based on a Mass Flux Representation of Thermals , 2002 .

[81]  W. Parton,et al.  Dynamics of C, N, P and S in grassland soils: a model , 1988 .

[82]  William J. Collins,et al.  Evaluation of the new UKCA climate-composition model – Part 2: The Troposphere , 2008 .

[83]  M. V. Vilariño,et al.  Mitigation pathways compatible with 1.5°C in the context of sustainable development , 2018 .

[84]  Christoph Heinze,et al.  Bergen Earth system model (BCM-C): model description and regional climate-carbon cycle feedbacks assessment , 2009 .

[85]  Pierre Friedlingstein,et al.  C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: Experimental protocol for CMIP6 , 2016 .

[86]  A. Ito,et al.  Development of the MIROC-ES2L Earth system model and the evaluation of biogeochemical processes and feedbacks , 2020, Geoscientific Model Development.

[87]  C. Skinner,et al.  The Role of Plant CO2 Physiological Forcing in Shaping Future Daily-Scale Precipitation , 2017 .

[88]  H. Damon Matthews,et al.  The proportionality of global warming to cumulative carbon emissions , 2009, Nature.

[89]  J. Gregory,et al.  Quantifying Carbon Cycle Feedbacks , 2009 .

[90]  P. Friedlingstein,et al.  The cumulative carbon budget and its implications , 2016 .

[91]  D. Salas Mélia,et al.  A global coupled sea ice–ocean model , 2002 .

[92]  Li Zhang,et al.  Global carbon budgets simulated by the Beijing Climate Center Climate System Model for the last century , 2013 .

[93]  Veronika Eyring,et al.  Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization , 2015 .

[94]  J. Gregory,et al.  Relationship of tropospheric stability to climate sensitivity and Earth’s observed radiation budget , 2017, Proceedings of the National Academy of Sciences.

[95]  Christoph Heinze,et al.  Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM) , 2012 .

[96]  M. Maqueda,et al.  An elastic-viscous-plastic sea ice model formulated on Arakawa B and C grids , 2009 .

[97]  Christopher J. Smith,et al.  Estimating and tracking the remaining carbon budget for stringent climate targets , 2019, Nature.

[98]  H. Hasumi,et al.  Impact of deep ocean mixing on the climatic mean state in the Southern Ocean , 2018, Scientific Reports.

[99]  Bertrand Decharme,et al.  Recent Changes in the ISBA‐CTRIP Land Surface System for Use in the CNRM‐CM6 Climate Model and in Global Off‐Line Hydrological Applications , 2019, Journal of Advances in Modeling Earth Systems.

[100]  Olivier Aumont,et al.  PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies , 2015 .

[101]  R. Leuning,et al.  A two-leaf model for canopy conductance, photosynthesis and partitioning of available energy I:: Model description and comparison with a multi-layered model , 1998 .

[102]  Diana Verseghy,et al.  The Canadian Fourth Generation Atmospheric Global Climate Model (CanAM4). Part I: Representation of Physical Processes , 2013, Data, Models and Analysis.

[103]  J. Orr,et al.  Improved routines to model the ocean carbonate system: mocsy 2.0 , 2015 .

[104]  J. Schwinger,et al.  Ocean Carbon Cycle Feedbacks Under Negative Emissions , 2018 .

[105]  Krista,et al.  GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models. Part II: Carbon System Formulation and Baseline Simulation Characteristics* , 2013 .

[106]  T. Ziehn,et al.  The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) – Part 2: Historical simulations , 2016 .

[107]  K. Denman,et al.  The global carbon cycle in the Canadian Earth system model (CanESM1): Preindustrial control simulation , 2010 .

[108]  Quantifying process-level uncertainty contributions to TCRE and carbon budgets for meeting Paris Agreement climate targets , 2020, Environmental Research Letters.

[109]  T. Stocker,et al.  An improved method for detecting anthropogenic CO2 in the oceans , 1996 .

[110]  Gurvan Madec,et al.  The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities , 2015 .

[111]  M. Toohey,et al.  What was the source of the atmospheric CO2 increase during the Holocene? , 2019, Biogeosciences.

[112]  M. Follows,et al.  Wind-driven changes in Southern Ocean residual circulation, ocean carbon reservoirs and atmospheric CO2 , 2013, Climate Dynamics.

[113]  Ian N. Harman,et al.  The land surface model component of ACCESS: description and impact on the simulated surface climatology , 2013 .

[114]  Akihiko Ito,et al.  A simulation model of the carbon cycle in land ecosystems (Sim-CYCLE) : A description based on dry-matter production theory and plot-scale validation , 2002 .

[115]  Donald R. Zak,et al.  Ecological Lessons from Free-Air CO2 Enrichment (FACE) Experiments , 2011 .

[116]  R. Q. Thomas,et al.  Beyond Static Benchmarking: Using Experimental Manipulations to Evaluate Land Model Assumptions , 2019, Global biogeochemical cycles.

[117]  C. Tucker,et al.  Interactions between vegetation and climate: radiative and physiological effects of doubled atmospheric co2 , 1999 .

[118]  T. Matsuno,et al.  Geographical distribution of the feedback between future climate change and the carbon cycle , 2008 .

[119]  L. Bopp,et al.  Sensitivity of Global Warming to Carbon Emissions: Effects of Heat and Carbon Uptake in a Suite of Earth System Models , 2017 .

[120]  T. Lenton,et al.  Quantifying the feedback between ocean heating and CO2 solubility as an equivalent carbon emission , 2009 .

[121]  C. Heinze,et al.  The Norwegian Earth System Model, NorESM2 – Evaluation of theCMIP6 DECK and historical simulations , 2020 .

[122]  G. Boer,et al.  Geographic Aspects of Temperature and Concentration Feedbacks in the Carbon Budget , 2010 .

[123]  D. Jenkinson,et al.  RothC-26.3 - A Model for the turnover of carbon in soil , 1996 .

[124]  W. G. Strand,et al.  The Community Earth System Model Version 2 (CESM2) , 2020, Journal of Advances in Modeling Earth Systems.

[125]  Hajime Okamoto,et al.  Global three‐dimensional simulation of aerosol optical thickness distribution of various origins , 2000 .

[126]  P. Cox,et al.  Emergent constraints on climate‐carbon cycle feedbacks in the CMIP5 Earth system models , 2014 .

[127]  C. Steyaert,et al.  Atmosphere , 2018, The Creativity Complex.

[128]  J. Randerson,et al.  Carbon-nitrogen interactions regulate climate-carbon cycle feedbacks: results from an atmosphere-ocean general circulation model , 2009 .

[129]  H. Hasumi,et al.  Improved Climate Simulation by MIROC5: Mean States, Variability, and Climate Sensitivity , 2010, Journal of Climate.

[130]  B. Stevens,et al.  Climate and carbon cycle changes from 1850 to 2100 in MPI‐ESM simulations for the Coupled Model Intercomparison Project phase 5 , 2013 .

[131]  V. Arora,et al.  Constraining the strength of the terrestrial CO 2 fertilization effectin the Canadian Earth system model version 4.2 (CanESM4.2) , 2016 .

[132]  M. Allen,et al.  Cumulative emissions and climate policy , 2014 .

[133]  J. Goudriaan,et al.  Photosynthesis, CO2 and Plant Production , 1985 .

[134]  K. Assmann,et al.  Evaluation of NorESM-OC (versions 1 and 1.2), the ocean carbon-cycle stand-alone configuration of the Norwegian Earth System Model (NorESM1) , 2016 .

[135]  G. Collatz,et al.  Coupled Photosynthesis-Stomatal Conductance Model for Leaves of C4 Plants , 1992 .

[136]  D. Verseghy,et al.  The Canadian land surface scheme (CLASS): Its history and future , 2000 .

[137]  EK VIV,et al.  A parameterization of leaf phenology for the terrestrial ecosystem component of climate models , 2004 .

[138]  T. Ziehn,et al.  The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) – Part 1: Model description and pre-industrial simulation , 2015 .

[139]  Alexander J. Winkler,et al.  Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO2 , 2019, Journal of advances in modeling earth systems.

[140]  T. Fichefet,et al.  Simulating the mass balance and salinity of Arctic and Antarctic sea ice 2: Importance of sea ice salinity variations , 2009 .

[141]  Elena Shevliakova,et al.  An Enhanced Model of Land Water and Energy for Global Hydrologic and Earth-System Studies , 2014 .

[142]  V. Brovkin,et al.  Strong dependence of CO2 emissions from anthropogenic land cover change on initial land cover and soil carbon parametrization , 2015 .

[143]  L. Bopp,et al.  A framework to understand the transient climate response to emissions , 2016 .

[144]  F. Joos,et al.  Regional Impacts of Climate Change and Atmospheric CO2on Future Ocean Carbon Uptake: A Multimodel Linear Feedback Analysis , 2011 .

[145]  Martyn P. Chipperfield,et al.  Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model , 2010 .

[146]  S. Malyshev,et al.  Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA‐TV) , 2020, Global change biology.

[147]  Jean-Philippe Lafore,et al.  A Density Current Parameterization Coupled with Emanuel’s Convection Scheme. Part I: The Models , 2010 .

[148]  Kirsten Thonicke,et al.  SPITFIRE within the MPI Earth system model: Model development and evaluation , 2014 .

[149]  Till Kuhlbrodt,et al.  UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions , 2018, Geoscientific Model Development.

[150]  I. C. Prentice,et al.  Carbon-nitrogen interactions in idealized simulations with JSBACH (version 3.10) , 2017 .

[151]  C. Heinze,et al.  Ocean biogeochemistry in the Norwegian Earth System Model version 2 (NorESM2) , 2020, Geoscientific Model Development.

[152]  Stephanie Dutkiewicz,et al.  On the solution of the carbonate chemistry system in ocean biogeochemistry models , 2006 .

[153]  A. J. Hewitt,et al.  UKESM1: Description and Evaluation of the U.K. Earth System Model , 2019, Journal of Advances in Modeling Earth Systems.

[154]  Lisa Dresner,et al.  Ocean Dynamics And The Carbon Cycle Principles And Mechanisms , 2016 .

[155]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[156]  Thomas Reichler,et al.  Analysis and Reduction of Systematic Errors through a Seamless Approach to Modeling Weather and Climate , 2010 .

[157]  Richard G. Williams,et al.  Carbon-Cycle Feedbacks Operating in the Climate System , 2019, Current Climate Change Reports.

[158]  H. Douville,et al.  Timeslice experiments for understanding regional climate projections: applications to the tropical hydrological cycle and European winter circulation , 2017, Climate Dynamics.

[159]  B. Stevens,et al.  The Max Planck Institute Grand Ensemble: Enabling the Exploration of Climate System Variability , 2019, Journal of Advances in Modeling Earth Systems.

[160]  S. Long,et al.  What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. , 2004, The New phytologist.

[161]  K. Shine,et al.  Intergovernmental panel on Climate change (IPCC),in encyclopedia of Enviroment and society,Vol.3 , 2007 .

[162]  A. Ito,et al.  Uncertainty of Concentration–Terrestrial Carbon Feedback in Earth System Models* , 2014 .

[163]  Inez Y. Fung,et al.  Climate Sensitivity: Analysis of Feedback Mechanisms , 2013 .