Method to Determine A CDR Target


Collaboration with Foundation for Climate Restoration on a brief using MAGICC 6.8 is in progress. Experiments to test 300 ppm, then to 280 ppm, and calibrating MAGICC 6.8 for removal is in progress. Seeking additional funding for a full detailed paper.

The full experimental paper is on hold until the experiments can be rerun on a full CDRMIP Atmosphere-Ocean General Circulation Model. Once the experiments are run on a full AOGCM the results will more accurately (compared to a Reduced-complexity Model such as MAGICC 6.8) show if the hypothesis of halting anthropogenic emissions from all greenhouse gasses and additionally remove cumulative anthropogenic carbon dioxide, would restore the climate to that existed at 1800 with a CO₂ concentration of about 280 ppm.

Note, a brief commentary on Reduced Complexity Model results may have limited impact as the experiments would need to be repeated on a cluster running the full AOGCM to better project the impact of strong feedbacks.


Theory paper

Presented version: Targeting All Anthropogenic Carbon Dioxide Emissions

Revised version: Alternative Method to Determine a Carbon Dioxide Removal Target (2018)

Authors: Shannon A. Fiume

Short paper outlining how much carbon we need to solidify for complete climate restoration and the carbon's location. Shows why 300 ppm and less needs to be fully explored for complete climate restoration.

Experimental Validation Paper

Working draft title 'Modeling of large-scale CDR Scenarios'.

Experimental validation of Targeting All Anthropogenic Carbon Dioxide Emissions with MAGICC 6, and pymagicc.

Authors: Shannon A. Fiume


The experiments explore the effects of halting anthropogenic emissions from all greenhouse gasses and additionally removing cumulative anthropogenic carbon dioxide in less than 100 years. Two pairs of idealized greenhouse gas emissions modeling experiments were completed in MAGICC 6.801, a Reduced Complexity Model. The experiment pair explores the difference between exponential removal and linear removal for both a forty- and eighty-year time frame. Results were graphed, extending to 2500, showing a converging temperature, greenhouse concentration, and warming. The Reduced Complexity climate model, when all greenhouse gas emissions were halted, and cumulative anthropogenic carbon dioxide was removed, excluding ammonia under .1ºC of warming was realized.

Results Summary

The experiments removed all anthropogenic carbon dioxide and forced all other GHGs to zero, excluding ammonia, which resulted in under .1ºC of warming.

Graphs of Experiment Scenarios

CO₂ ppm

CO₂-eq ppm

CO₂ RF W/m²

Total Anthro RF W/m²

Global Temp ºC

Maximum Exponential Decline CDR Scenario (emax)






Maximum Linear Decline CDR Scenario (lmax)






Minimum Exponential Decline CDR Scenario (emin)






Minimum Linear Decline CDR Scenario (lmin)












Std dev






Pymagicc output: Shows SSP-1 1.9 in orange. The graphing artifacts for SSP 1 1.9 are due to errors in the dataset from bugs in pymagicc and ipcc explorer data output. The raw MAGICC output is also shown in the links to the Graphs of Experiment Scenarios above.

Data Area

CSV of control files (Also see the SCENemax, SCENlmax, etc. tabs in Total Emitted Carbon Graphs and Comparisons gsheets)

SCEN Control files

Code Area

CDR Modeling Experiment Github repository:


  • wine - Wine Is Not an Emulator, emulation software for running Windows programs on Linux and Unixes including MacOS
  • pymagicc

Pymagicc will install the following:

MAGICC 6.801


Code to translate CSVs and display scenarios are forthcoming.

SSP Database, International Institute for Applied Systems Analysis:, About page


Reference Papers

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Emulating atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 2: Applications, Meinshausen, M., Wigley, T. M. L., and Raper, S. C. B., Atmos. Chem. Phys.,11, 1457–1471, DOI: 10.5194/acp-11-1457-2011, 2011

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Target atmospheric CO2: Where should humanity aim?, Hansen, J., M. Sato, P. Kharecha, D. Beerling, R. Berner, V. Masson-Delmotte, M. Pagani, M. Raymo, D.L. Royer, and J.C. Zachos, Open Atmos. Sci. J., 2, 217-231, DOI: 10.2174/1874282300802010217, 2008

Related Papers

The Carbon Dioxide Removal Model Intercomparison Project (CDR-MIP): Rationale and experimental protocol for CMIP6, Keller, D. P., Lenton, A., Scott, V., Vaughan, N. E., Bauer, N., Ji, D., Jones, C. D., Kravitz, B., Muri, H., and Zickfeld, K., Geosci. Model Dev., DOI: 10.5194/gmd-2017-168, 2018.

The SSP greenhouse gas concentrations and their extensions to 2500, Meinshausen, M., Nicholls, Z., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J.P., Daniel, J.S., John, A., Krummel, P., Luderer, G., Meinshausen, N., Montzka, S., Rayner, P., Reimann, S., Smith, S.J.,  van den Berg, M., Velders, G.J.M., Vollmer, M., Wang, H.J.R., DOI: 10.5194/gmd-2019-222, 2019 (preprint)

Projecting Antarctica’s contribution to future sea level rise from basal ice-shelf melt using linear response functions of 16 ice sheet models (LARMIP-2), Levermann,A., Winkelmann, R.,Albrecht, T., Goelzer, H., Golledge, N.R., Greve, R., Huybrechts, P., Jordan, J., Leguy, G., Martin, D., Morlighem, M., Pattyn, F., Pollard, D., Quiquet, A., Rodehacke, C.Seroussi, H., Sutter, J., Zhang, T., Van Breedam, J., DeConto, R., Dumas, C., Garbe, J., Gudmundsson, G.H., Hoffman, M.J., Humbert, A., Kleiner, T., Lipscomb, W., Meinshausen, M., Ng, E., Perego, M., Price, S.F., Saito, F., Schlegel, N., Sun, S., van de Wal, R.S.W., DOI: 10.5194/esd-2019-23, 2020
Synthesizing long-term sea level rise projections - the MAGICC sealevel model, Alexander Nauels, Malte Meinshausen, Matthias Mengel, Katja Lorbacher, and Tom M.L. Wigley, DOI: 10.5194/gmd-2016-233

Reduced Complexity Model Intercomparison Project Phase 1:introduction and evaluation of global-mean temperature response,

Zebedee R. J. Nicholls1,2, Malte Meinshausen1,2,3, Jared Lewis1, Robert Gieseke4, Dietmar Dommenget5,Kalyn Dorheim6, Chen-Shuo Fan5, Jan S. Fuglestvedt7, Thomas Gasser8, Ulrich Golüke9, Philip Goodwin10,Corinne Hartin6, Austin P. Hope11, Elmar Kriegler3, Nicholas J. Leach12, Davide Marchegiani5, Laura A. McBride13,Yann Quilcaille8, Joeri Rogelj8,14, Ross J. Salawitch11,13,15, Bjørn H. Samset7, Marit Sandstad7,Alexey N. Shiklomanov6, Ragnhild B. Skeie7, Christopher J. Smith8,16, Steve Smith6, Katsumasa Tanaka17,18,Junichi Tsutsui19, and Zhiang Xie

Is there warming in the pipeline? A multi-model analysis of the Zero Emissions Commitment from CO,

Andrew H. MacDougall1, Thomas L. Frölicher2,3, Chris D. Jones4, Joeri Rogelj5,6, H. Damon Matthews7,Kirsten Zickfeld8, Vivek K. Arora9, Noah J. Barrett1, Victor Brovkin10,11, Friedrich A. Burger2,3, Micheal Eby12,Alexey V. Eliseev13,14, Tomohiro Hajima15, Philip B. Holden16, Aurich Jeltsch-Thömmes2,3, Charles Koven17,Nadine Mengis18, Laurie Menviel19, Martine Michou20, Igor I. Mokhov13,14, Akira Oka21, Jörg Schwinger22,Roland Séférian20, Gary Shaffer23,24, Andrei Sokolov25, Kaoru Tachiiri15, Jerry Tjiputra22, Andrew Wiltshire4, andTilo Ziehn2

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