MAGICC7

Here we provide, after registration, access to both the MAGICCv7.5.3 binary and the probabilistic distribution used in the IPCC’s Sixth Assessment Report (AR6).

We provide both these files in the interest of reproducibility, transparency and progress towards open-source. We hope that this step will improve understanding and lead to new scientific insights. We include registration so we have some idea of where our works are being used and can provide updates as needed.

License and expectations

The binary is provided under the permissive Creative Commons Attribution 4.0 International License (CC BY 4.0). The probabilistic distribution is provided under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0), which explicitly prohibits commercial use. Beyond the legal text of the licenses, we rely on the ethics and integrity of users to ensure that the MAGICC development team receives fair credit for its work. As a result, we have the following expectations of users:

If you plan to use MAGICCv7.5.3 or the probabilistic distribution in a presentation or a paper, please contact us (malte.meinshausen@unimelb.edu.au, zebedee.nicholls@climate-energy-college.org, jared.lewis@climate-resource.com) at the start of the project so that we can discuss how you’re planning on using the works, how to represent the caveats appropriately and how best to collaborate. If the tools are a key part of the analysis, co-authorship may be appropriate and should be discussed early in the analysis process
Do not distribute the works yourselves, please direct all new users to this web page so they can obtain their own copy
If you wish to use the probabilistic distribution in a commercial context, or for commissioned or funded research, please contact us (malte.meinshausen@unimelb.edu.au, zebedee.nicholls@climate-energy-college.org, jared.lewis@climate-resource.com)

We considered making these expectations part of the license. We decided not to so that we could avoid the headaches associated with custom, otherwise untested, licenses. In return for avoiding such headaches, we ask that these expectations are taken as seriously as license terms.

The expectations ensure that a) we can keep track of where the works are being used and how b) we can provide updates to users and c) you recognise the significant work that went into producing these works. Unfortunately, in the world of science, the major currency is publications. As a result, we ask users to discuss collaboration with us before submission because this is the only way to truly recognise the effort we have put in. Often, we will not ask to be involved (due to e.g. lack of time) but the offer of collaboration is the minimum we ask for.

Citation

If you make any use of this work, please cite:

Meinshausen, M., Meinshausen, N., Hare, W., Raper, S. C. B., Frieler, K., Knutti, R., Frame, D. J., & Allen, M. R. (2009). Greenhouse-gas emission targets for limiting global warming to 2°C. Nature, 458(7242), 1158–1162 https://doi.org/10.1038/nature08017

Meinshausen, M., Raper, S. C. B., & Wigley, T. M. L. (2011). Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration. Atmospheric Chemistry and Physics, 11(4), 1417–1456 https://doi.org/10.5194/acp-11-1417-2011

Meinshausen, M., Nicholls, Z. R. J., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J. G., Daniel, J. S., John, A., Krummel, P. B., Luderer, G., Meinshausen, N., Montzka, S. A., Rayner, P. J., Reimann, S., Wang, R. H. J. (2020). The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500. Geoscientific Model Development, 13(8), 3571–3605 https://doi.org/10.5194/gmd-13-3571-2020

Nicholls, Z. R. J., Meinshausen, M., Lewis, J., Meinshausen, N., Hirons, N. (in prep.). Capturing climate science assessments with probabilistic distributions for reduced complexity climate models. Geoscientific Model Development Discussions

When is MAGICC going open-source?

MAGICC has received funding to go open-source as part of the ESM2025 project. We are currently preparing the source code and other development requirements (e.g. tests, documentation) for this release. We hope to have an open-source release ready in early to mid 2023.

In case you are looking for an easy, fully-fledged, out of the box, access to MAGICC7, why not try the fancy user-interface via live.magicc.org?

Download MAGICC7

To download, please fill out the form below. After submitting, we will email you with details on how to access the binary and probabilistic distribution.