MAGICC (Model for the Assessment of Greenhouse Gas Induced Climate Change) is widely used in the assessment of future emissions pathways in climate policy analyses, e.g. in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change or to model the physical aspects of climate change in Integrated Assessment Models (IAMs).
Pymagicc makes the MAGICC model easily installable and usable from Python and allows for the easy modification of all MAGICC model parameters and emissions scenarios directly from Python. In climate research it can, for example, be used in the analysis of mitigation scenarios, in Integrated Assessment Models, complex climate model emulation, and uncertainty analyses, as well as in climate science education and communication.
The compiled MAGICC binary by Tom Wigley, Sarah Raper, and Malte Meinshausen included in this package is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
pymagicc wrapper itself is released under a BSD-3 license. For details, see LICENSE.
If you make any use of MAGICC, its license requires citing of:
M. Meinshausen, S. C. B. Raper and T. M. L. Wigley (2011). “Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6: Part I “Model Description and Calibration.” Atmospheric Chemistry and Physics 11: 1417-1456. https://doi.org/10.5194/acp-11-1417-2011
If you use Pymagicc in your research, please additionally cite
R. Gieseke, S. N. Willner and M. Mengel, (2018). Pymagicc: A Python wrapper for the simple climate model MAGICC. Journal of Open Source Software, 3(22), 516, https://doi.org/10.21105/joss.00516
For proper reproducibility please reference the version of Pymagicc used. In Python it can be printed with
import pymagicc print(pymagicc.__version__)
Pymagicc releases are archived at Zenodo and the version used should also be cited. See https://doi.org/10.5281/zenodo.1111815.
- MAGICC variables
- MAGICC file conventions
- MAGICC flags