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https://github.com/OMS-NetZero/FAIR

Finite-amplitude Impulse Response simple climate model
https://github.com/OMS-NetZero/FAIR

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Finite-amplitude Impulse Response simple climate model

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# FaIR



FaIR (the Finite-amplitude Impulse-Response) climate model is a simple

climate model, or *emulator*, useful for producing global mean

temperature projections from a wide range of emissions or prescribed

forcing scenarios.



## Requirements



-   python 3.8, 3.9, 3.10, 3.11 or 3.12



## Installation



### From anaconda (recommended)



**NEW!** from v2.1.4, `fair` is available on `conda-forge`:



    conda install -c conda-forge fair



Older versions of `fair` (1.6.2+, 2.1.0-4) can be installed from the `chrisroadmap` channel:



    conda install -c chrisroadmap fair==X.Y.Z



### From the Python Package Index



    pip install fair



### From source



Refer to [the

documentation](https://fair.readthedocs.io/en/latest/install.html)



## Usage



FaIR can be driven by emissions of greenhouse gases (GHGs) and

short-lived forcers (SLCFs), concentrations of GHGs, or effective

radiative forcing (ERF), with different input methods for different

species possible in the same run. If run concentration-driven, emissions

are back-calculated. Custom GHGs and SLCFs can be defined, and all

components are optional allowing experiments such as pulse-response

analyses to single forcers or gathering up non-CO~2~ species as an

aggregate forcing.



## Examples



The examples directory contains Jupyter notebooks with some

simple examples showing how to run FaIR and the standalone energy

balance model.



If you want to try this out online, [go

here](https://mybinder.org/v2/gh/OMS-NetZero/FAIR/master?filepath=examples/basic_run_example.ipynb).



## Important: A note about calibrating and constraining



FaIR is naive. It will run whatever climate scenario and climate

configuration you give it. If you violate the laws of physics, FaIR

won\'t stop you. For simple climate models as for complex, garbage in

leads to garbage out. More subtle to spot are those analyses with simple

climate models where the present day warming (or historical) is wrong or

the climate is warming too slowly or too quickly. At least, plot a

historical temperature reconstruction over your results and see if it

looks right.



We have produced IPCC AR6 Working Group 1 consistent probabilistic

ensembles to run with. The calibration data can be obtained

[here](https://doi.org/10.5281/zenodo.7112539). These parameter sets are

calibrated to CMIP6 models, run in a large Monte Carlo ensemble, and

constrained based on observed and assessed climate metrics. For an

example of how to use this calibration data set with SSP emissions, see

[this

example](https://docs.fairmodel.net/en/latest/examples/calibrated_constrained_ensemble.html).

If you\'re writing a paper using FaIR, you should use these. A paper describing this method has been submitted, but for now please cite the Zenodo DOI.



## Citation



If you use FaIR in your work, please cite the following references

depending on the version:



-   **v2.0+:** Leach, N. J., Jenkins, S., Nicholls, Z., Smith, C. J.,

    Lynch, J., Cain, M., Walsh, T., Wu, B., Tsutsui, J., and Allen, M.

    R.: FaIRv2.0.0: a generalized impulse response model for climate

    uncertainty and future scenario exploration, Geosci. Model Dev., 14,

    3007--3036, , 2021

-   **v1.1-v1.6**: Smith, C. J., Forster, P. M., Allen, M., Leach, N.,

    Millar, R. J., Passerello, G. A., and Regayre, L. A.: FAIR v1.3: A

    simple emissions-based impulse response and carbon cycle model,

    Geosci. Model Dev.,

    , 2018.

-   **v1.0** (or the concept of the state-dependent impulse-response

    function for CO2): Millar, R. J., Nicholls, Z. R., Friedlingstein,

    P., and Allen, M. R.: A modified impulse-response representation of

    the global near-surface air temperature and atmospheric

    concentration response to carbon dioxide emissions, Atmos. Chem.

    Phys., 17, 7213-7228,

    , 2017.