Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2017-266
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Model description paper
07 Dec 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).
FAIR v1.1: A simple emissions-based impulse response and carbon cycle model
Christopher J. Smith1, Piers M. Forster1, Myles Allen2, Nicholas Leach2, Richard J. Millar3,4, Giovanni A. Passerello1, and Leighton A. Regayre1 1School of Earth and Environment, University of Leeds, Leeds, UK
2Atmospheric Physics Department, University of Oxford, Oxford, UK
3College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
4Environmental Change Institute, University of Oxford, Oxford, UK
Abstract. Simple climate models can be valuable if they are able to replicate aspects of complex fully coupled earth system models. Larger ensembles can be produced, enabling a probabilistic view of future climate change. A simple emissions-based climate model, FAIR, is presented which calculates atmospheric concentrations of greenhouse gases and effective radiative forcing (ERF) from greenhouse gases, aerosols, ozone precursors and other agents. The ERFs are integrated into global mean surface temperature change. Model runs are constrained to observed temperature change from 1880 to 2016 and produce a range of future projections under the Representative Concentration Pathway (RCP) scenarios. For the historical period the ERF time series in FAIR emulates the results in the IPCC Fifth Assessment Report (AR5), whereas for RCP historical and future scenarios, the greenhouse gas concentrations in FAIR closely track the observations and projections in the RCPs. The constrained estimates of equilibrium climate sensitivity (ECS) of 2.79 (1.97 to 4.08) K, transient climate response (TCR) of 1.47 (1.03 to 2.23) K and transient climate response to cumulative CO2 emissions (TCRE) of 1.43 (1.01 to 2.16) K (1000 GtC)−1 (median and 5–95 % credible intervals) are in good agreement, with tighter uncertainty bounds, than AR5 (1.5 to 4.5 K, 1.0 to 2.5 K, and 0.8 to 2.5 K respectively). The ranges of future projections of temperature and ranges of estimates of ECS, TCR and TCRE are moderately sensitive to the historical temperature dataset used to constrain, prior distributions of ECS/TCR parameters, aerosol radiative forcing relationship and ERF from a doubling of CO2. Taking these sensitivities into account, there is no evidence to suggest that the median and credible range of observationally constrained TCR or ECS differ from climate model-derived estimates. However, the range of temperature projections under the RCP scenarios for 2081–2100 in the constrained FAIR model ensemble are lower than the emissions-based estimates reported in AR5.

Citation: Smith, C. J., Forster, P. M., Allen, M., Leach, N., Millar, R. J., Passerello, G. A., and Regayre, L. A.: FAIR v1.1: A simple emissions-based impulse response and carbon cycle model, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-266, in review, 2017.
Christopher J. Smith et al.
Christopher J. Smith et al.
Christopher J. Smith et al.

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Short summary
FAIR 1.1 is a simple Python-based climate model emulator. It takes emissions of greenhouse gases and aerosol and ozone precursors to calculate radiative forcing and temperature change. It includes a simple representation of carbon cycle feedbacks due to temperature and accumulated carbon uptake. Large ensembles can be run with minimal computational expense for any user-specified emissions pathway. We produce such an ensemble using the RCP emissions datasets.
FAIR 1.1 is a simple Python-based climate model emulator. It takes emissions of greenhouse gases...
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