Preprints
https://doi.org/10.5194/egusphere-2024-708
https://doi.org/10.5194/egusphere-2024-708
11 Apr 2024
 | 11 Apr 2024
Status: this preprint is open for discussion.

fair-calibrate v1.4.1: calibration, constraining and validation of the FaIR simple climate model for reliable future climate projections

Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen

Abstract. Simple climate models (also known as emulators) have re-emerged as critical tools for analysis of climate policy. Emulators are efficient and highly parameterised, where the parameters are tunable to produce a diversity of global mean surface temperature (GMST) response pathways to a given emissions scenario. Only a small fraction of possible parameter combinations will produce historically consistent climate hindcasts, a necessary condition for trust in future projections. Alongside historical GMST, additional observed (e.g. ocean heat content) and emergent climate metrics (such as the equilibrium climate sensitivity) can be used as constraints upon the parameter sets used for climate projections. This paper describes a multi-variable constraining package for the FaIR simple climate model (FaIR versions 2.1.0 onwards) using a Bayesian framework. The steps are firstly to generate prior distributions of parameters for FaIR based on Coupled Model Intercomparison Project (CMIP6) Earth System models or Intergovernmental Panel on Climate Change (IPCC) assessed ranges, secondly to generate a large Monte Carlo prior ensemble of parameters to run FaIR with, and thirdly to produce a posterior set of parameters constrained on several observable and assessed climate metrics. Different calibrations can be produced for different emissions datasets or observed climate constraints, allowing version-controlled and continually updated calibrations to be produced. We show that two very different future projections to a given emission scenario can be obtained using emissions from the IPCC Sixth Assessment Report (AR6) (fair-calibrate v1.4.0) and from updated emissions datasets through 2022 (fair-calibrate v1.4.1) for similar climate constraints in both cases. fair-calibrate can be reconfigured for different source emissions datasets or target climate distributions, and new versions will be produced upon availability of new climate system data.

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Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen

Status: open (until 09 Jun 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-708', Anonymous Referee #1, 20 May 2024 reply
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen

Data sets

FaIR calibration data Chris Smith https://zenodo.org/records/10566813

Model code and software

fair-calibrate Chris Smith https://github.com/chrisroadmap/fair-calibrate/tree/v1.4.1

Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen

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Short summary
Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalize a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth System models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity, are used to constrain the model output.