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

Abstract

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.

How much methane removal is required to avoid overshooting 1.5 ∘C?

“…We use an 841 member ensemble of the Finiteamplitude Impulse Response (FaIR) simple climate model (v2.1.3) [30], using calibration v1.4.0 [31]. FaIR is a simple climate model that determines atmospheric concentrations of greenhouse gases from their emissions, radiative forcing of greenhouse gases and other anthropogenic forcers from their concentrations and emissions, and global mean surface temperature projections from radiative forcing using a threelayer energy balance model.…”

“…The 841-member ensemble is constrained from a prior of 1.6 million members that are calibrated to the responses of CMIP6 Earth System models for their temperature response to forcing, carbon cycle feedbacks, aerosol and ozone radiative forcing [31]. The sampled ensemble members forming the prior distributions also include the assessed uncertainty in methane radiative forcing of ±20% around its best estimate [35].…”

“…The ECS, TCR and aerosol constraints are from IPCC AR6 WG1 [35] and other constraints from the Indicators of Global Climate Change (IGCC) project which updates the IPCC assessments to 2022 [6]. The sampling and constraining procedure is described in [31].…”