FaIRv2.0.0: a generalized impulse response model for climate uncertainty and future scenario exploration

Abstract. Here we present an update to the FaIR model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis, education. In this have focussed on identifying a minimum level of structural complexity model. The result is set six equations, five which correspond standard impulse response used greenhouse gas (GHG) metric calculations IPCC's Fifth Assessment Report, plus one additional physically motivated equation represent state-dependent feedbacks timescales each cycle. This necessary reproduce non-linearities carbon cycle apparent both Earth system models observations. These equations are transparent sufficiently simple that able be ported into tabular data analysis packages, such as Excel, increasing potential user base considerably. However, demonstrate flexible enough tuned emulate behaviour several key processes within more complex from CMIP6. exceptionally quick run, making it ideal integrating large ensembles. We apply constraint based current estimates global warming trend million-member ensemble, using constrained ensemble make scenario-dependent projections infer ranges properties system. Through these analyses, reaffirm (unlike models) not themselves intrinsically biased “hot” or “cold”: choice parameters how those selected determines response, something appears been misunderstood past. updated GHG aerosol emissions with sufficient accuracy useful wide range applications therefore could lowest-common-denominator provide consistency different contexts. fact can written down just greatly aids transparency