The updated CICERO Simple Climate Model – an open-source emulator contribution to the AR6 process

The Cicero Simple Climate Model (CICERO-SCM) is an energy balance model originally developed around 20 years ago, in Fortran, that has since been in continuous use and subject to minor revisions to keep up with updated best estimates in the science. It was recently used as one of a suite of emulators linking Working Groups 1 and 3 of the IPCC 6^th Assessment Report. In this presentation, we outline the model and its key features and components and show its native projections of future climate following the SSP Pathways and its performance as an IPCC AR6 emulator. We also present a python port of the model that will shortly be made publicly available.

 

For AR6, CICERO-SCM was tuned to reproduce the surface temperature evolution assessed by Working Group 1, as well as a range of other parameters. For probabilistic uncertainty estimation, we built on the method of (Skeie et al. 2018) where a large set of observation based prior assumptions on ocean heat content and temperature change was ran through the model to create a large consistent set of parameters. In the AR6 process, this set of parameters was used as an initial pool of useable parameter sets. From there the AR6 statistical distributions of current temperature, ECS and aerosol forcing were used to create a parameter subset. As part of this effort, a python wrapper was developed and integrated into the openscm-runner framework, to go between the formats and setups of the AR6 inputs, and the setup expected by the Fortran based binary.

CICERO-SCM has recently been ported to python, and is currently being tested for public, open-source release. The base version will include tunable parameters and the possibility for running user generated scenarios and will form the basis for a number of planned extensions – notably regarding short-lived climate forcers and the interaction of anthropogenic climate change with natural variability.