The Model for Economic Tipping point Analysis (META) is one of a new generation of climate-economy integrated assessment models used to study the economic impacts of climate change. A typical output of such models is an estimate of the social cost of greenhouse gas emissions, a measure of the economic damage caused over its lifetime by a ton of greenhouse gas such as CO2 or CH4.

META, however, computes many other economic as well as geophysical indicators. As its name suggests, META was built specifically to estimate the economic impact of tipping points in the climate system. To do so, META incorporates different tipping points modules, each of which replicate a geophysically realistic tipping point module from a study in the climate economics research literature.

META was originally introduced in Dietz, Rising, Stoerk and Wagner (2021, Proceedings of the National Academy of Sciences, https://www.pnas.org/doi/full/10.1073/pnas.2103081118), and has since been updated and ported to Julia using the Mimi Framework. Follow-up research has improved several components of META. Similarly, META estimates have been used to inform conversations with authorities in the EU and the US.

In this talk, I will give a short overview of META's structure, its capabilities, and ideas for the community on how to further improve and use META for open research in the future.

META is freely available on Github under a GPL-3.0 copyleft licence: https://github.com/openmodels/META