OSCAR is a model of reduced-complexity that describes the interactions between large-scale components of the Earth system that relate to anthropogenic climate change. Its modules are calibrated to emulate the behavior of complex process-based models.

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OSCAR is a system of differential equations that describe the temporal dynamic of key physical quantities through mass and energy balance. Among the models of its category, OSCAR is one of the most complex and heavy, with about 150 equations, 25 state variables, and 200 parameters (although many are duplicated along extra dimensions such as regions). It is however very flexible, as sub-models can easily be isolated, or new equations plugged in.

As input, the model takes annual time series of emission of anthropogenic greenhouse gases and other climatically active species (e.g. aerosol precursors), as well as time series of land use and land cover change drivers. As output, the model produces annual time series of global temperature change (without stochasticity) and of any intermediate variable of the system (e.g. greenhouse gas concentrations). While OSCAR is firstly designed to provide a global perspective, a number of processes are differentiated at the regional scale (most notably, the land carbon cycle).

Bookkeeping module and contribution to the Global Carbon Budget

Gitz & Ciais (2003) designed the first version of OSCAR as a land carbon cycle model with bookkeeping capabilities, to estimate CO2 emissions from land use change at the scale of broad world regions. This feature – unique for such a reduced-complexity model – has remained integral to OSCAR. Since the update by Gasser et al. (2020), OSCAR is one of three bookkeeping models that contribute to the annual Global Carbon Budget with estimates of historical CO2 emissions from land use change.


Selection of illustrative past works with OSCAR:

  • Xu et al. (2022) investigated how negative climate impacts on agricultural production could reduce the potential to use bioenergy with carbon capture and storage as a means to mitigate future climate change.
  • Fu et al. (2020) demonstrated that short-lived species (e.g. ozone and aerosols) have a long-term climate effect through the climate-carbon feedback.
  • Gasser et al. (2018) expanded OSCAR with a model of permafrost carbon thaw, and estimated by how much the remaining carbon budget may be reduced through this Earth system feedback.
  • Gasser et al. (2017) isolated the climate-carbon feedback, and provided corrections to the Global Warming Potentials (GWPs) that were adopted in the sixth IPCC report (chapter 7).
  • Li et al. (2016) estimated China’s historical contribution to the global radiative forcing that causes climate change.
  • Ciais et al. (2013) proposed two ways of attributing the carbon captured by natural forests: to the emitting regions that trigger the capture, or to the absorbing one that host it.