Evolving CO2 Rather Than SST Leads to a Factor of Ten Decrease in GCM Convergence Time.

The high computational cost of Global Climate Models (GCMs) is a problem that limits their use in many areas. Recently an inverse climate modeling (InvCM) method, which fixes the global mean sea surface temperature (SST) and evolves the CO2 mixing ratio to equilibrate climate, has been implemented in a cloud‐resolving model. In this article, we apply InvCM to ExoCAM GCM aquaplanet simulations, allowing the SST pattern to evolve while maintaining a fixed global‐mean SST. We find that InvCM produces the same climate as normal slab‐ocean simulations but converges an order of magnitude faster. We then use InvCM to calculate the equilibrium CO2 for SSTs ranging from 290 to 340 K at 1 K intervals and reproduce the large increase in climate sensitivity at an SST of about 315 K at much higher temperature resolution. The speedup provided by InvCM could be used to equilibrate GCMs at higher spatial resolution or to perform broader parameter space exploration in order to gain new insight into the climate system. Additionally, InvCM could be used to find unstable and hidden climate states, and to find climate states close to bifurcations such as the runaway greenhouse transition. Plain Language Summary: A large portion of the computational cost in climate simulation is spent in the initial equilibration phase before the model produces relevant output. This is because in normal Global Climate Model (GCM) simulations, you prescribe the atmospheric CO2 and allow the surface temperature to evolve until it reaches a roughly constant global‐mean value. In this article, we instead prescribe a global‐mean surface temperature and evolve the CO2 until the GCM is in energy balance. This leads to about a factor of ten decrease in equilibration time, which represents a considerable savings of computational resources. This allows us to investigate the change in climate sensitivity as the global‐mean temperature increases at high‐temperature resolution. Although the results we describe are for an idealized model set‐up, we believe that the method can be applied more generally. Additionally, the method could be used to investigate the climate response to given SST patterns and to find climate states that are unstable and/or hidden from normal GCM simulations. Key Points: We converge a GCM by varying the CO2 while keeping the global‐mean surface temperature fixed (the inverse climate modeling method)Inverse climate modeling converges about 10 times faster than normal slab‐ocean simulationsThe SST gradient response timescale is the bottleneck on the convergence rate of inverse climate modeling [ABSTRACT FROM AUTHOR]