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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.

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.

The mammalian pre-mRNA 3'-end-processing machinery consists of cleavage and polyadenylation specificity factor (CPSF), cleavage stimulation factor (CstF), and other proteins, but the overall architecture of this machinery remains unclear. CPSF contains two functionally distinct modules: a cleavage factor (mCF) and a polyadenylation specificity factor (mPSF). Here, we have produced recombinant human CPSF and CstF and examined these factors by electron microscopy (EM). We find that mPSF is the organizational core of the machinery, while the conformations of mCF and CstF and the position of mCF relative to mPSF are highly variable. We have identified by cryo-EM a segment in CPSF100 that tethers mCF to mPSF, and we have named it the PSF interaction motif (PIM). Mutations in the PIM can abolish CPSF formation, indicating that it is a crucial contact in CPSF. We have also obtained reconstructions of mCF and CstF77 by cryo-EM, assembled around the mPSF core.