On the effect of historical SST patterns on radiative feedback

Abstract

We investigate the dependence of radiative feedback on the pattern of sea-surface temperature (SST) change in fourteen Atmospheric General Circulation Models (AGCMs) forced with observed variations in SST and sea-ice over the historical record from 1871 to near-present. We find that over 1871-1980, the Earth warmed with feedbacks largely consistent and strongly correlated with longterm climate sensitivity feedbacks (diagnosed from corresponding atmosphere-ocean GCM abrupt-4xCO2 simulations). Post 1980 however, the Earth warmed with unusual trends in tropical Pacific SSTs (enhanced warming in the west, cooling in the east) that drove climate feedback to be uncorrelated with -and indicating much lower climate sensitivity than -that expected for long-term CO 2 increase. We show that these conclusions are not strongly dependent on the AMIP II SST dataset used to force the AGCMs, though the magnitude of feedback post 1980 is generally smaller in eight AGCMs forced with alternative HadISST1 SST boundary conditions. We quantify a 'pattern effect' (defined as the difference between historical and long-term CO 2 feedback) equal to 0.44 ± 0.47 [5-95%] W m -2 K -1 for the time-period 1871-2010, which increases by 0.05 ± 0.04 W m -2 K -1 if calculated over 1871-2014. Assessed changes in the Earth's historical energy budget are in agreement with the AGCM feedback estimates. Furthermore satellite observations of changes in top-of-atmosphere radiative fluxes since 1985 suggest that the pattern effect was particularly strong over recent decades, though this may be waning post 2014 due to a warming of the eastern Pacific.

On the Effect of Historical SST Patterns on Radiative Feedback

“…Global‐annual‐ensemble‐mean d T and d N data from all amip‐piForcing , hadSST‐piForcing, and abrupt‐4xCO2 simulations used in this study are provided at https://doi.org/10.5281/zenodo.6799004 (Andrews et al., 2022). Raw data from CMIP6 amip‐piForcing simulations (indicated in Table 1) are available at https://pcmdi.llnl.gov/CMIP6/ (Eyring et al., 2016).…”