Effective Climate Sensitivity Distributions from a 1D Model of Global Ocean and Land Temperature Trends, 1970-2021

Abstract

Abstract A 1D time-dependent forcing-feedback model of temperature departures from energy equilibrium is used to match measured ranges of global-average surface and sub-surface land and ocean temperature trends during 1970–2021. In response to two different radiative forcing scenarios, a wide range of three model free parameters are swept to produce fits to a range of observed surface temperature trends from four different land datasets and three ocean datasets, as well as deep-ocean temperature trends and borehole-based trend retrievals over land. Land-derived effective climate sensitivities (EffCS) are larger than those over the ocean, and EffCS is lower using the newer Shared Socioeconomic Pathways (SSP245, 1.94 deg. C global EffCS) than the older Representative Concentration Pathway forcing (RCP6, 2.60 deg. C global average EffCS). Diagnosed EffCS increases with increasing ocean or land heat storage, with close to 1 deg. C EffCS increase associated with ocean heat storage, but only 0.13 deg. C increase from land heat storage. The strongest dependence of the EffCS results is on the assumed radiative forcing dataset, underscoring the role of radiative forcing uncertainty in determining the sensitivity of the climate system to increasing greenhouse gas concentrations from observations alone.