Quantifying both socioeconomic and climate uncertainty in coupled human–Earth systems analysis

Abstract

Information about the likelihood of various outcomes is needed to inform discussions about climate mitigation and adaptation. Here we provide integrated, probabilistic socio-economic and climate projections, using estimates of probability distributions for key parameters in both human and Earth system components of a coupled model. We find that policy lowers the upper tail of temperature change more than the median. We also find that while human system uncertainties dominate uncertainty of radiative forcing, Earth system uncertainties contribute more than twice as much to temperature uncertainty in scenarios without fixed emissions paths, reflecting the uncertainty of translating radiative forcing into temperature. The combination of human and Earth system uncertainty is less than additive, illustrating the value of integrated modeling. Further, we find that policy costs are more uncertain in low- and middle-income economies, and that renewables are robust investments across a wide range of policies and socio-economic uncertainties.