Observational uncertainty is the primary source of climate uncertainty in impacts projections

Kevin Schwarzwald , Nathan Lenssen, Tom Bearpark, Alia Bonanno, Radley Horton, Gernot Wagner

Projections of future climate damages underpin environmental policy and risk management but depend on inherently uncertain climate data. Uncertainty in historical climate observations, used to train impact models and calibrate climate projections to the observed record, is rarely considered. We show this “observational uncertainty” contributes more than the spread across or within global climate models to projections of mortality, GDP per capita growth, and payroll. Most of this uncertainty stems from training impact models; even small differences in historic weather estimates can cause large differences in projected damages. Incorporating this uncertainty increases the spread in climate uncertainty by up to 300%, highlighting the importance of impact model design and the need for better constraints on observations, and implying a higher Social Cost of Carbon.