Benchmark Calculations of Radiative Forcing by Greenhouse Gases

Changes in concentrations of greenhouse gases lead to changes in radiative fluxes throughout the atmosphere. The value of this change, the instantaneous radiative forcing, varies across climate models, due partly to differences in the distribution of clouds, humidity, and temperature across models and partly due to errors introduced by approximate treatments of radiative transfer. This paper describes an experiment within the Radiative Forcing Model Intercomparision Project that uses benchmark calculations made with line‐by‐line models to identify parameterization error in the representation of absorption and emission by greenhouse gases. Clear‐sky instantaneous forcing by greenhouse gases is computed using a set of 100 profiles, selected from a reanalysis of present‐day conditions, that represent the global annual mean forcing from preindustrial times to the present day with sampling errors of less than 0.01 W m−2. Six contributing line‐by‐line models agree in their estimate of this forcing to within 0.025 W m−2 while even recently developed parameterizations have typical errors 4 or more times larger, suggesting both that the samples reveal true differences among line‐by‐line models and that parameterization error will be readily identifiable. Agreement among line‐by‐line models is better in the longwave than in the shortwave where differing treatments of the water vapor continuum affect estimates of forcing by carbon dioxide and methane. The impacts of clouds on instantaneous radiative forcing are estimated from climate model simulations, and the adjustment due to stratospheric temperature changes estimated by assuming fixed dynamical heating. Adjustments are large only for ozone and for carbon dioxide, for which stratospheric cooling introduces modest nonlinearity. Key Points Mean clear‐sky instantaneous radiative forcing by greenhouse gases is computed with six benchmark models using 100 atmospheric profiles Sampling error is several times smaller than the level of disagreement among models, which is itself smaller than parameterization error The impacts of clouds and stratospheric adjustment are roughly estimated; adjustments are large only for carbon dioxide and ozone