fluxes are required by dynamical models of the atmosphere to compute heating and cooling rates within the atmosphere and surface fluxes of energy. The opacity of the cloud‐ and aerosol‐free atmosphere (e.g., the "clear, clean" conditions of *Ghan* \[[2013](#grl53099-bib-0014){ref-type="ref"}\]) depends strongly enough on temperature and radiatively active gas concentrations that the extinction of the gaseous atmosphere is computed anew at each location and time. Line‐by‐line models are impractically slow for this task because absorption coefficients due to gases vary by many orders of magnitude over very narrow spectral intervals. Computationally efficient parameterizations therefore use techniques such as exponential sum fitting of transmissivities \[*Hunt and Grant*, [1969](#grl53099-bib-0016){ref-type="ref"}; *Wiscombe and Evans*, [1977](#grl53099-bib-0036){ref-type="ref"}\], correlated *k*‐distributions \[*Lacis and Oinas*, [1991](#grl53099-bib-0018){ref-type="ref"}; *Fu and Liou*, [1992](#grl53099-bib-0013){ref-type="ref"}\], or the simplified exchange approximation \[*Fels and Schwarzkopf*, [1981](#grl53099-bib-0011){ref-type="ref"}; *Schwarzkopf and Ramaswamy*, [1999](#grl53099-bib-0031){ref-type="ref"}\] to approximate the spectral integral using a relatively small number of quadrature points minimizing some measure of error across a distribution of atmospheric states. (Other simplifications frequently used in parameterizations, such as low angular resolution or the neglect of scattering in the longwave, do not introduce significant errors in aerosol‐free clear skies.)

Systematic assessments of parameterizations against the reference models on which they are based date back more than two decades \[*Ellingson and Fouquart*, [1991](#grl53099-bib-0009){ref-type="ref"}; *Cess et al.*, [1993](#grl53099-bib-0004){ref-type="ref"}\]. Parameterizations have improved over time such that the best now reproduce line‐by‐line flux calculations in present‐day conditions to within about 1 W/m^2^ \[*Ore