s) and, conversely, that parameterizations with small errors in the present day may still have significant forcing errors (e.g., the CCC and RRTMG parameterizations).

4. Tracing Error From a Few Aerosol‐Free Clear Skies to Projections of Climate Change {#grl53099-sec-0004}
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A focus on clear skies may seem narrow given that roughly two thirds of the planet\'s surface at any given time is covered by some kind of cloud \[e.g., *Stubenrauch et al.*, [2013](#grl53099-bib-0033){ref-type="ref"}\]. But clear‐sky errors exist even in cloudy skies (though they need not add linearly to errors introduced in the treatment of clouds), and clouds do not affect forcing directly, so that characterizing the error in aerosol‐free clear skies remains a useful starting point for assessing errors in radiative forcing.

The errors reported here come from snapshots at an essentially arbitrary point in time. In particular, the models to be used in CMIP6 \[*Meehl et al.*, [2014](#grl53099-bib-0019){ref-type="ref"}\] are still under construction and the radiation parameterizations are subject to revision before simulations are made and shared. One goal of intercomparison exercises is to identify errors so they may be fixed (see discussions in *Cahalan et al.* \[[2005](#grl53099-bib-0003){ref-type="ref"}\], for example), and this study has already motivated two changes reflected in our results: spectroscopy was updated in the GISS parameterizations, and an important simplification (the assumption that surface skin and surface air temperature are identical) was relaxed in the LMDZ and CNRM longwave parameterizations after initial calculations demonstrated relatively large errors in two cases. Further revisions may be expected in the next generation of climate models. Some, we hope, will expand the range of atmospheres used to train the parameterization to include conditions such as large concentrations of greenhouse gases.

The reference models on wh