Effects of cloud overlap on radiative feedbacks

Abstract

The column radiative model (CRM) of the National Center for Atmospheric Research Community Climate Model has been used to test feedbacks associated with changes in monthly mean cloudiness for atmospheres with two different prescriptions of how clouds overlap in the vertical. The first specification is the default CRM random overlap assumption. The second, called the nonrandom case, uses an estimate of the observed overlap based upon an analysis of satellite- and surface-based observations. The results are presented primarily in terms of the changes in top-of-the-atmosphere net cloud radiative forcing resulting from a 25% increase in total cloud water and separate 16.5% increases in low, middle and high cloud layer amounts and differences that occurred during the 1987 El Niño/Southern Oscillation (ENSO) event. Overall, the random model is about 20% more sensitive to 16.5% increases in low clouds than the nonrandom model, but the nonrandom model is about twice as sensitive to increases in middle cloud. Differences in sensitivity for changes in high cloud amount and total cloud water are relatively small. In the areas near the large sea surface temperature anomalies the 1987 ENSO related departures in the nonrandom model are 0.5–2 Wm⁻² greater than for the random model. Thus, this analysis strongly suggests that accurate specification of overlap in climate models is critical to the calculation of the appropriate radiative feedbacks and sensitivities of models to external forcing such as increased carbon dioxide or sulfate aerosols.