The simulations of clouds in climate models are improving. In the newest models, there is widespread reduction of a bias associated with too many highly reflective clouds, with the best models having eliminated this bias. Figure 1 shows this improvement by displaying how the amount of highly reflective clouds, indicated by the cloud optical depths τ > 23, has been reduced in newer models from individual model families (Figure 1). With increased amounts of clouds with lesser reflectivity, there is a significant reduction in the “too few – too bright” problem where the time-mean radiation balance is well-simulated by having the compensating errors of too few clouds which are too reflective.

Quantitatively, scalar measures of model performance for cloud amount and cloud properties demonstrative objective improvement (Figure 2). In this figure, each climate model is plotted with a symbol and stratified into the older (CFMIP1) and newer (CFMIP2) models. Arrows track progress in individual models or the ensemble mean and if they point to left indicate improvement with time. Model improvement is most marked for a scalar measure of cloud properties (right panel) that results mostly from the improvement in cloud reflectance rather than cloud altitude. Errors in cloud amount (left panel) on average show little or no improvement, although greater improvement can be found in individual models.