2004: An assessment of the parameterization of subgrid-scale cloud effects on radiative transfer. Part I: Vertical overlap

Different approaches for parameterizing the effects of vertical variability of cloudiness on radiative transfer are assessed using a database constructed from observations derived from lidar and millimeter cloud radar data collected from three different locations. Five different methods for dealing with the vertical overlap of clouds were incorporated into a single radiation model that was applied to the lidar/radar data averaged in time. The calculated fluxes and heating rates derived with this model are compared to broadband fluxes and heating rates calculated with the independent column approximation using the time-resolved cloud data. These comparisons provide a way of evaluating the effects of different overlap assumptions on the calculation of domain-mean fluxes. It was demonstrated how two of the most commonly used overlap schemes, the random and maximum-random methods, suffer a severe problem in that the total cloud amount defined by these methods depends on the vertical resolution of the host model thus creating a vertical-resolution-dependent bias in model total cloud-iness and radiative fluxes. A new method is introduced to overcome this problem by preserving the total column cloud amount. Despite these problems, the comparisons presented show that most methods introduce a relatively small bias with respect to the single-column data. This is largely a consequence of the nature of the cloud cover statistic