Overlap of fractional cloud for radiation calculations in GCMs: A global analysis using CloudSat and CALIPSO data

Assumptions made by global climate models (GCMs) regarding vertical overlap of fractional amounts of clouds have significant impacts on simulated radiation budgets. A global survey of fractional cloud overlap properties was performed using 2 months of cloud mask data derived from CloudSat-CALIPSO satellite measurements. Cloud overlap was diagnosed as a combination of maximum and random overlap and characterized by vertically constant decorrelation length ℒcf*. Typically, clouds overlap between maximum and random with smallest ℒcf* (medians → 0 km) associated with small total cloud amounts Ĉ, while the largest ℒcf* (medians ∼3 km) tend to occur at Ĉ near 0.7. Global median ℒcf* ∼2 km with a slight tendency for largest values in the tropics and polar regions during winter. By crudely excising near-surface precipitation from cloud mask data, ℒcf* were reduced by typically <1 km. Median values of ℒcf* when Sun is down exceed those when Sun is up by almost 1 km when cloud masks are based on radar and lidar data; use of radar only shows minimal diurnal variation but significantly larger ℒcf*. This suggests that sunup inferences of ℒcf* might be biased low by solar noise in lidar data. Cloud mask cross-section lengths L of 50, 100, 200, 500, and 1000 km were considered. Distributions of ℒcf* are mildly sensitive to L thus suggesting the convenient possibility that a GCM parametrization of ℒcf* might be resolution-independent over a wide range of resolutions. Simple parametrization of ℒ cf* might be possible if excessive random noise in Ĉ, and hence radiative fluxes, can be tolerated. Using just cloud mask data and assuming a global mean shortwave cloud radiative effect of -45 W m^-2, top of atmosphere shortwave radiative sensitivity to ℒcf* was estimated at 2 to 3 W m^-2 km^-1.