Robert Wood and Dennis L. Hartmann

Journal of Climate, in press

Liquid water path ($\mathit{LWP}$) mesoscale spatial variability in marine low cloud over the eastern subtropical oceans is examined using two months of daytime retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra satellite. Approximately 20000 scenes of size 256$\times$256~km are used in the analysis. It is found that cloud fractional coverage is strongly linked with the ($\mathit{LWP}$) variability in the cloudy fraction of the scene. We show that in most cases ($\mathit{LWP}$) spatial variance is dominated by horizonal scales of 10-50~km, and increases as the variance-containing scale increases, indicating the importance of organized mesoscale cellular convection (MCC). A neural network technique is used to classify MODIS scenes by the spatial variability type (no MCC, closed MCC, open MCC, cellular but disorganized). It is shown how the different types tend to occupy distinct geographical regions and different physical regimes within the subtropics, although the results suggest considerable overlap of the large scale meteorological conditions associated with each scene type. We demonstrate that the both the frequency of occurrence, and the variance-containing horizontal scale of the MCC increases as the MBL depth $z_{i}$ increases. However, for the deepest MBLs, the MCC tends to be replaced by clouds containing cells but lacking organization. In regions where MCC is prevalent, we found a lack of sensitivity of the MCC type (open or closed) to the large scale meteorology, suggesting a mechanism internal to the MBL may be important in determining MCC type. The results indicate that a knowledge of the physics of mesoscale cellular convection (MCC) will be required to completely understand and predict low cloud coverage and variability in the subtropics.