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Mean Structure and diurnal cycle of Southeast Atlantic boundary layer clouds:...

Painemal, D., K. Xu, A. Cheng, P. Minnis, and R. Palikonda (2014), Mean Structure and diurnal cycle of Southeast Atlantic boundary layer clouds: Insights from satellite observations and multiscale modeling framework simulations, J. Climate (submitted).

The mean structure and diurnal cycle of Southeast Atlantic boundary layer clouds are described with satellite observations and multi-scale modeling framework (MMF) simulations during austral spring (September-November). Hourly resolution cloud fraction (CF) and cloud top height (HT) are retrieved from Meteosat-9 radiances using modified CERES-MODIS algorithms, whereas liquid water path (LWP) is from the University of Wisconsin microwave satellite climatology. The MMF simulations use a 2-D cloud-resolving model (CRM) that contains an advanced third-order turbulence closure to explicitly simulate cloud physical processes in every grid column of a general circulation model. The model accurately reproduces the marine stratocumulus spatial extent and cloud cover. The mean cloud cover spatial variability in the model is primarily explained by the boundary layer decoupling strength, whereas a boundary layer shoaling accounts for a coastal decrease in CF. Moreover, the core of the stratocumulus cloud deck is concomitant with the location of the strongest temperature inversion. Although the model reproduces the observed westward boundary layer deepening and the spatial variability of LWP, it overestimates LWP by 50%. Diurnal cycles of HT, CF, and LWP from satellites and the model have the same phase, with maxima during the early morning and minima near 15:00 local time, which suggests that the diurnal cycle is driven primarily by solar heating. Comparisons with the SE Pacific cloud deck indicate that the observed amplitude of the diurnal cycle is modest over the SE Atlantic, with a shallower boundary layer as well. The model qualitatively reproduces these regime inter-differences.

Research Program: 
Modeling Analysis and Prediction Program (MAP)