Estimating Vertical Motion Profile Shape within Tropical Weather States

The vertical structure of tropical deep convection strongly influences interactions with larger scale circulations and climate. Our research focuses on investigating this vertical structure and its relationship with mesoscale tropical weather states. We test the hypothesis that latent heating profile shape varies (in space and time) in association with weather state type.

We estimate mean state vertical motion profile shapes for six tropical weather states defined using cloud top pressure and optical depth properties from the ISCCP dataset. We assume two modes of vertical motion profile variability. We empirically determine these two modes from reanalysis data using a principal component analysis. We use these modes, along with the relationship between vertical motion, the dry static energy budget and mass continuity to estimate vertical motion profile shape for each space-time point considered. We do this because the shape of each estimated profile at a particular point is shown to be associated with the magnitude of precipitation and surface convergence. We use GPCP daily precipitation and QuikSCAT surface convergence data in the ITCZ region (15°S to 15°N latitude; all longitudes) from 2001-2006 for our profile estimations. Finally, these profile shapes are organized into six weather state bins and then spatial-temporally averaged to generate mean state vertical motion profiles.

We find that cloud regimes do vary with vertical motion profile shape. We observe that the isolated systems convective regime exhibits a more "bottom-heavy" profile shape compared to the convective/thick cirrus and vigorous deep convective regimes, with maximum upward vertical motion occurring in the lower troposphere rather than the middle to upper troposphere. We find this to be an interesting result, because the variability that we observe with our method does not coincide with the conventional profile variability based on stratiform rain fraction.