The sensitivity of Earth's climate to an increase in greenhouse gases depends critically on the response of clouds. The roles of tropical convective clouds are particularly important in this regard and are the focus of this proposal. Tropical convection plays a key role in regulating the water budget of the upper troposphere. The resulting feedbacks from upper tropospheric water vapor and cirrus, and their dependence upon tropical convective sources, represent some of the most important and most controversial within the climate system.

Despite their importance, large gaps remain in our understanding of the lifecycle of tropical cloud systems and the fidelity of their representation in global climate models. The physical processes which determine the outflow of cirrus condensate, its lifetime, and the evolution of radiative properties throughout this lifetime are not well known. Likewise, the role of cirrus condensate in modifying the moisture budget of the upper troposphere and the potential feedback of this humidification upon the subsequent formation of cirrus remains controversial. In particular, the partitioning of detrained moisture between vapor and condensate, and the radiative characteristics of the detrained cirrus condensate remain a poorly constrained problem whose representation is, by all accounts, greatly simplified in current climate models.

This paper will describe an innovative method of combining CloudSat/CALIPSO measurements with Lagrangian cloud trajectories from geostationary satellites to examine the lifecycle of tropical cloud systems and their impacts on the radiative and hydrologic budgets. The high time sampling provided by geostationary satellites offers the unique opportunity to track the movement and evolution of cloud and water vapor structures on hourly time scales. By analyzing satellite data within a dynamical Lagrangian framework, the evolution of individual cloud systems will be studied over their lifecycle. This will provide an integrated view of the coupling between convection, clouds, and humidity to compliment the more conventional Eulerian based diagnostics.