The Information Available in A-Train Data Regarding Precipitation Processes in Warm Cumulus

Abstract:

The processes that result in the conversion of cloud water to rain water are fundamentally important to the lifecycle of warm marine cumulus clouds. The rates at which these processes proceed in a particular cloud element depend on environmental conditions including turbulent air motions and boundary layer properties and the aerosol background. The processes occurring in a particular cloud element do not occur in isolation from other cloud elements both current and previous. Diagnosing the precipitation process rates from remote sensing data require, at a minimum, some simultaneous information on the properties of the cloud droplet and precipitation droplet modes. The remote sensors on the A-Train provide the most comprehensive global measurements of warm marine cumulus. We wish to address in this paper whether and under what conditions sufficient simultaneous information is present in the A-Train measurements to diagnose the precipitation processes of auto conversion and accretion. In particular we will attempt to combine radar reflectivity measured by cloudsat, microwave brightness temperature derived from cloudsat data, and two MODIS reflectance channels. The information content in the combined data will be considered using Bayesian optimal estimation techniques, and Markov Chain Monte Carlo algorithms.