The algorithm behind these estimates, called the Wisconsin Algorithm for Latent Heating and Rainfall using Satellites, or WALRUS, is a Bayesian Monte Carlo algorithm that compares observations of key integrated and structural characteristics of the reflectivity profile (such as echo top height and path integrated attenuation) to a database assembled from a suite of oceanic warm rain simulations generated using the Regional Atmospheric Modeling System. WALRUS output consists of not only vertically resolved latent heating profiles, but also surface warm rain intensities, total liquid water path, vertical velocity profiles, and several other cloud properties.
Using four years of data from CloudSat, we analyze the global distribution of latent heating from warm rain and place this in the perspective of the global energy budget. The response of warm rain process rates to changing environmental conditions will be assessed by contrasting different ocean basins and compositing WALRUS latent heating estimates with several environmental variables including estimated inversion strength, free tropospheric humidity, and zonal winds. The results provide insights into the effects of the large-scale environment on the nature of diabatic heating occurring in warm rain systems.