Convective Cloud Velocity and Mass-Flux Characteristics from Wind Profiler Observations During GoAmazon14/15

Description

Understanding deep convective clouds and simulating their impacts is a major challenge at cloud resolving model (CRM) to global climate model (GCMs) scales. To GCM scales, convective parameterizations are intertwined with global energy balance, cumulus cloud radiative properties and strength of the larger-scale atmospheric circulations these models explicitly resolve. The inability to adequately resolve the role of deep convective clouds is therefore a primary driver for GCM uncertainty in the prediction of possible climate change. There is steady demand for new observational constraints to better isolate the connections between deep cloud humidity, entrainment and microphysical treatments. However, since deep convective clouds operate over a wide range of scales, it is difficult for any single observational platform to inform on convective lifecycle from detailed microphysical process scales to larger-scale global cloud cover and energetic implications. One notable recommendation has been to improve upon the observations of convective vertical velocity and mass flux over larger domains, necessary to evaluate traditional mass flux-driven ensemble GCM parameterization modes. Recently, Kumar et al. [2015] proposed a statistical profiler-based solution aimed at retrieving observational velocity and mass flux profiles better aligned with ensemble GCM expectations. Their efforts broke from traditional velocity core definitions, but required an extended profiler and surveillance radar dataset to ensure a statistical alignment between point and horizontal domain convective sampling. Our study follows similar methods and motivations, using an extended ARM profiler dataset to build on our knowledge of deep convective velocity and mass flux properties. We document our findings on the vertical structure of convective mass flux, the relative role of convective area fraction and velocity on mass flux, and the sensitivity of mass flux profiles to changes in environmental forcing. This study draws originality from the convective dataset collected within the Amazon basin during the recently concluded Observations and Modeling of the Green Ocean Amazon (GoAmazon14/15) Experiment. The profiler site is under the umbrella of the distributed System for the Protection of Amazonia (SIPAM) S-band (3 GHz) conventional Doppler radar network that gives additional context for convective events summarized in this study.