Exploring Deep Convective Vertical Velocity and Precipitation Applications for ARM Radar Wind Profilers and Disdrometers

 

Authors

Scott Giangrande — Brookhaven National Laboratory
Die Wang — Brookhaven National Laboratory
Joseph Clinton Hardin — Pacific Northwest National Laboratory
Jeffery Thomas Mitchell — Brookhaven National Laboratory

Category

Convective clouds, including aerosol interactions

Description

The Department of Energy Atmospheric Radiation Measurement (ARM) program has accumulated an extended archive of deep convective cloud insights from deployments and novel configurations of its radar wind profilers (RWP). Coupled with additional ground disdrometer observations, these unique-to-ARM pairings have demonstrated reliable operation, routinely capturing continuous records of column precipitation quantities of interest to anchor scanning radar activities. However, advances in RWP convective studies have also facilitated new insights into deep convective processes, introducing better constraints on vertical air velocity in deep convection, improved cloud regime classification and diurnal fractional coverages, and composite reflectivity factor profiling (alignment with forward model operators). Recent deployments to the Amazon basin (GoAmazon2014/5) have also extended tropical cloud property contrasts to the growing multi-year, multi-profiler convective observations from fixed ARM SGP and ENA facilities. These combined datasets serve as a suitable testbed to explore possible use of new applications such as machine learning that promote hydrological retrievals of interest (e.g., radar rainfall, drop size distribution DSD, echo classification, latent heating profiling), as well as proxy radar insights into convective vertical air velocity for continuing climate model validation and constraint.