Probing Vertical Air Motions in Deep Convective Clouds Using ARM Radar Observations

ARM multi-Doppler radar observations can be used to retrieve the 3-D vertical wind field in deep convective clouds.

The Science

Deep convective clouds contribute to Earth’s hydrological cycle and the vertical transport of energy, moisture, and mass from near the earth’s surface to the upper troposphere. The vertical motions in these clouds regulate precipitation amount, intensity, and associated cloudiness. However, despite the fundamental importance of these vertical motions, they are challenging to observe. This paper demonstrates an advanced technique for retrieving three-dimensional (3-D) vertical winds over cloud system scales from scanning radar measurements. Comparisons with complementary vertically-pointing radar wind profiler observations show close agreement.

The Impact

The advanced technique provides a robust, stable solution of 3-D vertical winds in cases for which traditional techniques have difficulty. The Atmospheric Radiation Measurements (ARM) Climate Research Facility at the Southern Great Plains (SGP) radar network provides the necessary observations for retrieving 3-D vertical wind fields in deep convective events. These retrievals have the potential to accelerate our understanding of the dynamical and microphysical processes of deep convective clouds and provide robust observational targets for evaluating high-resolution model simulations.


The radars at the SGP ARM Climate Research Facility include several precipitation-probing scanning and profiling weather radars that operate as a network and, thus, provide state-of-the-art measurement capabilities in deep convective clouds. Complimentary radar measurements are also provided by the National Weather Service’s Next Generation Weather Radars (NEXRAD). A team of scientists combined the information of the radar Doppler velocity measurements from all these radars in a multi-Doppler data assimilation technique using a 3-D variational (3DVAR) algorithm. The aim is to retrieve the best estimate of the 3-D air motions within deep convective cloud systems that best matches all of the multi-Doppler radar observations. The 3DVAR technique was applied to several deep convective cloud events observed during the Midlatitude Continental Convective Cloud Experiment (MC3E), a joint field program between ARM and the National Aeronautics and Space Administration (NASA). For the first time, a direct evaluation is performed of retrieved 3-D vertical air velocities with those from collocated, vertically pointing radar wind profilers. The retrieved vertical velocity is well matched with that from the radar wind profilers at each height. An analysis comparing with a traditional integration technique suggests that the 3DVAR technique provides a robust, stable solution for cases in which traditional integration techniques have difficulty with satisfying velocity observations and a mass continuity equation simultaneously.

Principal Investigator(s)

Mariko Oue
Stony Brook University

Pavlos Kollias
Stony Brook University, Brookhaven National Laboratory

Related Links


This paper was authored by employees (Pavlos Kollias, Scott Giangrande) of Brookhaven Science Associates, LLC under contract no. DE-SC0012704 with the US Department of Energy (DOE). The contribution of Scott Collis through Argonne National Laboratory was supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, under contract DE-AC02-06CH11357. Data were obtained from the Atmospheric Radiation Measurement (ARM) Program, sponsored by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division.

All ARM datasets used for this study may be downloaded at http://www.arm.gov (ARM, 1996, 2011a, b, c).


North, K.W., M. Oue, P. Kollias, S. E. Giangrande, S. M. Collis, and C. K. Potvin. “Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E.” Atmospheric Measurement Techniques, 10, 2785-2806 (2017) [DOI: 10.5194/amt-10-2785-2017]